CONTROL OF WIP AND REDUCTION OF LEAD TIME IN A FOOD
PACKAGING COMPANY
by
MASAUET~TS INTITT
OF TECHNOLOGY
KEVAN YONG CAI CHIM
NOV 042010
B.Eng., Mechanical Engineering (2009)
Nanyang Technological University, Singapore
LI BRARI ES
SUBMITTED TO THE DEPARTMENT OF MECHANICAL ENGINEERING IN
PARTIAL
FOR THE DEGREE OF
REQUIREMENTS
THE
OF
FULFILLMENT
ARCHIVES
MASTER OF ENGINEERING IN MANUFACTURING
AT THE
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
SEPTEMBER 2010
C20 10 Massachusetts Institute of Technology. All rights reserved.
Signature of Author:
(
/
Department of Mechanical Engineering
August 18, 2010
Certified by:
Stephen C. Graves
Abraham J. Siegel Professor of Management Science
Department of Mechanical Enginng and Engineering Systems
TJhesi Sunervisor
Accepted Dy:
David E. Hardt
Ralph E. and Eloise F. Cross Professor of Mechanical Engineering
Chairman, Committee on Graduate Students
CONTROL OF WIP AND REDUCTION OF LEAD TIME IN A FOOD
PACKAGING COMPANY
by
KEVAN YONG CAI CHIM
Submitted to the Department of Mechanical Engineering
on August 18, 2010 in partial fulfilment of the
requirements for Degree of Master of Engineering in
Manufacturing
Abstract
High inventory holding costs, strain on warehouse capacity and the competition of lead
time are concerns of a food packaging manufacturer. In this work, causes of high WIP
were identified and three approaches were developed to reduce and control better the
WIP. We propose to split the production line into dedicated lines, to change the push
production system to a pull production system, and to align the process times to the takt
time. A simulation model of the proposed production line was analyzed and was verified
by a simulation model of the current production line. Three configurations were tested for
production line A and production line B. We found that the proposed production line
reduced the WIP by 70% and saved $990,000 annually in inventory holding costs. In
addition, the lead time was reduced from 6.4 days to 1.9 days and the strain on the
warehouse capacity was eliminated.
Thesis Supervisor: Stephen C. Graves
Title: Abraham J. Siegel Professor of Management Science
Table of Contents
C hapter 1: Introduction ......................................................................................
......--- 1
1.1
Company background .........................................................................................
1
1.2
Com pany products ................................................................................................
1
1.3
M arkets and customers .........................................................................................
3
1.4
CA S operations .....................................................................................................
5
1.4.1
D esign departm ent ..................................................................................
6
1.4.2
Planning departm ent ...............................................................................
6
1.4.2.1
M aterials planning ..................................................................................
6
1.4.2.2
Production planning ................................................................................
7
Production departm ent .............................................................................
8
1.4.3.1
Pre-press process.......................................................................................
9
1.4.3.2
Printing process.......................................................................................
10
1.4.3.3
Lam inating process ................................................................................
11
1.4.3.4
Slitting process.......................................................................................
12
1.4.3.5
D octoring process ..................................................................................
13
1.4.3.6
Palletizing process .................................................................................
13
1.4.4
Storage and w arehousing ......................................................................
13
1.4.5
Purchasing departm ent...........................................................................
15
1.4.3
Chapter 2: Problem statement......................................16
2.1
Project m otivation..............................................................................................
........
...................................
16
16
2.1.1
H igh inventory holding cost.........
2.1.2
Exceed w arehouse capacity ....................................................................
17
2.1.3
Competition of lead tim e ........................................................................
18
Causes of high W IP ...........................................................................................
20
2.2.1
Complexity............................................................................................
20
2.2.2
Local autonom y of production rate........................................................
20
2.2.1
Em phasis on O EE ..................................................................................
21
2.2.1
Push production system ........................................................................
21
2.2
2.3
Project objective................................................................................................
22
C hapter 3: Literature review .......................................................................................
23
3.1
Little's law .............................................................................................................
23
3.2
Push and pull production system ......................................................................
24
3.2.1
M aterial and inform ation flow ...............................................................
24
3.2.2
Control of W IP and throughput .............................................................
25
3.3
K anban system .......................................................................................................
25
3.4
Conw ip system .......................................................................................................
26
3.4.1
N umber of cards....................................................................................
27
3.4.2
Stress level of w orkers...........................................................................
27
Simulation..........................................................................................................
28
C hapter 4: M ethodology..............................................................................................
29
3.5
4.1
Problem solving phase ...........................................................................................
29
4.2
D esign proposed production line ......................................................................
30
Changes to current production line ........................................................
30
4.2.1.1
Dedicated production lines ...............................
30
4.2.1.2
Pull production system ...........................................................................
33
4.2.1.3
Takt time ................................................................................................
34
4.2.2
Selection of dem and..............................................................................
36
4.2.3
Products allocation.................................................................................
38
4.2.4
Sequence of production...
4.2.5
W ork station stoppage...........................................................................
44
Sim ulation m odeling.........................................................................................
48
4.3.1
Proposed production line ......................................................................
48
4.3.2
Current production line .........................................................................
51
4.2.1
4.3
4.4
..........................
.......... 42
Im provem ent analysis .......................................................................................
53
4.4.1
Conversion betw een rolls and reels ........................................................
53
4.4.2
Inventory holding costs.........................................................................
54
4.4.3
Lead tim e ................................................................................................
54
C hapter 5: R esults and discussion.............................................................................
55
5.1
Current production line .......................................................................................
55
5.2
Line A perform ance ...............................................................................................
56
5.2.1
Throughput and card num ber..................................................................
56
5.2.2
W IP inventory .......................................................................................
57
5.3
Line B perform ance .....................................................................
.................. 59
5.3.1
Throughput and card num ber................................................................
59
5.3.2
W IP inventory.......................................................................................
60
5.4
Inventory level and holding costs ......................................................................
63
5.5
W arehouse capacity ...........................................................................................
65
5.6
Lead tim e ...............................................................................................................
67
Chapter 6: R ecom mendations and conclusion..........................................................
68
C hapter 7: Future opportunities ...............................................................................
70
R eferences.........................................................................................................................71
Table of Figures
Figure 1.1: Major Products of CAS.......................................................
I
Figure 1.2: The different layers of a package..........................................
2
Figure 1.3: Markets served by Company A.............................................
3
Figure 1.4: Order Flow Diagram..........................................................
5
Figure 1.5: Block planning system........................................................
8
Figure 1.6: An overview of the manufacturing processes.............................
9
Figure 1.7: Cliche used for printing.......................................................
9
Figure 1.8: M ounted sleeves...............................................................
10
Figure 1.9: The Printing Process..........................................................
10
Figure 1.10: The Laminating Process.....................................................
I1
Figure 1.11: Process of slitting station...................................................
12
Figure 1.12: Capacity of warehouse......................................................
14
Figure 2.1: Inventory holding costs for 2009............................................
16
Figure 2.2: Warehouse capacity for printed, laminated and doctor WIP............
17
Figure 2.3: Lead time.......................................................................
18
Figure 2.4: Comparison of lead time with other factories.............................
19
Figure 2.5: Mixed flow production........................................................
20
Figure 3.1: Queuing system...............................................................
23
Figure 3.2: Material and information flow in a push system and pull system......
25
Figure 3.3: Kanban system.................................................................
26
Figure 3.4: CONWIP system...............................................................
26
Figure 3.5: Steps in a simulation study..................................................
28
Figure 4.1: Phases of problem solving....................................................
29
Figure 4.2: Dedicated production lines..................................................
32
Figure 4.3: Pull production system with card return...................................
34
Figure 4.4: Simulation model of proposed production line...........................
48
Figure 4.5: Simulation model of current production line..............................
51
Figure 4.6: Slitting of a roll into reels.....................................................
53
Figure 5.1: Throughput trend of line A..................................................
56
Figure 5.2: Throughput trend of line B..................................................
59
Figure 5.3: Printed WIP with L22 process time = 14minutes
...............
Figure 5.4: Printed WIP with L22 process time = 12minutes
...............
Figure 5.5: Inventory cost of proposed production line.....
Figure 5.6: Capacity of printed and laminated WIP.........
..........
..........
Figure 5.7: Capacity of doctor WIP.....................................
Figure 5.8: Lead time of proposed production line..........
...........
List of Tables
Table 1.1: Shipping schedules.............................................................
4
Table 4.1: Work station capabilities......................................................
30
Table 4.2: Takt time of work stations ....................................................
36
Table 4.3: Demand of first three months in 2010.......................................
36
Table 4.4: Demand breakdown of March 2010.........................................
37
Table 4.5: Maximum rate of work stations.............................................
38
Table 4.6: Products allocation based on initial assignment ..........................
39
Table 4.7: Products allocation after demand adjustments ............................
41
Table 4.8: Setup costs of laminators ...................................
42
Table 4.9: Sequence of production ......................................................
43
Table 4.10: Breakdown of work stations ...............................................
44
Table 4.11: Rest time of work stations ................................................
45
Table 4.12: Short stop of work stations ................................................
45
Table 4.13: Setup time of work stations................................................
46
Table 4.14: Reel inspection time of slitters ..........................................
47
Table 4.15: Process time of work stations in proposed model .....................
50
Table 4.16: Percentage of rolls processed by each work station ..................
52
.......
52
Table 4.18: Inventory holding costs of three types of WIP .........................
54
...........
55
Table 5.2: Error in the current production line model ..............................
55
Table 5.3: Throughput mean and standard deviation in line A .....................
57
Table 5.4: Average printed WIP in line A .............................................
58
Table 5.5: Average laminated WIP in line A ..........................................
58
Table 5.6: Average doctor WIP in line A ..............................................
58
Table 5.7: Throughput mean and standard deviation in line B .....................
60
Table 5.8: Average printed WIP in line B .............................................
60
Table 5.9: Average laminated WIP in line B ........................................
60
Table 5.10: Average doctor WIP in line B ............................................
61
Table 5.11: Inventory reduction ..........................................................
63
Table 4.17: Process time used in current production line model ........
Table 5.1: Performance of the current production line model .......
Table 5.12: Inventory holding cost savings .............................................
64
CHAPTER 1: INTRODUCTION
1.1
Company Background
Company A, Singapore (CAS) is a multinational food processing and packaging
company of Swedish origin. Founded in 1951, it is one of the largest manufacturers in the
food processing and packaging industry. Company A provides integrated processing,
packaging and distribution lines as well as plant solutions for liquid food manufacturing.
Today, the business spans more than 150 countries with 43 packaging material
production plants worldwide.
CAS was established in 1982. CAS focused on manufacturing finished packaging
material for customers in 19 countries. CAS and Company A, Pune, in India are the
production plants in the South and Southeast Asia Cluster. In year 2007, CAS received
the Manufacturing Excellence Award (MAXA) for overall excellence in innovations,
operations and sustainability as well as its World Class Manufacturing (WCM) approach
to ensure operational improvement and downtime minimization.
Due to the increase in complexity of Company A's supply material plants worldwide and
increase in both complexity and number of products, Company A has been focusing on
improving their supply chain and production efficiency.
1.2
Company Products
Company A is one of the world's major packaging providers. It offers a wide range of
packaging products, filling machines, processing equipment, distribution equipment and
services. Figure 1.1 shows the major products of Company A.
Figure 1.1: Major Products of CAS.
...........
..
CAS produces carton packs, also known as CA packs. CA packs are used for food items
like milk, juice and soy products. Designing service is also available for customers. Each
CA pack is made of 6 layers of materials, including aluminum, paper and polyethylene,
to prevent spoilage of the content. The base material for each package is paper. It
provides structure and support to each package. After the design is printed onto the paper,
it will be coated with a layer of aluminum foil, which makes the pack aseptic and
preserve the flavor of the content. Four layers of polyethylene will also be coated onto the
paper. The outside layer prevents damage from moisture; the adhesive layer between the
paper and aluminum foil provide structure support and two protective innermost layers
seals the liquid content. The layers of the package and their respective functions are
shown in Figure 1.2.
1.PE - protects against outside
moisture & enhance appearance
2 Paper - for stability and
strength
5
&
2
3.PE - adhesion layer
4. Aluminium foil - oxygen,
flavour and light barrier
5.PE - adhesion layer
6. PE - seals the liquid
Figure 1.2: The different layers of a package.
There are 10 classes of package available for CA packs. They are Brik, Brik Aseptic,
Prisma Aseptic, Gemina Aseptic, Fino Aseptic, Classic Aseptic, Wedge Aseptic, Rex,
Top and Recart. Different sizes are offered for each class of package, while the
polyethylene layers are different for different carton content.
Currently, different products are distinguished by the system code, size code, quality
code and design code. The system code defines the class of the package, which describes
whether the carton is aseptic, refrigerated or ambient. Different classes require different
creasing in the printing stage. System codes also have a suffix indicating the content of
.....
......
the carton (juice or milk), which would affect the laminating stage as different contents
require different polyethylene formulations. The size codes indicate the volume of liquid
contained by the package and its shape (slim, base, square). Thus it describes two
attributes and affects the printing, slitting process and sorting on the laminator. Products
with the same size code would have same overall width and therefore, same number of
webs. Quality codes determine the type, thickness in grams per square meter and the
brand of paper used. Lastly, design codes describe a single attribute that is the design of
the product.
Compared with other factories of company A, CAS offers a large range of different CA
pack products. Currently, around 20 different products of different package classes,
carton sizes and polyethylene formulations are able to be produced in CAS.
1.3
Markets and Customers
Positioned in Singapore, CAS efficiently serves customers in the South and South East
Asia cluster. There are also customers from Europe and the Middle East. In total, CAS
ships its finished products to customers in 19 different countries, as shown in Figure 1.3.
Figure 1.3: Markets served by Company A.
...............
The customers of CAS currently need to place their orders through a market company.
The market company has a sales office in the customers' respective country. They take
orders from beverage producing companies then receive and distribute the finished
products to the customers.
The Thailand market is the largest by volume, followed by Malaysia, Indonesia and
Vietnam. Most of the products are ocean freight to the customers. At the moment, only
the Malaysia market is being served by truck freight. For most shipping routes, the
containers are only picked up from Singapore ports twice a week and the shipping dates
are fixed. For example, for the case of the Thailand market, finish goods are shipped out
on every Tuesday and Saturday. For the Malaysia market, the freight truck delivers
orders from CAS everyday. The details are documented in Table 1.1 below.
Table 1.1: Shipping schedules.
usrana
hina
ng Kong
ndonesia
nu, bun
on, Thu
laysia
epal
akistan
us, Sat
Hiippines
hu, Sun
audi Arabia
pan
Korean
Zealand
tanka
Mon, Fri
Daily
on
aiwan
land
let Nam
ue, Thu
Mon
ue, Sat
ue
ri
Mon, Wed
ue, Sat
Mon, Wed, Thu
1.4
CAS operations
The core corporate functions of CAS are the design, production, planning and purchasing
departments. There is also a market company operating in CAS' premises and this is an
independent entity from CAS. The market company is responsible for order management
and customer service. CAS' warehouse and delivery operations are outsourced to a third
party logistic company. Figure 1.4 shows the steps at which an order is processed.
*Goods are being delivered out of the
warehouse everyday
Figure 1.4: Order Flow Diagram.
1.4.1
Design Department
After the customers' designs have been submitted to CAS's design department, the
design department reviews and adapts these designs to suit CAS's production systems.
When faced with difficulty, the customers do receive assistance from the design
department in designing the carton. Once the design is confirmed, the design is broken
down according to the component colors. The process colors are Cyan (C), magenta (M),
yellow (Y) and black or key (K). Special or spot colors may also be used to obtain
specific shades of color. The number of spot colors can vary from none to seven. A sales
order can only be made once the designed is confirmed.
1.4.2
Planning Department
The planning department at CAS is responsible for materials planning and production
planning.
1.4.2.1 Materials Planning
Materials Requirement Planning does the ordering of the raw materials needed for
production. The base materials ordered are paper, polyethylene and aluminium foil with
many types of variants in terms of grade and size. The purchasing department is
responsible for acquiring the additional materials such as water based inks, pallets and
tapes that are used for production as they are relatively low volume and low cost.
Company A International (CAI) is the parent body of CAS. CAI issues the annual global
forecasts for number of packs and marketing directives. CAI's Global Supply places
blanket orders on the basis of the annual forecast for each of the converting factories with
the suppliers in order to obtain economies of scale and to pool the variation in demand.
The converting factories then place the actual orders with the suppliers to withdraw from
the blanket order placed initially.
In addition, monthly forecasts are also issued and updated regularly. As the lead time of
raw materials is very long, the ordering is done well in advance. The ordering is done on
a weekly basis as this time period coincides with the frequency of dispatch. A continuous
6
review method is used to determine the ordering quantities. The re-order point is set at
approximately 40% of the monthly demand while the order up-to point is around 60% of
the monthly demand.
1.4.2.2 Production Planning
The production system of CAS is make-to-order. The production schedule is drafted only
upon receipt of a production order from the sales department. The scheduling is done on
the SAP based P2 system and the current production lead time is around 12 days.
Planning is based on the delivery due date. CAS uses three core work stations for their
processes. They are the printer, laminator, and slitter. On each of the three work stations,
the orders are grouped together based on certain criterions to minimize setups. The
grouping for the printer is done on the basis of size and shape. The criterion for the
laminator is the overall width of the roll. Lastly, the slitter orders are arranged based on
pack width.
A block scheduling system is used to plan the production schedule. In this collaborative
planning, the planning department generates a weekly production schedule with blocks
according to width of the paper rolls. This is to reduce the number of setups at the
laminator. Customer orders are then fitted into the blocks. The latest order date for the
customers is 4 days before the production cycle starts. The production cycle starts on
every Monday. Thus, the customers must place their orders by Thursday of the previous
week. The estimated delivery date is 3 days after the end of the production cycle.
Therefore, the products would be ready on the Wednesday after the production cycle. The
customers would be able to place orders many weeks earlier. However, when the orders
are placed too early, the orders would be kept in the system and be produced in the
subsequent production cycles. Figure 1.5 shows the block planning.
However, some customers tend to place last minute orders, which would create
disruptions to the planned production schedule. These last minute orders are rush orders
which lower equipment efficiency. These last-minute orders are urgent orders that are
placed within 1 to 3 days before the start of the production cycle in which it needs to be
produced in. Also, when the current production schedule has been completed ahead of
7
time, the planning department would also bring forward some orders to fill up the empty
block in the block schedule. By doing this, the equipment efficiency is improved but
advanced production will also result in higher work in process (WIP) and finished goods
inventory.
4 days
7 days
M
Latest order
date
T
W
TH F
3 days
S
Production cycle
S
Estimated
delivery date
Figure 1.5: Block planning system.
1.4.3
Production Department
The Production Department performs the major manufacturing processes to produce the
packing materials. The 3 major processes in CAS are printing, laminating and slitting.
Before printing, a pre-press process has to be carried out, and after slitting, a doctoring
process sometimes needs to be done. An overview of all the production processes is
shown in figure 1.6.
...
.
PRODUCTION PROCESS
WAM BASMDI
SR~MDPAM
PBOD
L~IHNENG
PALLETZEG
PA
Figure 1.6: An overview of the manufacturing processes.
1.4.3.1 Pre-Press Process
This is the first stage in the production process. In the pre-press stage, the clich6s for
printing are prepared from the negatives. The cliches are polymeric stamps with elevated
portions for the areas to be printed. These clich6s are prepared on photopolymer plates
through a process of controlled exposure to UV light. There will be a cliche prepared for
each color used for printing. After which, the cliches are mounted onto a sleeve with a
rotating spindle. The number of cliches mounted on one sleeve depends on the width of
the individual pack and the paper roll. This corresponds to the number of webs. A cliche
used for printing is shown in figure 1.7. Figure 1.8 shows the mounted sleeves.
Figure 1.7: Cliche used for printing.
...
Figure 1.8: Mounted sleeves.
1.4.3.2 Printing Process
In the printing stage, the flexography method is used. This is a method of direct rotary
printing that uses resilient relief image plates of photopolymer material. The design
pattern on the cliches is reproduced onto the paper board by rotary contact of the paper
roll with the stamp. Water based ink is used. The incoming paper roll is loaded on the unwinder, which opens it up and feeds it to the printing stations. An illustration is shown in
Figure 1.9.
Ink transferred
Impression
Cylinder
Ink transferred
from anilox to
plate
Doctor
Chamber
Figure 1.9: The Printing Process.
......
....
-
.................
..
0000000000VWOV
There are seven stations on the printer. Each station holds the sleeves and the water based
inks for one of the colors of the design. Depending on the design colors, some of the
stations may be idle for a design as not all colors are used for every design. A colored
image is formed by 4 process colors, Cyan (C), magenta (M), yellow (Y) and black or
key (K). The different colors are then superimposed one over the other to get the
complete final printed design.
Fold creases for the produced cartons are also form during the printing process. The
purpose of creasing is to enable proper folding of the pack during the filling stage at the
customer site. The tool is used to form creases also punched the holes for straws. For
routine printing, flexographic technology is used. For higher resolution designs, CAS
uses offset printing, which is more expensive compared to flexography.
1.4.3.3 Laminating Process
Laminating involves the coating of aluminum foil and polyethylene (PE) layers onto the
printed paper. A roll is first unwound at the unwinder. It then goes through three stations
for the coating process. The last step is to rewind the laminated paper into a roll. In the
first station, a layer of aluminium foil is layered onto the printed paper. After which, PE
film is coated in the inner surface of the packaging material to prevent contamination and
leakage. The final station adds another layer of PE on the outer surface of the packaging
material to protect the paper. This process is shown in figure 1.10.
Polymer
Laminator I
Laminate layer
Lwminhtor2
inside layer
Laminator3
D6cor layer
Figure 1.10: The Laminating Process.
1.4.3.4 Slitting Process
The paper roll can have 4, 5, 6, 7, 8 or 9 webs (columns) depending on the product size.
The slitting process cuts the entire roll into reels of a single pack width so that they can
be fed into the filling machines at customer production plant. The rolls are unwound, slit
using a row of knives and counter-knives and then rewound to form reels. The reels are
then grouped into defective reels and non-defective reels. Defective reels are reels that
consist of at least one defect and these reels need to go through the doctoring process to
have the defects removed. Non-defective reels are reels which have no recorded defects
throughout all the processes and they do not need to go through the doctoring process. A
schematic diagram of slitting process is shown in figure 1.11.
Figure 1.11: Process of slitting station.
1.4.3.5 Doctoring Process
After the slitting process, the defective and non-defective reels are separated. The nondefective reels would be kept at the shop floor and the defective reels would be doctored.
Doctoring or rework is the process of removing the packs with defects from the reels.
Approximately 24% of the reels require doctoring. These defects are due to any of the
upstream processes and they are removed collectively at this stage. There are 14
doctoring stations after the slitting process. Each doctoring work station would have an
operator to find the defects and remove them using a machine. One reel could be
doctored every 24 minutes on average by an operator.
1.4.3.6 Palletizing Process
The doctored reels would join the good reels to be palletized. Palletizing is the process of
stacking reels together on a pallet and wrapped with a plastic layer. There would be 5
reels on the pallet on average. The palletizing time is 8 minutes. The palletized reels
would be transported to the warehouse and await delivery. These palletized reels are
handled solely by a third party logistics company from this point onwards.
1.4.4
Storage and Warehousing
CAS' in-house warehouse is shared among raw materials; work in process (WIP) and part
of total finish good inventory (FGI). Currently, the in-house warehouse is managed by a
third-party logistics company.
The current daily FGI level is around 1000 rolls (converted from pallets), among which
up to 600 rolls are stored in the internal warehouse. Each roll is approximately 5513m
long and it takes up about 3 pallets. The current daily FGI level of about 1000 rolls is
approximately equal to about 6 to 7 days of inventory as CAS produces approximately
130 to 150 rolls per day on average. The external warehouse is engaged when there is not
enough space.
The floor layout and capacity for each category of inventories are
illustrated in figure 1.12. As we can see from the figure, the full capacity for WIP is
approximately 500 rolls only. Yet currently, average WIP levels can reach over 1000
13
zzv
v
Zzzzzw
::':_
-
-
-
-
- -
- . "-
-----------
rolls, not including raw material rolls. The raw material rolls are stored in a huge
container yard beside the warehouse and it can hold up to 800 rolls of raw material.
The movement of raw material, WIP and FGI between the production floor and in-house
warehouse is facilitated by the laser guided vehicles (LGVs). These vehicles can move a
roll at a time and they are programmed to follow a specific route. Forklifts and clamp
trucks are used for the movements of the rolls within the internal warehouse.
Capacity
1800
FG Storage Area (Pallets)
Paper Storage Area (Rolls)
700
100
Alum Foil Storage Area
(Crates/Boxes)
WIP Storage Area (Rolls)
500
70
Additional Storage Area
(Pallets)
Doctor Reels Storage Area
(Pallets)
200
Malaysian Picking and Storage
Area (Pallets)
Total Warehouse Storage Space
Figure 1.12: Capacity of warehouse.
100
1.4.5
Purchasing Department
The purchasing department at CAS is responsible for the purchase of additional materials
and indirect services. Examples of additional materials include inks, pallets, cores, straws
etc. Indirect services mainly refer to equipment maintenance, electricity, and water
utilities. The base materials comprise 60% of the total monetary value spent by the
purchasing department, while additional materials and indirect services make up the
remaining 40%. There are more than 10 suppliers for the additional materials and more
than 500 providers for indirect services. The purchasing reviews all the suppliers
regularly and will provide assistance when the suppliers are underperforming. The
purchasing department has a well-established system to source for alternative suppliers.
Hence, suppliers who consistently underperform will be substituted.
..
....................
:. .............
........
. ..............
............
.........
.....
....
-
CHAPTER 2: PROBLEM STATEMENT
2.1 Project motivation
2.1.1
High inventory holding cost
CAS has incurred high inventory holding cost. The inventory holding costs of each
month in 2009 is shown in figure 2.1. The printed WIP holding costs is $315,305 for the
year, while the laminated WIP holding costs is $570,372 for the year. The total WIP
inventory holding costs is $885,677 for the year of 2009. CAS has a production of over
1.2 billion packs per month since March 2010. CAS' marketing company has projected
that sales will grow at 12 percent annually. Therefore, CAS needs to produce over 1.35
billion packs by March 2011. As such, the inventory holding costs would be even higher
in 2011. CAS would be able to reduce the capital tied up by the inventories by reducing
the WIP.
120,000
N Laminated
100,000
* Printed
80,000 -
60,000
40,000 20,000 0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2009
Figure 2.1: Inventory holding costs for 2009.
2.1.2
Exceed warehouse capacity
CAS stores its WIP in the internal warehouse. Capacity has been allocated to different
types of inventory. The capacity allocated for printed and laminated WIP is 500 rolls
while the capacity allocated for the doctor WIP is 500 reels. Doctor WIP is the term CAS
uses to refer to the WIP awaiting to be doctored. Figure 2.2 shows that the WIP has
exceeded the capacity allocated for them. This has two impacts. Firstly, it forced CAS to
store WIP at forklift lanes. As such, the forklift operators have a harder time to retrieve
the rolls and it might cause safety issues. Secondly, CAS has to relocate some of the
finished goods inventory to the external warehouse. The external warehouse incurs
additional expenses for CAS.
Printed and Laminated WP
1000
900
Doctor WIP
1800
-__
__
1600
-
1400
1200
1000
7'A
600
--
,
-0
600
50
400
400
200
300
0_FbJn
Jan Feb Mar Apr May Jun
Jul Aug Sep Oct Nov Dec
2009
Jan Feb Mar Apr May
Jun
Jl
c
Jul
Aug Sep Oc
2009
Figure 2.2: Warehouse capacity for printed, laminated and doctor WIP.
o
e
Nov Dec
-iiW ft im ! E M" m
...........
2.1.3
.
.....
I...
...................
. ..
.......
...
Competition of lead time
The lead time quoted to customers is 12 days from time of order placement until the order
is shipped by CAS. (The lead time from point of shipment until the receipt by customer is
outside of the control of CAS. The shipment is arranged between the customer and the
logistics company.) The production lead time takes up about 10 of these 12 days. The
remaining 2 days is due to the handling of the finished goods by the
3 rd
party logistics
company. This long lead time is mainly due to the long waiting time between processes.
An illustration of the current lead time is shown below in figure 2.3.
1 day
<0.5 day
4 days
<0.5 day
3 days
<1.5 days
Figure 2.3: Lead time.
There is both internal and external competition on the lead time. The internal competition
comes from the comparison of CAS and other factories within the same company. Figure
2.4 shows the lead time quoted to customers by other factories. The factories in India and
China are of concern to CAS as they are the neighbouring clusters. The lead time at India
is only one day behind that of CAS. The lead time of 7 days in China is 60% of that in
CAS. Thus, there is a strong internal competition. The external competition comes from
company C. Company C is able to quote a lead time that is comparable to CAS. CAS has
a strong desire to shorten its lead time to stay ahead in the competition.
Others
Others
17
Others
16
Others
15
Others
14
India
13
CAS
12
Others
12
Company C
9
Others
9
Others
China
7
China
7
China
7
Others
7
0
2
4
6
Smaller number
= shorter lead time
8
10
8
10
I
I
12
14
16
Figure 2.4: Comparison of lead time with other factories.
18
20
2.2
Causes of high WIP
2.2.1
Complexity
CAS is using a mixed flow production such that a product can flow to almost any station
downstream (subjected to work station capability). This mixed flow production is shown
below in figure 2.5. There is no clear route for the production. It is too complex for CAS
to set an appropriate route at which the products are produced at each stage. The mix of
orders for each week is different, and CAS has a fast pace environment. As such, it is
difficult for the planners to determine a good routing plan. This difficulty is coupled with
rush orders (i.e. orders made by customer after the weekly production cycle has started).
The planned production route would be disrupted by these rush orders.
S52
P13
D1 to D14
L21
S54
Pal
Queue
S53
P18
FGI
L22
Pa2
S55
Figure 2.5: Mixed flow production.
2.2.2
Local autonomy of production rate
There is no fixed rule to control the production rate of the individual work stations. Each
process manager would be given a production schedule and sequence. However, they
have the autonomy to choose the work station speed at each stage. As such, every stage is
producing at different rates. The general rule is that the individual process must not starve
the downstream process. Thus, the process managers will produce a suitable level of
safety stock based on their judgment to prevent the starvation of the downstream
processes. As there is no 'pacer' in the production line, the WIP tends to build up. When
sufficient WIP has built up, the work stations are rested.
2.2.3
Emphasis on OEE
The overall equipment effectiveness (OEE) is an important key performance index (KPI)
for the production employees as their bonuses are tied to this KPI. As such, every process
has an incentive to process the rolls that will bring the OEE to the target OEE. This builds
up unnecessary WIP.
2.2.4
Push production system
CAS is currently using a pure push production system. The system ignores the real
production shop-floor situation. Thus, the upstream work station continues to produce
even when the downstream work station is having a breakdown or a long setup change.
This causes the WIP to build up. The laminator is currently the bottleneck of the entire
system and it is estimated to have a capacity of 100 rolls per day. CAS would estimate
the capacities of all work stations to plan the production for the push system. However, it
is difficult to estimate the capacity as the actual capacity of the work stations would be
altered by variations. Thus, if the actual capacity of the laminator drops and the actual
capacity of the printer increase, there would be more WIP between these 2 stages.
2.3
Project Objective
The author aims to improve the production system in CAS by the following means:
1) Control the WIP to reduce capital tied up by inventories and to eliminate the
problem of warehouse capacity.
2) Reduce the lead time to keep CAS competitive in the industry.
3) Reduce the complexity of the production system to have better visibility and
control and improve cooperation between processes.
CHAPTER 3: LITERATURE REVIEW
3.1
Little's law
Lead time and inventory level are two major concerns in a production system. A discreteparts production system can be viewed as a queuing system where the items are queuing
to be processed by a number of steps. Little's law offers an understanding on the queuing
system. A simple queuing system is shown in figure 3.1. The work items arrive at the
system where there is one server. The rest of the work items that are not served
immediately have to wait in a queue for their turn to be processed. When a work item is
processed by the server, it departs from the system. The Little's law relates the average
number of items in a queuing system, the average arrival rate for the work items and the
average queue time of work items by Eq. (3.1) [1]
Eq. (3.1)
L = XW
Where L=average number of work items in queuing system
A=average arrival rate of work items
W=average queue time of work items
Departure
Arrival
Queue
Server )
Figure 3.1: Queuing system [1].
Little's law is general and could be applied in different systems. For example, Little's law
could be applied in a production system where it relates the work items' flow time,
throughput and the level of WIP by Eq. (3.2) [1]
WIP = TH x FT
Eq. (3.2)
Where WIP=average number of work items between start and end of production system
TH=throughput rate of work items (which is assumed to match the arrival rate)
FT=average flow time of work items
Little's law applied at the production system is similar to its original form. However,
there is a distinct difference. The original Little's law is using the arrival rate of work
items. On the other hand, Spearman et. al. used the departure rate (throughput) of the
system [2]. It is more meaningful to use throughput as it is often a measure of the system
performance.
3.2
Push and pull production system
In a push system, a production release date is calculated by taking into account the time
planned for production, shipping and other operations. Once these orders are released into
the production system, they are pushed to the end of the system. As such, an upstream
process would produce work items without considering the situation at the downstream
process. This might build up the WIP unknowingly. Thus, in a push system, the
throughput is controlled and the WIP (and flow time) is used as a performance measure
[3]. In a pull system, the work item cannot move downstream without authorization. The
work item would be pulled downstream when the downstream process gives a signal to
the upstream. Thus, in a pull system, the WIP is controlled and the throughput is a
performance measure [3].
3.2.1
Material and information flow
In the push system, the work items flow is in the same direction as the information flow
[4]. The information in this case could be a master production schedule where the work
items are produced according to predefined due dates. In the pull production system, the
work items flow is in the opposite direction as the information flow. The information
flow in this case would be a signal from the downstream process that the work item is
ready to be produced downstream. Figure 3.2 show the information flow in the push and
pull system.
.............
... .. .........
-
Work items flow
Push System
M
7)
(
Information flow
Work items flow
Pull System
Information flow
Figure 3.2: Material and information flow in a push system and pull system [4].
3.2.2
Control of WIP and throughput
Spearman et al. discussed that a pull system is relatively easier to control as compared to
a push system [5]. WIP would be easier to control than throughput in practice as WIP
could be observed in a straightforward manner. In addition, capacity estimation of the
plant is required when throughput is the parameter to be controlled as in the push system.
However, the capacity of the plant is difficult to estimate as it is subjected to many
variations. These variations includes worker efficiency, machine breakdown and setup
time. The orders could exceed the perceived capacity and cause the WIP to build up. The
building up of WIP would be aggravated when seeking high utilization is of importance.
3.3
Kanban system
Kanban system is a type of pull production system where there is a set of kanban cards
circulating between each pair of buffer and the upstream machine [6]. These kanban
cards are localized and not transferred along the entire line. When a work item has
become a finished good, the kanban card is returned to the immediate upstream machine
to signal that it has the authority to process one more work item. This relationship is the
same throughout the line. Figure 3.3 illustrates a kanban system. Thus, the demand
propagates up the production line. The machines will stop processing when the buffer is
full. On the other hand, they will continue to process when the buffer is not full.
............................
Although kanban helps to reduce the WIP, it cannot be used under some environments.
Kanban would not be useful when [5]:
1) The setup time is long
2) The scrap loss is high
3) The demand has large and unpredictable demand
M
-
M
B
-*
B
M
-*G
Figure 3.3: Kanban system [6].
3.4
CONWIP system
CONWIP system is different from kanban system. There is only one set of cards that
circulates around the entire line [6]. When a work item has become a finished good, the
card is returned to the first machine to signal that it has the authority to process one more
work item. The new work item would then be processed down the line like a push system.
As the card is always transferred to the first machine, the WIP in the system should
always be a constant number, assuming that the first station is never starved. A CONWIP
system is shown in figure 3.4.
M
FrB
34
M
W
B
Figure 3.4: CONWIP system [6].
Msytm
3.4.1
Number of cards
CONWIP is easier to control and less complex than kanban as there is only one set of
cards as compared to having one set of cards between each pair of adjacent processes in
the kanban system [3]. There are more set of cards to be determined on the line in the
case of the kanban system. Since the number of cards in the system might need
continuous adjustments over time, a kanban system is harder to control and maintain.
However, the number of cards used in a CONWIP system can be more than that in a
kanban system. Thus, the WIP level is likely to be higher in a CONWIP system. This
implies that the cycle time is higher for the case in CONWIP system.
3.4.2
Stress level of workers
Spearman et. al. has also pointed out that a CONWIP system is less stressful to the
production workers as compared to the kanban system [3]. There would be more pacing
stress in the kanban system as the upstream workers need to replenish the void in the
system to prevent the starvation of downstream machine. On the other hand, the workers
in the CONWIP system experience less pacing stress as CONWIP acts as a push system
at any machines other than the first one.
3.5
Simulation
It is possible to obtain analytic solution when the problem of interest is simple. However,
many real life problems are complex. Simulation is useful in problems that are too
complex to be evaluated analytically. It is more cost effective to carry out simulations to
determine the suitability of the proposed plan as compared to experimentation with the
real system. The simulation allows the user to have an insight on the performance of the
plan. Simulation models could be static or dynamic. A dynamic model would be more
applicable here as the production line evolves over time. Discrete event simulation is a
model where it is dynamic, discrete and stochastic. Computer package that provides
discrete event simulation includes Arena, ProModel and Simul8. Averill et. al. has
proposed the following steps in a simulation modeling that would help in modeling a
system [7]. These steps are shown in figure 3.5.
Figure 3.5: Steps in a simulation study [7].
CHAPTER 4: METHODOLOGY
4.1
Problem solving phase
The author proposed 6 problem solving phases to meet the 3 objectives stated in chapter
2 of the thesis. The phases are shown in figure 4.1. Phase 1 introduces the production line
proposed by the author. Different aspects of the proposed production line are discussed in
this phase. Phase 2 involves the building of a simulation model of the proposed
production line. In phase 3, a model of the current production line is created to act as a
form of verification. In phase 4, three alternative configurations are tested for each line to
find a suitable system for CAS. An improvement analysis is done in phase 5 to measure
the performance of the proposed system. In phase 6, the author proposes the production
line and makes recommendations to CAS.
Pha,-se I
Des(in prIopiosed pr-oductOio
P ase 2
Veif1ication1 using( Model Of
current piroduction1 line
Pl ase 4
Collnpare- alterna~tive system1
conlfigur-ations
Pha'.se 5
lIiimos
etet anial ,s s
Phai~se 6
P -opose sOtolto
Figure 4.1: Phases of problem solving.
.................
ONERM
4.2.
Design proposed production line
4.2.1
Changes to current production line
-,
-
The author proposed to make three major changes to the current production line to meet
the objectives outlined in chapter 2. These changes are:
e
Use of dedicated production lines
* Change to pull production system
* Align production to takt time
4.2.1.1 Dedicated production lines
The current production system is a mixed flow line where the products can flow to almost
any downstream work stations. However, some work stations are unable to process all of
the products. The products that could be processed by each work station are shown in
table 4.1. A shaded box means that that product could be processed by that work station.
For example, L22 could process both juice and milk products while L21 could only
process juice products. The planner in CAS has to plan the route of the products during
each production cycle to ensure that there are no clashes between the product routings
and the work station capabilities.
Table 4.1: Work station capabilities.
Products
Juice 567
Juice 350
P13
P18
L21
L22
S52
S53
S54
S55
.............................
In order to reduce the complexity of the current production line, the author proposes to
split the entire line into two dedicated production lines A and B as shown in figure 4.2.
The allocation of products between the two lines is explained in greater detail in section
4.2.3. There are several motivations to use dedicated production lines over the mixed
flow production lines:
e The lines are simpler to manage by CAS.
* There is more visibility of the products flow and decisions are made faster.
e Any rush orders inserted into line A does not affect line B and vice versa.
e
Planning lead time during each production cycle is reduced because planning
should be simpler.
Figure 4.2: Dedicated production lines.
One slitter (S54) is assigned to line A while three slitters are assigned to line B. This is
due to two reasons. Firstly, the demand assigned to line A is less than that of line B.
Secondly, only 5 and 9 web products are assigned to line A while 5, 7, 8 and 9 web
products are assigned to line B. The setup time for changing of webs at the slitters is 60
minutes. Since there is more type of webs on line B, frequent setups are expected and the
capacity of the slitter is taken up by these setups. This situation would be aggravated
when rush orders of different webs are inserted after the production cycle has started. The
number of setups is reduced by dedicating slitters to slit only products of 1 or 2 web types.
S54 and S55 are assigned to slit 5 and 9 webs products. S53 is dedicated to slit 7 webs
products and S52 is dedicated to slit 8 webs products. The advantage of the assignment
on S54 and S55 is that when either S54 or S55 experience unexpected and prolonged
downtime, products could be switched from one slitter to the other without disrupting
other products on either line A or line B.
There are 14 doctoring work stations in CAS. 4 Doctoring work stations are assigned to
line A while 7 doctoring work stations are assigned to line B. This is because line B has a
higher demand and this is explained in the later sections. Thus, the defects on line B are
higher and more doctoring work stations are required. The remaining 3 doctoring work
stations act as backup for either of the line.
4.2.1.2 Pull production system
The current production system is a pure push production system. Orders are released into
the production line through P13 or P18 when the printers have finished processing the
previous roll. The current production system does not consider the status of the
downstream work stations. Orders are still released to the printers into the production line
even when the downstream work stations are stopped for a prolonged period of time.
A CONWIP pull production system is able to react to the actual situation in the
production line and allow CAS to have a better control over the WIP. There are several
advantages of CONWIP production system over the current push system.
*
Orders are not released into the system when the WIP has reached a predefined
level using CONWIP cards.
*
The total WIP in the production system stays relatively constant.
*
The lead time to customers could be better estimated when the WIP stays at a near
constant level.
Figure 4.3 shows a schematic of the pull production system proposed by the author.
There are separate queues in each of the dedicated lines just before the printers. An order
is released into the production line when there are available cards at the entry point. As
CAS has a large production floor area, a physical card is not appropriate to be attached to
each of the roll. CAS has initiated a concurrent project where radio frequency
identification is used to track the rolls in the production line. When a roll leaves the end
of the line (palletizer), a signal is sent back to the queuing area and authorizes that a new
roll can be released into the production line. The products in line A go through the
following path:
P13 -+ L21 -> S54 -> D1 to D7 (only defective products) -> Pal
and the products in line B go through the following path:
P18 -+ L22 -*
S53 or S52 or S55 -*
D8 to D14 (only defective products) -> Pa2
....................
......
..............
.................
...
.......
... - .....
11-,.....
Conwip card
53 7
B
web
D5 to D11
P18
L22
S52we
8
& 9web
Conwip card
Figure 4.3: Pull production system with card return.
4.2.1.3 Takt time
The current production line utilizes all the work stations at their maximum rate to
increase their OEE. When a sufficient WIP buffer has been built up, the work stations are
made to rest. The author proposes that the work stations rate should be aligned to the takt
time of the demand during each production cycle. This implies that the work stations do
not process the rolls at their maximum rate. When the demand is high, all work stations
operate at a high rate and vice versa. The takt time for a given week for line A and line B
is found using Eq. (4.1)
Takt time (mins/roll)
(mins)-Time loss (mins)
= Total time in production
per week(roll)
Demand cycle
Eq. (4.1)
Net avaliable time (mins)
Demand per week(roll)
The total time in each production cycle is the same. Each production cycle comprises 7
days or 10,080 minutes. The time loss comprises planned maintenance, setups and other
types of stoppages that can be anticipated or expected. The time loss is estimated from
past data in CAS internal P2 system. The net available time for each work station is
different as their time loss is different. The demand in the denominator of Eq. (4.1) is the
demand in a week (one production cycle) expressed in rolls. Rush orders are not
considered in the models due to two reasons. Firstly, the percentage of rush orders is
small. Secondly, CAS is currently working on a customer order management project to
minimize the occurrence of rush orders.
The doctoring work stations and palletizers do not have any planned maintenance, setups
and other types of stoppages. Thus, their net available time is the total time in each
production cycle. The number of doctoring work stations required on each line is
different. 24% of the rolls on each line contain defects and require doctoring. The number
of doctoring work stations is determined by Eq. (4.2)
Number of doctors
=
Process time (mins)
+
Number of doctors
=
Process time (mins)
+
Net avaliable time (mins)
Demand require doctoring per week(rolls)
Eq. (4.2)
Net avaliable time (mins)
Demand per week(rolls)x Defects (%)
The takt time for each of the work station is shown in table 4.2. The takt time required for
the doctoring work stations are much slower than the rest of the work stations as only 24%
of the rolls on each line contain defects and are directed to the doctoring work stations. A
doctoring work station takes 392 mins (standard deviation of 72) to rework a roll. It is
found that line A requires 4 doctoring work stations and line B requires 7 doctoring work
stations. Thus, 11 doctoring work stations are required for the entire production line. This
is the same as the number of doctoring work stations in the current production line. This
leaves 3 doctoring work stations unused and assigned as backup. This assignment of the
doctoring work stations is based on the assumption that the percentage of defects on each
line remains at 24% regardless of the assignment of products on each line. CAS has to do
further analysis to determine whether there is a correlation between product type and the
percentage of defects.
Table 4.2: Takt time of work stations.
Line A
Rate required
(mins/roll)
Capacity
(mins/roll)
Work station
Net avaliable time
(mins per week)
P13
L21
6,498
9,491
15.8
22.9
9.2
12.8
S54 (5 & 9 web)
5,523
13.3
6.8
Doctoring (4)
10,080
101.3
392 per station
Pal
10,080
24.3
8.3
Work station
Net avaliable time
(mins per week)
Rate required
(mins/roll)
Capacity
(mins/roll)
P18
L22
S52 (8 web)
S53 (7 web)
S55 (5 & 9 web)
Doctoring (7)
Pa2
6,408
9,545
7,269
7,623
7,078
10,080
10,080
9.3
13.9
10.6
11.1
10.3
61.1
14.7
9.2
9.2
5.4
7.5
4.5
392 per station
8.3
B
Line
4.2.2
Selection of demand
Table 4.3 shows the demand of the first three months in 2010. CAS has estimated that the
future demand would increase by 12% a year. The demand of March 2010 is 4461 rolls
and this is the highest among the three months. Thus, the demand of March would reflect
the future demand better. As such, the author chose the demand of March for the
modeling of the production system.
Table 4.3: Demand of first three months in 2010.
Week
Weekly
demand (rolls)
Monthly total
(rolls)
1
2
3
4
747
1019
987
771
3524
March
February
January
Month
1
2
3
4
1
2
3
4
1003
798
1505
674
900
1142
1177
1242
3980
4461
The author excluded products that have infrequent and low demand in order to simplify
the problem. These products account for 1.2% of the total demand, so it would not have a
big impact on the accuracy of the model. The demand breakdown of all the products used
in the modeling is shown in table 4.4. The products are differentiated by two codes. The
lamination code is juice or milk. The size codes are numbers such as 465 and 350. The
lamination and size code together would form a product, for example Juice 465.
Table 4.4: Demand breakdown of March 2010.
Products
Juice 465
Wk 1 Wk 2 Wk 3
368
359
March
1079
181
489
Juice 350
89
Juice 811
31
Juice 813
95
243
258
173
769
Juice 466
Juice 565
Juice 460
Juice 560
Juice 585
13
291
7
80
86
98
131
17
15
83
48
136
81
32
57
172
67
94
71
216
730
172
221
240
Juice 600
8
2
39
49
Milk 465
Milk 460
Milk 702
87
78
8
37
16
28
8
163
134
24
Milk 811
9
1242
4404
Total (rolls)
882
132
Wk 4
352
87
58
89
11
32
16
20
1142
1138
___
29
4.2.3
Products allocation
The capacity on each line is determined to ensure that the weekly demand does not
exceed the capacity of line A and line B. The bottleneck (based on work station rate) of
each line is at the laminating stage. Table 4.5 illustrates the maximum rate of each work
station. The maximum rate on line A is 430m/min while the maximum rate on line B is
600m/min. The doctoring work stations and palletizers have a higher capacity than the
printers, laminators and slitters.
Table 4.5: Maximum rate of work stations.
Line B
Line A
Work station Maximum rate (rn/min)
600
P13
430
L21
1000
S54
Work station
P18
L22
S52
S53
S55
Maximum rate (m/min)
600
600
1000
800
1200
CAS has estimated that the maximum daily output of L21 and L22 is 80 rolls and 110
rolls respectively. The total time in a day is 1,440 minutes and the average length of a roll
is 5513m. The processing time, based on the maximum capacity of 430m/min (L21) and
600m/min (L22), is 12.8 minutes per roll and 9.2 minutes per roll, respectively. CAS
estimates that there is a capacity loss of 30%. This capacity loss includes setups, trial runs,
break downs, short stops, rush orders and others. Thus, the available time per day is 1,008
minutes (70% of 1,440 minutes). The maximum daily output is found using Eq. (4.3)
Maximum daily output =
Eq. (4.3)
Available time per day (mins)
Fastest processing time (mins)
1,008
Maximum daily output of L21 or line A =128
12.8
78.75 ~ 80 rolls per day
1,008
Maximum daily output of L22 or line B = 1
9.2
109.57 - 110 rolls per day
Thus, the weekly capacity of the two lines A and B are 560 rolls per week and 770 rolls
per week respectively. As such, the demand allocated to each production line must not
exceed this capacity.
The initial assignment of products to each line is based on the maximization of the
number of flying setups on line B. The setup time and setup cost is minimized by
maximizing the number of flying setups on line B. Table 4.6 illustrates the demand
breakdown of every product and their allocation on line A and line B based on the initial
assignment. The demand on line B is within the capacity of the line. However, the
demand on line A has exceeded the capacity of the line in three of the weeks. The
capacity of line A is 560 rolls a production cycle, but the demand for week 2, 3 and 4 is
more than 700 rolls.
Table 4.6: Products allocation based on initial assignment.
Line
Products
Juice 465
Wk 1 Wk 2
368
Line
A
Wk 3
359
Wk 4
352
March
1079
769
95
243
258
173
Juice 350
89
132
87
181
A Total
184
Juice 813
Products
Juice 466
Juice 565
Wk 1 Wk 2
13
98
B
Wk 3
48
Wk 4
57
March
216
730
291
131
136
172
489
Juice 460
7
17
81
67
172
2337
Juice 560
80
15
32
94
221
Juice 585
86
83
71
240
Juice 600
8
2
39
49
Juice 811
31
Milk 465
87
37
11
28
163
Milk 460
78
16
32
8
134
Milk 702
8
Milk 811
89
58
16
9
24
20
29
B Total
698
399
434
536
2067
A & B Total
882
1142
1138
1242
4404
One of the challenges in using dedicated production lines is the allocation of products on
each line. We observe that the demand on each line, based on the initial assignment, is
more than the capacity of the line. Therefore, CAS has to do products reallocation
between the lines during some of the production cycles to keep the demand on each line
within the capacity. The author has established three simple rules to determine the
allocation of products
1) All milk products are assigned to line B. Only L22 is capable of processing milk
products. Thus, all milk products must be on line B.
2) Juice products that are capable of having flying setups are assigned to line B.
Only L22 is capable of doing flying setups (for width difference smaller than
20mm). Setup time and cost is minimized by assigning products with width
difference smaller than 20mm to line B.
3) When the demand exceeds the capacity on line A, some products are moved from
line A to line B and vice versa. Both line A and line B have been assigned with 5
and 9 webs products. Only 5 or 9 webs products would be moved from line A to
line B when the capacity of the line is exceeded and vice versa. Products with
other types of webs on line B are not moved as this would be very disruptive to
the setup planning for the slitters. The routing of the products to the slitters is not
affected since S54 and S55 is assigned to slit the 5 and 9 web products.
Table 4.7 illustrates the product allocation on each line after demand adjustments. Some
of the products are moved from line A to line B. The author chose to move Juice 813 to
line B as moving other products do not help to keep the demand within capacity. Juice
811 is moved from line B to line A to increase the demand allocated on line A as flying
setup could not be done on Juice 811 alone on line B.
Demand fluctuations of each product are a hurdle for the dedicated production line as the
products might have to go through reallocations during some of the production cycles.
However, it is less complex for CAS to do product reallocation during some of the
production cycles than to plan the route for every product in each production cycle.
Table 4.7: Products allocation after demand adjustments.
Line A
Products
Wk 1
Juice 465
Juice 350
89
Juice 811
31
A Total
120
Wk 2
Wk 3
Wk 4
March
368
359
352
1079
132
87
181
489
58
500
B
Line
504
533
Products
Wk 1
Wk 2
Wk 3
Wk 4
March
Juice 813
95
243
258
173
769
Juice 466
13
98
48
57
216
89
Juice 565
291
131
136
172
730
1657
Juice 460
7
17
81
67
172
Juice 560
80
15
32
94
221
Juice 585
86
83
71
240
Juice 600
8
2
39
49
Milk 465
87
37
11
28
163
Milk 460
78
16
32
8
134
Milk 702
8
Milk 811
16
9
24
20
29
B Total
762
642
634
709
2747
A & B Total
882
1142
1138
1242
4404
4.2.4
Sequence of production
The production planning is done on a weekly basis in CAS. The orders are confirmed
several days before the start of each production cycle. Each production cycle starts on a
Monday and the cycle is 7 days. These orders are divided to each line according to the
assignment given in section 4.2.3 and then sequenced on each line. The proposed
production uses the first in first out (FIFO) rule on both lines. The production is
sequenced solely based on the setup costs of laminators as the setup costs on other work
stations are negligible compared to that of the laminators. Setup is required at the
laminators when there is a product family change or a paper width change. The PE
continues to flow down as waste during these setups and this waste is called drooling
waste. CAS estimates that the drooling waste costs $49 per minute.
The cost of drooling waste for different types of lamination setup is illustrated in table 4.8.
L22 is capable of doing flying setup when the paper width change is less than 20mm
from wide to narrow. Flying setup allows the setup to take place with minimum loss of
speed. Thus, the setup time is approximately zero minutes.
Table 4.8: Setup costs of laminators.
setup
time Drooling
($)
Work
station
Type of setup
Average
(mins)
L21, L22
40
L21, L22
Product family (juice to milk;
milk to juice)
Width (narrow to wide)
30
1,470
L21, L22
L21
L22
Width (wide to narrow, >20mm)
Width (wide to narrow, <20mm)
Width (wide to narrow, <20mm)
20
20
0 (flying setup)
980
980
0
waste
1,960
The author determined the sequence of the production on each line using three steps:
*
Separate the products into juice product family and milk product family. It is
indifferent in the order of the two groups. This step is only applicable to line B as
all the products on line A are juice products. This is the first step as the setup time
between product families is the longest. Thus, the setup between product families
is minimized.
wV
: -.....................
.- :::::
"
-
-
---
Sort the products within each group by their width with the widest width product
at the top. Thus, within each product family, the product with the widest width is
processed first and the product with the narrowest width is processed last. This is
because the setup time for wide to narrow is shorter than the setup time from
narrow to wide.
* When the product width is the same (e.g. Juice 350 and Juice 811), the products
with the same webs are placed together to minimize the setup time at the slitters.
The sequence of production is shown in table 4.9. The sequence of production line A is
Juice 465, followed by Juice 350 and Juice 811. Juice 350 and Juice 811 have the same
width of 1468mm. Juice 350 is produced first followed by Juice 811 so as to reduce the
number of web setups on S54 on line A. CAS is required to do 1 web setup during every
production cycle to change the web number from 9 to 5.
Table 4.9: Sequence of production.
Line B
Line A
Products
Juice 813
Products [Width (mm)
1574
Juice 465
webs
Sequence
1468
9
2
Juice 466
1468
5
3
Juice 565
Juice 460
Juice 560
Juice 585
Juice 600
Milk 465
Milk 460
Milk 702
Milk 811
Juice 350
Juice 811
Width (mm)
1533
webs Sequence
1
5
2
8
8
3
7
4
7
7
7
1574
1506
1506
1468
9
7
7
5
5
6
7
8
9
10
11
There are some products on line B that are highlighted. Products with the same
highlighted color indicate that flying setup is possible on that group of products. It is
found that there is no web setup time on loss on any of the slitters on line B. Although
43
S55 on line B is assigned to produce 5 web and 9 web products, time is not lost to do the
web setup of 60 minutes. After the production of Juice 813 (5 webs), the subsequent
products are 8 and 7 web products. Thus, S55 can do the web setup during this idle time.
After the production of Milk 465, the subsequent products are 7 web products. Thus, S55
can do the web setup during this idle time. After the production of Milk 811 (5 webs), the
subsequent product is also a 5 webs product (Juice 813). Thus, no web setup is required.
Therefore, there is no web setup of 60 minutes on any of the slitters on line B and there is
no disruption to the flow from L22 to the slitters.
4.2.5
Work station stoppage
There are several types of stoppages that would cause a work station in CAS to stop
production. They are categorized and explained in the following sections. These stoppage
data is extracted from CAS internal P2 system and analyzed using the Minitab software
to determine a suitable distribution. These stoppages are used in the simulation models of
the proposed production line and the current production line.
Breakdown
The printers, laminators and slitters experience breakdowns. However, the doctoring
work stations and the palletizers are well maintained by CAS and they do not breakdown.
The mean time between failures (MTBF) and average mean time to repair (MTTR) in
minutes for January to April 2010 are shown in table 4.10. The slitters are more reliable
than the printers and the laminators.
Table 4.10: Breakdown of work stations.
Work station MTBF (mins)
P13
P18
L21
L22
S52
S53
S54
S55
13,964
12,570
13,011
11,185
15,982
18,548
19,403
18,001
MTTR (mins)
61
63
57
65
11
9.5
9
6.5
Rest time
Work stations are made to rest due to 2 reasons. Firstly, they are rested during planned
maintenance. CAS does not have a fixed schedule for planned maintenance and the
planned maintenance time is very short. For example, the S54 has maintenance of 12
minutes in the entire month of March. Secondly, they are made to rest when sufficient
WIP is built up. The sufficient level of the WIP is based on the judgment of the process
managers. Thus, there are no strict rules to determine the level of WIP. The rest of the
work stations are shown in table 4.11.
Table 4.11: Rest time of work stations.
Work station
Total time (mins)
Mean (mins)
Frequency of rest
periods over month
of March
P13
P18
L21
L22
S52
S53
S54
S55
1,616
404
4,316
1,079
13,254
6,627
4,212
1,053
13,680
4,560
19,260
6,420
14,772
7,386
12,024
4,008
4
4
2
4
3
3
2
3
Short stop
Short stops occur when the work station did not breakdown but other activities caused the
production to stop. These activities could be formation of air bubbles, roll breakage and
misalignments. Short stop only occurs at the printers and laminators. The other work
stations do not experience short stops. Short stops occur at random. Table 4.12 shows the
distribution and frequency of the short stops.
Table 4.12: Short stop of work stations.
Work station
Mean (mins) per stop
Standard deviation
Distribution
Frequency of short stops
over month of March
P13
P18
L21
L22
17.7
13.3
Lognormal
17.8
17.4
Lognormal
33.9
26.7
Lognormal
39.1
31
Lognormal
146
172
41
81
Setup
Table 4.13 shows the setup time of the work stations. Printer setups occur when there is a
change of design or paper width. Laminator setups occur when the there is a change in
product family or paper width. The setup time of the printers and laminators varies
substantially even for the same type of setup. Thus, the author used the actual setup time
of printers and laminators in March for the simulation models. This distribution is more
reflective of the actual setup than the usage of a fixed setup time. Slitter setups occur
when there is a change in number of webs or paper stiffness. There is no actual data on
the web change setup as the slitters are assigned to slit only a single web in the current
production system. The web and paper stiffness change setup time is modeled as
deterministic whenever there is a change in the web and paper stiffness respectively.
Table 4.13: Setup time of work stations.
Work station
Mean (mins)
Slitters
P13
P18
Laminators
Slitters
17.6
15.1
Refer to table 4.5
60
15
0
Deterministic
Paper
stiffness
Standard deviation
11
9.3
0
0
Distribution
Lognormal
Lognormal
Deterministic
Frequency
654
678
Deterministic
Product family or
width change
Web
Reel inspection
Reel inspection only occurs at the slitters. The rolls are slit into smaller reels at the slitters.
The average roll length is 5513m. The reel length is 2595m. Thus, a single roll could be
slit into 2.12 sets of reels. Every time a set of rolls has been slit, the operators would need
to check the reels and separate the defective and non defective reels before sending them
to the doctoring work stations or palletizers. Table 4.14 shows the reel inspection time at
the slitters. These are actual data captured from CAS P2 system. The time in the table is
for the inspection for 1 roll and this inspection is required for every roll. Thus, it is
modeled for every roll that is processed by the slitter.
Table 4.14: Reel inspection time of slitters.
Work
S52
S53
station
S54
10.4
9.7
9.8
Mean (mins)
3.3
3.2
Standard deviation 3.1
Normal Normal Normal
Distribution
S55
10.6
3.1
Normal
4.3
Simulation modeling
4.3.1
Proposed production line
The modeling of the proposed production line is done using the SIMUL8 simulation
software. Figure 4.4 shows the screenshot of the proposed production line A and line B in
the software interface. There are 3 objectives for simulating the proposed production line.
Firstly, it is used to test out the feasibility of the route of products. Secondly, it is used to
determine a suitable configuration of the process times of the work stations in each line.
Thirdly, it is used to determine the card number (or level of WIP) of each line to meet the
demand of 1,657 rolls in line A and 2,747 rolls in line B. The demand used in both lines
is the March 2010 demand as explained in section 4.2.3. The simulation time is 40,320
minutes (4 production cycles, equal to four weeks). The simulation time is chosen to get
stable results. We found that a simulation time of 10,080 (1 production cycle) is not long
enough to determine stable results. However, a simulation time of 40,320 is able to
achieve stable results.
Juice465 Juice 350 Juice811
Line A co
LineAiorder
P135h
Juice813 Juice466 Juice565
0
0
0
stop
P13
Doctor1 (4)
L21 shortstop
L21
1111111S53
Juice460 Juice560 Juice585
S54reelinspection
354 (5 and9 webs)
Pa
r
1
Pa 1
ine A FGI
Paroute2
Pa2
Line8FGl
reelinspectionS53 (7webs)
c
LineB order
E
Juice 600 Milk 65 Milk460
card post
P18sh~rtstop
a]~~
Pit
L22shortstop
L22
4
S52reelinspection
0
S52(8webs)
'
0
0
0
t n lweis
reel inspection S53ou
S53
Milk 702 Mile811
0
0
Figure 4.4: Simulation model of proposed production line.
A
D c2(7)
The author made several assumptions in the simulation model of the proposed production
line. These assumptions are
" The travel time between work stations are zero. This is reasonable as the travel is
very short as compared to the other events such as processing time and stoppages.
" The raw materials required at every work station are always available. CAS kept
about 2 days of raw materials in the internal warehouse, so the chance of starving
the work stations is low.
* The production is modeled for the whole month of March. So, the demand for the
entire month is constant across the 4 weeks.
* There are no rush orders. There is no record of rush orders and the proportion of
rush orders is likely to be small. Thus, it is not important to model it.
e The entire roll is sent to the doctoring work stations when defects are found. In
the actual production, only reels with defects are sent to the doctoring work
stations. However, as the author used percentage (24%) to define the proportion
of defects present, it does not affect the accuracy whether it is modeled as a roll or
a reel.
The takt time required for each work station is calculated in section 4.1.2.3. The author
set the process time of each work stations to equal the takt time. The work stations are set
equal to the takt time to remove the imbalances in the production line. Thus, the work
stations all work at the same rate and do not produce ahead and build up inventory, as is
seen in the current production line. The process time of the work stations in each line are
shown in table 4.15. The card number (WIP) is varied in each of the configuration with
increment of 50 cards. Each line starts off with WIP in the laminating and slitting queue.
This is reasonable as each production cycle does not start with zero WIP. If 100 cards are
used, the laminating queue starts with 50 cards while the slitter queue starts with 50 cards.
Table 4.15: Process time of work stations in proposed model.
Line A work station
Number of station
Process time (mins)
P13
1
L21
1
16
23
S54
Doctor
1
4
392
Pal
1
24
Line B work station
Number of station
P18
1
Process time (mins)
9
L22
1
14
S52
1
10
S53
S55
1
11
1
10
Doctor
7
392
Pa2
1
14
13
There are 2 tools in SIMUL8 to model the proposed production line. The first tool is the
visual logic, which is the language used in the software. The author used this visual logic
to route the cards from the palletizers to the 'CONWIP card post'. When a roll leaves the
line through the palletizer, visual logic increases the number of cards in the 'CONWIP
card post' by 1. An order only enters the system when there is both an order and a card at
the 'CONWIP card post'. The visual logic used for the routing of the cards in both lines
is
Pal Work Complete logic
Add Work to Queue Products, Line A CONWIP card post
Pa2 Work Complete logic
Add Work to Queue Products, Line B CONWIP card post
The second tool is called label. The author attached labels to each roll to direct the roll to
the correct slitter based on the number of webs the roll has. A roll with 7 webs is labeled
as '1', a roll with 8 webs is labeled as '2' while a roll with 5 or 9 webs is labeled as '3'.
These labels are read when the roll leaves L22 and then directed to the intended slitter.
4.3.2
Current production line
The modeling of the current production line is also done by SIMUL8 software. Figure 4.5
shows the screenshot of the current production line in the software interface. The
objective of simulating the current production line is to verify that the method of
modeling the proposed production line is credible. The printed WIP (WIP between
printers and laminators), laminated WIP (WIP between laminators and slitters) and the
doctor WIP (WIP waiting to be doctored) in the model is compared with the actual WIP
in March for verification. The demand is 4404 rolls and the simulation time is 40,320
minutes (4 production cycles).
052 reelinspecaionS52 rest S52(5 and8 webs)
0 0
Juice465Juice350 Juice811
0
Juice813 Juice466 Juice565 Pl3shortstop Pl3rest
P13
L21 shodstop L21rest
L2e
Dodor(11)
o
s
Pal
Or~rs
Pr
g
L ro ngi-
a ute
FG
Pa 2
Juce40 Jue
c6 5
Juice585 P18ish
itstop
P18rest
P8
L22 sh
stop L22rest
02
54 teel ispecton
S54 est
S54(9 webs)'
4r
Juice600 Milk465 Milk460
9 vb routinr
0S55
Milk702 Mik~l1
S4 (9wes
reenspection
esS55
(9
wet)
Figure 4.5: Simulation model of current production line.
The assumptions made in this model are the same as that in the model of the proposed
production line. In the current model, S52 is assigned to slit 5 and 8 webs products, S53
is assigned to slit 7 web products and S54 and S55 are assigned to slit 9 web products. 11
doctoring work stations are used in the current model. The current production line is
modeled to have WIP at the laminator and slitter queues at the start of the simulation.
There are 396 rolls in the laminator queue and 564 rolls in the slitter queue on the last day
before the start of the March production. Therefore, the author used the same number for
modeling.
.....
The number of rolls processed by each work station is extracted from CAS internal P2
system. The length of the products produced by each work station in March is shown in
table 4.16. The percentage of the rolls going to each work stations is calculated using Eq.
(4.4)
% of rolls =
Length processed at work station(m)
Total length produced at same type of work station(m)
Eq. (4.4)
The percentage of rolls processed by the doctoring work stations is extracted directly
from CAS internal P2 system. The process time for each of work station is shown in table
4.17. The data is also extracted from CAS internal P2 system.
Table 4.16: Percentage of rolls processed by each work station.
Work
station
P13
P18
L21
L22
Doctors
Processed
length(m)
15,280,000
13,237,000
11,787,000
19,371,000
% of
rolls
Rolls
53
47
37
63
2334
2070
1629
2775
24
1052
Work
station
S52
S53
S54
S55
Processed
length(m)
7,121,000
5,679,000
6,829,000
8,264,000
% of
rolls
25.5
20.3
24.6
29.6
Table 4.17: Process time used in current production line model.
Work
station
P13
P18
L21
L22
S52
IS53
IS53
Run
speed
(m/min)
546
519
410
548
1,000
800
800
Process
time
(min/roll)
10.1
10.6
13.4
10.1
5.5
Work
station
S54
Run
speed
(m/min)
1,000
S55
1 200
Doctoring
(11)
Pal
Pa2
Process
time
(min/roll)
5.5
4.6
392
8.3
8.3
Rolls
1123
894
1083
1303
4.4
Improvement analysis
4.4.1
Conversion between rolls and reels
Figure 4.6 illustrates the splitting of a single roll into smaller reels. A roll is equivalent to
16.5 reels. The weighted average length of a roll is 5513m and all reels have the same
length of 2595m. Thus, a roll is split into 2 sets of reels of normal length (2595m) and a
third set of reel of shorter length (323m on average). The shorter reel is combined with
other shorter reels and delivered to the customers like the reels of normal length. As such,
a roll is equivalent to 2.12 sets of reels on average. For each set of reels, there are several
webs (5, 7, 8 or 9). The weighted average number of webs is 7.8 webs. Therefore, the
number of reels in a roll is found using equation Eq. (4.5)
Number of reel
=
Number of webs x
Length of roll ()(4.5)
Length of reel (in)Eq(45
Number of set of reel
Number
of webs
2595m
5513m
Figure 4.6: Slitting of a roll into reels.
4.4.2
Inventory holding costs
CAS estimated the inventory holding costs for the three types of inventory. Table 4.18
shows the inventory holding costs for the printed WIP, laminated WIP and the doctor
WIP. The inventory holding costs of each month is found using equation Eq. (4.6)
Inventory holding cost($/month) = Number of rolls x holding cost ($/roll/month)
Eq. (4.6)
Table 4.18: Inventory holding costs of three types of WIP.
Inventory type Inventory holding cost per roll per month ($)
Printed WIP
Laminated WIP
Doctor WIP
4.4.3
95
116
130
Lead time
The lead time is calculated using the Little's Law. The total WIP is calculated by adding
the printed WIP, laminated WIP and the doctor WIP. The lead time is then found using
Eq. (4.7)
Lead time
(days) =
Total WIP in production line(rolls)
Throughput (rolls/day)
Eq. (4.7)
CHAPTER 5: RESULTS AND DISCUSSION
5.1 Current production line
The purpose of building the simulation model of the current production line is to verify
that the method of modeling the production line is credible. Table 5.1 shows the average
printed WIP, laminated WIP, doctor WIP and their standard deviation from 20 simulation
runs. The throughput of the model is 4,526.6 rolls. This throughput is reasonable as the
author has excluded a small percentage of the products. Thus, the throughput is higher
than 4,404 rolls. The average printed WIP is 310.7 rolls while the average laminated WIP
is 618.2 rolls. The average doctor reel WIP 861.0 reels. A roll is equivalent to 16.5 reels.
Table 5.1: Performance of the current production line model.
Simulation Object
Throughput (4 weeks)
Printed WIP
Laminated WIP
Doctor WIP (reels)
Average (rolls) Standard deviation
35.8
4,526.6
25.0
310.7
7.0
617.0
85.8
861.0
The results from the model of the current production line are compared with the actual
inventory level in March 2010 to find the error of the model. Table 5.2 shows the
inventory level of the model and the actual production line as well as the percentage error.
It is found that the model has underestimated the printed WIP and the laminated WIP and
has overestimated the doctor WIP. However, the percentage error of the model is low.
The highest percentage error is only 6.8%. Thus, the method of modeling the current
production line represents the actual production line well. It is expected that the modeling
of the proposed production line has a good prediction of the actual performance since the
method of modeling is the same.
Table 5.2: Error in the current production line model.
Model (roll) March inventory (roll) Error (%)
Inventory type
2.5
318.7
310.7
Printed WIP
6.3
658.5
617.0
Laminated WIP
6.8
806.3
Doctor WIP (reel) 861.0
5.2 Line A performance
5.2.1
Throughput and card number
The number of cards has been varied to find the number of cards that gives the
production line A a throughput of more than 1657 rolls in a four-week period (four
production cycles). Figure 5.1 illustrates the throughput trend when the card number is
increased at interval of 50 cards while table 5.3 shows the throughput mean and standard
deviation of the 20 simulations. We found that the throughput is increased when the card
number is increased. However, there is a critical point beyond which a higher card
number does not help to increase the throughput of the production line. The throughput
reached its highest throughput of 1714 rolls at the card number of 250 and the increment
of card number to 300 does not help to increase the throughput.
1,720
1,710
1,700
0
.21,0
.
0
1,680
1,670
1,660
1,650
50
100
150
200
250
300
Card number
Figure 5.1: Throughput trend of line A.
It is also found that the increment of throughput increment diminished as the card number
is increased. Thus, holding more inventories in CAS does not give the same throughout
increment. Holding more inventories would only cause CAS to incur unnecessary
inventory holding costs and tie up the capital.
We found that line A is able to give a throughput of more than 1657 rolls when the card
number is 100. A card number of 50 is not able to achieve the target throughput. Thus,
the use of 50 cards is not feasible. If the work stations are made to work at a faster rate,
an even lower card number could be achieved for the same throughput requirement.
However, a lower card number is not realistic as unexpected variations might cause the
work stations to be starved during production.
Table 5.3: Throughput mean and standard deviation in line A.
Card number
50
100
150
200
250
300
5.2.2
Mean (rolls) Standard deviation
11.8
1,655.4
12.0
1,678.2
12.6
1,703.5
10.4
1,713.0
10.1
1,714.4
10.2
1,714.0
WIP inventory
The next performance measure of the configurations is the average printed, laminated and
doctor WIP. The 3 types of WIP are shown in table 5.4, 5.5 and 5.6. A shaded box means
that the particular card number is not feasible as the throughput is below 1657 rolls.
These non feasible card numbers are not discussed in the rest of the discussion.
We found that the minimum average printed WIP is 63.5 rolls and it is achieved when
100 cards are used. The average printed, laminated and doctor WIP increases when the
card number is increased. The minimum average laminated WIP is 15.7 rolls while the
minimum average doctor WIP is 142.5 rolls.
11I'll-
111,__- _R,
w"aLQij%
I
,
-
Table 5.4: Average printed WIP in line A.
Card number
50
100
150
200
250
300
Mean (rolls) Standard deviation
4.5
27.2
6.1
63.5
8.0
94.5
9.5
121.2
9.7
146.9
9.8
172.3
Table 5.5: Average laminated WIP in line A.
Card number
50
100
150
200
250
300
Mean (rolls)
5.3
15.7
31.9
53.4
77.6
102.2
Standard deviation
1.2
3.3
6.0
8.5
9.3
9.3
Table 5.6: Average doctor WIP in line A.
Card number Mean (reels)
110.4
50
142.5
100
164.6
150
174.7
200
177.2
250
178.0
300
Standard deviation
63.4
79.4
89.0
90.6
90.2
90.5
...............................................
....
.....................................
.....
...
..
.
5.3 Line B performance
5.3.1
Throughput and card number
The number of cards has been varied to find the number of cards that gives the
production line B a throughput of more than 2747 rolls in a four-week period. Figure 5.2
illustrates the throughput trend when the card number is increased at interval of 50 cards
while table 5.7 shows the throughput mean and standard deviation of the 20 simulations.
We also observe in production line B that the increment of throughput decreased when
the card number is higher. Thus, a high card number has diminishing effects on the
throughput increment of the line.
2,900
2,800
2,700
U1
-5
:
0
2,600
2,500
,00
2,300
2,200
50
100
150
200
250
300
Card number
Figure 5.2: Throughput trend of line B.
We found that the minimum card number required to achieve the throughput of 2747 rolls
is 200 cards. We note that 150 cards are able to achieve a throughput of nearly 2747 rolls,
but it does not reach the target. Thus, card numbers 50 to 150 are not feasible.
Table 5.7: Throughput mean and standard deviation in line B.
Card number
50
100
150
200
250
300
5.3.2
Mean (rolls) Standard deviation
15.7
2,222.9
15.9
2,644.5
13.4
2,722.4
14.0
2,753.9
14.9
2,785.2
18.4
2,785.2
WIP inventory
The average printed, laminated and doctor WIP are shown in table 5.8, 5.9 and 5.10. A
shaded box means that the particular card number is not feasible as the throughput is
below 2747 rolls. Thus, they are ignored in the rest of the discussion. We found that the
minimum average printed WIP is 109.4 rolls when 200 cards are used. The minimum
average laminated WIP is 59.9 rolls while the average doctor WIP is 108.6 reels.
Table 5.8: Average printed WIP in line B.
Card number Mean (rolls)
Standard deviation
50
4.0
0.4
100
150
200
250
300
21.5
62.1
109.4
155.1
201.0
2.2
3.6
3.5
4.2
4.2
Table 5.9: Average laminated WIP in line B.
Card number Mean (rolls) Standard deviation
0.9
34.3
50
100
54.5
1.7
150
200
250
300
58.3
59.9
61.8
63.2
1.8
1.9
1.8
1.8
Table 5.10: Average doctor WIP in line B.
Card number Mean (reels)
16.9
50
Standard deviation
6.3
100
77.2
34.4
150
99.1
45.5
200
250
300
108.6
125.1
118.1
49.4
61.9
25.0
The laminators are the only work stations in CAS that must be in operation continuously.
It is expensive to starve the laminators. When the laminator is starved, it has to be shut
down and it is required to be restarted (cold start) to process the roll. It costs about $9,000
each time a cost start is required. The process time of L22 is 14 minutes in the proposed
production system. The average length of a roll is 5513m. Thus, the work station rate is
393 m/minute. Figure 5.3 depicts the printed WIP during the simulation when L22
process time is 14 minutes (aligned to takt time) and 200 cards are used. It is observed
that the minimum printed WIP is 71 rolls. Therefore, L22 is not starved at all times.
Figure 5.3: Printed WIP with L22 process time = 14minutes.
CAS should take precautions to prevent local autonomy of the laminator workers to
change the work station rate and stray away from the intended takt time. Figure 5.4
shows an illustration of the printed WIP during the simulation when L22 process time is
12 minutes (not aligned to takt time) and 200 cards are used. A process time of 12
minutes corresponds to work station rate 460 m/minute. We observe in figure 5.4 that the
printed WIP reached zero about 7 times, which would force a shutdown of the printer. If
L22 were starved 7 times, the cold start costs are about $63,000.
Figure 5.4: Printed WIP with L22 process time = 12minutes.
5.4 Inventory level and holding costs
The inventory level in both line A and line B are compared with the actual inventory
level in March 2010 to determine the cost savings for the proposed production lines.
Table 5.11 shows the inventory of the proposed production line and the actual inventory
in March 2010. It is evident that all the inventory types are lower for the proposed
production line. The printed WIP is reduced by 46%, the laminated WIP is reduced by 88%
and the doctor WIP is reduced by 68%. The total WIP is reduced by 74% from 1,026
rolls to 263 rolls.
Table 5.11: Inventory reduction.
Printed WIP
(rolls)
Laminated
WIP (rolls)
Doctor WIP
(reels)
Total WIP
Line A
Line B
Proposed production
line total
Actual inventory
level (March)
% reduction
63.5
109.4
172.9 (65%)
318.7 (31%)
46
15.7
59.9
75.6 (29%)
658.5 (64%)
88
142.5
87.8
108.6
175.9
251.1 (6%)
263.7
806.3 (5%)
1,026.1
68
74
In the current production line, more WIP is stored as laminated WIP (64%) instead of
printed WIP (31%). It is more expensive to store buffers downstream as more value has
been added to the roll. Thus, the inventory holding costs is much higher in March. In the
proposed production line, 65% of the inventory is stored as printed WIP while 29% is
stored as laminated WIP. As such, the inventory holding costs is lower.
Table 5.12 illustrates the inventory holding costs of the proposed production line and the
current production line in March 2010. It is found that the inventory holding costs is
$27,173 per month for the proposed production line while the inventory holding costs is
$113,014 for the current production line. Thus, the inventory holding cost savings is
85,840 per month. This is a 76% reduction in inventory holding costs.
Table 5.12: Inventory holding cost savings.
Proposed
Actual inventory
Line A
Line B
production line total
level (March)
Savings
Printed WIP ($)
6,033
10,393
16,426
30,275
13,849
Laminated WIP ($)
Doctor WIP($)
1,821
1,123
6,948
856
Total
8,770
1,978
27,173
76,386
67,616
6,353
113,014
4,374
85,840
Figure 5.5 depicts the inventory holding costs of the proposed production line, the current
production line from January to May 2010 and the average inventory holding costs of
these 5 months. It is observed that the proposed production line has a lower inventory
holding costs as compared to any of the months in 2010. The monthly average inventory
holding costs in 2010 is $109,530. Therefore, the annual inventory holding costs of the
current production line is estimated to be $1,314,360. The annual inventory holding costs
of the proposed production line is expected to be $326,076. Thus, the annual inventory
holding costs savings is $988,284.
Figure 5.5: Inventory cost of proposed production line.
- t --
--
--
-
-
- -
- - -
-Aw-A
I
'-
- --
5.5 Warehouse capacity
The warehouse capacity allocated for the printed and laminated WIP is 500 rolls while
the warehouse capacity allocated for the doctor WIP is 500 reels. Figure 5.6 illustrates the
capacity allocated for the printed and laminated WIP and the actual WIP in the first 5
months of 2010. It is evident that all the 5 months in 2010 has exceeded the warehouse
capacity allocated to the WIP. The WIP has exceeded the warehouse capacity by about
100% in February, March and April. As such, the warehouse has been piled up with too
much inventory and the working lanes for forklift are forced to make way for these
excess inventory. This high inventory caused the workers to take a longer time to excess
the rolls.
From the simulation, it is found that the proposed production line has an average of 248.5
rolls of WIP. This is 50% of the capacity allocated for it. Thus, the proposed production
line WIP is kept within the capacity. During the actual production, the WIP would
fluctuate. However, as the total card number used is 300 cards, the WIP in the production
line would not exceed 300 rolls. Thus, the capacity allocated would not be exceeded at
any point of time.
1200
1039
1000 -
-
-
97f
-983
901
832
800
0
50
600
E
2
-500
z
400
200
0
Proposed
Capacity
Jan
Feb
Mar
Apr
2010
Figure 5.6: Capacity of printed and laminated WIP.
May
The capacity allocated for the doctor WIP is 500 reels. Figure 5.7 shows the capacity
allocated for the doctor WIP and the doctor WIP in the first 5 months of 2010. It is
observed that the capacity allocated for the doctor has been exceeded in all the months.
The doctor WIP in April is about 3 times of the capacity while the doctor WIP in May is
nearly 4 times of the capacity. CAS has a general area allocated to store the doctor WIP.
However, within that area, the reels could be placed anywhere. Thus, it is difficult for the
workers to find the correct reel to be doctored when the number of doctor WIP is high.
The workers mainly rely on their experience to navigate and find the correct reel.
We found that the doctor WIP in the proposed production line is 251.1 reels. This is 50%
of the capacity. Thus, WIP is kept within the capacity. In addition, the workers would be
able to find the correct reel to be doctored faster as the number of doctor WIP reels is
lower. Since the printed, laminated and doctor WIP utilizes about 50% of the capacity
allocated to them, it gives CAS the opportunity to bring some of the inventories stored in
the external warehouse back to the internal warehouse. This gives CAS the added
advantage of reducing the high inventory costs in the external warehouse.
2000
1880
1800
1657
1600
1400
1200
0
1000
.0
E
806
800
600
--
3
400
251.1
200
0
Proposed
Capacity
Jan
Feb
Mar
2010
Figure 5.7: Capacity of doctor WIP.
Apr
May
5.6 Lead time
The production lead time quoted to customers is 12 days. The production lead time takes
up about 10 days while the 3 rd party logistic company requires about 2 days to manage
the finished goods inventory. Figure 5.8 shows the production lead time of the proposed
production line and the production lead time in the first 3 months in 2010.The production
lead time is about 6 to 7 days. The current production lead time is long as the WIP in the
production line is high. A roll has to wait for all the previous rolls to be processed before
it could be processed. Thus, the average time a roll spends in the production is long.
From the simulation, the lead time of the proposed production line is found to be 1.9 days.
This lead time of the proposed production line is the time from the release of a roll to the
completion of a roll. It should be noted that this lead time does not include the waiting
time of a roll to get a CONWIP card. This proposed production lead time is compared
with current production lead time in March 2010. The lead time reduction is 4.5 days or
70%. This shorter lead time would make CAS more competitive within the company. The
shortest lead time is quoted by the plant in China, and is 7days. The 1.9 days of
production lead time together with the 2 days of lead time required by the 3 rd party
logistic company makes the total lead time to be 3.9 days. Thus, this lead time is shorter
than any of the other plants. As the lead time is shortened, it makes CAS more
competitive to the external company C.
7.0
6.4
6.0
5.0
E
4.0
-U
e3.0
2.0
1.0
0.0
Proposed
)an
Feb
Mar
2010
Figure 5.8: Lead time of proposed production line.
CHAPTER 6: RECOMMENDATIONS AND CONCLUSION
This thesis uncovered the problems with the current production line. It is demonstrated
that the production line could be improved by making the three major changes of using
dedicated production lines, changing to pull production system and aligning the
production rate to the takt time. It is found that the WIP in the production line is reduced
by 70% from 1,026 rolls to 300 rolls when the proposed production line is used. This
improvement helps CAS to save $988,284 annually and eliminates the capital tied up by
the inventories. In addition, the strain on the internal warehouse capacity is removed as
the printed WIP, laminated WIP and the doctor WIP takes up only about 50% of the total
warehouse capacity. The reduction in WIP also alleviates the potential safety issues and
time wasted in looking for the WIP in the internal warehouse. In addition, the production
lead time is reduced from 6.4 days to 1.9 days. The reduction in production lead time puts
CAS in a better position to fend off internal and external competition.
There are several recommendations to CAS. Firstly, the author recommends switching
only 5 and 9 webs products between lines when the demand has exceeded the capacity of
the lines. This reduced the need of reassigning products to the slitters since S54 and S55
are both assigned to slit 5 and 9 web products. However, there is an opportunity for CAS
to look for a more detailed rule for switching products across lines.
Secondly, it is recommended that each slitter is assigned to slit only one or two type of
products. This avoids the disruption of flow by the long web setup time. Thirdly, it is
recommended that 4 doctoring work stations are assigned to line A while 7 doctoring
work stations are assigned to line B. The rest of the work stations should remained as
backup to either lines. These backups would help to buffer against any unexpected
fluctuations of the percentage of defects on each line. CAS should do further analysis to
determine if there is any correlation between product types and percentage of defects.
Fourthly, the minimum WIP required for line A is 100 rolls while the minimum WIP for
line B is 200 rolls. Thus, the total WIP required is 300 rolls. The author recommends that
CAS does not reduce the total WIP to 300 rolls at once. The proposed production line is a
major change to the way CAS has been operating. Since the warehouse capacity allocated
to the printed and laminated is 500 rolls while the warehouse capacity allocated to the
doctor WIP is 500 reels, CAS could first reduce the level of WIP to 500 rolls to eliminate
the warehouse capacity problem. CAS could then reduce the WIP level gradually to 300
rolls. This would allow all the employees to have time to adapt to the changes and to
build up their confidence in the proposed production line.
Lastly, it is recommended that CAS should look into the way the KPI is structured. The
OEE KPI is tied to the employees' bonuses. Thus, there would be resistance to the
implementation of the proposed production line. The changes to the production line
should be communicated carefully to the employees. In addition, the KPI should be
altered to ensure that no one is penalized by moving towards the proposed production line.
Without changes to the KPI, the employees would have a tendency to fall back to the old
way of doing things.
In conclusion, CAS is recommended to adopt the three major changes of using dedicated
production lines, changing to pull production system and aligning the production rate to
the takt time to control the WIP.
CHAPTER 7: FUTURE OPPORTUNITIES
The author identified two areas where future studies could be made. Firstly, it is
mentioned that the cold start of the laminators costs $9,000 each time and it is expensive
to CAS. Therefore, the laminators are made to run continuously. However, it costs CAS
about $840 an hour to run the laminators. This cost includes the energy and the labor cost.
Therefore, there is a trade off between running the laminators continuously and shutting
down the laminators. This trade off is important when the demand on the line is low and
the laminators have the chance to be switched off when the demand has been met. It is
worthwhile to determine two things. Firstly, verifications should be done to determine
whether the laminators should be shut down at times to achieve a lower cost. Secondly,
the duration of each shut down should be determined.
The second area is to reduce other types of inventory that CAS holds. This thesis is
focused on the control of WIP in the internal warehouse. These WIP make up 19% of all
the inventories in monetary value. The base materials make up 35% and the FGI make up
another 35%. The remaining 11% of the inventories are the straws and packaging
materials. Due to the high level of inventory, CAS internal warehouse could not
accommodate all of the inventories. CAS stores an average of 2031 rolls of FGI in the
internal warehouse and stores an average of 1720 rolls of FGI in the external warehouse
in 2010. The author has identified a few causes of the high FGI. Firstly, the shipment to
the customers is infrequent (twice a week). Therefore, the FGI has to wait in the
warehouse for the shipment date. Secondly, some customers postponed the delivery date
after the production has been completed. Thus, CAS stores these FGI in the warehouse
out of goodwill. The storage of the FGI in the external warehouse is expensive. Thus,
there is a huge opportunity to reduce the level of FGI in order to reduce the inventory
costs.
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