Chapter 6: Inventory Control

Chapter 6: Inventory Control
1.Reasons for Holding Inventories
Summarize Sheet Final (2/2014)
IBM4715: Designing and Managing
Global Operations
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Economies of Scale
Uncertainty in delivery lead times
Speculation. Changing Costs Over Time
Demand Uncertainty
Costs of Maintaining Control System
2.Relevant Costs
1.Holding Costs - Costs proportional to the quantity of inventory held.
2.Ordering Cost (or Production Cost). Includes both fixed and variable components.
3.Penalty or Shortage Costs. All costs that accrue when insufficient stock is available
to meet demand leading to Loss of revenue for lost demand, Costs of bookkeeping for
backordered demands ,Loss of goodwill for being unable to satisfy demands
3. Inventory Systems
3.1Single-period inventory:
One time purchasing decision and seeks to balance
the costs of inventory overstock and under stock
3.2Multi-period Models:
Demand for the product is constant and uniform
throughout the period.
Lead time (time from ordering to receipt) is
constant. Price per unit of product is constant.
Inventory holding cost is based on average
inventory ,Ordering or setup costs are constant , all
demands for the product will be satisfied---- FixedOrder Quantity Models
***Fixed-Order Quantity Models formula
Question: An auto parts supplier sells Hardy-brand batteries to car dealers and auto
mechanics. The annual demand is approximately 1,200 batteries. The supplier pays $28
for each battery and estimates that the annual holding cost is 30 percent of the battery’s
value. It costs approximately $20 to place an order (managerial and clerical costs). The
supplier currently orders 100 batteries per month. Determine the ordering, holding, and
total inventory costs for the current order quantity and find EOQ?
Solution: The current ordering and holding costs are
: The EOQ is
***Quantity Discount Models ----divide into 2 methods
All Units Discounts: the discount is applied to ALL
of the units in the order. Gives rise to an order cost
function such as that pictured in Figure 4-9 .For all
units discounts, the optimal will occur at the bottom
of one of the cost curves or at a breakpoint. (It is
generally at a breakpoint.). One compares the cost at
the largest realizable EOQ and all of the breakpoints
succeeding it.
Incremental Discounts: the discount is applied only
to the number of units above the breakpoint. Gives
rise to an order cost function such as that pictured in
Figure 4-10. For incremental discounts, the optimal
will always occur at a realizable EOQ value.
Compare costs at all realizable EOQ’s.
Chapter 8: Lean Production
Lean Production
can be defined as an integrated set of activities designed to achieve high-volume
production using minimal inventories (raw materials, work in process, and finished
goods) involves
The elimination of waste in production effort
The timing of production resources (i.e., parts arrive at the next workstation “just
in time”
Elimination of Waste
1. Focused factory networks
2. Group technology
3. Quality at the source
4. JIT production
5. Uniform plant loading
6. Kanban production control system
7. Minimized setup times
Focused Factory Networks
Small factories gather together because if let only one big firm responds for each
region separately it has some eliminations such as
 Resource of quality labor – limited amount of qualified engineers
 Risk of the firm – economic, political, environmental risk
 Small, medium firms can be controlled easily
Minimizing Waste: Group Technology
Old Fashion – Department Specialization, Chaos order and slow
Base on sequence – Lesser mistakes, easier
• Card which indicates standard quantity of production
• Derived from two-bin inventory system
• Maintain discipline of pull production
• Authorize production and movement of goods
Kanban Production Control Systems
Types of Kanban
• Production kanban – authorizes production of goods
• Withdrawal kanban – authorizes movement of goods
• Kanban square – a marked area designated to hold items
• Signal kanban – a triangular kanban used to signal production at the previous
• Material kanban – used to order material in advance of a process
• Supplier kanban – rotates between the factory and suppliers
Determining the Number of Kanbans Needed
• Setting up a kanban system requires determining the number of kanbans cards (or
containers) needed
• Each container represents the minimum production lot size
• An accurate estimate of the lead time required to produce a container is key to
determining how many kanbans are required
Respect for People
• Level payrolls
• Cooperative employee unions
• Subcontractor networks
• Bottom-round management style
• Quality circles (Small Group Involvement Activities or SGIA’s)
Lean Implementation Requirements: Design Flow Process
• Link operations
• Balance workstation capacities
• Redesign layout for flow
• Emphasize preventive maintenance
Chapter 9: Facilities Location
What is Logistics?
The movement of goods through the supply chain
“the art and science of and product in the proobtaining, producing, and distributing
material per place and in proper quantities”
How to best transport goods?
Modes of transportation
1. Truck
2. Ship
3. Rail pipelines
1. Consolidation
2. Cross Docking
3. Hub-and-Spoke systems
Plant Location Methodology: Transportation Method of Linear Programming
Transportation method of linear programming seeks to minimize costs of shipping n
units to m destinations or its seeks to maximize profit of shipping n units to m
Plant Location Methodology: Centroid Method
The centroid method is used for locating single facilities that considers existing
facilities, the distances between them, and the volumes of goods to be shipped
between them.
This methodology involves formulas used to compute the coordinates of the twodimensional point that meets the distance and volume criteria stated above.
Cx = X coordinate of centroid
Cy = X coordinate of centroid
dix = X coordinate of the its location
diy = Y coordinate of the its location
Vi = volume of goods moved to or from its location
To find what is the best location?
1. To begin, you must identify the existing facilities on a two- dimensional plane or
grid and determine their coordinates.
2. You must also have the volume information on the business activity at the existing
3. You then compute the new coordinates using the formulas.
4. You then take the coordinates and place them on the map.
Chapter 10: Quality Management
1.Meaning of Quality
Consumer’s and producer perspectives depend on each other
-Consumer’s perspective: PRICE ƒ
-Producer’s perspective: COST
Consumer’s view must dominate
**** Quality of conformance:
Making sure product or service is produced according to design.
for example, if a hotel room is not clean when a guest checks, hotel is not
functioning according to specifications of its design
2.Total Quality Management
Partnering: a relationship between a company
and its supplier based on mutual quality
Customers: system must measure customer
Information Technology: infrastructure of
hardware, networks, and software necessary to
support a quality program
Participative problem solving: employees
involved quality management every employee has undergone extensive training to
provide quality service to Disney’s guests
Six Sigma
A process for developing and delivering near perfect products and services.
Measure of how much a process deviates from perfection.
It allows managers to readily describe process performance using a common metric:
Defects per Million
Opportunities (DPMO)
Cost of Quality :
Cost of Achieving Good Quality
--Prevention costs:costs incurred during product design
--Appraisal costs: costs of measuring, testing, and analyzing
Cost of Poor Quality:
-- Internal failure costs include scrap, rework, process failure, downtime,
include scrap, rework, process failure, downtime, and price reductions
- - External failure costs include complaints, returns, warranty claims,
include complaints, returns, warranty claims, liability, and lost sales
Seven Quality Control Tools Seven Quality Control Tools
1.Pareto Analysis
2. Flow Chart
5.Scatter Diagram
7. Cause--an d--Effect Diagram
3.Check Sheet
6. SPC Chart
Chapter 11: Statistic Process Control
Assignable variation is caused by factors that can be clearly identified and possibly
Also called special causes of variation
Generally this is some change in the process
Variations that can be traced to a specific reason
The objective is to discover when assignable causes are present
Eliminate the bad causes
Incorporate the good causes
Common/ Natural variation is inherent in the production process.
Also called common causes
Affect virtually all production processes
Expected amount of variation
Output measures follow a probability distribution
For any distribution there is a measure of central tendency and dispersion
If the distribution of outputs falls within acceptable limits, the process is said to
be “In control”
Process Capability
– Design specifications reflecting product requirements
Process capability
– Range of natural variability in a process what we measure with control
charts Process capability index
– Capability Index shows how well parts being produced fit into design
limit specifications.
– As a production process produces items small shifts in equipment or
systems can cause differences in production performance from differing
– A Standard Measure of How Good a Process Is. We use a simple ratio to
– This is a “one-sided” Capability Index Concentration on the side which is
closest to the specification - closest to being “bad”.
– A capable process must have a Cpk of at least 1.0
– A capable process is not necessarily in the center of the specification, but
it falls within the specification limit at both extremes
Interpreting Cpk
Types of Statistical Sampling
Attribute (Go or no-go information)
– Defective refers to the acceptability of product across a range of
– Defects refer to the number of defects per unit which may be higher than
the number of defectives.
– p-chart application
Variable (Continuous)
– Usually measured by the mean and the standard deviation.
– X-bar and R chart applications
Patterns in Control Charts
Steps in Creating Control Charts
1. Take samples from the population and compute the appropriate sample statistic
2. Use the sample statistic to calculate control limits and draw the control chart
3. Plot sample results on the control chart and determine the state of the process (in
or out of control)
4. Investigate possible assignable causes and take any indicated actions
5. Continue sampling from the process and reset the control limits when necessary
Control Charts for Attributes
For variables that are categorical - Good/bad, yes/no, acceptable/unacceptable
Measurement is typically counting defectives
Charts may measure - Percent defective (p-chart)
Control Limits for p-Charts
Population will be a binomial distribution, but applying the Central Limit
Theorem allows us to assume a normal distribution for the sample statistics
p = mean fraction defective in the sample z = number of standard deviations
σp^ = standard deviation of the sampling distribution
n = sample size
Control Charts for Variables
For variables that have continuous dimensions
Weight, speed, length, strength, etc.
X-charts are to control the central tendency of the process
R-charts are to control the dispersion of the process
These two charts must be used together
Setting Chart Limits
For x-Charts when we know σ
Upper control limit (UCL) = x + zσx
Lower control limit (LCL) = x - zσx
x = mean of the sample means or a target value set for the process
z = number of normal standard deviations
σx = standard deviation of the sample means = σ/ n
σ = population standard deviation n
n = sample size
R – Chart
Type of variables control chart
Shows sample ranges over time
Difference between smallest and largest values in sample
Monitors process variability
Independent from process mean
Upper control limit (UCLR) = D4R
Lower control limit (LCLR) = D3R
R = average range of the samples
D3 and D4 = control chart factors from
Table S6.1
Acceptance Sampling
Form of quality testing used for incoming materials or finished goods
Take samples at random from a lot (shipment) of items
Inspect each of the items in the sample
Decide whether to reject the whole lot based on the inspection results
Only screens lots; does not drive quality improvement efforts
Operating Characteristic Curve
Shows how well a sampling plan discriminates between good and bad lots
Shows the relationship between the probability of accepting a lot and its quality
Average Outgoing Quality
Pd = true percent defective of the lot
Pa = probability of accepting the lot
N = number of items in the lot
n = number of items in the sample
1. If a sampling plan replaces all defectives
2. If we know the incoming percent defective for the lot
We can compute the average outgoing quality (AOQ) in percent defective
The maximum AOQ is the highest percent defective or the lowest average quality
and is called the average outgoing quality level (AOQL)
SPC and Process Variability