Process Flexibility in Supply Chains

Graves, Stephen C.; Tomlin, Brian

doi:10.1287/mnsc.49.7.907.16381

Cited by 277 publications

(129 citation statements)

References 9 publications

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“…In other words, "a little flexibility goes a long way." Graves and Tomlin (2003) showed that similar chaining benefits extend to multistage systems. 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.…”

Section: Introductionmentioning

confidence: 91%

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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Section: Introductionmentioning

confidence: 91%

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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“…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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“…Another focus of SC flexibility is the design of SCs. Chandra and Grabis (2009) present potential tools and techniques for designing and modeling flexibility in SCs, and Graves and Tomlin (2003) study how SCs can cost-efficiently deliver mix flexibility based on a mathematical model and subsequent simulation. Tsay and Lovejoy (1999) and Liao, Hong, and Rao (2010) have contributed to the topic of SC flexibility measurement by studying how to quantify flexibility and its impact on SC performance.…”

Section: Flexibilitymentioning

confidence: 99%

Supply Chain Resilience Analysis: A Brazilian Automotive Case

et al. 2015

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Supply chain (SC) resilience and flexibility are important research topics receiving growing attention. However, the academic literature needs empirical studies on SC resilience capable of investigating the inter-organizational components of flexibility along different tiers. Therefore, this paper analyzes the main lack of flexibilities in three Brazilian automotive SCs that limit their resilience and therefore their capacity to better support and meet the demand changes in the marketplace. A multi-tier case study approach is adopted. Research findings identify lack of flexibilities in different tiers that inhibit the SC resilience as well as manufacturing and SC flexibilities that build SC resilience. The findings also highlight that the same SC may have the flexibility to be resilient for one of its products but not for another product, what sheds new lights on the academic literature. Finally, flexible SCs should be designed to increase SC resilience to cope with mishaps as significant demand changes.KEYWORDS | Supply chain resilience, flexibility, supply chain flexibility, automotive industry, case study. RESUMO RAE-Revista de Administração de Empresas | FGV-EAESP

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Process Flexibility in Supply Chains

Cited by 277 publications

References 9 publications

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

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

Worst-Case Analysis of Process Flexibility Designs

Supply Chain Resilience Analysis: A Brazilian Automotive Case

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