Design, coordination and control of hybrid factories

Doerr, Ken; Magazine, Michael J.

doi:10.1108/eum0000000005306

Cited by 6 publications

(3 citation statements)

References 34 publications

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“…capacity management, line balancing, set-up time reduction, mixed-model production; see Monden, 1983) could be customised to increase the usage of productive assets in this species. Similarly, the recommendations and research directions for the design, co-ordination and control of hybrid factories identified by Doerr and Magazine (2000) apply to this species.…”

Section: Directions For Manufacturing Innovationsmentioning

confidence: 99%

Manufacturing strategies in the hand tool industry

Leseure

2000

International Journal of Operations &Amp; Production Management

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The lack of contextual sensitivity of best practices thinking can be a deterrent to innovation in small and medium‐size enterprises if owners and managers feel that the specificity of their companies are not taken into account. Presents cladistics, an evolutionary classification technique, as a tool to be used to craft and validate manufacturing strategies. Cladistics provides a compromise between over‐prescriptive generic business solutions and cost inefficient, high‐risk idiosyncratic solutions. The contribution of cladistics as a qualitative methodology in operations strategy research is illustrated by an evolutionary classification of the hand tool industry and recommendations for innovation in this industry.

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Section: Directions For Manufacturing Innovationsmentioning

confidence: 99%

Manufacturing strategies in the hand tool industry

Leseure

2000

International Journal of Operations &Amp; Production Management

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“…Bullinger and Sauer [6] changed the number of production system resources to be optimised until obtaining a state judged satisfactory. Other authors performed simulation studies system design [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Sizing manufacturing cell machines based on the simulation and an expert system

Masmoudi¹

2006

Int. j. simul. model.

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This article developed a new method of the manufacturing cell sizing according to an approach based on the simulation and expert system. This method takes into consideration the stochastic aspect which governs the production system, the production scales of the product family to be treated, the products arrival law, the adopted scheduling and the used optimization criteria. This study starts with the modeling of a manufacturing cell and the simulation of its functioning using the software "ARENA", which provides performance ratings. In a second stage, the expert system exploits these performance measures by a confrontation of the obtained results to the pre-defined objectives. This step permits to lead to a possible decision in order to size each of the machines to obtain a better manufacturing cell functioning. This process is repeated iteratively until the obtention of a cell having the performances which conform to the objectives already defined. The method represents a very useful and economical approach to predict the system size. Finally, applications of the developed method for the sizing of manufacturing cell machines permitted to get satisfactory results.

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“…This would require developing the capacity to manufacture both components in both plants. This investment in production capability at both plants for both components should reduce shipping costs and generate greater responsiveness/flexibility to market (see Doerr and Magazine 2000).…”

Section: Introductionmentioning

confidence: 99%

Risk Pooling Advantages of Manufacturing Network Configuration

Kulkarni

Magazine

Raturi

2004

Production and Operations Management

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The decision of a firm to set up a plant network is influenced by a number of factors, including demand fluctuations across its portfolio of products, logistics costs, and service level requirements. Product plant networks offer the benefits of consolidated production and reduced transshipment costs; on the other hand, process plant networks allow intensive dedication to process expertise and economies of scale. In this paper, we show that, aside from these benefits, process plant networks offer significant risk pooling advantages under a wide range of conditions. We analytically demonstrate that, even without accounting for economies of scale advantages, firms may prefer the process plant network configuration due to the risk pooling benefits offered.

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Design, coordination and control of hybrid factories

Cited by 6 publications

References 34 publications

Manufacturing strategies in the hand tool industry

Manufacturing strategies in the hand tool industry

Sizing manufacturing cell machines based on the simulation and an expert system

Risk Pooling Advantages of Manufacturing Network Configuration

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