Analysis of decentralized multi-product pull systems with lost sales

被引:7
|
作者
Gurgur, Cigdern Z. [1 ]
Altiok, Tayfur
机构
[1] Colorado Sch Mines, Div Business & Econ, Golden, CO 80401 USA
[2] Rutgers State Univ, Dept Ind & Syst Engn, Piscataway, NJ USA
关键词
decentralized production/inventory; kanban systems pull-type; batch transfers; multi-item/echelon/stage;
D O I
10.1002/nav.20210
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
We study a pull-type, flexible, multi-product, and multi-stage production/inventory systein with decentralized two-card kariban control policies. Each stage involves a processor and two buffers with finite target levels. Production stages, arranged in series, can process several product types one at a time. Transportation of seini-finished parts ftorri one staae to another is performed in fixed lot sizes. The exact analysis is mathematically intractable even for sinaller systems. We present a robust approximation algorithm to model two-card kanban systems with batch transfers under arbitrary complexity. The algorithm uses phase-type modefing to find effective processing times and busy period analysis to identify delays among product types in resource contention. Our algorithm reduces the effort required for estimating performance measures by a considerable margin and resolves the state-space explosion problem of analytical approaches. Using this analytical tool, we present new findings for a better understanding of soine tactical and operational issues. We show that flow of material in sinall procurement sizes smoothes flow of information within the system, but also necessitates iriore frequent shipments between stages, raising the risk of late delivery. Balancing the risk of information delays vis- -vis shipment delays is critical for the success of two-card kanban systems. Although product variety causes time wasted in setup operations, it also facilitates relatively short production cycles enabling processors to switch froin one product type to another more rapidly. The latter point is crucial especially in high-deniand environments. Increasing production line size prevents quick response to customer demand, but it may improve system performance if the vendor lead-tinie is lon, or Subject to high variation. Finally, variability in transportation and processing times causes the most damage if it arises at stages closer to the customer. (C) 2007 Wiley Periodicals, Inc.
引用
收藏
页码:357 / 370
页数:14
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