Concurrent process planning and scheduling in distributed virtual manufacturing

Wu, Shangyuan; Fuh, Jerry Ying Hsi; Nee, A.Y.C.

doi:10.1080/07408170208928851

Cited by 35 publications

(20 citation statements)

References 8 publications

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“…Finally, an optimal set of processes and partners (λ * ) is determined by minimizing the comprehensive cost function as described in Eq. (11).…”

Section: Comprehensive Examinationmentioning

confidence: 95%

“…Their reports are not involved in such an important issue as optimal manufacturing partner selection. Also, some researchers developed several approaches or methodologies for the selection and evaluation of partners [10][11][12][13][14]. However, there are, to date, few papers that give a practical and optimal solution, capable of meeting the requirements of real enterprise practices including processing time, partners' locations, and product due date, to the problem of concurrently executing process planning and partner selection in a virtual enterprise environment.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A pragmatic approach for optimal selection of plant-specific process plans in a virtual enterprise

Feng

Yamashiro

2006

Journal of Materials Processing Technology

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“…Finally, an optimal set of processes and partners (λ * ) is determined by minimizing the comprehensive cost function as described in Eq. (11).…”

Section: Comprehensive Examinationmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

A pragmatic approach for optimal selection of plant-specific process plans in a virtual enterprise

Feng

Yamashiro

2006

Journal of Materials Processing Technology

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“…Chan et al [32] established a DPP system IDCPPS, the process planning and workshop scheduling are divided into three steps, such as initial planning, process selection, and fine planning, and the scheduling constraint is considered in every step of the process planning. Wang et al [33] proposed a new methodology of DPP which is constructed by a two-layered framework and multi-agent system (Wu et al [34]). This paper presents a computerized model through a multi-agent approach, which can integrate these manufacturing functions and resolve some of the critical problems in distributed virtual manufacturing, such as virtual cooperation, optimal partner selection.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of ant colony optimization algorithm in integrated process planning and scheduling

Liu

Zhang

Qiu

2015

Int J Adv Manuf Technol

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Optimization of integrated process planning and scheduling has important practical significance for balancing the load of the process resources, shortening production cycle, and reducing production costs. An optimization algorithm base on ant colony optimization (ACO) for integrated process planning and scheduling is proposed, which can handle the dynamic emergency situation. Firstly, the representation mechanisms of candidate operation and the scheduling scheme construction mechanism is proposed. Then, the process constraints and time cost functions are given; based on this, the mathematical model is constructed. The ACO algorithm has been developed to solve the proposed mathematical model of integrated process planning and scheduling. The optimization algorithm is divided into two stages: the scheduling scheme optimization algorithm and dynamic emergency situation handling mechanism. The scheduling scheme optimization algorithm is used to get feasible and optimize scheduling scheme, and the dynamic emergency situation handling mechanism is used to handle dynamic emergency situation, such as inserting new parts. An example is also provided to demonstrate the effectiveness of the algorithm, and the computing results show that the proposed algorithm performs well in searching the good scheduling scheme.

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“…Manufacturing strategy of companies, under these circumstances, therefore has to be modified in accordance with the changing market and environments. A viable manufacturing strategy has to reduce geographical distances and allow products to be manufactured and marketed on a regional or global basis (Wu, Fuh, & Nee, 2002). Distributed manufacturing across multiple facilities can respond rapidly to market changes and make resource sharing more efficient among global manufacturing deployment (Chen & Chio, 2006).…”

Section: Introductionmentioning

confidence: 99%