Framework for flexibility in dynamic supply chain management

Wadhwa, Subhash; Saxena, Abhinav; Chan, Felix T. S.

doi:10.1080/00207540600570432

Cited by 89 publications

(36 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Coronado and Lyons (2007) investigated the implications of operations flexibility in industrial supply chains and the effect it has on supporting initiatives designed for build-to-order manufacturing. Wadhwa, Saxena, and Chan (2008) presented a study on the role of different flexibility options (i.e. no flexibility, partial flexibility and full flexibility) in a dynamic supply chain model based on key parameters and performance measures.…”

Section: Flexibility In Manufacturing Service and Supply Chain Systemsmentioning

confidence: 99%

New flexibility drivers for manufacturing, supply chain and service operations

Ivanov

Das

Choi

2018

International Journal of Production Research

112

View full text Add to dashboard Cite

Increasing product proliferation, customisation, competition and customer expectations, as well as supply side disruptions, pose significant challenges to firm operations. Such challenges require improved efficiency and resilience in manufacturing, service and supply chain systems. New and innovative flexibility concepts and models offer a prospective route to such operational improvements. Several emerging issues in flexibility, such as risk and uncertainty management, environmental sustainability, optimal strategies under competition, optimal operations with strategic consumer behaviours are being examined in this regard. This overview provides a concise review of these critical research issues, and discusses related papers featured in this special issue. Four major flexibility drivers are classified: disruption risks, resilience and the ripple effect in the supply chain; digitalisation, smart operations and e-supply chains; sustainability and closedloop supply chains; and supplier integration and behavioural flexibility.Keywords: flexibility; flexible manufacturing; supply chain management; supply chain risk management; supply chain coordination; Industry 4.0; manufacturing systems; service supply chain; ripple effect Flexibility in manufacturing, service and supply chain systemsWith increasing product proliferation, reduced unit demand volumes and next-day delivery expectations, flexibility in operations, service and supply chains has become an important focal area for research and industry. This special issue of IJPR aims to present state-of-the-art research in the field of flexibility in manufacturing, supply chain and service operations.A brief background on flexibility is provided in this section. Flexibility refers to the ability of a system to change (adapt) in dynamic environments. Operational system flexibility has been studied extensively in the manufacturing, service and supply chain literature from various strategic, tactical and operative perspectives (Slack 1987;Bordoloi, Cooper, and Matsuo 1999;Koste and Malhotra 1999;D'Souza and Williams 2000;Das 2001;Van Mieghem 2003;Zhang, Vonderembse, and Lim 2003;Wu, Erkoc, and Karabuk 2005;Alp and Tan 2008;Chang 2012;Jain et al. 2013;Choi, Cheng, and Zhao 2016;Cobb 2016;Ivanov, Tsipoulanidis and Schönberger 2017).A substantive part of this research studies capacity flexibility, classifying investigations into two main areas, i.e. decisions on investment in dedicated versus flexible capacity (Li and Tirupati 1994;Bish, Muriel, and Biller 2005), and process flexibility (or capacity adaptability). Process flexibility (Jordan and Graves 1995;Chou et al. 2010) analyses the ability of a company to change manufacturing setups at flexible lines according to demand or supply changes. It relies, in part on the capability to produce multiple products on multiple production facilities or lines (Jordan and Graves 1995;Simchi-Levi and Wei 2015). In particular, the design of a flexible production network under stochastic demand has been studied by Jordan and Graves (199...

show abstract

Section: Flexibility In Manufacturing Service and Supply Chain Systemsmentioning

confidence: 99%

New flexibility drivers for manufacturing, supply chain and service operations

Ivanov

Das

Choi

2018

International Journal of Production Research

112

View full text Add to dashboard Cite

show abstract

“…Reinforcement learning approach for Global supply chain management may be seen from the works of Pontrandolfo et al (2002). Wadhwa et al (2003) introduced the concept of flexibility in dynamic supply chain management. The concept of a collaborative agent-based infrastructure for internet-enabled collaborative enterprise, proposed by Shen et al (2003), provided supply chain a new form.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated model for line balancing with workstation inventory management

Roy¹,

Khan²

2010

IJIEC

View full text Add to dashboard Cite

In this paper, we address the optimization of an integrated line balancing process with workstation inventory management. While doing so, we have studied the interconnection between line balancing and its conversion process. Almost each and every moderate to large manufacturing industry depends on a long and integrated supply chain, consisting of inbound logistic, conversion process and outbound logistic. In this sense an approach addresses a very general problem of integrated line balancing. Research works reported in the literature so far mainly deals with minimization of cost for inbound and outbound logistic subsystems. In most of the cases conversion process has been ignored. We suggest a generic approach for linking the balancing of the line of production in the conversion area with the customers' rate of demand in the market and for configuring the related stock chambers. Thus, the main aim of this paper is to translate the underlying problem in the form of mixed nonlinear programming problem and design the optimum supply chain so that the total inventory cost and the cost of balancing loss of the conversion process is jointly minimized and ideal cycle time of the production process is determined along with ideal sizes of the stock chambers. A numerical example has been added to demonstrate the suitability of our approach.

show abstract

“…Unfortunately, modelling real-world problems can yield large and complex models (Arns et al 2002). Alternative options and flexibility within the SC also add to complexity (Wadwa et al 2008). Nevertheless, Wadwa et al (2008) argued that improved decision-making can have a significant impact on SC performance.…”

Section: Introductionmentioning

confidence: 97%

“…Alternative options and flexibility within the SC also add to complexity (Wadwa et al 2008). Nevertheless, Wadwa et al (2008) argued that improved decision-making can have a significant impact on SC performance. Modelling and understanding the underlying mechanisms of SC dynamics can reduce inventory and backorder costs (Bourland et al 1996) and the bullwhip effect (Lee et al 1997), thus ensuring the smoothest flow of materials at the lowest cost (Wadwa et al 2008).…”

Section: Introductionmentioning

confidence: 98%

Early-stage firms and delay-based inventory control using decision-making tableaux

Marion

Sipahi

2009

International Journal of Production Research

View full text Add to dashboard Cite

A resource constrained early-stage firm commercialising assembled products faces supply chain (SC) problems that could ultimately cause the company to fail. Delays, complexity, and associated cost overruns throughout the SC can quickly drain cash flow, putting a new firm in a disadvantaged position. This is exacerbated by the increased use of outsourced global suppliers, demands of resellers, and pressure for rapid growth. A decision-making tableau over a conceptual delay-based SC model is proposed, which identifies qualitative behaviour of inventories with respect to delays inherently present in the SC. The method can foster improved strategic decisions in new venture SC set-up and management that can reduce costly variations. A real-world case scenario is given illustrating a current state and substantially improved future state with the help of the proposed approach. The paper concludes with a discussion on the results, limitations, and direction of future research.

show abstract

Framework for flexibility in dynamic supply chain management

Cited by 89 publications

References 40 publications

New flexibility drivers for manufacturing, supply chain and service operations

New flexibility drivers for manufacturing, supply chain and service operations

Integrated model for line balancing with workstation inventory management

Early-stage firms and delay-based inventory control using decision-making tableaux

Contact Info

Product

Resources

About