Optimal design of a generalized conveyor-serviced production station: Fixed and removal item cases

Feyzbakhsh, S.; Matsui, Masayuki; Itai, K.

doi:10.1016/s0925-5273(98)00058-9

Cited by 16 publications

(3 citation statements)

References 11 publications

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“…First, we consider this balancing point by the cost decomposition. In Feyzbakhsh et al [16], the operating cost of CSPS is given by…”

Section: Effect Of Cost Decompositionmentioning

confidence: 99%

Economic Station-Centered Network and Invisible Collaboration: A Cyclic vs. Semi-Cyclic View

Matsui¹

2012

TEL

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By our past review, this paper will verify the hypothesis that the autonomous (invisible) body balancing would be better under changeable demand speed and a leading principle in the collaborative networks. This hypothesis was first utilized in the Conveyor-Serviced Production System (CSP System) with cycle time by a Station-Centered Approach to the physical networks. Recently, we are ascertaining this hypothesis in cost/profit balancing under demand speed (invisible hand) at the economic body chain networks. Generally, it becomes simpler at series (cyclic) type, but would not be so at parallel (semi-cyclic) type. Throughout this paper, we will point out the principle of autonomous (invisible) body ba-lancing by demand speed (cycle time), and would extend to a parallel (semi-cyclic) supply chain by the Station-Centered Approach. This thing would bring the invisible merit that the profit maximization occurs at the relative cost balancing of each enterprise in a series-parallel body network

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“…First, we consider this balancing point by the cost decomposition. In Feyzbakhsh et al [16], the operating cost of CSPS is given by…”

Section: Effect Of Cost Decompositionmentioning

confidence: 99%

Economic Station-Centered Network and Invisible Collaboration: A Cyclic vs. Semi-Cyclic View

Matsui¹

2012

TEL

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“…The generalized conveyor-serviced production station (Generalized CSPS) (Feyzbakhsh et al, 1998) is regarded as a unit station. Un-processed and arriving units on the conveyors are removed into the in-process inventory called the reserve at each station, and wait in buffers.…”

Section: Fcsmentioning

confidence: 99%

Strategic selection of assembly systems under viable demands

Yamada

Satomi

Matsui

2006

Assembly Automation

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PurposeAims to strategically compare assembly lines to cell production including flexible cell system (FCS) under viable demands using the pair matrix table by the lot size and the number of stations and select the efficient assembly systems on demand fluctuations.Design/methodology/approachThis paper sets an assembly problem of the respective models for assembly line systems, autonomous cell system and FCS, and presents a comparative approach by the pair matrix table for the strategic selection. The simulators were constructed for the respective models, and the pair matrix tables with the profit and lead time were drawn and shown.FindingsFinds that the pair matrix table by the lot size and the number of stations are applicable in the strategic selection for comparative assembly systems, and FCS, consisting of multiple self‐completion stations connected by conveyors, is stable when there are viable changes in the demand quantity and the number of stations.Research limitations/implicationsProvides an economic comparative approach for a strategic selection in assembly models with different system configurations by simulation.Practical implicationsThe approach proposed in this paper will provide a strategic selection quantitatively with system managers to achieve higher profit and shorter lead times under viable demands.Originality/valueIntroduces the pair matrix table by the lot size and the number of stations, and compares strategically and quantitatively the respective assembly models based on an optimal design by the two‐stage design method in view of profits and lead times under viable demands.

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“…1). The Generalized Conveyor-Serviced Production Station (Generalized CSPS) (8) with the working zone, W i , is used as a unit station. Here, the line length, LL, which is the sum of the working zone, W i , at each station is introduced as a constraint related to the production lead time.…”

Section: Definitions and Notationmentioning

confidence: 99%

A Design Problem of Assembly Line Systems using Genetic Algorithm under the BTO Environment

2004

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Non-memberUnder the BTO environment, stochastic assembly lines require design methods which shorten not only the production lead time but also the ready time for the line design. We propose a design method for Assembly Line Systems (ALS) in Yamada et al. (2001) by using Genetic Algorithm (GA) and Adam-Eve GA, in which all design variables are determined in consideration of constraints such as line length related to the production lead time. First, an ALS model with a line length constraint is introduced, and an optimal design problem is set to maximize the net reward under shorter lead time. Next, a simulation optimization method is developed using Adam-Eve GA and traditional GA. Finally, an optimal design example is shown and discussed by comparing the 2-stage design by Yamada et al. (2001) and both the GA designs. It is shown that the Adam-Eve GA is superior to the traditional GA design in terms of computational time though there is only a slight difference in terms of net reward.

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Optimal design of a generalized conveyor-serviced production station: Fixed and removal item cases

Cited by 16 publications

References 11 publications

Economic Station-Centered Network and Invisible Collaboration: A Cyclic vs. Semi-Cyclic View

Economic Station-Centered Network and Invisible Collaboration: A Cyclic vs. Semi-Cyclic View

Strategic selection of assembly systems under viable demands

A Design Problem of Assembly Line Systems using Genetic Algorithm under the BTO Environment

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