The effect of lead time variation on the performance of disassembly release mechanisms

Guide, V. Daniel R.; Jayaraman, Vaidy; Srivastava, Rajesh

doi:10.1016/s0360-8352(99)00164-3

Cited by 27 publications

(11 citation statements)

References 16 publications

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“…Simulation (Ashayeri et al. 1996; Guide and Srivastava 1997a,b, 1998; Guide et al. 1996, 1997a,b,c, 1999b, 2000b; Haas and Murphy 2002; Hirsch et al.…”

Section: Classification Based On Methodology/approachmentioning

confidence: 99%

Green supply‐chain management: A state‐of‐the‐art literature review

Srivastava

2007

Int J Management Reviews

3,094

1,828

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There is a growing need for integrating environmentally sound choices into supply‐chain management research and practice. Perusal of the literature shows that a broad frame of reference for green supply‐chain management (GrSCM) is not adequately developed. Regulatory bodies that formulate regulations to meet societal and ecological concerns to facilitate growth of business and economy also suffer from its absence. A succinct classification to help academicians, researchers and practitioners in understanding integrated GrSCM from a wider perspective is needed. Further, sufficient literature is available to warrant such classification. This paper takes an integrated and fresh look into the area of GrSCM. The literature on GrSCM is covered exhaustively from its conceptualization, primarily taking a ‘reverse logistics angle’. Using the rich body of available literature, including earlier reviews that had relatively limited perspectives, the literature on GrSCM is classified on the basis of the problem context in supply chain's major influential areas. It is also classified on the basis of methodology and approach adopted. Various mathematical tools/techniques used in literature vis‐à‐vis the contexts of GrSCM are mapped. A timeline indicating relevant papers is also provided as a ready reference. Finally, the findings and interpretations are summarized, and the main research issues and opportunities are highlighted.

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“…Simulation (Ashayeri et al. 1996; Guide and Srivastava 1997a,b, 1998; Guide et al. 1996, 1997a,b,c, 1999b, 2000b; Haas and Murphy 2002; Hirsch et al.…”

Section: Classification Based On Methodology/approachmentioning

confidence: 99%

Green supply‐chain management: A state‐of‐the‐art literature review

Srivastava

2007

Int J Management Reviews

3,094

1,828

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“…analyze the effect of proactive expediting policies on mean flow time, mean lateness, mean root mean square lateness and mean percentage late criteria by using a DES model. Guide et al (1999b) develop a DES model to investigate the effect of lead time variation on the performance of the disassembly release mechanisms. carry out a DES analysis to examine the performance of several priority dispatching rules for a repair shop.…”

Section: Production Schedulingmentioning

confidence: 99%

Environmentally conscious manufacturing and product recovery (ECMPRO): A review of the state of the art

Ilgın

Gupta

2010

Journal of Environmental Management

808

377

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“…Jacobs (1994) illustrated that converting recycled materials into manufactured products requires additional energy because the energy integrated in the materials in the early manufacture of the product is wasted during the recycling process. McCaskey (1994), Hormozi (1996) and Guide (1999) explained that remanufacturing is an essential reuse policy in waste material handling, wealth and employment creation, recovery of material and environmentally responsible manufacturing. Ishii (1999) illustrated that although recycling has attracted more attention among design and manufacturing engineers, remanufacturing is superior to recycling from both an environmental and a financial point of view.…”

Section: The Remanufacturing Domainmentioning

confidence: 99%

A dual factor decision making model in green manufacturing

Jamshidy¹

2021

Preprint

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This study focuses on the evaluation of different methods of product recovery for GM. The evaluation is conducted through the application of a decision making model. The model evaluates product recovery options on the basis of two categories: optimization of objective factors and market demand. The first category in the model focuses on optimization of five objective factors, including environmental impact (E), cost (C), quality (Q), resource consumption (R), and time (T). Goal programming is used to solve the optimization problem. The goal programming is supported by the construction of a decision making tree with three branches: remanufacturing, refurbishing, and current manufacturing. The solution of the decision tree helps determine the best method of product recovery for GM. The second category in the model focuses on the evaluation of market demand. This further supports the selection of the best method for product recovery. To evaluate market demand, a Bayesian forecasting model is used in the construction of a decision making tree. The study shows that the availably of products information including the objective factors and market demand, has a positive impact on making product recovery decisions. It also shows how recovery decisions can be modeled in decision making tress to represent the impact of product information on those decisions.

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The effect of lead time variation on the performance of disassembly release mechanisms

Cited by 27 publications

References 16 publications

Green supply‐chain management: A state‐of‐the‐art literature review

Green supply‐chain management: A state‐of‐the‐art literature review

Environmentally conscious manufacturing and product recovery (ECMPRO): A review of the state of the art

A dual factor decision making model in green manufacturing

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