Managing Flexible Capacity in a Make-to-Order Environment

Bish, Ebru K.; Muriel, Ana; Biller, Stephan

doi:10.1287/mnsc.1040.0322

Cited by 83 publications

(59 citation statements)

References 16 publications

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“…Graves and Tomlin (2003), Bish et al (2005)), flexible workforce scheduling (cf. de Farias and Van Roy (2004), Hopp et al (2004)), and queuing (cf.…”

Section: Literature Reviewmentioning

confidence: 99%

“…For example, Graves and Tomlin (2003) extended Jordan and Graves (1995) to obtain flexibility guidelines for multistage supply chains. On the other hand, Bish et al (2005) cautioned that certain practices that might seem reasonable in a flexible system would lead to greater swings in production, resulting in higher operational costs, and might reduce profits. Iravani et al (2005) proposed a new perspective on process flexibility.…”

Section: Literature Reviewmentioning

confidence: 99%

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Process Flexibility Revisited: The Graph Expander and Its Applications

Chou

Chua

Teo

et al. 2011

Operations Research

110

104

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We examine how a flexible process structure might be designed to allow the production system to better cope with fluctuating supply and demand, and to match supply with demand in a more effective manner.We argue that good flexible process structures are essentially highly connected graphs, and use the concept of graph expansion (a measure of graph connectivity) to achieve various insights into this design problem.A number of design guidelines are well known in the literature. Principles such as "a long chain performs better than many short chains," and that one should "try to equalize the number of plants (resp. products), measured in total units of capacity (resp. mean demand), which each product (resp. plant) in the chain is directly connected to," can now be interpreted from this new angle as a development of different ways in which the underlying network can achieve a good expansion ratio. The same principle extends to other new design guidelines -trying to equalize the number of plants (measured in total number of units) assigned to each pair (or even triplet) of products, or vice versa, can also help the decision maker to arrive at a good process structure.We analyze the worst-case performance of the flexible design problem under a more general setting, which encompasses a large class of objective functions. We show that whenever demand and supply are balanced and symmetrical, the graph expander structure (a highly connected but sparse graph) is within ǫ optimality of the fully flexible system, for all demand scenarios, although it uses a far smaller number of links. Furthermore, the same graph expander structure works uniformly well for all objective functions in this class.Based on this insight, we develop a simple and easy-to-implement heuristic to design flexible process structure. Numerical results show that this heuristic performs well for a variety of numerical examples previously studied in the literature. We also use this idea on a set of real data obtained from a bread delivery system in Singapore, with the goal of minimizing the excess amounts of bread brought to each location.

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“…Graves and Tomlin (2003), Bish et al (2005)), flexible workforce scheduling (cf. de Farias and Van Roy (2004), Hopp et al (2004)), and queuing (cf.…”

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Process Flexibility Revisited: The Graph Expander and Its Applications

Chou

Chua

Teo

et al. 2011

Operations Research

110

104

View full text Add to dashboard Cite

show abstract

“…Production flexibility has a lot of measures and dimensions (D'Souza and Williams, 2000;Bertrand, 2003) and has been studied in the literature as a strategy to deal with innovation, uncertainties, short life cycles, and increased competition (Frazelle, 1986;Gupta and Goyal, 1989;Sethi and Sethi, 1990;Beach et al, 2000;Bish et al, 2005;Slack, 2005). This literature characterizes different types and measures of flexibilities, but does not model it formally to decide on the optimal level of flexibility.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In Bish et al (2005), the management of flexible capacity in a dynamic make-to-order environment is studied, where the focus is on the allocation of products to the different production plants. This line of research does not consider the operational implications of the flexibility decisions taken at higher level for a joint production capacity.…”

Section: Literature Reviewmentioning

confidence: 99%

Capacity flexibility allocation in an outsourced supply chain with reservation

Boulaksil

Grunow

Fransoo

2011

International Journal of Production Economics

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“…These necessitate the resource investment decision to be made early, under high demand uncertainty. An example is the automotive industry, where the average deviation of the demand forecast in the capacity investment stage from the actual sales is about 40% [Bish et al (2001), Jordan and Graves (1995)]. …”

Section: Introduction 11 Introduction and Motivationmentioning

confidence: 99%

Optimal Investment Strategies for Flexible Resources, Considering Pricing and Correlated Demands

Bish

Wang

2004

Operations Research

Self Cite

111

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We study the resource investment decision faced by a firm that offers two demandclasses (i.e., products, services), while incorporating the firm's pricing decision into the investment decision. For this purpose, we consider a monopolistic situation and model the demand curve of each demand-class as a downward sloping linear function of its own price.The firm can invest in dedicated resources, which can only satisfy a specific demand-class, and/or in a more expensive, flexible resource, which can satisfy both demand-classes.We consider a two-stage stochastic decision model: In the first stage, the firm determines the dedicated and flexible resource capacities to invest in under demand uncertainty.In the second stage, demand curves are realized and the firm optimizes its revenue through pricing and resource allocation decisions, constrained by its capacity investment decision in the first stage.Our analysis provides the structure of the firm's optimal resource investment strategy as a function of price elasticities and investment costs, and shows how the value of resource flexibility depends on these parameters and demand correlations. Based on our analysis, we provide principles on the firm's optimal resource investment strategy under uncertainty.We show that it can be optimal for the firm to invest in the flexible resource when demand patterns are perfectly positively correlated, while it is not always optimal to invest in the flexible resource when demand patterns are perfectly negatively correlated.

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Managing Flexible Capacity in a Make-to-Order Environment

Cited by 83 publications

References 16 publications

Process Flexibility Revisited: The Graph Expander and Its Applications

Process Flexibility Revisited: The Graph Expander and Its Applications

Capacity flexibility allocation in an outsourced supply chain with reservation

Optimal Investment Strategies for Flexible Resources, Considering Pricing and Correlated Demands

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