1 fall 2005 analysis of global and local decision rules in a dual kanban job shop rafael diaz, ph.d....
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Fall 2005 1
Analysis of global and local decision rules in a
dual kanban job shop
Rafael Diaz, Ph.D. Student, Old Dominion University
Ali Ardalan, Ph.D., Old Dominion University
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Fall 2005 2
Content• Introduction• Background
– Push System versus Pull System – Kanban system - Definitions– Flow shop versus Job shop – JIT
• The model• Measures of performance• Results
– Customer Waiting lines– Total inventory– Input stock point inventory– Output stock point inventory
• Conclusions
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Fall 2005 3
Introduction• This study simulated the operation of four-station,
dual-kanban controlled, pure job shop that manufactures four products.
• Products went through the four stations in a different sequence.
• Results demonstrated that considering information regarding the length of customer queues, improves performance measures of both customer waiting time and total inventory.
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Fall 2005 4
Introduction• This work analyzes the effects of four kanban
policy variables – number of kanbans – length of withdrawal cycle– priority rule– information regarding the length of the customer queues
• on four performance criteria – average customer wait-time – total inventory – average of full containers in the input stock points of stations.
– average of full containers in the output stock points of stations.
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Fall 2005 5
C1 C2 C3 C4
C2
C3
C1
C4
C2C1
C2C1
C2C1
C2C1
C2C1
C2C1
C2C1
C2C1
Raw Material
Raw Material
Job Shop
Flow Shop
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Fall 2005 6
Just In Time - JIT• JIT refers to a scheduling system that minimizes inventory by having
material arrive just as it is about to be put in use. • To accomplish its goal, it is necessary to design production systems
wherein required materials are made available on the production floor exactly when is needed.
• JIT systems use containers and cards (kanbans). • A dual-kanban system has two types of cards: production and
withdrawal card.
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Fall 2005 7
Kanban System – Definitions•The Pull System means that materials are drawn or sent for by the users of the material as needed. [Hall]
•The Kanban System is an information system that harmoniously controls the production of the necessary products in the necessary quantities at the necessary time in every process of a factory and also among companies, which is known as the JIT production. [Monden]
•A Kanban is a tool to achieve JIT production. It is simply a card which is usually put in a rectangular vinyl envelope. [Monden]
•Two types of Kanban cards in general:
- Production-Ordering Kanban (or simply Production Kanban)
- Withdrawal Kanban (Conveyance or Transportation Kanban)
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Fall 2005 8
C2C1
C2C1
JIT Dual-Card Kanban Job Shop
O1
O2
O2
O3
C1
Empty Containers Full Containers
Withdrawal Card Assigned to take
Material inventories
Production Card Assigned to produce
Part 1 or Part2
C2C1
C1
Raw Material
12
3
4
C2C1
C2C1
C2C1
C2C1
C2C1
C2C1
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Fall 2005 9
JIT - Recent Studies• Bett et al (2005) - importance of replenishment in JIT and
investment in capital. • Takahashi, (2004) - JIT that considered changes in the
mean and variance of demand. • Chen et al (2004) methodology for integrating supplier and
manufacturer capabilities. • Richter et al (2003) developed a dynamic programming
solution for a general non-linear alternate deterministic dynamic product recovery model - suppliers & customers considered.
• Ardalan (1997) investigated the effects of local decision rules in a dual-kanban Flow Shop.
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Fall 2005 10
The Model• Description:
– The model system consists of:• Customer requirement arrivals • Four manufacturing Cells• Customer Departures
– The system produces 4 parts, each visiting different sequence of station:
• Exponential and Poisson distributions for interarrival and process times.
• Interarrival time provided about 90% utilization level. • The study considered systems with one, two, and three kanbans.
Part
1 3 2 1 42 4 1 2 33 1 4 3 24 2 3 4 1
Part Sequence PlansCell
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Fall 2005 11
Description• Description:
– The time to move between any pair of cell is 1 minute, regardless of the distance.
– Replication length 10,000 hours. Number of replication:100.
– Cell producing a single-item class.– The inputs to the production process (raw material or
labor) are always available.– Simulation Application: Arena.– Statistical Analysis: SAS.
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Fall 2005 12
The Model - Continuation• We considered two of the most accepted priority
rules – First In, First Out (FIFO)– Shortest Processing Time (SPT).
• Two levels of length of customer queues – use the information of the length of the customer – not use this information.
• Five levels of Withdrawal Cycle, were 28, 36, 44, 52, and 60 periods.
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Fall 2005 13
Measures of performance• The policies were evaluated with respect to
– Average customer wait time– The total of full containers in the system– The sum of the average number of full containers
in the input and output stock points.
• The first criterion is a measure of customer service, and the last two criteria are measures of WIP in the input and output stock point
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Fall 2005 14
Results
• Using full factorial analysis of variance
• Confidence levels of 95%.
• Indicated significant interaction among the four components.
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Fall 2005 15
Results – Customer Waiting Times
Using Customer Queue Info
Without Using Customer Queue Info
# Kabans SPT FIFO SPT FIFO
3 24.86 31.38 38.43 54.38
2 61.72 68.11 89.96 113.68
1 423.12 422.55 540.61 463.75
Customer Waiting Time
0
100
200
300
400
500
600
1 2 3
# Kabans
W. Cycle = 60
SPT – Using Info
FIFO – Using Info
SPT – Without Using Info
FIFO – Without Using Info
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Fall 2005 16
Results - Customer waiting time
• Statistically significant differences between the average wait times.
• Overall, for those treatments that used information, results were up to 37 % shorter than those treatments that ignored this information.
• Effects of withdrawal cycle for treatments with one kanban were observed more markedly.
• With one kanban - using FIFO and information performed better than the ones that used SPT and ignored the information on the customer waiting line.
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Fall 2005 17
Customer waiting time • A large number of kanbans increases the availability of
WIP that stations use to produce end products. • It reduces the possibility of starvation and improves
the availability of end products. • Short withdrawal cycle improves the station’s
responsiveness to demand The result is short customer wait times.
• Using the information increases the likelihood of producing the items that have real customer demand rather than producing items just to replenish inventory.
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Fall 2005 18
Total inventory • There were interactions: number of kanbans, the withdrawal cycle,
and the priority rule. • Treatments with 1, 2, and 3 kanbans and withdrawal cycles were
significantly different. • There exist interactions between the number of kanbans, priority
rule, and the status of the customer line length information. • With one kanban had significantly lower inventory levels than those
with two and three kanbans. • Similar results for 2 and 3 kanbans.• There is no evidence of mean differences for a treatment with one
kanban that used FIFO and those that used SPT.• The priority rule had a minor effect on total inventory
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Fall 2005 19
Input stock point inventory
• Treatments with two kanbans using FIFO or SPT priority rule were not significantly different from each other.
• Using the information regarding status of customer waiting line was significantly different.
• Magnitude of the effects are number of kanbans, the status of customer waiting line, and priority rule.
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Fall 2005 20
Output stock point inventory• Those that used the information regarding the length
of the customer queue had significantly smaller WIP than those that ignored such information.
• Treatments with two kanbans that used the information, those with FIFO had significantly smaller WIP in output stock points than those with SPT.
• The analysis of all pairwise comparisons of treatments means shows that: – One kanban and withdrawal cycle 60: lowest level
of inventory – Three kanbans and withdrawal cycle of 28 :
highest level of inventory.
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Fall 2005 21
Output stock point inventory
• Using the information results in assigning higher priority to production of products that have an immediate customer demand.
• Using information reduces the inventory levels in the output stock point of station: As soon as these items are made, they will be moved to succeeding stations..
• The priority rule FIFO results in low levels of inventory : since it may assign a higher priority to jobs that take a long time to be processed, therefore, it may replenish output stock point inventory at slower rate than Short Processing Time (SPT).
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Fall 2005 22
Conclusions • Using the information regarding customer
queue length in job shops:– It increases service levels, and – It reduces total inventory simultaneously.
• Treatments that used the information of customer queue length result in shorter customer wait time.
• It is more marked when smaller number of kanbans is used.
• Whenever the information is used, finished and semi-finished products that have higher customer demand will be produced.
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Fall 2005 23
Conclusions
• Priority rules and status of customer waiting line had a minor effect on total inventory, treatments with FIFO that used the information regarding the length of the customer queue, resulted in the lowest total inventory.
• The experiments demonstrated that the input and output stock point inventory responded similarly to the number of kanbans and withdrawal cycle changes.
• Increasing the number of kanbans from 1 to 2, and from 2 to 3, resulted in a similar increase in both input and outputs stock point inventories.
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Fall 2005 24
Conclusions • When the number of kanbans was reduced from two to
one for treatments with cycle of 60, the inventory dropped significantly.
• Although customer wait time increased, when the number of kanban was reduced from three to two, the decrease in total inventory was disproportionately larger.
• It may be possible to decrease the number of kanbans and have a significant decrease in WIP inventory without severely increasing the average customer wait time.
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Fall 2005 25
References • Ardalan, Alireza, “Analysis of local decision rules in a dual-kanban Flow
Shop,” Decision Sciences, Vol. 28, No. 1 (1997), pp. 195- 211. • Betts, John M., and Robert B. Johnston, “Just-in-time component
replenishment decisions for assemble-to-order manufacturing under capital constraint and stochastic demand,” International Journal of Production Economics, Amsterdam: January 28, Vol. 95, (2005), pp. 51-70.
• Chen, Chee-Cheng, Tsu-Ming Yeh, and Ching-Chow, Yang, “Customer-focused
rating system of supplier quality performance,” Journal of Manufacturing Technology Management, Bradford, Vol. 15, Issue 7 (2004), pp. 599-617.
• Richter Knut, and Barbara Gobsch, “The market-oriented dynamic product
recovery model in the just-in-time framework International,” Journal of Production Economics, Amsterdam: January 11, Vol. 81/82 (2003), pp. 369-374.
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Fall 2005 26
References• Stephe, Shmanske, “JIT and the complementarity of buffers and lot size,”
American Business Review, West Haven: January, Vol. 21, Issue 1, (2003), pp. 100-106.
• Takahashi, Katsuhiko, Katsumi Morikawa, and Nobuto Nakamura, “Reactive
JIT ordering system for changes in the mean and variance of demand,” International Journal of Production Economics, Amsterdam, Vol. 92, Issue. 2 (2004), pp. 181-196.
• White, Richard E, and John N. Pearson, “JIT system integration and
customer service,” International Journal of Physical Distribution & Logistics Management, Bradford, Vol. 31, Issue 5, (2001), pp. 313-333.
• Yang, Jiaqin, and Richard H. Deane, “A lotsize reduction model for just-in-
time manufacturing systems,” Integrated Manufacturing Systems,Vol. 13, Issue 7, (2002), pp. 471-488.
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Fall 2005 27
Thank you!