Transcript Module 8B Lean Systems
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Lean Systems
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For Operations Management, 9e by Krajewski/Ritzman/Malhotra © 2010 Pearson Education 8 – 1
Lean Systems
Lean systems affect a firm’s internal linkages between its core and supporting processes and its external linkages with its customers and suppliers.
One of the most popular systems that incorporate the generic elements of lean systems is the just-in time (JIT) system.
The Japanese term for this approach is Kaizen. The key to kaizen is the understanding that excess capacity or inventory hides process problems.
The goal is to eliminate the eight types of waste.
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Eight Wastes
TABLE 8.1 | THE EIGHT TYPES OF WASTE OR MUDA Waste 1. Overproduction 2. Inappropriate Processing 3. Waiting 4. Transportation 5. Motion 1. Inventory 1. Defects 1. Underutilization of Employees Definition Manufacturing an item before it is needed.
Using expensive high precision equipment when simpler machines would suffice. Wasteful time incurred when product is not being moved or processed. Excessive movement and material handling of product between processes.
Unnecessary effort related to the ergonomics of bending, stretching, reaching, lifting, and walking.
Excess inventory hides problems on the shop floor, consumes space, increases lead times, and inhibits communication.
Quality defects result in rework and scrap, and add wasteful costs to the system in the form of lost capacity, rescheduling effort, increased inspection, and loss of customer good will.
Failure of the firm to learn from and capitalize on its employees’ knowledge and creativity impedes long term efforts to eliminate waste.
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Continuous Improvement
Figure 8.1 – Continuous Improvement with Lean Systems
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Supply Chain Considerations
Close supplier ties
Low levels of capacity slack or inventory
Look for ways to improve efficiency and reduce inventories throughout the supply chain
JIT II
In-plant representative
Benefits to both buyers and suppliers
Small lot sizes
Reduces the average level of inventory
Pass through system faster
Uniform workload and prevents overproduction
Increases setup frequency
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Process Considerations
Pull method of work flow
Push method
Pull method
Quality at the source
Jidoka
Poka-yoke
Anadon
Uniform workstation loads
Takt time
Heijunka
Mixed-model assembly
Lot size of one
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Process Considerations
Standardized components and work methods
Flexible workforce
Automation
Five S (5S) practices
Total Preventive Maintenance (TPM)
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Five S Method
TABLE 8.2 | 5S DEFINED 5S Term 1. Sort 2. Straighten 3. Shine 4. Standardize 5. Sustain 5S Defined Separate needed from unneeded items (including tools, parts, materials, and paperwork), and discard the unneeded.
Neatly arrange what is left, with a place for everything and everything in its place. Organize the work area so that it is easy to find what is needed.
Clean and wash the work area and make it shine.
Establish schedules and methods of performing the cleaning and sorting. Formalize the cleanliness that results from regularly doing the first three S practices so that perpetual cleanliness and a state of readiness are maintained.
Create discipline to perform the first four S practices, whereby everyone understands, obeys, and practices the rules when in the plant. Implement mechanisms to sustain the gains by involving people and recognizing them via a performance measurement system.
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Designing Lean System Layouts
Line flows recommended
Eliminate waste
One worker, multiple machines (OWMM)
Group technology
Group parts or products with similar characteristics into families
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Group Technology
Figure 8.2 – One-Worker, Multiple-Machines (OWMM) Cell
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Group Technology
Figure 8.3 – Process Flows Before and After the Use of GT Cells Lathing Milling L L M M D Drilling D D D L L M M L L M M G Grinding G L L Receiving and shipping A Assembly A A A (a) Jumbled flows in a job shop without GT cells
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G G G G 8 – 11
Group Technology
Figure 8.3 – Process Flows Before and After the Use of GT Cells L Receiving L L Cell 1 L Cell 3 M D M D M Cell 2 G G G (b) Line flows in a job shop with three GT cells A Assembly area A Shipping
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The Kanban System
Receiving post Kanban card for product 1 Kanban card for product 2 Storage area Empty containers O 2 O 1 Fabrication cell O 3 O 2 Figure 8.4 – Single-Card Kanban System
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Full containers Assembly line 1 Assembly line 2 8 – 13
The Kanban System
Receiving post Kanban card for product 1 Kanban card for product 2 Storage area Empty containers O 2 O 1 Fabrication cell O 3 O 2 Figure 8.4 – Single-Card Kanban System
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Full containers Assembly line 1 Assembly line 2 8 – 14
The Kanban System
Receiving post Kanban card for product 1 Kanban card for product 2 Storage area Empty containers O 2 O 1 Fabrication cell O 3 O 2 Figure 8.4 – Single-Card Kanban System
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Full containers Assembly line 1 Assembly line 2 8 – 15
The Kanban System
Receiving post Kanban card for product 1 Kanban card for product 2 Storage area Empty containers O 2 O 1 Fabrication cell O 3 O 2 Figure 8.4 – Single-Card Kanban System
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Full containers Assembly line 1 Assembly line 2 8 – 16
The Kanban System
Receiving post Kanban card for product 1 Kanban card for product 2 Storage area Empty containers O 2 O 1 Fabrication cell O 3 O 2 Figure 8.4 – Single-Card Kanban System
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Full containers Assembly line 1 Assembly line 2 8 – 17
The Kanban System
Receiving post Kanban card for product 1 Kanban card for product 2 Storage area Empty containers O 2 O 1 Fabrication cell O 3 O 2 Figure 8.4 – Single-Card Kanban System
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Full containers Assembly line 1 Assembly line 2 8 – 18
The Kanban System
Receiving post Kanban card for product 1 Kanban card for product 2 Storage area Empty containers O 2 O 1 Fabrication cell O 3 O 2 Figure 8.4 – Single-Card Kanban System
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Full containers Assembly line 1 Assembly line 2 8 – 19
The Kanban System
1.
2.
3.
4.
5.
6.
Each container must have a card Assembly always withdraws from fabrication (pull system) Containers cannot be moved without a kanban Containers should contain the same number of parts Only good parts are passed along Production should not exceed authorization
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Number of Containers
Two determinations
Number of units to be held by each container
Determines lot size
Number of containers
Estimate the average lead time needed to produce a container of parts
Little’s law
Average work-in-process inventory equals the average demand rate multiplied by the average time a unit spends in the manufacturing process
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Number of Containers
WIP = (average demand rate)
(average time a container spends in the manufacturing process) + safety stock WIP =
kc kc
=
d
(
w
+
p
)(1 + α)
k
=
d
(
w
+
p
)(1 + α)
c
where
k
= number of containers
d
= expected daily demand for the part
w
= average waiting time
p
= average processing time
c
= number of units in each container α = policy variable
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Number of Containers
Formula for the number of containers
k
= Average demand during lead time + Safety stock Number of units per container WIP = (average demand rate)(average time a container spends in the manufacturing process) + safety stock
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Determining the Appropriate Number of Containers
EXAMPLE 8.1
The Westerville Auto Parts Company produces rocker-arm assemblies
A container of parts spends 0.02 day in processing and 0.08 day in materials handling and waiting
Daily demand for the part is 2,000 units
Safety stock equivalent of 10 percent of inventory a. If each container contains 22 parts, how many containers should be authorized?
b. Suppose that a proposal to revise the plant layout would cut materials handling and waiting time per container to 0.06 day. How many containers would be needed?
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Determining the Appropriate Number of Containers
SOLUTION a. If
d p
= 0.02 day, α = 0.10,
w c
= 2,000 units/day, = 0.08 day, and = 22 units b. Figure 8.5 from OM Explorer shows that the number of containers drops to 8.
k
= 2,000(0.08 + 0.02)(1.10) 22 220 22 Figure 8.5 – OM Explorer Solver for Number of Containers
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Other Kanban Signals
Cards are not the only way to signal need
Container system
Containerless system
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Value Stream Mapping (VSM)
Value stream mapping is a qualitative lean tool for eliminating waste Creates a visual “map” of every process involved in the flow of materials and information in a product’s value chain
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Product family Current state drawing Future state drawing Work plan and implementation Figure 8.6 – Value Stream Mapping Steps 8 – 27
Value Stream Mapping
Figure 8.7 – Selected Set of Value Stream Mapping Icons
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Value Stream Mapping
Figure 8.8 – A Representative Current State Map for a Family of Retainers at a Bearings Manufacturing Company
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House of Toyota
A key challenge is to bring underlying philosophy of lean to employees in an easy-to-understand fashion
The house conveys stability
The roof represents the primary goals of high quality, low cost, waste elimination, and short lead-times
The twin pillars, which supports the roof, represents JIT and jidoka
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House of Toyota
Just in Time (JIT)
Takt time One-piece flow Pull system Highest quality, lowest cost, shortest lead time by eliminating wasted time and activity Culture of Continuous Improvement
Jidoka
Manual or automatic line stop
Separate operator and machine activities Error-proofing Visual control Heijunka Figure 8.9 – House of Toyota
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Operational Stability Standard Work TPM Supply Chain 8 – 31
Operational Benefits and Implementation Issues
Organizational considerations
Human costs of lean systems
Cooperation and trust
Reward systems and labor classifications
Process considerations
Inventory and scheduling
Schedule stability
Setups
Purchasing and logistics
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Solved Problem
A company using a kanban system has an inefficient machine group. For example, the daily demand for part L105A is 3,000 units. The average waiting time for a container of parts is 0.8 day. The processing time for a container of L105A is 0.2 day, and a container holds 270 units. Currently, 20 containers are used for this item.
a. What is the value of the policy variable, α?
b. What is the total planned inventory (work-in-process and finished goods) for item L105A?
c. Suppose that the policy variable, policy variable in this example?
α, was 0. How many containers would be needed now? What is the effect of the
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Solved Problem
SOLUTION a. We use the equation for the number of containers and then solve for α:
k
=
d
(
w
+
p
)(1 + α)
c
= 3,000(0.8 + 0.2)(1 + α) 270 so 20(27) (1 + α) = = 1.8 3,000(0.8 + 0.2) α = 1.8 – 1 = 0.8
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Solved Problem
b. With 20 containers in the system and each container holding 270 units, the total planned inventory is 20(270) = 5,400 units c. If α = 0
k
= 3,000(0.8 + 0.2)(1 + 0) 270 = 11.11, or 12 containers The policy variable adjusts the number of containers. In this case, the difference is quite dramatic because daily demand.
w
+
p
is fairly large and the number of units per container is small relative to
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Application 8.1
Item B52R has an average daily demand of 1000 units. The average waiting time per container of parts (which holds 100 units) is 0.5 day. The processing time per container is 0.1 day. If the policy variable is set at 10 percent, how many containers are required?
k
=
d
(
w
+
p
)(1 + α)
c
= 1,000(0.05 + 0.01)(1 + 0.1) 100 = 6.6, or 7 containers
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