Analysis of the Production System at
ABB Combustion Engineering Newington Operations
by
Rhonda L. Patton
B.S., Mechanical Engineering (1999)
Massachusetts Institute of Technology
Submitted to the Department of Mechanical Engineering
in Partial Fulfillment of the Requirements for the Degree of
Master of Science in Mechanical Engineering
at the
Massachusetts Institute of Technology
June 2000
0 2000 Rhonda L. Patton
All rights reserved
The author hereby grants to MIT permission to reproduce and to
distribute publicly paper and electronic copies of this thesis document in whole or in part.
Signature of A uthor...............................................
Department of Mechanical Engineering
May 5> 2000
C ertified by ........................................................
David S. Cochran
Assistant Professor of Mechanical Engineering
A ccepted by .........................................................
Am A. )omn
Chairman, Committee on Graduate Students
MASSACHUSETTS INSTITUTE
OF TECHNOLOGY
SEP 2 0 2000
LIBRARIES
Analysis of the Production System at
ABB Combustion Engineering Newington Operations
by
Rhonda L. Patton
Submitted to the Department of Mechanical Engineering
on May 5, 2000 in partial fulfillment of the
requirements for the Degree of Master of Science in
Mechanical Engineering
ABSTRACT
ABB Combustion Engineering Nuclear Power Newington Operations is a manufacturer
of industrial and nuclear equipment located in Newington, New Hampshire. This thesis
examines the current production system at ABB and applies the Manufacturing System Design
Decomposition, developed by Professor David Cochran, Professor Paulo Lima, and the students
of the Production System Design Laboratory at MIT, to begin planning the transition to a lean
manufacturing system for the production of spent fuel dry storage canisters. Lean manufacturing
is based on the philosophies of the Toyota Production System, developed by Taiichi Ohno. Justin-time and autonomation are the two main pillars of TPS. The ultimate goal of TPS is to
eliminate all waste in the system, which is accomplished by setting up cells, which reduce travel
distance, producing exactly the amount needed when needed, which minimizes inventory and
prevents overproduction, and eliminates all non-value adding activities.
The main obstacles that ABB must deal with in transitioning to a lean manufacturing
system are resistance to change, the challenge of combining a cellular manufacturing system
with a project shop manufacturing system, and working with the quality regulations set forth in
the ASME Boiler and Pressure Vessel Code. ABB Newington has been producing industrial and
nuclear equipment for over 40 years now. Many of the employees at ABB have been working
there for a significant length of time. For these reasons, changing the philosophy of production
is going to be difficult. Some of the components of the spent fuel canisters are extremely large
and can't be moved easily. As a result, the production system at ABB will have to combine
typical cellular manufacturing methods with project shop methods, where some of the
components remain stationary and other parts come to them. Lastly, ABB must deal with the
fact that the ASME Code prohibits inspection of parts by anyone that performed or directly
supervised the work being inspected. Thus, self inspection as part of the cell work loop is
impossible. ABB must be creative in dealing with this challenge and try to find ways to
compromise between the stipulated inspection requirements and the ideals of TPS.
Thesis Supervisor: David S. Cochran
Title: Assistant Professor of Mechanical Engineering
3
4
TABLE OF CONTENTS
TABLE OF CONTENTS ..............................................................................
L IST O FIG URE S ......................................................................................
LIST O F T A B LE S ......................................................................................
ACKNOWLEDGEMENTS ............................................................................
1.0 Introduction and General Background Information................................................9
1.1 ABB Combustion Engineering Nuclear Power Newington Operation..............
1.2 Spent Fuel Dry Storage Canister Production..........................................
1.3 O u tlin e ........................................................................................
2.0 "Lean" Manufacturing..............................................................................
2.1 Toyota Production System...............................................................
2.2 Manufacturing System Design Decomposition..........................................
2.2.1 Axiom atic D esign...............................................................................
2.2.2 Manufacturing System Design Decomposition.............................................15
5
6
6
7
9
10
11
12
12
14
14
16
2 .3 In spection ...................................................................................
2.3.1 Statistical Process Control and Acceptable Quality Levels.................................17
2.3.2 Judgem ent Inspection...............................................................................22
. 22
2.3.3 Inform ative Inspection.......................................................................
3.0 Existing Conditions and Project Goals...........................................................
3.1 C urrent Plant L ayout........................................................................24
3.2 Flow of Parts and Information.............................................................26
3.3 Scrap, Non-conformances, and Corrective Action...................................28
3 .4 Inspection ...................................................................................
3.5 W orker Activities.........................................................................
3 .6 S chedulin g ....................................................................................
3.7 Project G oals..............................................................................
4.0 MSD Decomposition Applied to ABB Newington..............................................
4.1 Top Three Levels of PSD Decomposition...............................................
4 .2 Qu ality ........................................................................................
4.3 Identifying and Resolving Problems....................................................
4.4 Predictable Output.......................................................................42
4.5 D elay Reduction...........................................................................
4 .5 .1 T akt Tim e ............................................................................................
24
29
30
32
33
34
34
37
40
45
47
4.5.2 F loor L ayout...................................................................................
. .. 49
4.5.3 Sam ple M achining C ell........................................................................
4 .5 .4 In spection .......................................................................................
51
. . 55
4 .6 D irect L ab or.................................................................................
4 .7 Indirect L abor................................................................................59
5.0 Concluding Comments.............................................................................
5.1 S ummary ....................................................................................
5 .2 O b stacles....................................................................................
5.3 T he N ext Steps..............................................................................
5.4 F inal C om ment..............................................................................
R EFE R E N CE S ..........................................................................................
A PP EN D IX A .............................................................................................
5
57
60
60
60
61
63
65
66
LIST OF FIGURES
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
2-1:
2-2:
2-3:
2-4:
2-5:
3-1:
3-2:
3-3:
3-4:
3-5:
O verall layout of the M SD D ..............................................................
16
Normal distribution curve with p = 0, a&= 1.........................................
18
Graphical representation of (x-error....................................................
19
Graphical representation of B-error....................................................
20
Confidence intervals of a standard normal distribution...............................
21
Current layout of the Light Manufacturing Building.................................
25
Current layout of the Heavy Manufacturing Building...............................
25
Histogram of inspection times...........................................................
30
Pareto chart of worker activities during a random 2-hour time slot...............31
Percentage of total worker hours spent on each operation/activity during
a random 2-hour time slot.............................................................
31
Figure 3-6: Pie chart of value adding, non-value adding but necessary, and waste
during a random 2-hour time slot......................................................
32
Figure 4-1: Levels I, II, and III of the MSDD.........................................................35
Figure 4-2: "Quality" branch of the MSDD.........................................................
38
Figure 4-3: "Identifying and Resolving Problems" branch of the MSDD.......................
41
Figure 4-4: "Predictable Output" branch of the MSDD...........................................
43
Figure 4-5: "Delay Reduction" branch of the MSDD.............................................
46
Figure 4-6: Typical cellular manufacturing layout of the ship building industry................ 49
Figure 4-7: Possible linked-cell layout for production of canisters at ABB.....................
50
Figure 4-8: Machine-part matrix used to establish part families..................................
52
Figure 4-9: Possible layout for the sample machining cell........................................
54
Figure 4-10: "Direct Labor" branch of the MSDD................................................
57
Figure 4-11: "Indirect Labor" branch of the MSDD.................................................
59
LIST OF TABLES
Table 2-1:
Table 3-1:
Table 4-1:
Table 4-2:
Table 4-3:
Type I and Type II errors of the Decision Making process............................
Sample travel distances of selected parts.................................................
Part demand in sample machining cell...................................................
Cycles times of each part at each machine in the sample cell.........................
Improvements resulting from formation of sample machining cell..................
6
20
28
52
53
54
ACKNOWLEDGEMENTS
I would like to thank Professor David Cochran for providing guidance and inspiration for
this thesis. I would also like to thank everyone at ABB Combustion Engineering in Newington,
New Hampshire for their constant support and assistance. I certainly couldn't have done this
thesis without their help.
'7
8
1.0 INTRODUCTION AND GENERAL BACKGROUND INFORMATION
This thesis presents a methodology that can be used as a guideline in the transformation
of a traditional job shop plant to a lean manufacturing plant in the nuclear industry and is based
on studies done during an internship at ABB Combustion Engineering Nuclear Power (ABBCENP), Newington Operations (Newington) in Newington, New Hampshire. The internship
project was primarily a "feasibility study" to examine the major roadblocks that ABB would
have to confront in developing a lean manufacturing system and devise a plan to deal with these
major issues. While the details of the system pertain particularly to ABB-CENP Newington
Operations, the general philosophies and methodologies can be applied to many other
manufacturing plants, particularly those in the nuclear industry or other highly regulated
industries.
In particular, the issue of quality control and quality assurance is largely addressed in this
thesis. The requirements for quality inspection imposed upon ABB (and the nuclear industry, in
general) by the U.S. government are in direct conflict with the main principles of cellular
manufacturing. The work done in this thesis examines that conflict and addresses possible
compromise.
1.1 ABB Combustion Engineering Nuclear Power Newington Operations
ABB-CENP Newington Operations is a manufacturer of industrial and nuclear
equipment. For more than 40 years, Newington has been manufacturing high precision stainless
steel and high alloy components for the nuclear energy industry. Newington manufactures the
reactor vessel internals (RVIs), which provide a support structure for the core and provide a flow
path within the reactor vessel; the control element drive mechanisms (CEDMs), which are
9
electromechanical devices that insert and withdraw the control element assembly; and the reactor
coolant pumps (RCPs), four pumps that circulate water through the reactor coolant system, each
with a rated flow from 85,000 to 120,000 gallons per minutes at 8,000 to 12,000 horsepower.
Newington Operations is part of Nuclear Systems, a division of ABB Combustion
Engineering Nuclear Power, Inc.. Newington Operations employs 144 employees, 95 of which
are hourly employees.
The facilities in Newington consist of two large manufacturing warehouses, one known
as the "light manufacturing" building and the other known as the "heavy manufacturing"
building. The light manufacturing building runs two shifts, while the heavy manufacturing
building runs three shifts. There is also a building that houses quality assurance, including all
retained quality assurance records, and another building that houses design engineering, human
resources, production control, and purchasing.
1.2 Spent Fuel Dry Storage Canister Production
In December of 1998, ABB-CENP Nuclear Systems won a contract to build spent fuel
dry storage canisters. This contract is the first of many contracts that ABB expects to win over
the next few years.
Newington Operations is simply the fabricator of these canisters. External firms did the
design. There are three basic designs to the canisters that ABB may build over the next few
years, that are all similar in basic structure but vary in the amount of machining, welding, and
assembling involved.
During this internship period, production of the first canister contract was underway.
However, a major design problem was discovered partway through the internship period and
10
production of the canisters was halted. ABB then began assisting in an R&D effort to correct the
problem. The projected restart is 2002, which is when rework on the partially constructed
canisters will be done, as well as complete production of additional canisters for the contract.
Fabrication of a second type of canister has already started at ABB, though no finished
products are scheduled to ship until July 2000.
Thus, this thesis focuses on the general state of the production system in Newington with
examples taken from canister production.
1.3 Outline
Chapter 2 gives a brief description of the Toyota Production System (TPS) and the
Manufacturing System Design Decomposition (MSDD), which are used to analyze the
production system at ABB and suggest improvements to the system. This chapter also details the
inspection philosophies of mass production and TPS.
The current state of the production system at ABB-CE Newington Operations is
described in Chapter 3. The goals of this project are also laid out.
Chapter 4 is the heart of this thesis. The MSDD is used as a tool to analyze the
production system at ABB and determine feasible ways to improve the system. Certain sections
of the MSDD are emphasized over others due to their pertinence to ABB's production system.
Finally, in Chapter 5, comments are made regarding inspection at ABB and the
regulations infringed upon the industry. Chapter 5 also includes a summary of the analysis
presented in this thesis and recommends the next steps for ABB to take.
11
2.0 "LEAN" MANUFACTURING
This chapter provides a brief history and overview of the Toyota Production System, as
well as describes the Production System Design Decomposition Framework that was used to
analyze the current production system at ABB. Finally, a detailed look at the inspection
procedures and philosophies of mass versus "lean" production is presented.
2.1 Toyota Production System
Lean manufacturing, the Toyota Production System (TPS), and Just-in-Time
manufacturing are all synonyms for the production system developed by Taiichi Ohno.
Following World War II, when Japan was in a state of rebuilding and resources were scarce, the
President of the Toyota Motor Company, Kiichiro Toyoda, said, "Catch up with America in
three years. Otherwise, the automobile industry of Japan will not survive" [Ohno, 1988]. Ohno,
who worked for Toyota, looked at the mass production systems in existence in America at the
time to try to find ways to keep his company in business. Ohno had once been told that the work
force ratio between Japan and America was 1-to-9 [Ohno, 1988]. How could this be? Ohno
knew that there was no way that American workers could actually exerted ten times more
physical effort than Japanese workers. This was when he realized that there was simply too
much waste in the Japanese system that was getting in the way of productivity.
In Japan, demand for automobiles was not as high as in America and Toyota did not have
as many resources as the American companies. As a result, Ohno created a system based on two
pillars: just-in-time and autonomation (automation with a human touch). Just-in-time refers to
the method of making only what is needed, when it is needed. This meant that Toyota could
keep a minimal amount of inventory and work-in-process (WIP), which would reduce their costs.
12
Autonomation is the use of machines "with a human touch" [Ohno, 1988]. That is, machines
that can detect defects autonomously. When a defect is detected, the machine stops and cannot
continue until the source of the problem is corrected.
The ultimate goal of TPS is to reduce the amount of time between when the customer's
order is taken and when the company receives the cash for the product. This time reduction is
accomplished by eliminating waste. The seven wastes as defined by TPS include [Ohno, 1988]:
"
"
"
"
"
*
"
waste of overproduction
waste of time on hand (waiting on machines)
waste in transportation
waste of processing itself
waste of stock on hand (inventory)
waste of movement
waste of making defective products
Elimination of these wastes can improve system efficiency and reduce costs.
The main working unit of TPS is the cell. In mass production systems, all machines of
the same type are in one department, which requires parts to criss-cross through the shop from
one operation to another. Ohno realized that if he set up a sequence of machines in the proper
order of operations, the parts could quickly travel, one part at a time (referred to as single-piece
flow), through the U-shaped or L-shaped cell, drastically reducing the distance that the parts had
to travel. This layout also allowed workers to operate multiple machines at once. The worker
could set-up a part in a particular machine, hit a switch to make the machine begin, and while
that machine was running, move onto the next machine in the cell continuing in a similar
manner. By creating these "work loops," production efficiency drastically improved over the
"one operator, one process" methods of mass production.
To keep inventory levels low and assure smooth flow of parts through the cells, balanced
production and leveled production were implemented. In balanced production, all operations or
13
cells produce at the same cycle time, which is less than or equal to the takt time [Cochran, 1999,
2.82/2.812 class notes]. Takt time is the pace at which parts should be produced to meet
customer demand, and is defined as the available time per shift divided by the average demand
per shift. Leveled production means that all operations make the quantity and mix of products
demanded by the final customer within a given time interval [Cochran, 1999, 2.82/2.812 class
notes]. Thus, instead of producing long runs of the same type of parts, a variety of parts are
produced in smaller runs. To achieve this objective, however, changeover times had to be
drastically reduced, which was accomplished through single-minute exchange of dies (SMED)
[Shingo, 1989]. Takt time and leveling of production should be recalculated and adjusted on a
regular basis. This could be weekly, monthly, or annually, depending on the rate of change of
customer demand.
The method used to enforce just-in-time is called kanban, which is the Japanese word for
"card." A kanban is typically a small card in a protective envelope that contains information
about pickup, transfer, and production [Ohno, 1988]. The use of kanban prevents
overproduction or production of the wrong parts.
The bottom line of Ohno's system is constant improvement. In taking a look around the
plant, small increments of progress can always be made to help get the product to the customer
faster and reduce waste. The Japanese word used to describe this philosophy is "kaizen."
2.2 Manufacturing System Design Decomposition
2.2.1 Axiomatic Design
Axiomatic Design provides a means to translate customer needs into specific design
implementations through mapping the Functional Requirements (FRs) and Design Parameters
14
(DPs) [Suh, 1990]. The FRs, in the functional domain, are determined directly from the needs of
the customer and detail specific requirements that the design must accomplish. The DPs are in
the physical domain, and specify the physical implementations set forth by the FRs. Put simply,
the FRs state what to accomplish and the DPs state how to accomplish it.
A top-level functional requirement is established, with its corresponding design
parameter. More functional requirements are derived from the top level DP, which each have
their appropriate DPs. This breakdown continues until the bottom level DPs are feasible,
implementable solutions to the desired goals. The mapping of FRs and DPs must follow two
design axioms [Suh, 1990]:
Axiomi: The IndependenceAxiom
Maintain the independence of functional requirements (FRs).
Axiom 2: The Information Axiom
Minimize the information content.
2.2.2
Manufacturing System Design Decomposition
Professor David Cochran, Professor Paulo Lima, and the students of the Production
System Design Laboratory at MIT have developed a Design Decomposition, using the method of
axiomatic design, for a production system. The Manufacturing System Design Decomposition
(MSDD) can be used to closely examine "lean" production systems. A better understanding of
what needs to be achieved in order to attain a "lean" production system and how to achieve it can
be achieved by "zig-zagging" along the path mapped out by the FRs and DPs of the
Decomposition.
15
The overall layout of the MSDD is shown in Figure 2-1. The MSD Decomposition can
be divided into six sections: (1) Quality, (2) Identifying and Resolving Problems, (3) Predictable
are detailed
Output, (4) Delay Reduction, (5) Direct Labor, and (6) Indirect Labor. The sections
in Chapter 4.
Indirect
Labor
. . . . . .. .......
Quality
Identifying and
Resolving
Problems
Direct
Labor
Delay
Reduction
Predictable
Output
Figure 2-1: Overall layout of the MSD Decomposition
with the six branches labeled.
2.3 Inspection
Because this thesis emphasizes the problems with inspection found at ABB and in the
methods
nuclear industry, in general, we must first examine the differences between inspection
Production
at mass production plants and job shops versus the inspection methods in the Toyota
System.
16
2.3.1 Statistical Process Control (SPC) and Acceptable Quality Levels (AQL)
In the 1920s, at Bell Telephone Laboratories, statistical process control (SPC) began
[DeVor et al., 1992]. SPC uses statistics and probability concepts to draw conclusions about a
population after examining a small amount of data. These conclusions, however, cannot be
stated with absolute certainty. The introduction of uncertainty into the picture causes some
problems. Typically, sample inspection involves two particular monitoring tools, acceptance
sampling and/or control charts.
Sampling is done when it is either too costly, too difficult, or impossible to inspect all the
parts. For example, the cost associated with the time needed to inspect every part may be too
much, inspection of the parts may be destructive, or not all of the parts may yet to have been
produced.
In acceptance sampling, a maximum amount of defective parts is allowed to be produced
for the lot to be considered satisfactory. This "acceptable quality level" (AQL) means that some
defects are accepted in each lot sampled. In today's competitive world of high-quality, no
defects are acceptable.
Control charts are used to track the mean and variability of a process. Key characteristics
of the parts produced are, again, sampled, and their mean value is plotted on an X-average chart,
while their range or variability is plotted on an R chart or cy chart, respectively. These charts are
known as Shewhart Control Charts, named after their founder, W.A. Shewhart, who worked at
Bell Labs in the 1920's. Upper and lower control limits are set on each chart and the
characteristics of each sample are plotted. The plot is examined for trends or "out-of-control"
data points, which are then evaluated for their probable cause. The theory behind control charts
is that there are two types of causes of variation. "Chance" causes are natural causes that are
17
inherent in the process. They are extremely difficult to isolate, and, frankly, are usually too
small to really care about. Chance causes result from inherent variability in, for example,
material properties and measurement error. Control charts are mainly used to detect the presence
of "assignable" causes. Assignable causes are events that alter the accuracy and/or precision of
the process. Examples of assignable causes are environmental changes (temperature fluctuations
in the factory), tool wear, noise resulting from excessive machine vibrations, and intentional
adjustments to the machine's settings. When assignable causes are detected, they must be
evaluated and fixed to bring the process under control.
Shewhart developed this method of charting the mean and variability of key
characteristics of processes based on the fact that natural sample statistics will be "normally
distributed" about its mean value. Figure 2-2 shows a normal distribution with the mean value at
zero. The width of the curve is determined by the variability, c2. This figure also shows how the
normal distribution curve, when still centered at a mean value of zero, "narrows" when
022
<
7
. The upper and lower control limits, in this case, set at +/-2o, are shown on the chart.
LCL
UCL
22
2
-4y
-3c
-27
-ic7
0
icy
2cy
3(y
4a
x
Figure 2-2: Normal distribution curve with p=O,
18
02=1.
The region under the curve and outside the control limits is called the x-error, also
known as a Type I error. A Type I error is defined as "viewing a process as bad, when it is
actually not making defects." cx is known as the "significance of the test." See Figure 2-3.
UCL
LCL
aY2
W2
-4a
-3a
-2a
-la
0
la
2a
3a
4cy
x
Figure 2-3: The area under the normal curve and
outside of the control limits is the x-error.
The opposite kind of error that can be made is to "view a process as good, when it is actually
making defects." This is known as a Type II error or
P-error.
The value (1-$) is known as the
"power of the test." The value of P is determined from the area under the curve that is inside the
original control limits when a shift in the mean value of the process has occurred. Figure 2-4
depicts the value of P for a process whose mean value has shifted over +3a.
In a manufacturing setting, either ct-error or 1-error can be minimized, but not both.
Minimizing one type of error compromises the other. Table 2-1 illustrates the decision-making
(DM) process that results from control charts and Type I and Type II errors [Black, 1991].
19
0
LC L
-4a
-3cy
-2a
-la
0
x
L
la
2a
Enew
3a
4a
Figure 2-4: The value of P is equal to the area under the curve
of the shifted curve that is within the original control limits.
The sample suggested to the DM that:
The truth was that the
process had not changed.
The truth was that the
process had changed.
The process has not
changed.
DM takes no actions as
nothing is wrong.
DM takes no action, but
process making more defects;
Type II error.
The process has changed.
DM takes action, but nothing
can be found to be wrong with
the process; Type I error, DM
embarrassed.
DM takes action, finds
problem with process. DM
looks good!
Table 2-1: Two types of errors can be made during the "Decision Making"
process, Type I and Type II errors.
This type of inspection is known as "judgement inspection." Improving judgement
inspection increases the chances of detecting defects (minimizing a-error), but does not actually
reduce the number of defects produced.
20
To illustrate Type I and Type II errors numerically, consider a standard normal
distribution curve with control limits set at +/-3G from the mean value, which is a typical
acceptance range. 99.7% of the measured values will fall inside this acceptance range. (See
Figure 2-5.) Thus, the u-error, the probability that a part will be marked defective when it is
actually a good part, is 0.3%. In other words, there is a 3/1000 chance that the inspector will
think that the process is bad, when it has not changed at all.
UCL
LCL
-4cy
Ry
2y
ICT
0
95.4%
G
(
Cr
4cy
P
99.7%
Figure 2-5: Confidence intervals of a standard normal distribution.
Now suppose that the mean value shifts over one standard deviation. Instead of the mean
value of the process being at zero, the mean value of the process is now at +1.
For this shifted
standard normal distribution, the area under the shifted curve but still inside the control limits is
$ = 97.7%. There is a 97.7% chance that the part will be detected as good, when in reality, the
process has shifted. Due to the fact that sample inspection is being used, instead of 100%
inspection, this failure to detect the mean shift allows defective parts to be passed on to the
customer (internal or external).
21
2.3.2
Judgement Inspection
At many companies, inspection is simply defect detection. Improving judgement
inspection increases the chances of finding defective parts, but does not actually decrease the
number of defective parts.
2.3.3
Informative Inspection
TPS used "informative inspection" methods to detect defects immediately after they are
made, or, better yet, to detect defects at their source, before the defects are actually made.
Preventative inspection reduces the amount of waste (defects) produced, which reduces overall
costs. While production is often stopped (money lost) while the problem that caused the defect
is being corrected, the cost associated with this production loss is less than the cost that would
have incurred due to the production of defective parts (cost of scrap or rework). There are three
basic types of informative inspection: self inspection and successive inspection, enhance self
inspection, and source inspection. All three methods are used in TPS.
In self inspection, each worker inspects his/her own work. A few problems can arise with
this type of inspection, though. If the worker misunderstood the work orders, he/she may
unintentionally pass along parts that should have been rejected. Another drawback is that the
worker may compromise judgement and knowingly accept parts that are actually defective. To
keep inspection within the cell but avoid these problems, the worker can pass along his/her parts
to the next worker who inspects them. Successive inspection provides the immediate feedback
that self inspection provides, but provides more objectivity.
Another solution to address the conflict of interest that can arise in self inspection is to
provide a "mistake-proofing" device, or poka-yoke, to assist in the inspection. Again,
22
production benefits from the immediate feedback provided by enhanced self-inspection, without
the drawbacks of standard self inspection.
The best inspection method is source inspection. By monitoring and controlling the
conditions at the source of the operation, defects can be prevented rather than detected. Source
inspection can trace the problems "vertically" through the process flow or "horizontally" within
an operation.
The most important aspect of the inspection philosophies of TPS is that every part is
inspected. 100% inspection assures that defects are not passed to subsequent processes and
certainly not to the final customer. All it takes is for one customer to buy one defective product
and that company has lost that person's business forever.
23
3.0 EXISTING CONDITIONS AND PROJECT GOALS
3.1 Current Plant Layout
Production of parts in Newington is split up into two categories: light and heavy
manufacturing, which also (generally) corresponds to small and large components. These
components are appropriately machined and sub-assembled in the respective light and heavy
manufacturing buildings.
The light manufacturing building is set up mainly in a departmental layout. It also houses
a warehouse for the storage of raw stock, as well as partially machined parts and fully-machined
parts that are awaiting assembly. A 2-ton boom crane in the light manufacturing building
facilitates material handling. See Figure 3-1 for a schematic of the light manufacturing building.
The heavy manufacturing building contains assembly areas, as well as machines needed
to produce the large components that Newington makes. These machines are permanent fixtures
in the building. The heavy manufacturing building is divided into two halves, one of which is
served by a 30 ton crane with a height of 29 feet, while the other half is served by a 100 ton
crane with a height of 70 feet. See Figure 3-2 for a schematic of the heavy manufacturing
building. There are also three fork trucks that are used to move material around - small,
medium, and large.
In June, at the beginning of the internship, production of the canisters was already
underway and plans for a new building (300 feet x 85 feet in area) dedicated to canister
production were being developed. In the meantime, fabrication of the canisters occurred on the
existing machines in the shops and wherever floor space could be found.
24
m
==
Celt
RCP
ASSEMBLY
Assembly
- storage
of finished
components
awaiting
assembly
Classroom
WAREHOUSE
storage
of finished
receiving
components
awaiting
assembly
cut-off
s
Machine poison strip,..
assembly
storage
E
wellsaj
!
-
bands
0C
_torage
tat es
aw
Lunch
M"eNE ROOM
TOOL
&
CUnER
GRNINNG
AREA
-ai
Crossee
Assembly
storage
___-
11~
grinders--
he
""*i
deburrng
Figure 3-1: Schematic of Light Manufacturing Building.
(Note: Drawing not to scale.)
SYS 80
CORE
SHROUD
The work in
this area
changes daily ,
CNC
6 G&L
HBM
CARLTON
RADIAL
DRILL
LOW BAY (30 TON)
SYS 80 FAB &
FINAL ASSY
RCP FINAL ASSY
HIGH BAY (100 TON)
______
-CNC
GAGE
ROOM
RCP ASSY
FROREIP
VBM
VBM
MAINT.
CNC HBM
GRAY
~7"
TROOM
INT
ASSY
DORRIES
VEM
TN
STAND
OFFICES
TEST
LOOP
CRAVEN
VBM
POWER
SUB-STATION
BLAST/PAINT
FACILITY
Figure 3-2: Schematic of the Heavy Manufacturing Building.
(Note: Drawing not to scale.)
25
3.2 Flow of Parts and Information
Production begins when a project engineer creates a Manufacturing Process Sheet (MPS).
The main body of an MPS contains manufacturing and inspection instructions set up in
sequences of operations. The MPS also includes a list of parts/raw materials needed (called the
"items checklist"), referenced drawings, weld procedures (which are added later), and inspection
procedures. The last page of the MPS is an accounting document called a "J50", which is
basically the engineer's best estimate of how long each sequence in the MPS should take, and is
used to record the actual hours that each sequence takes.
The MPS then moves to the weld engineer, who adds the specific welding instructions, if
any are necessary. Next, the MPS goes to Quality Assurance (QA), who writes up any
Dimensional Inspection Reports (DIR) if they are needed. Manufacturing services receives the
MPS next and checks to make sure that all items listed in the items checklist are currently in the
warehouse. If they are, then the MPS is ready to be released to the shop floor.
At the same time that the MPS is travelling around getting all its necessary components,
the project engineer orders the parts/raw stock needed. When the material arrives in Newington,
it must go through the receiving department. Large items that will be machined in the heavy
manufacturing building are delivered directly to that building. The parts are received at one of
two doors, depending on the weight of the material. (Anything greater than 30 tons must be
received at the back entrance, where there is a 100 ton overhead crane. The overhead crane at
the front of the building is a 30 ton crane.) All other items are delivered to the light
manufacturing building, which contains the warehouse. (Note: The warehouse only contains
material that has been approved for use. Nothing can be kept in the warehouse until it has passed
through receiving inspection.) The receiving department checks to make sure that what has been
26
delivered is truly what was ordered, and also checks to make sure that the material has all
necessary certification documents with it. If everything checks out okay, the material is placed
in the warehouse until needed. If receiving doesn't approve the shipment, a Non-Conformance
Report (NCR) is written stating what the problem is, which then must be verified by QA. The
material can either then be returned to the supplier, scrapped, or "repaired" if possible.
At this point, manufacturing services releases the MPS to the shop floor. The items
checklist is given to a material handler, who kits the parts and delivers them to the proper work
station, which could be in either the light manufacturing building or the heavy manufacturing
building. If the machining is happening in the heavy manufacturing building, the items checklist
page is usually given to a material handler a day or so in advance of when the parts are actually
needed. In the light manufacturing building, if the MPS is currently on the shop floor, it is
common for the machinist to walk over to the warehouse, himself, and fill out a "material
withdrawal request" to get the material that he needs, rather than go through the shop foreman
again. The machinist then begins working.
After the first part is machined, it must be inspected by Quality Control (QC). To do this,
the machinist must go to his immediate supervisor (the shop foreman) and tell the foreman that
he needs an inspector for a first piece inspection. The foreman then fills out an Inspection
Service Request (ISR), which he usually then brings directly to a QC inspector. Inspection
generally happens on a first come, first serve basis, so if an inspector is currently free, he
performs the first piece inspection. Otherwise, the machinist must wait for a few minutes until
an inspector is available. If QC approves the part, the machinist can then continue machining the
remaining parts for that particular sequence of the MPS. Sometimes first piece inspection will
happen after a few sequences of the MPS have been performed, which then allows the machinist
27
to perform all of those operations on the remaining pieces. Other times, first piece inspection
happens after each individual sequence of the MPS. The project engineer that wrote the MPS
determines which of the above procedures to follow.
When the machinist has finished machining all the parts, a QC inspector is needed, again,
for final inspection, which can be either 100% inspection or sample inspection, depending on the
type and number of the parts. At this point, typically, the machinist will move on to another job,
and the ISR will be dropped off in the QC "in-box" and tended to the next day or at the first
convenience. If necessary, certain inspection requests can be prioritized over others if the job is
in high demand.
The above procedures hold true for assembly, also.
Parts travel all over the shop in Newington. They also travel a good deal between the
light manufacturing and heavy manufacturing buildings. Below is a table of a few selected
canister parts and the distances that those parts traveled in the current production system at ABB.
Part Name, Number
Distance traveled (ft.)
5x2 tube steel arms, P05-001
580
Structural Ed, P04-001
2,196.5
Shield Lid, top plate, P03-001
1,293.6
Shield Lid, bottom plate, P03-003
1,293.6
3,009.6
Shield Lid, P03-001 welded to P03-003
Table 3-1: Sample travel distances of selected parts.
3.3 Scrap, Non-conformances and Corrective Action
To date, there is no numerical record of the level of scrap in Newington. As for nonconformances, ABB keeps a large database detailing the disposition of all non-conformance
28
reports (NCR). They track failures, defects, operator, and machine work center involved with
each non-conformance, as well as all NCRs caused by suppliers.
When an in-process defect is made, the machinist brings it to the attention of the
foreman, who then fills out an NCR detailing the defect. In the NCR, the foreman will also
describe any corrective action measures that could be taken to prevent such a defect from
occurring in the future. The NCR then goes back to the project engineer, who writes another
MPS to either repair the damaged parts or produce completely new ones. Hopefully, also, the
project engineer uses the "corrective action" suggestion in the NCR and edits the old MPS so as
to improve the instructions and prevent the same mistake from happening in the future. At the
same time, the machinists usually take notes on the operations that they do and keep track, for
themselves, of things that go wrong, why, and how to prevent them in the future. Unfortunately,
the machinists do not always refer back to these notes and thus, repeat the same mistake.
3.4 Inspection
As describe in the previous section, inspection happens many times during each MPS.
The first sequence of most MPSs is "QI verify items checklist," which simply requires an
inspector to verify that the material has been approved for use. QI is needed for first piece
inspection, for verification of fit-ups and weld tacks, for dimensional inspection, as well as for
inspection of welds.
Inspection of parts can take anywhere from a few minutes to a few hours, depending on
the type of inspection that is performed, the size of the part being inspected, and the complexity
of the part being inspected. The following histogram shows the distribution of inspection times
per part for 26 MPSs that were part of the first canister contract. The mean inspection time is
29
just over half an hour (33 minutes), though the range is from 6 seconds (for a quality inspector to
verify the part number of 2816 parts in 3 hours) to 97.5 hours (for the first piece inspection of the
5x2 tube steel arm for the main cross assembly).
Histogram
70
1
61
60
50
40
a)
IL
30
20
13
10
1
0
0.001
0.751
1 .501
0
0
3.001
3.750
-- --- - - -------
2.251
-
1
0
1
5.250
More
-- ---
4.500
Inspection Time (hours)
Figure 3-3: Histogram of inspection times per part for 26 MPSs of the initial canister contract.
3.5 Worker Activities
ABB Newington is a union shop. Each worker has a specified role and never cross-trains
between roles. There are machinists, assemblers, welders, material handlers, and quality
inspectors. Machining and assembly in Newington is highly manual. There is very, very little
automation in the plant.
To document typical daily activities, a random 2-hour time slot was chosen and 9
workers were observed during this time slot. The following charts show a breakdown of the time
spent on each activity per worker and the percentage of total time (9 workers x 125 minutes of
30
observation
=1125
minutes) spent on each value adding and non-value adding but necessary
operations.
Pareto Chart of Activities
250
S200
S150
-
-
*~1000.
4)
50
0)
C
)
aCUC
)C)U
0
0
C
-
Ra-)c
r-
a)0C
a)~--
)
.C
c
.-
0
LL
CU
LU
V>
0
-O
0
0)
00
Activity
Figure 3-4: Pareto chart of worker activities during a random 2-hour time slot.
Total Time Spent on Each Operation/Activity
E 40%-
P 35%
* 30%,* 25%'1 20%15%
S10%
0)
:92
0)
E
-Y
0
(
C
0)0
-
7~
(D
C.
.0-
0)0.
V~(
Operation/Activity
Figure 3-5: Percentage of total worker hours spent on each operation/activity
during the same random 2-hour time slot.
31
tM
0
C
W.
)
.0=
0)>
a)
4) .9
0@
E/
0a
0
E
.
CL
Sorting the above activities into value-adding, waste, and non-value adding but
necessary, results in the following breakdown:
Non-value
adding but
necessary
27%
Value adding
37%
Waste
36%
Figure 3-6: Pie chart of value adding, non-value adding but necessary, and pure waste
observed during the random 2-hour observation period.
3.6 Scheduling
Initial scheduling put together for the bidding process is based on experience for up-front
engineering span, long lead material spans, and rough estimates on duration (normally, the latter
is a high level look), plus shipping added onto the end. Production scheduling is based on actual
engineering/QA tasks scheduled in hours for 40 hours per week per person. Shop work is based
on estimated duration for major operations at the sub-MPS level, but not quite at the operation
level.
A typical contract at ABB for the System 80 Power Plant components (described briefly
in Section 1.1) takes three years to complete. There is a good amount of play in a 3-year
schedule, so ABB doesn't necessarily have to adhere to the nitty-gritty details of their proposed
32
schedule. There is a lot of opportunity to "catch up" to the schedule and ship the final product(s)
on time. For the canisters, however, ABB must adhere to a much stricter schedule. For
example, production of one particular canister contract began in the beginning of March and the
first finished canister is expected to ship in July, with another finished product following every
two weeks thereafter.
3.7 Project Goals
The purpose of this project is to determine to what extent a cellular manufacturing system
is truly feasible at ABB-CENP Newington Operations. The intentions of creating a cellular
manufacturing system are to improve the flow of parts through the shop, reduce the amount of
inventory and work-in-process (WIP), reduce the amount of floor space taken up by production,
and reduce the throughput time and manufacturing lead time.
It is intended that, at the end of this project, ABB can use this thesis as a basis to begin
making changes in their manufacturing system. The ideas set forth in this thesis will provide a
starting point for ABB to work off of, as well as illustrate the improvements that can be made by
making simple changes.
Another goal of this thesis is to address the conflict that arises between the ideals of
cellular manufacturing and the necessary "evils" of the nuclear power industry. Specifically, the
issue of quality assurance is addressed, as well as the combination of cellular manufacturing and
project-shop manufacturing that must take place for the production of these spent fuel canisters.
Chapters 4 and 5 explore these issues deeper.
33
4.0 MSD DECOMPOSITION APPPLIED TO ABB NEWINGTON
The main goal of this thesis is to analyze the current production system at ABB in order
to systematically improve the system as a whole. In Chapter 3, the current situation at ABB was
described. In this chapter, the MSD Decomposition will be detailed branch-by-branch and
applied to the production system at ABB to determine the necessary path that ABB needs to take
in order to transform their plant into a "lean" production system. Suggestions are made or
examples are given wherever possible to illustrate potential improvements to ABB's system.
As discussed in Chapter 2, the MSD Decomposition is based on axiomatic design and
provides a comprehensive approach to designing a lean production system. The ideas of TPS are
encapsulated in the structured MSDD. The MSDD is used in this thesis because it provides a
systematic framework for analyzing a production system.
4.1 Top Three Levels of the MSD Decomposition
Levels I, II, and III of the MSD Decomposition are detailed in Figure 4-1. "FR" states
the functional requirement, "PM" details the performance measurement, and "DP" lists the
corresponding design parameter.
The functional requirements of these three levels outline the ultimate goals of the system.
As a company, ABB wants to maximize the long-term return on investment, which means
maximizing sales revenue, minimizing manufacturing costs, and minimizing investment over the
production system lifecycle.
To maximize sales revenue, a company must make sure it's producing quality parts,
delivering products on time, and meeting the customers' expected lead time. Minimizing
34
Level I
FR1I
Maximize long-term
return on Investment
PM1
Return on investment over
system lifecycle
DP1
Manufacturing System Design
FR11
Leve II
Maximize sales revenue
PM11
Sales revenue
FR12
Minimize manufacturing costs
FR13
Minimize investment over
PM12
Manufacturing costs
PM13
DP1 2
Elimination of non-value adding
customer satisfaction
Level Ill
Investment over system
lifecycle
-I
- - - -
DP11
DP1 1
Production to maximize
production system lifecycle
sources of cost
DP1 3
Investment
based on a long
term strategy
I
FR111
FR112
FR113
FR121
Manufacture
products to
target design
specifications
Deliver
products on
time
FR122
Meet
customer
expected lead
time
Reduce waste
in direct labor
Reduce waste
PM111
Process
capability
PM112
Percentage
labor
Difference
between mean
throughput
time and
PM121
Percentage of
operators'
time spent on
wasted
motions and
customer's
waiting
PM113
on-time
deliveries
in indirect
FR123
Minimize
facilities cost
PM123
PM122
Amount of
required
Facilities cost
indirect labor
expected lead
timi
DP-111
Production
processes
with minimal
variation from
the target
Quality
DP112
Throughput
time variation
reduction
DP113
Mean
throughput
time reduction
DP121
Elimination of
non-value
adding manual
tasks
DP122
Reduction of
indirect labor
tasks
Identifying
Predictable
Delay
Direct
Indirect
and
Output
Reduction
Labor
Labor
DP123
Reduction of
consumed
floor space
Resolving
Problems
Figure 4-1: Levels I, II, and III of the MSD Decomposition.
35
manufacturing costs involves reducing waste in both direct and indirect labor, as well as
minimizing facilities cost.
These functional requirements lead to design parameters that describe a cellular
manufacturing system perfectly. The design parameters call for a system that produces with
minimal variation from the target, works to reduce mean throughput time and throughput time
variation, eliminates all non-value adding tasks, reduces indirect labor tasks, and reduces the
necessary floor space. A linked-cell production system exemplifying the philosophies of the
Toyota Production System is the best way to implement these design parameters.
Before beginning a discussion on each Level IV branch of the MSDD, FR-123
"Minimize facilities cost" needs to be addressed. DP-123 calls for the "reduction of consumed
floor space." ABB is currently constructing a new building to house the spent-fuel canister
production. At the same time, approximately 30-40% of the already-existing Light
Manufacturing Building is occupied by a warehouse. This warehouse contains a large amount of
inventory. Much of this inventory is parts that are needed for upcoming contracts that may be
received a few months to a few years in advance of when they are actually needed. There are
also many smaller components that are ordered in bulk and stored in the warehouse for use
whenever needed. If ABB would simply reduced the amount of inventory in the warehouse, they
could cut the size of the warehouse drastically and use that added floor space for production. By
employing the concept of "just-in-time," whereby parts are received when needed and in the
amount needed, ABB can eliminate the need to store parts in the warehouse. To meet this
objective, requires having confidence in suppliers to deliver quality products on time, which is an
issue that will be addressed in section 4.2, and may not even be feasible.
36
4.2 Quality
Figure 4-2 details Level IV of the Quality branch of the MSDD. The very first functional
requirement is FR-Q 1: "Operate processes within control limits." As mentioned in Chapter 3,
ABB does not currently monitor in-process production or provide immediate (or even moderate)
feedback to the operator regarding the quality of the parts. After first-piece inspection, the parts
are produced in large batches (usually the entire quantity needed for that particular contract) and
are not inspected again until final/sample inspection. At which point, prevention of defects is
impossible. It is recommended that ABB begin use of a control system to determine the
characteristics of the parts being produced immediately after they are produced. A simple first
step would be dimensional inspection, by the operator, of each part as it is produced. Run charts
can then be used to alert the operator of the presence of assignable causes of variation. Should
problems arise, an investigation must be done to determine the cause of variation and then action
must be taken to eliminate the assignable causes of variation due to the machine, operator,
method, and material (FR-Q1 1 through FR-Q 14). (For further reading on this subject, refer to
Statistical Quality Design and Control: Contemporary Concepts and Methods, DeVor, Chang,
and Sutherland, Prentice Hall, 1992.) It should be noted, however, that, as discussed in Chapter
2, sample inspection allows defects to be passed on through the system. 100% inspection is
the only way to assure that no defects end up in the hands of the final customer.
Taking a slightly deeper look into the elimination of operator assignable causes, FRQ122 states: "Ensure that operator consistently performs tasks correctly." The corresponding
DP-Q122 is the use of "standard work methods." This is an area where ABB can make some
significant improvements. As it currently stands, the Manufacturing Process Sheets (MPSs)
37
FR-Q1
Operate processes within
control limits
Level IV
FR-Q2
Center process mean on the
target
FR-Q3
Reduce variation in process
output
PM-Q3
Variance of process output
PM-Q1
Number of defects per n parts
with an assignable cause
PM-Q2
Difference between process
mean and target
I---------------------
DP-Q1
Elimination of assignable
DP-Q3
Reduction of process noise
DP-Q2
Process parameter adjustment
causes of variation
I
FR-Q11
Eliminate machine
FR-Q12
Eliminate operator
FR-Q13
Eliminate method
FR-Q14
Eliminate material
FR-Q31
Reduce noise in
FR-Q32
Reduce impact of
assignable causes
assignable causes
assignable causes
assignable causes
process inputs
input noise on
process output
PM-Q11
Number of defects
PM-Q12
Number of defects
PM-Q13
Number of defects
PM-Q14
Number of defects
PM-Q31
PM-Q32
per n parts
assignable to
equipment
per n parts
assignable to
operators
per n parts
assignable to the
process
per n parts
assignable to the
quality of incoming
material
Variance of process
inputs
Output variance /
input variance
DP-Q11
Failure mode and
DP-Q12
Stable output from
DP-Q13
Process plan design
DP-Q14
Supplier quality
DP-Q31
Conversion of
DP-Q32
Robust process
effects analysis
operators
program
common causes
design
into assignable
causes
FR-Q121
Ensure that operator has
knowledge of required tasks
PM-Q121
Number of defects per n parts
caused by an operator's lack of
understanding about methods
DP-Q121
Training program'
FR-Q122
Ensure that operator
consistently performs tasks
correctly
FR-Q123
Ensure that operator human
PM-Q122
Number of defects per n parts
caused by non-standard
methods
PM-Q1123
Number of defects per n parts
caused by human error
DP-Q122
Standard work methods
DP-Q123
errors do not translate to
defects
Mistake proof operations (Poka-
Yoke)
Figure 4-2: Level IV of the "Quality" branch of the MSD Decomposition.
38
written by the project engineers are intended to be the guidelines for outlining the proper
operations that need to be done on a part. However, the instructions in the MPSs are not detailed
enough to serve as step by step instructions. Thus, many times the machinists have to consult the
foreman for exact procedures or decide on their own the best way to go about the process. As a
result, multiple methods are employed to produce the same part over time and mistakes are often
repeated on subsequent contracts. Though each machinist takes notes on each job for future
reference, there's no guarantee that the same machinist will perform the same operations for the
next contract. The new machinist may not know about the previous machinist's notes, which
may result in the same mistakes being made twice. Therefore, MPSs need to be more detailed
and contain specific operating procedures to assure that each worker is using standard work
methods.
FR-Q14 is another area that ABB needs to look closely at. This functional requirement
calls for the elimination of material assignable causes. The corresponding design parameter is a
"supplier quality program." As detailed in the performance measure, ABB needs to minimize
"the number of defects per n parts assignable to the quality of incoming material." Between
March 1999 and February 2000, there were a total of 232 non-conformance reports filed on
incoming material. 22% of those Non-Conformance Reports (NCRs) were due to "document
deficiency," which means that the material was delivered to ABB without the necessary
paperwork stating exactly what the material is, the lot that the material came from, the fact that it
meets specified standards, etc.. 9.1% were filed because the certifications on the material were
illegible. These types of errors are not acceptable. During the 1999 calendar year, ABB had six
suppliers that caused 10 or more NCRs each. One of the key aspects to creating a wellfunctioning production system is to have the same type of "lean" system occur upstream and
39
downstream. In ABB's instance, the quality aspect of a lean production system is not happening
upstream, which is resulting in ABB's receipt of defects. As it stands right now, ABB must
inspect all incoming material to make sure it meets all requirements and regulations. Ideally,
however, ABB shouldn't have to inspect any incoming material at all. Perhaps the best approach
that ABB could take to resolve this problem is to tally the NCRs caused by each supplier and
note the types of defects that occur and how often each defect occurs from the same supplier.
Then, ABB can approach the most troublesome suppliers about improving their quality and have
specific aspects of the suppliers' system that need special attention. Creating this linked chain of
improvement will benefit the entire production stream.
4.3 Identifying and Resolving Problems
This branch of the MSD Decomposition addresses ways to minimize disruptions in
production. Figure 4-3 shows the components of this particular branch. Because most
operations at ABB are manual, detection of production disruptions is immediate. When a
disruption occurs, the machinist/welder/assembler brings it to the attention of his/her supervisor.
If possible, the problem is resolved at this point and production resumes. Sometimes, however,
either the worker and/or the shop foreman will bring the disruption to the attention of the project
engineer that issued the MPS under which the disruption occurred. Again, if the problem can be
resolved at this level, then production begins again. Otherwise, management becomes involved,
also.
FR-R13 states: "Solve problems immediately." This functional requirement is not
always fulfilled at ABB. A production disruption is most likely caused by the production of a
40
FR-R1
Respond rapidly to production
Level IV
disruptions
PM-R1
Time between occurrence and
resolution of disruptions
DP-R1
Procedure for detection &
response to production
disruptions
FR-R11
Rapidly recognize production
disruptions
FR-R12
FR-R13
Communicate problems to the
Solve problems immediately
PM-R11
PM-R12
Time between identification of
what the disruption is and
support resource understanding
what the disruption is
right people
Time between occurrence of
disruption and identification of
what the disruption is
-i171
- I
DP-R11
Subsystem configuration to
enable operator's detection of
disruptions
71
DP-R12
Process for feedback of
operation's state
PM-R13
Time between support resource
understanding what the
disruption is and problem
resolution
Vl
V1
- -
DP-R13
Standard method to identify and
eliminate root cause
I
FR-R111
Identify disruptions
when they occur
FR-R1 12
Identify disruptions
where they occur
PM-R111
Time between
PM-R112
occurrence and
identification of
recognition that
disruption occurred
disruption and
FR-R113
Identify what the
disruption is
FR-R1 21
Identify correct
FR-R1i22
Minimize delay in
support resources
contacting correct
support resources
PM-R121
PM-R122
Time between
identification and
Time between
identification of
where the disruption
PM-R113
Time between
identification of
where disruption
occurred
occurred and
correct support
resource
DP-R112
Simplified material
flow paths
Minimize time for
support resource to
understand
disruption
Time between
identification
identification of what
the disruption is and
identification of the
of what
contact of correct
support resource
PM-R123
Time between
contact of correct
support resource
and support
resource
understanding what
the disruption is
the disruption is
DP-R111
Increased operator
sampling rate of
equipment status
FR-R1i23
DP-R121
Specified support
resources for each
failure mode
DP-R113
Context sensitive
feedback
DP-R122
Rapid support
contact procedure
DP-R123
System that
conveys what the
disruption is
Figure 4-3: Level IV of the "Identifying and Resolving Problems"
branch of the MSD Decomposition.
defective part, which means that an NCR needs to be filed. As mentioned in Chapter 3, the
physical piece of paper detailing the non-conformance travels to approximately 3-4 people,
41
depending on whether the Quality Assurance department is involved or not. It isn't until the
project engineer gets the NCR and writes a "repair traveler" to either fix the defective parts or
produce new parts, that action can be taken to solve the problem. Quite often, a few days or even
weeks will pass before the new MPS is issued. This time delay needs to be eliminated so that
production disruption delays are as short as possible.
4.4 Predictable Output
Not only do disruptions need to be identified and corrected rapidly, but they need to be
minimized, as well. Both the length of time and the frequency of the disruptions must be
addressed. The "Predictable Output" branch of the MSDD is detailed in Figure 4-4.
The spent fuel storage canisters are a new product for ABB. Construction is at an
"experimental" level at this stage in production. One of the main causes for this is that the
design of the canisters was completely separate from the manufacturing. Another firm designed
the canisters and then "tossed the design over the wall" to ABB, who is fabricating the canisters.
For this reason, the beginning of production of each new type of canisters is going to be filled
with trial and error procedures until the best methods are found. Once the best methods are
determined, ABB can then focus on the "Predictable Output" branch of the Decomposition.
Functional requirements FR-P13 and FR-P14 and the subsequent lower level FRs will be
key areas for ABB to focus on once they establish exact production methods. To "ensure
predictable worker output" (FR-P13), ABB must have a "motivated work-force performing
standard work" (DP-P13). Once again, this issue of standard work arises. Knowing exactly
which operations were performed on a part makes it easy to pinpoint the source of error and
correct it. If different procedures are used to make the same part, multiple reasons may arise
42
FR-P1
Minimize production disruptions
Level IV
PM-P1
Number of occurrence of
disruptions & Amount of time
lost to disruptions
DP-P1
Predictable production
resources (people, equipment,
info)
FR-P11h
Ensure availability of
relevant production
information
PM-Ph1
Number of occurrences of
information disruptions,
Amount of interruption
time for information
disruptions
DP-P11
Capable and reliable
information system
FR-P121
Ensure that
equipment is
easily
serviceable
PM-P121
Amount of
time required
to service
equipment
DP-P121
Machines
designed for
serviceability
FR-P122
Service
equipment
regularly
PM-P122
Frequency of
equipment
servicing
FR-P12
Ensure predictable
equipment output
PM-P12
Number of occurrences of
unplanned equipment
downtime, Amount of
unplanned equipment
downtime
D DP-P13
Maintenance of
equipment reliability
FR-P131
Reduce
variability of
task
completion
time
PM-P131
Variance in
task
completion
time
DP-P122
Regular
preventative
maintenance
DP-P131
Standard work
methods to
provide
program
repeatable
processing
FR-P13
FR-P14
Ensure predictable worker
output
availability
PM-P13
Number of disruptions
due to operators, Amount
Ensure material
PM-P14
Number of disruptions
of interruption time for
operators
due to material shortages,
amount of interruption
time for material
shortages
Motivated work-force
performing standard work
DP-P1 4
Standard material
replenishment system
FR-P132
Ensure
availability of
workers
PM-P132
Number of
occurrences of
operator
lateness,
Amount of
operator
lateness
DP-P132
Perfect
Attendance
Program
FR-P133
Do not
interrupt
production for
worker
allowances
FR-P141
Ensure that
parts are
available to
the material
handlers
FR-P142
Ensure proper
timing of part
arrivals
PM-P133
Number of
disruptions
due to
operator
allowances,
amount of
interruption
time for
worker
allowances
PM-P141
Number of
occurrences of
marketplace
shortages
PM-P142
Parts
demanded parts delivered
DP-P133
Mutual Relief
System with
cross-trained
workers
DP-P141
Standard work
DP-P142
Parts moved
in process
between sub-
to downstream
operations
systems
according to
pitch
Figure 4-4: Level IV of the "Predictable Output" branch of the MSD Decomposition.
43
when trying to determine what caused a defect. In order to be able to predict the output, the
same operations need to be performed in the same order each time the same part is made.
Standardizing the work will also help in predicting how much time it will take to
complete a task. Currently, production scheduling is done at the sub-MPS level, but not quite at
the operation level. If standardized work was employed, scheduling could be done at the
individual operation level, which would make scheduling more accurate and predictable. This
practice will improve scheduling for bidding purposes and increase the chance of delivering the
finished products on time to the customer.
"Ensure material availability" is FR-P14, with its corresponding DP-P14 of "Standard
material replenishment system." The next functional requirements are "Ensure that parts are
available to the material handlers" (FR-P141) and "Ensure proper timing of part arrivals" (FRP142). Both of these bottom level FRs would drastically improve ABB's material handling
system. The utilization of the computerized inventory system at ABB needs to be improved, as
well as the overall philosophy regarding the level of inventory, in general, and the manner in
which material is delivered to each work station.
Currently, when material is received from a supplier, it is immediately entered into the
computerized inventory system. The information entered into the system includes the part
number, part description, quantity, location in the warehouse where the material will be stored,
who ordered the material, and how much the material cost. Not everyone at ABB uses the same
notation to designate, within the program, when a quantity of parts has been allotted to a specific
job, which often causes confusion and occasionally either a shortage or an excess of parts. Even
though many employees at ABB have been working there for quite some time, if ABB wants to
44
make this inventory system work properly, they need to have another training session and come
to a consensus on proper notation and designation methods within the system.
Regarding the level of inventory, in general, however, ABB shouldn't need a
"warehouse" to store parts. A typical contract for System 80 power plant components takes three
years to build. Many of the components arrive at ABB pre-machined, cast, sandblasted, etc..
Each project engineer must keep track of the parts that he will need a few years in advance and
make sure that he places the order to the supplier far enough ahead of schedule so that the parts
arrive in time for assembly. Quite often, however, parts will be ordered so far in advance that
the parts sit in the warehouse for months or even years. This practice is an ineffective use of
capital. As discussed in section 4.1, purchasing materials when needed and in the quantity
needed will reduce the amount of money invested by the company and also free up space in the
Light Manufacturing Building that can be used for production instead of storage.
Standardizing the work throughout the system will also help to assure that the material
handlers always have the proper quantity of parts that they need to deliver to the next work
station at the proper time. When parts are produced on a regular schedule, the material handlers
will always know how many parts will be produced in a certain amount of time and can use that
fact to stick to a regular material delivery schedule. This notion of producing parts at regular
intervals of time will be discussed in more detail in section 4.5 when the idea of "takt time"
arises.
4.5 Delay Reduction
As can be seen in Figure 4-5, the top design parameters of Level IV of the "Delay
Reduction" branch of the MSDD call for single-piece flow, production to run at takt time,
45
Level IV
FR-T1
FR-T2
Reduce lot delay
FR-T3
Reduce process
FR-T4
Reduce run size
Reduce
delay
(caused by ra > r,)
delay
transportation delay
FR-T5
Reduce systematic
operational delays
PM-T1
PM-T2
PM-T3
Inventory due to lot
size delay
PM-T4
Inventory due to
process delay
Inventory due to run
size delay
Inventory due to
transportation delay
PM-T5
Production time lost
due to interferences
among resources
DP- T1
Reduction of transfer
batch size
(single-piece flow)
DP-T2
Production designed
for the takt time
DP-T3
Production of the
desired mix and
quantity during each
DP-T4
Material flow
oriented layout
design
DP-T5
Subsystem design
to avoid production
interruptions
demand interval
FR-T21
Define
takt time(s)
FR-T22
Ensure that
production
FR-T23
Ensure that
part arrival
FR-T31
Provide
knowledge of
FR-T32
Produce in
sufficiently
cycle time
FR-T51
Ensure that
support
rate is equal to
demanded
small run
resources
equals takt
time
service rate
(ra=rs)
product mix
(part types
sizes
don't interfere
with
and quantities)
PM-T21
Has takt time
been defined?
(Yes / No)
PM-T22
Difference
between
production
cycle time and
PM-T23
Difference
between
arrival and
service rates
takt time
PM-T31
Has this
information
been
provided?
PM-T32
Actual run size
- target run
size
(Yes/No)
FR-T52
Ensure that
FR-T53
Ensure that
production
resources
support
resources
production
(people/autom
ation) don't
interfere with
(people/autom
ation) don't
interfere with
resources
one another
one another
PM-T51
Production
time lost due
to support
PM-T52
Production
time lost due
PM-T53
Production
time lost due
to production
resources
interferences
to support
resources
interferences
with one
another
with one
another
DP-T51
DP-T52
DP-T53
Subsystems
Ensure
Ensure
and
separation of
production
work patterns
coordination
and
separation of
support work
patterns
resources
interferences
with
production
resources
DP-T21
Definition or
grouping of
DP-T22
Subsystem
enabled to
customers to
DP-T23
Arrival of parts
at downstream
meet the
operations
achieve takt
times within
an ideal range
desired takt
time (design
and operation)
according to
pitch
DP-T31
Information
flow from
downstream
DP-T32
Design quick
changeover
for material
customer
handling and
and
equipment
configured to
equipment
separate
support and
production
coordination
access req'ts
FR-T221
Ensure that automatic cycle
time minimum takt time
FR-T222
Ensure that
FR-T223
Ensure level cycle time mix
manual cycle time 5 takt time
PM-T221
Has this been achieved? (Yes /
No)
DP- T221
Design of appropriate automatic
work content at each station
PM-T223
Is average cycle time less than
PM-T222
Has this been achieved? (Yes /
takt time in desire d time
Nol
interval?
DP- T222
Design of appropriate operator
work content/loops
DP-T223
Stagger productio n of parts with
different cycle tim es
Figure 4-5: Level IV of the "Delay Reduction" branch of the MSD Decomposition.
46
balanced and level production, as well as minimum transport of material. All of these
parameters are prime descriptors of a cellular manufacturing system.
The first step in reducing delay is to create single-piece flow. When large batch sizes are
used, parts end up sitting after being machined or assembled, waiting for the rest of the batch to
go through the same operation. The parts don't move on to the next operation until that
particular operation has been performed on every piece in the batch. This routine is one of the
seven wastes as defined by the Toyota Production System. In a cellular manufacturing system,
each part is passed on one at a time as each operation is completed. This allows for final
products to be produced much sooner than in batch production and also reduces the quantity of
work-in-process (WIP).
The next functional requirement, FR-T2, is to "reduce process delay." This is
accomplished by running production at "takt time," which is the available time per shift divided
by the average demand per shift. At the time of this thesis project, ABB was working on its first
canister contract. While this contract ended up being put on hold due to design problems, the
cellular design suggested in this thesis is based on this initial contract. This thesis aims to set an
example of how to design the cellular system, not necessarily detail the exact system that ABB
should develop. Therefore, all numbers and details used to design the cellular system described
in the remainder of this thesis are fictitious.
4.5.1 Takt Time
FR-T21 says that takt time(s) need to be defined. At ABB, based on a working schedule
of 6 hours and 45 minutes of work per shift (which results from subtracting breaks from the full
47
8-hour day), 2 shifts per day, and 22 working days per month, and assuming customer demand of
50 canisters per year, the takt time is:
405 minutes/shift
(50 canisters/12 months)/(44 shifts/month)
=
4276.8 minutes/canister = 71.28 hours/canister
This calculation means that every 71.28 hours of operation, a finished product should be
produced. The finished canister is made up of subassemblies, which are, in turn, made up of
individual components. Each of these subassemblies will be made in separate cells, which will
run at their own takt times, depending on the quantity of subassemblies needed per canister. For
example, there is only one shell per canister. The shell arrives at ABB in four segments, which
are welded together and then go through a series of machining operations. One shell should be
produced every 71.28 hours to feed the final assembly cell. There are 32 main cross assemblies,
however, which means that the main cross assembly cell should produce one complete product
every 133 minutes.
Continuing with the example of the main cross assemblies, we further break them down
into individual components, which will come from machining cells. Each machining cell will
produce at its own takt time, depending on the number of parts going through the cell and the
level of demand.
48
4.5.2
Floor Layout
One of the main ideas of a linked-cell system is to minimize the throughput time, to
maximize workers' effectivity, to highlight problems, and to provide an environment for
continuous improvement. As a result, cells are typically U-shaped and machining cells are
physically located so that they feed easily into the subassembly cells, which, likewise, are set up
to feed easily into the final assembly cell. The ship building industry uses a set-up similar to that
shown in Figure 4-6 [Storch et al.]. Note, however, that the overall shape of this layout is a
square. ABB's new building, however, in going to be 300 feet x 85 feet. Such a rectangle
makes it difficult to surround final assembly with the subassembly cells, and impossible to place
machining cells in a ring beyond that. Adequate pathways must be left between the cells to
allow for passage of fork trucks and large parts moved by overhead cranes. Adjusting to this
long, skinny rectangular shape, a possible layout for the canister production is shown in Figure
4-7. This possible layout pertains to a general form of a spent fuel canister with components
Machining
Cell
ubcssemb y Subassembly
aol
components
come from
machining
cells
Machinir g
Cells
components
purchased
from outside
vendor
Fina
ALAemhly
LA
Shipping/
Receiving
Subassembly Subassembly
Machining
Cell
all
components
purchased
from outside
vendor
components
come from
machinig
cLls
Figure 4-6: A square layout, with the final assembly cell surrounded by a ring of
subassembly cells, which are fed by machining cells, is typical of the ship building industry.
49
consisting of a shell, a top lid with a ventilation system, a bottom lid, and some type of inner
network that holds the fuel rods and keeps them separated within the canister. Material flow is
shown by solid lines, while information flow is shown by dashed lines.
( \Machining
KJjJHiH1H
Celts
FinaL
s rb
-0.A
U
L
0
Network
Sub as sembly
10 ni
--
V
ti
t
Ventilati ni
Ma
system
hini
n
Cel
To
U
Lid-
TpSubassemby
osrk1y(H
1
material
Top Lid and Bottom
Lid machining occurs
in Heavy
Manufacturing
Building
Shell machining occurs in
Heavy Manufacturing
Building
information
Figure 4-7: Possible linked-cell layout for the production of canisters at ABB.
Within this system, kanban would be used for final assembly to notify each subassembly cell
when to produce another part, which, in turn, would signal the appropriate machining cells.
Material handling loops would need to be established to provide the proper amount of material to
the proper cells at a specified interval of time.
For the machining cells, new machining centers will need to be purchased and/or
machines currently in other buildings may need to be moved to the canister building. The
current system of machining some parts in the Light Manufacturing Building and transporting
them to the Heavy Manufacturing Building for final assembly is inefficient. The overall cost of
purchasing new machines (such as a small lathe or milling machine) will be less than the cost
associated with transporting parts back and forth between all three buildings over time. There is
50
a catch to this layout, however. The two lids and the shell require machining on the large (2-3
story high) machining centers that are located in the heavy manufacturing building, located
adjacent to the canister building. These machines are extremely expensive and are, literally, part
of the building. Purchasing multiples of these machines is simply not practical. The canister
building will be build adjacent to the Heavy Manufacturing Building. Therefore, it is
recommended that the current machines in the Heavy Manufacturing Building remain the
machining centers used for these large canister components. However, it is important to try to
minimize the distance that the parts need to travel. That is why, as can be seen in Figure 4-7, the
subassembly areas for these large components of the canisters should be located as close as
possible to one of the pathways between the buildings. It is also important to note that these
pathways and doorways should be large enough to handle the passage of such components and
that overhead cranes, if needed, should be installed appropriately.
4.5.3
Sample Machining Cell
Functional requirements FR-T221, FR-T222, and FR-T223 all deal with the subsystems
of the entire system, whereas the previous section dealt with the system as a whole. FR-T221
states, "Ensure that automatic cycle time
minimum takt time." Most of the operations at ABB
are manual, so this FR can't quite be dealt with yet. As ABB acquires more and more automated
machinery (which is recommended if new machines are purchased for the machining cells), then
this FR and corresponding DP can be addressed.
FR-T222 states "Ensure that manual cycle time
takt time." This FR is extremely
important to a cellular system at ABB. DP-T222 calls for the "design of appropriate operator
work content/loops." To illustrate what this FR and DP mean, a sample machining cell will be
51
discussed. To create this sample machining cell, various steps were taken. First, all parts of the
canister were compared to determine which machining centers were used to make the part and in
which order the machining centers were used. Each cluster of the machine-part matrix
represents a part family that can be produced in a cell. The sample machining cell described in
this thesis is shown by the shaded portion of the chart in Figure 4-8.
Part Number
Part#
1
TMM
AJV
X
X
Li
X
2
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
X
X
X
X I
X
X
X
XX X
XX
X
X
X
X
X
X
X
X
VM
TMM2
WS
BSW
VH3
Pch
CPM
COS2
TMM3
SBE
TMM4
X
X
X
X X
X
X
-
_
X
X
X X
X X X .X
X x X
X
X
X
X
X
GHBM
CRD
FRP
DOR
32 33
X
HBM
COS1
3
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X X
X
X
X
X
Figure 4-8: Machine-part matrix used to establish part families.
To determine the takt time of the cell, the demand of the parts (quantity per canister x 50
canisters per year) must be determined.
Part Number
Quantity/Canister
17
64
18
128
19
16
20
12
21
12
22
32
23
4
Total # of Parts
268
Table 4-1: Part demand in sample machining cell.
52
Thus, the takt time of the cell is 15.96 minutes/part. This takt time means that the cycle
time of each operation within the cell must be less than or equal to 15.96 minutes/part. Table 4-2
lists the cycle times at each machine for each part in the sample cell.
VH3
Pch
CPM
3.5
0.35
14.2
6.67
Part #
COS
TMM
WS
BSW
17
18
2.81
2
1.5
1.5
4.23
6.44
19
20
21
22
2
1.03
1.03
3.32
1.5
1.5
1.5
1.5
23
1.5
3.32
Table 4-2: Cycle times of each part at each machine in the sample cell.
All times are in minutes.
1.8
4.05
SBE
6.67
3.2
3.2
Fortunately, the cycle times are all less than takt time already, so there is no need to
divide any operations into multiple tasks. To achieve leveled production, there should be a
proper mix of parts going through the cell. Before small run sizes of parts can be achieved,
however, set-up times must be drastically reduced [Shingo, 1989].
Figure 4-9 shows a possible layout for this sample machining cell. This cell produces the
main cross braces, as well, as the corner braces for the corner cell assemblies. Two of the
standardized work combination sheets for two of the parts that go through this cell are in
Appendix A. Similar charts were done for all parts in the cell. In this particular cell, not every
part goes to every work station. The numbering system in the figure refers to the order in which
the parts move to each machining center. Part number (P/N) 18 follows path a, P/N 19 follows
path b, P/N 17 follows path c, and P/N 20 follows path d. P/N 22 and P/N 23 exit the cell after
operation #3 and go to the sandblasting area. P/N 21 exits the cell and goes to the next
subassembly cell after operation #3. Possible work loops are shown.
53
P/N 22,
P/N 23 to
sonoblost
All drenslons
ore a4,proxlnote.
PN2
xt
1e t
P/
ColM
7
'_8q
T
Punct4o
sJ w
Insa.eu
hole
Saw
Horionta
ext
_
_cl
__
_
_
__
J[~~J
I
a
I~e7
NI
_
__
__Q_
6c-
Fiure 4-9
osbelyu o h ahnigcl htpoue
9s
ela hecre9el rcs
the
mancos rcs
at
o
Tabe 43 sowstheimpoveent ofthesamle ellove th jo shp mtho.o
prdcngtesmeprs.(l Istane anaieaeapoxmt.
Floor space
Throughput time
Job Shop
3700 sq. ft.
4131 minutes
(additional waiting
Machining Cell
1250 sq. ft.
25 minutes
% Improvement
66% reduction
99% reduction
2 (+occasional
50% reduction
time possible)
Number of workers
minimum of 4
required
Travel distance of
inspector)
580 ft.
105 ft.
82% reduction
parts
Table 4-3: Improvements resulting from formation of sample machining cell.
(All times and distances are approximate.)
Similar machining cells can be formed for other part families. Assembly cells must be
formed, also. Much of the assembly of the canisters is stationary. Because the canister
components are so large when they are sub-assembled, and especially final assembled, moving
54
the assemblies from work station to work station would be inefficient and costly. This is where
ABB's system must combine a traditional "project shop" atmosphere with the improvements of a
cellular manufacturing system.
4.5.4
Inspection
In the above sample machining cell, note that the inspection stations are integrated into
the cell. The procedure of physically taking parts to a gauge room to inspect them is a waste of
time and material handling. There is no need to relocate parts simply to inspect their
dimensional features. In theory, there is also no need to call in special "inspectors" to do the job,
either. Unfortunately, this is where ABB runs into a need to compromise the TPS ideals.
ABB Newington must abide by the regulations set forth in "The American Society of
Mechanical Engineers Boiler and Pressure Vessel Code, Section III, Division 1, Nuclear Power
Plant Components" and/or "Section III, Division 3, Nuclear Power Plant Components
(Containment Systems and Transport Packagings for Spent Nuclear Fuel and High Level of
Radioactive Waste)." All components that fall into this category must be physically "Code
Stamped" with either N, N-TP, NA, NPT, or NPT-TP ASMIE Code Stamps. As stated in the
"Quality Assurance Program Requirements for Nuclear Facilities, ANSI/ASME NQA-1," Basic
Requirement 10: Inspection:
"Inspections required to verify conformance of an item or
activity to specified requirements shall be planned and executed.
Characteristics to be inspected and inspection methods to be
employed shall be specified. Inspection results shall be
documented. Inspectionfor acceptance shall be performed by
persons other than those who performed or directly supervised the
work being inspected." (emphasis added)
55
This requirement is in direct conflict with the philosophies of the Toyota Production System,
where the ideal is to have 100% inspection performed by the workers, themselves.
Changing this practice involves more politics and economics than technology. To change
the code would require joining ASME, serving on the committee that forms the codes and
standards, and working from the inside to change them. ABB would have to form a cell,
knowing that using an external inspector is not the best way to go, and include the inspector in
the work loop of the cell to allow the inspector to see the difference between the job shop way of
inspection versus the lean way of inspection. To change the ASME Code would require the
cooperation of a qualified inspector who understands lean manufacturing. A preliminary code
would have to be drafted for inspection requirements in a lean manufacturing cell environment
(Black, 2000).
Another compromise between the TPS ideals and the ASME Code is possible. The
regulations require specially-qualified personnel to perform the final inspection and sign off that
the parts have been approved for use. The regulations also, however, allow for sample
inspection to be done, rather than requiring 100% inspection. This difference is where ABB can
take advantage of the regulations and create the compromise. 100% inspection can be performed
in the cells by the workers as stipulated by TPS, while a "qualified inspector" can roam between
a few cells to perform random sample inspection as required by the ASME regulations.
Inspection sometimes calls for non-destructive examination. These tests require more
time than simple dimensional inspection. Perhaps one or two of the inspectors on each shift
could be specifically designated to do all NDE tests, which would require these inspectors to
rotate between the cells that require such inspection. In any case, inspection should be
performed as part of the cell loop.
56
4.6
Direct Labor
The next branch of the MSDD is the "Direct Labor" branch and is show in Figure 4-10.
Level IV
FR-D1
Eliminate operators' waiting on
machines
FR-D2
Eliminate wasted motion of
operators
PM-D1
FR-D3
Eliminate operators' waiting on
other operators
PM-D3
Percentage of operators' time
PM-D2
spent waiting on equipment
Percentage of operators' time
spent on wasted motions
Percentage of operators' time
spent waiting on other operators
IZILIZ-7--i771
DP-D1
Human -Machine separation
DP-D2
Design of workstations / work-
loops to facilitate operator tasks
FR-D11
Reduce time
operators spend on
FR-D12
Enable worker to
operate more than
non-value added
tasks at each station
one machine /
station
PM-D11
PM-D12
Percentage of
operators' time
Percentage of
stations in a system
spent on non valueadding tasks while
that each worker
can operate
FR-D21
Minimize wasted
DP-D3
Balanced work-loops
FR-D22
FR-D23
motion of operators
between stations
Minimize wasted
motion in operators'
work preparation
Minimize wasted
motion in operators'
PM-D21
PM-D22
PM-D23
Percentage of
operators' time
Percentage of
operators' time
spent on wasted
motions during work
Percentage of
operators' time
spent on wasted
motions during work
spent walking
between stations
work tasks
prparti~n
prepaationroltina
waiting at a station
DP-D11
DP-D12
DP-D21
Machines &stations
designed to run
autonomously
DP-D22
Workers trained to
operate multiple
stations
DP-D23
Machines / stations
configured to reduce
walking distance
Standard tools /
equipment located
at each station
(5S)
Ergonomic interface
between the worker,
machine and fixture
Figure 4-10: Level IV of the "Direct Labor" branch of the MSD Decomposition.
FR-D1 requires elimination of "operators' waiting on machines," which is accomplished
by "human-machine separation." Currently at ABB, most of the work is manual. Many of the
simple lathes, milling machines, etc. that are used are not automated. This ties the workers to the
machines for extended periods of time. If ABB could purchase automated machinery, operations
could be performed at the push of a button and allow the worker to move on to the next operation
57
in the work loop. In order for this to be truly effective, though, the machines must also be
"autonomous," meaning that the machines can detect when a defect has occurred, and shut
themselves down until a worker can correct the source of the problem.
The next functional requirement is an area where ABB can easily take large strides
toward improving their system. FR-D2 states "Eliminate wasted motion of operators," which is
further broken down into three FRs. The first of which, FR-D21, states: "Minimize wasted
motion of operators between stations," which is accomplished by DP-D21: "Machines/stations
configured to reduce walking distance." The development of a linked-cellular system will do
exactly this. The walking distance to the next machine in the sequence will be 5 feet instead of
30 feet.
FR-D22 calls for minimizing "wasted motion in operators' work preparation." Having
all necessary tools/equipment at each workstation is the best way to accomplish this. As noted in
Figure 3-6, 36% of the worker time observed during a random 2-hour period was waste. Much
of this wasted time was due to the fact that workers had to walk across the shop to get the tools
that they needed. This retrieval time is a waste of resources. Each work station should contain
every tool and supply that the worker will need for the job. This could mean that there are
"mobile" tools/supplies that move around to various stations depending on the type of work that
is to occur at each station on that particular day. Such a system would mean that some tools that
are only used occasionally could be traded between stations, rather than having to supply each
station with every tool only to have some of them sit there, not being used, for extended periods
of time. Any tools or supplies that are used regularly at a station should be kept there
permanently so that the worker always has it on hand whenever he needs it.
58
The third FR in this sub-branch calls for minimizing "wasted motion in operators' work
tasks." The corresponding DP is the "ergonomic interface between the worker, machine, and
fixture." This means easy loading and unloading of parts and easy use of fixtures and jigs, which
were common improvements already being made during this internship.
The remaining segment of the Direct Labor branch requires "balanced work loops" as a
way to "eliminate operators' waiting on other operators." This functional requirement is an issue
that will have to be worked out in greater detail when the cells are actually formed.
4.7 Indirect Labor
Figure 4-11 shows the "Indirect Labor" branch of the MSDD. Both FRs and DPs of this
branch deal with decreasing the amount of indirect labor involved in running the production
system. This branch of the tree is a basic goal of any company and should always be improved
upon whenever possible.
Level IV
FR-11
Improve effectiveness of
production managers
FR-12
Eliminate information
disruptions
PM-11
Amount of indirect labor
required to manage system
PM-12
Amount of indirect labor
required to schedule system
DP-11
Self directed work teams
(horizontal organization)
DP-12
Seamless information flow
(visual factory)
Figure 4-11: Level IV of the "Indirect Labor" branch of the MSD Decomposition.
59
5.0 CONCLUDING COMMENTS
5.1 Summary
By making the transition from job shop to lean manufacturing, ABB will see significant
improvements in their production system. If the improvements suggested in this thesis are
implemented, ABB will see a reduction in the floor space consumed, reduced scrap and re-work
levels, decreased production costs, decreased throughput time, and increased quality. The
production system will become more structured and systematic, which will provide a better
atmosphere for making continuous improvements.
5.2 Obstacles
The major obstacles that ABB will encounter in making the transition to the "lean"
system design are resistance to change, the challenge of mixing cellular manufacturing with
project shop manufacturing, and the quality regulations set forth in the ASME Code. The first
two obstacles can be dealt with over time and with some patience and persistence. The key to
overcoming resistance to change is to make sure that all change is a team effort. The transition
cannot be made by one or two extremely motivated individuals. Everyone, from upper
management on through the machine operators, must be involved with making decisions and
implementing change. Hopefully, as changes are made, people will see the results and be
encouraged to continue.
Dealing with the mix of cellular and project shop manufacturing will be a challenge
because there aren't many examples in existence to learn from. Much of the literature on "lean"
manufacturing and implementation of the Toyota Production System describe fast-paced, high
volume production, such as the automobile industry, where parts are in continuous motion. This
60
is obviously not the case at ABB. Fortunately, some companies in the aerospace and ship
building industries have begun implementing cellular manufacturing systems that require some
parts/assemblies to remain stationary.
Working the ASME code regulations into a cellular manufacturing system, however, is
going to be very difficult. The Code prohibits self inspection and successive inspection since
inspection cannot be done by anyone involved in making the part, which means that separate
inspectors must be involved.
Quality in the nuclear industry takes on a slightly different meaning than most other
industries. Even the smallest defects can have devastating effects. Thus, it is understandable
that the nuclear industry is extra cautious about inspection. However, being cautious does not
mean that there must be specially designated inspectors. Dimensional inspection can be done
just as well by a worker in the cell as it can be done by a special inspector. If there is concern
that a worker may compromise judgement while inspecting parts that he, personally, made, then
successive inspection should be used. Of course, this means that the workers will have to be
properly trained to know exactly how to use the measuring devices, as well as how to read
drawings properly and understand tolerances.
When it comes to inspecting welds and performing NDE tests, however, specially trained
inspectors may still be needed. To train each worker to perform each NDE test would be more
time consuming and costly than employing a few specially trained inspectors.
5.3 The Next Steps
The very first step in a lean implementation process is forming a team of people, ranging
from top-level management, to engineers, to shop workers, who will be the heart and soul of the
61
changing process. At ABB-CE Newington Operations, that team would involve a wide variety
of people including the general manager, project manager, plant manager, union steward,
manufacturing engineer(s), design engineer, maintenance foreman, quality engineering, NDE
level III supervisor, production control, and shop workers.
Because Newington is so tight-staffed, it would be most beneficial if this team designated
a few people as the core of the group, the central cluster that would dedicate much of their time
to making this cellular implementation work and constantly working to improve the current
system. The rest of the larger team must also be involved in terms of keeping up to date on the
progress being made, giving their input whenever something new is implemented or whenever
they have an idea for improvement, and as support for the central core. Without the support and
backing of the entire team, the cellular implementation will not be successful.
Another step that needs to be taken early on is to improve the accounting system at ABB.
Having an accurate count of exactly how much time each operation takes is vital to making
improvements. Without this information, ABB won't know which operations are holding up
production and delaying throughput time.
First of all, the MPSs need to be more detailed and each process needs to be distinctly
separated. Currently, multiples tasks are included in the same "sequence" on the MPS, which
means that the times to perform each separate task are lumped into one total amount on the
accounting sheet. Another problem is that times for each sequence of the MPS often get
jumbled. For example, suppose a worker spends 6 hours of his day on one particular sequence
but then works on the next sequence for the last 45 minutes of his shift. Usually, the worker will
simply put all 6 hours 45 minutes down as the first sequence, rather than distinctly separating the
last 45 minutes. This results in inaccurate records of time requirements. Also, if a machine
62
breaks down, the downtime is recorded as time for the sequence that was currently being worked
on at the time of the breakdown. Thus, something that only takes 4 hours to complete, may
actually say that it took 8 hours to complete, when 4 hours of that time was spent repairing a
machine. Similarly, time spent retrieving tools and supplies is recorded as time spent on the
particular machining/welding/assembly sequence. All of the above misrepresentations of time
snowball into one large time chunk for each sequence that no one can completely explain. As a
result, the accounting records are of no use to anyone in the future. The records can't be used to
improve time estimates for bidding purposes, or as a means to pinpoint true critical paths and
improve processes.
In order for a truly smooth cellular manufacturing system to be designed and worked out,
the accounting system (time recording system) needs to be revamped. Accurate time logging
needs to be done for each sequence of each MPS, where each sequence consists of one operation.
Activities such as machine breakdowns, tool searching, lunch breaks need to be clearly
differentiated from actual production.
As mentioned in Chapter 4, ABB also needs to begin keeping track of the amount of
scrap produced, the amount of work-in-process, the amount of inventory, and the amount of
rework done. These performance measures will help provide motivation for making changes and
will also help gauge the level of improvement over time.
5.4 Final Comments
The main point of this thesis was to show how the MSD Decomposition, based on the
philosophies of the Toyota Production System, can be applied to the current production system at
ABB in order to make improvements to the system as a whole, while coping with the constraints
63
and speed bumps of the nuclear industry. The recommendations put forth in this thesis are only
starting points. Continuous improvement efforts must be made through kaizen teams.
This thesis has discussed each branch of the MSD Decomposition separately as related to
the production system at ABB. Certain FRs and DPs were emphasized over others because of
their relevance to the current system at ABB, though every single one is important to the system
as a whole. Making the transition to lean isn't easy or cheap, but is worth the investment in the
end when the money that the new system is saving over the old system begins to add up and
customers are more satisfied because they're receiving better quality products faster than before.
64
REFERENCES
American Society of Mechanical Engineers Boiler and Pressure Vessel Code, Section III,
Division 1, Nuclear Power Plant Components.
American Society of Mechanical Engineers Boiler and Pressure Vessel Code, Section III,
Division 3, Nuclear Power Plant Components (Containment Systems and Transport
Packagings for Spent Nuclear Fuel and High Level of Radioactive Waste.
Black, J.T., The Design of the Factory with a Future. McGraw-Hill, Inc., New York, NY,
1991.
Cochran, David S., "2.82/2.812 Design and Control of Manufacturing Systems Course Notes",
Massachusetts Institute of Technology, Cambridge, MA, 1999.
Cochran, David S. and Paulo C. Lima, "Manufacturing System Design Decomposition, version
5.1". Production System Design Laboratory, Massachusetts Institute of Technology,
2000.
DeVor, Richard, Tsong-how Chang, and John W. Sutherland, Statistical Quality Design and
Control: Contemporary Concepts and Methods. Prentice Hall, Upper Saddle River,
NJ, 1992.
Interviews with Richard Brillon, Gerry Dopp, Ken Fortin, Dave Kelley, Richard Talbot, Robert
Thompson, Scott Vallimont, and Carl Waterhouse, all of ABB Combustion Engineering
Nuclear Power Newington Operations.
Interview (via telephone) with Dr. J.T. Black, June 2, 2000.
Ohno, Taiichi, Toyota Production System: Beyond Large-Scale Production. Productivity
Press, Cambridge, MA, 1988.
Shingo, Shigeo, A Study of the Toyota Production System From an Industrial Engineering
Viewpoint. Productivity Press, Portland, OR, 1989.
Storch, Richard Lee, Cohn P. Hammon, Howard M. Bunch, and Richard C. Moore, Ship
Production, Second Edition. The Society of Naval Architects and Marine Engineers,
Jersey City, NJ, 1995.
Suh, Nam P., The Principles of Design. Oxford University Press, New York, NY, 1990.
65
Appendix A
The following standardized work combination sheets are for the tube steel arms in the sample machining cell presented in
Chapter 4. Similar sheets were done for all parts going through the cell. All operations are completely manual.
Page
Standard Operations
Work
sequence
02
5x2 Tube Steel Arm
Cell #
Work content
Machine
120s
3s
90s
2s
04
Inspect length
30s
06
Mark P/N, S/N
20s
08
Deburr & clean ID
60s
10
Punch holes
10s
12
Inspect holes
60s
5s
20
Deburr all edges (after milling)
360s
4s
14
Mill chamfers
30s
120s
16
Mill weld preps
30s
240s
18
Inspect chamfers & weld preps
240s
850s
5
Walk
I0s
Takt Time:
15.96
min.
10
15
-
-
4s
16s
3s
3s
2s
586s
pages
-
Walking
Operations Time (minutes)
Cut to length on cut off saw
TOTAL
Main
Cross
Assy
Time (seconds)
Manual
1
Machine Processing - - - - - -
Routine Sheet
Part name
of
Manual operation
Date:
17
Part no.
1
26s
Takt lime
1462s (24.4 min)
66
20
25
Page
19
Part no.
Standard Operations
Work content
Work
sequence
Cut to length on cut off saw
02
I0s
Machine
120s
5
Walk
3s
Takt Time:
15
10
-
30s
Inspect length
06
Mark P/N, S/N
08
Deburr & clean ID
60s
2s
10
Mill holes
20s
3s
2O0s
12
Inspect
60s
5s
20
Deburr all edges (after milling)
360s
4s
14
Mill chamfers
30s
120s
16
Mill weld preps
30s
240s
18
Inspect chamfers & weld preps
240s
TOTAL
15.96
min.
860s
3s
2s
670s
Walking
Operations Time (minutes)
Time (seconds)
04
holes
Main
Cross
Assy
Cell #
Manual
24s
1554s k2j.9 11n.)
1
~CA.
~
67
pages
Processing- - ---
______________________Machine
2x2 Tube Steel Arm
1
of
Manual operation
Date:
Routine Sheet
Part name
1
A
......
T
kdt
Ti,
a me,
20
25
-