Integrated process planning and scheduling in holonic manufacturing systems

Sugimura, Nobuhiro; Hino, Ryutaro; Moriwaki, Toshimichi

doi:10.1109/isatp.2001.928998

Cited by 29 publications

(16 citation statements)

References 2 publications

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“…Machining schedules were determined using a real-time scheduling procedure in which, individual job selected suitable machining equipment, in order to carry out next operation based on process plan. Sugimura et al, (2003) extended their earlier work (Sugimura et al, 2001). Here, optimum sequence of machining equipment, two objective functions viz., minimization of shop time and machining cost were used in DP approach.…”

Section: Closed-loop Process Planning and Scheduling Approachmentioning

confidence: 83%

“…For bottlenecks, block selection which plays cardinal role in bridging process planning and scheduling, a heuristic was developed by employing an entropy-based partitioning method to identified bottleneck periods. Sugimura et al, (2001) proposed an IPPS model in which process planning phase selected suitable sequence of machining feature using GA approach. This model was based on HMS.…”

Section: Closed-loop Process Planning and Scheduling Approachmentioning

confidence: 99%

See 1 more Smart Citation

Review on Integration of Process Planning and Scheduling

Phanden¹,

Jain²,

Verma³

2011

DAAAM International Scientific Book 2011

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Section: Closed-loop Process Planning and Scheduling Approachmentioning

confidence: 83%

Section: Closed-loop Process Planning and Scheduling Approachmentioning

confidence: 99%

Review on Integration of Process Planning and Scheduling

Phanden¹,

Jain²,

Verma³

2011

DAAAM International Scientific Book 2011

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“…The linear process plan obtained is then sent to a scheduling module to do the allocation task. In the scheduling approach proposed by Sugimura et al [109], the sequence generation of machining features is realized by a GA and the selection of machining equipment is completed by dynamic programming for each machining sequence. f) Palmer [77] applied simulated annealing (SA) to the integration problem and justified its optimization results.…”

Section: A Traditional Approaches 1) Centralized Optimization Algorimentioning

confidence: 99%

Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey

Shen

Wang

Hao

2006

IEEE Trans. Syst., Man, Cybern. C

353

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Abstract-Manufacturing process planning is the process of selecting and sequencing manufacturing processes such that they achieve one or more goals and satisfy a set of domain constraints. Manufacturing scheduling is the process of selecting a process plan and assigning manufacturing resources for specific time periods to the set of manufacturing processes in the plan. It is, in fact, an optimization process by which limited manufacturing resources are allocated over time among parallel and sequential activities. Manufacturing process planning and scheduling are usually considered to be two separate and distinct phases. Traditional optimization approaches to these problems do not consider the constraints of both domains simultaneously and result in suboptimal solutions. Without considering real-time machine workloads and shop floor dynamics, process plans may become suboptimal or even invalid at the time of execution. Therefore, there is a need for the integration of manufacturing process-planning and scheduling systems for generating more realistic and effective plans. After describing the complexity of the manufacturing process-planning and scheduling problems, this paper reviews the research literature on manufacturing process planning, scheduling as well as their integration, particularly on agent-based approaches to these difficult problems. Major issues in these research areas are discussed, and research opportunities and challenges are identified.

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“…They are referred to as autonomous distributed manufacturing systems, biological manufacturing systems and holonic manufacturing systems (Iwata et al 1994, Ueda and Ohkura 1995, Sugimura et al 1996, Sugimura et al 2001, Hosoi et al 2002, Fujii et al 2004.…”

Section: Introductionmentioning

confidence: 99%

“…Real-time scheduling algorithms were proposed for the individual material handling devices in the cellular manufacturing environment, which are capable of accommodating newly arriving jobs (Babiceanu et al 2005). Dispatching rule-based scheduling methods were also proposed and applied to the real-time production scheduling problems of the HMS (Sugimura et al 1996, Sugimura et al 2001. The proposed method is adaptable to the dynamic changes and the unforeseen disruptions, and it is suitable for the improvement of the objective functions of the whole HMS such as total make span.…”

Section: Introductionmentioning

confidence: 99%

Real-time scheduling for holonic manufacturing systems based on estimation of future status

Iwamura

Okubo

Tanimizu

et al. 2006

International Journal of Production Research

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This paper deals with a real-time scheduling system of holonic manufacturing systems (HMSs), which were proposed by an international cooperative research consortium called The HMS Consortium for Autonomous Distributed Management and Control of the Manufacturing Systems. The scheduling system generates real-time suitable production schedules, based on decision making by individual constituents named holons and their coordination. The objective of the present research is to improve the decision-making processes of the individual holons through the use of estimation process of the future status of the HMS. Procedures are developed and implemented to the individual holons, in order to estimate the future status of the HMS by applying the simulation model of the HMS. A neural network model is proposed to represent and to simulate the decision-making process of the individual holons.

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Integrated process planning and scheduling in holonic manufacturing systems

Cited by 29 publications

References 2 publications

Review on Integration of Process Planning and Scheduling

Review on Integration of Process Planning and Scheduling

Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey

Real-time scheduling for holonic manufacturing systems based on estimation of future status

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