Setup time reduction and competitive advantage in a closed manufacturing cell

Yang, Jiaqin; Deane, Richard H.

doi:10.1016/0377-2217(93)90025-i

Cited by 35 publications

(23 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Group 8) Finally, uncertainty in CMS problem can also be detected in products arrival time to cells. Classical models assume that all products are available at the beginning of the production planning while in real application we may have some cases where products arrive to cell with unknown time which could be studied using queuing theory [16]. The cases where a CMS is involved with cell formation integrated with scheduling ( [17], [18]), exceptional elements in CF ( [19], [20]), the implementation of meta-heuristics and heuristics to solve large-scale problems are more practical and appealing real-case problems ( [21], [22]).…”

Section: Published By Atlantis Pressmentioning

confidence: 99%

Integrating Strategic and Tactical Decisions to Robust Designing of Cellular Manufacturing under Uncertainty: Fixed Suppliers in Supply Chain

Ghezavati

Sadjadi

Nayeri

2011

IJCIS

View full text Add to dashboard Cite

Cellular manufacturing (CM) has been identified as an innovative practice for manufacturer to achieve efficiency as well as flexibility under an uncertain environment. This study addresses a new mathematical robust model for a cellular manufacturing problem integrated with tactical aspects under supply chain network characteristics in the presence of uncertain internal parameter (processing times) and external parameter (demands). The model aims to minimize total cost consisting expected value and variance of tactical cost (scheduling), strategic cost (employment of suppliers in supply chain network) to produce exceptional elements as well as the cost of resource underutilization. The model can give up a series of the solutions that are less sensitive to the changes in input data. To solve the robust model, an efficient hybrid method based on new combination of genetic algorithm (GA), simulated annealing (SA) in a parallel structure are proposed under an optimization rule. The effectiveness of the proposed model is demonstrated by numerical results and the trade-off between solution robustness and model robustness is also analyzed.

show abstract

Section: Published By Atlantis Pressmentioning

confidence: 99%

Integrating Strategic and Tactical Decisions to Robust Designing of Cellular Manufacturing under Uncertainty: Fixed Suppliers in Supply Chain

Ghezavati

Sadjadi

Nayeri

2011

IJCIS

View full text Add to dashboard Cite

show abstract

“…In some finite-capacity loading models (Kekre, 1987;Banker, Datar, and Kekre, 1988;Karmarkar and Kekre, 1992;Yang and Deane, 1993;Matsuura, Tsubone, and Kanezashi 1996;Tielemans and Kuik, 1996), a production facility is modeled as a queuing system where the expected queuing delay serves as a performance measure. For a high level of utilization (i.e., high system load), the expected queuing delay dominates the expected total manufacturing stay-time (defined as queuing delay plus processing time).…”

Section: Finite-capacity Loading Of Production Systemsmentioning

confidence: 99%

Managing Stochastic, Finite Capacity, Multi-Project Systems through the Cross-Entropy Methodology

2005

View full text Add to dashboard Cite

This paper addresses the problem of loading a finite capacity, stochastic (random) and dynamic multi-project system. The system is controlled by keeping a constant number of projects concurrently in the system. A new approach, based on the Cross-Entropy (CE) method, is proposed to determine optimal loading of the system. Through numerical experiments, we demonstrate the CE method performance and show new insights into its behavior in a noisy system. Particularly, we suggest a trade-off between the convergence time, the number of iterations and the noise level.

show abstract

“…The problems of the set-up time reduction in a production system have received considerable attention in recent years (Yang andDeane 1993, Leschke andWeiss 1997). In fact, Porteus (1985Porteus ( , 1986 initially provided a framework to analyse the set-up cost reduction.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal policy for set-up time reduction in a multistage production inventory system

Wu¹

2002

International Journal of Systems Science

View full text Add to dashboard Cite

A batch production-inventor y system consisting of multiple stages with an optimal policy of set-up time reduction and a ®xed increment cost are discussed. The ratio of set-up time reduction as a decision variable under various cases of demand in the batch production-inventor y model is considered. The ratio of set-up time reduction and lot size are solved simultaneously to obtain an optimal value of the total annual cost. A numerical example is presented to demonstrate the accuracy of the proposed method.

show abstract

Setup time reduction and competitive advantage in a closed manufacturing cell

Cited by 35 publications

References 8 publications

Integrating Strategic and Tactical Decisions to Robust Designing of Cellular Manufacturing under Uncertainty: Fixed Suppliers in Supply Chain

Integrating Strategic and Tactical Decisions to Robust Designing of Cellular Manufacturing under Uncertainty: Fixed Suppliers in Supply Chain

Managing Stochastic, Finite Capacity, Multi-Project Systems through the Cross-Entropy Methodology

Optimal policy for set-up time reduction in a multistage production inventory system

Contact Info

Product

Resources

About