Process flexibility: design, evaluation, and applications

Chou, Mabel C.; Teo, Chung‐Piaw; Zheng, Huan

doi:10.1007/s10696-008-9053-9

Cited by 73 publications

(41 citation statements)

References 34 publications

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“…To answer this question, the academic community started to develop flexibility design indices, following the original index developed in Jordan and Graves (1995), which we will refer to as the JG index. Other well-known indices include the Structural Flexibility index in Iravani et al (2005), WS-APL index in Iravani et al (2007), gMeasure in Graves and Tomlin (2003), and the Expansion index in Chou et al (2008). We refer the readers to , for a complete description of these indices.…”

Section: Literature Reviewmentioning

confidence: 99%

Worst-Case Analysis of Process Flexibility Designs

Simchi‐Levi

Wei

2015

Operations Research

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Authors are encouraged to submit new papers to INFORMS journals by means of a style file template, which includes the journal title. However, use of a template does not certify that the paper has been accepted for publication in the named journal. INFORMS journal templates are for the exclusive purpose of submitting to an INFORMS journal and should not be used to distribute the papers in print or online or to submit the papers to another publication. Theoretical studies of process flexibility designs have mostly focused on expected sales. In this paper, Worstwe take a different approach by studying process flexibility designs from the worst-case point of view. To study the worst-case performances, we introduce the plant cover indices (PCIs), defined by bottlenecks in flexibility designs containing a fixed number of products. We prove that given a flexibility design, a general class of worst-case performance measures can be expressed as functions of the design's PCIs and the given uncertainty set. This result has several major implications. First, it suggests a method to compare the worstcase performances of different flexibility designs without the need to know the specifics of the uncertainty sets. Second, we prove that under symmetric uncertainty sets and a large class of worst-case performance measures, the long-chain, a celebrated sparse design, is superior to a large class of sparse flexibility designs including any design that has a degree of two on each of its product nodes. Third, we show that under stochastic demand, the classical Jordan and Graves (JG) index can be expressed as a function of the PCIs.Furthermore, the PCIs motivate a modified JG index that is shown to be more effective in our numerical study. Finally, the PCIs lead to a heuristic for finding sparse flexibility designs that perform well under expected sales and have lower risk measures in our computational study.

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Section: Literature Reviewmentioning

confidence: 99%

Worst-Case Analysis of Process Flexibility Designs

Simchi‐Levi

Wei

2015

Operations Research

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“…generalized these chaining configurations that utilize level-2 flexible resources to D-skilled chains that consist of level-D flexible resources and showed that these configurations perform well in serial production lines. In recent work, Chou et al (2008) used the concept of graph expansion to construct flexible configurations that work well in newsvendor networks.…”

Section: Introductionmentioning

confidence: 99%

A Little Flexibility Is All You Need: On the Asymptotic Value of Flexible Capacity in Parallel Queuing Systems

Bassamboo

Randhawa

Mieghem

2012

Operations Research

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We analytically study optimal capacity and flexible technology selection in parallel queuing systems. We consider N stochastic arrival streams that may wait in N queues before being processed by one of many resources (technologies) that differ in their flexibility. A resource's ability to process k different arrival types or classes is referred to as level-k flexibility. We determine the capacity portfolio (consisting of all resources at all levels of flexibility) that minimizes linear capacity and linear holding costs in high-volume systems where the arrival rate → . We prove that "a little flexibility is all you need": the optimal portfolio invests O in specialized resources and only O √ in flexible resources and these optimal capacity choices bring the system into heavy traffic. Further, considering symmetric systems (with type-independent parameters), a novel "folding" methodology allows the specification of the asymptotic queue count process for any capacity portfolio under longest-queue scheduling in closed form that is amenable to optimization. This allows us to sharpen "a little flexibility is all you need": the asymptotically optimal flexibility configuration for symmetric systems with mild economies of scope invests a lot in specialized resources but only a little in flexible resources and only in level-2 flexibility, but effectively nothing (o √ ) in level-k > 2 flexibility. We characterize "tailored pairing" as the theoretical benchmark configuration that maximizes the value of flexibility when demand and service uncertainty are the main concerns.

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“…On the other hand, there is a mix-up risk, and an increased number of models could also give greater complexity and more work in progress. According to [32], there is a trade-off between the level of flexibility available in the system and the associated complexity and operating costs. The challenge is to have the "right" level of flexibility to capture Fig.…”

Section: Discussionmentioning

confidence: 99%

“…4 Potential for reduction of weld metal weight in the process of welded structures the benefits from a fully flexible system while controlling the increase in implementation costs. A slight increase in process flexibility can lead to a significant improvement in system performance [32].…”

Section: Discussionmentioning

confidence: 99%

Improved productivity by reduced variation in gas metal arc welding (GMAW)

Öberg

Åstrand

2017

Int J Adv Manuf Technol

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The purpose of the research conducted is to describe the consequences of variation in the welding industry and the effect it has on manufacturing productivity. The potential has shown to be hidden in unnecessarily stringent requirements and over-processing. This has been studied in steps: customer requirements, design and analysis, preparation, welding, and assessment. The effect of variation in each step has been analyzed including estimations of its productivity improvement potential. Theoretically, in a perfect situation, with customized requirements and eliminated variation, more than half of all welding could be removed. Such a reduction is certainly neither practical nor possible. However, a sensible, controlled reduction could still have a very high impact. The financial implications are therefore substantial. The improved productivity of the manufacturing resources could be used for business development and increased production. To be able to realize the potential, interdisciplinary efforts are necessary. Management across different functions need to agree on the intended product life and make decisions thereafter.

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Process flexibility: design, evaluation, and applications

Cited by 73 publications

References 34 publications

Worst-Case Analysis of Process Flexibility Designs

Worst-Case Analysis of Process Flexibility Designs

A Little Flexibility Is All You Need: On the Asymptotic Value of Flexible Capacity in Parallel Queuing Systems

Improved productivity by reduced variation in gas metal arc welding (GMAW)

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