FMS Designer: An expert system for flexible manufacturing system design

Mellichamp, Joseph M.; Kwon, Ojoung; Wahab, Ahmed F. A.

doi:10.1080/00207549008942849

Cited by 32 publications

(13 citation statements)

References 5 publications

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“…Due to the large number of decision variables, an effective approach to designing manufacturing cells and improving their performance is to use computer simulation for testing and selecting the configuration that meets the desired objectives (Antonelli, Volz, & Mudge, 1986;Watson & Sadowski, 1994). The primary objective of engineers is to obtain a superior solution by analyzing manufacturing cell simulation outputs that include throughput, utilization, time/ number in queue, and time/number in system (Mellichamp, Kwon, & Wahab, 1990). Based on simulation results, engineers can design a system by determining initial manufacturing cell parameters such as number of machines; speed of material handling systems, for example, conveyers; and necessary manpower assignment.…”

Section: Integrating Simulations Into the Design Processmentioning

confidence: 99%

“…However, even if the procedure of analyzing simulation results must rely on various guidelines and rules, the decision making still requires significant human expertise and computer resources. To use simulation efficiently in the decision process, knowledge-based systems with simulation have also been used (Ford & Schroer, 1987;Mellichamp, Kwon, & Wahab, 1990;O'Keefe, 1986).…”

Section: Integrating Simulations Into the Design Processmentioning

confidence: 99%

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An integrated methodology for manufacturing systems design using manual and computer simulation

Paquet

Lin

2003

Hum Ftrs & Erg Mfg Svc

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Traditional approaches to manufacturing systems design utilize a sequential procedure that focuses on production capacity requirements, with human operator task design developed late in the systems design phase. Implementing manufacturing systems in this way is difficult when operations management must design flexible and efficient processes, with an often incomplete understanding of how people can best perform within the system. This study developed an integrated methodology that uses both manual and computer simulations to evaluate system performance and ergonomic issues early in the system design process. Information about operator performance and ergonomics is obtained in the manual simulations, while estimates of operator utilization and system throughput is obtained through computer simulations. An iterative design process is used, with the results of manual and computer simulations informing each other during subsequent simulations. An industrial case study is presented here to demonstrate the effectiveness of this methodology. The results show that the methodology can be used to design manufacturing systems with significant savings in labor cost and improved manufacturing system flexibility.

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Section: Integrating Simulations Into the Design Processmentioning

confidence: 99%

Section: Integrating Simulations Into the Design Processmentioning

confidence: 99%

An integrated methodology for manufacturing systems design using manual and computer simulation

Paquet

Lin

2003

Hum Ftrs & Erg Mfg Svc

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“…Realising flexible manufacturing systems was greatly helped by advances in the mechatronics field to achieve the necessary levels of automation and programmability. FMS design models use various methods from expert systems to intelligent design methodologies and mathematical modelling (Vinod and Solberg 1985, Mellichamp et al 1990, Babic 1999. The wide use of this paradigm in industry is made possible by the wide availability of computer-numerical-control (CNC) machine tools and sophisticated material handling systems.…”

Section: Adaptation In Manufacturing Systemsmentioning

confidence: 99%

A model for co-evolution in manufacturing based on biological analogy

AlGeddawy

ElMaraghy

2011

International Journal of Production Research

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Manufacturing systems continue to adapt in order to survive the changing and challenging markets and global competition. Product and manufacturing design and capabilities are configured to allow the needed adaptation through innovative design, improved system paradigms, intelligent design and optimisation models, and product grouping to increase efficiency. In this research, it is hypothesised that the evolution and co-evolution of products and the machines used to manufacture them is akin to that observed in the adaptation of biological species. The symbiosis between products and manufacturing capabilities is studied using real examples, and a new model that establishes the symbiotic relationship between their evolution paths and observed co-evolution trends based on available historical information is proposed. Dual cladograms are used to track their evolution and detect useful potential development and plausible future evolution trends. When a state of co-evolution equilibrium is reached, a stimulus for more abrupt changes would be needed to cause further evolution on both sides. The co-evolution model has been applied to an example based on analysing the history of machine tools development and data from a major machine tools manufacturer. The evolution and co-evolution hypotheses of machined parts and machine tools were charted up to the currently observed state of equilibrium in this application field. This innovative model of co-evolution in manufacturing can help improve the utility of manufacturing resources and prolong the life of manufacturing systems beyond a single product generation and its variants.

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“…In addition, a variety of decision support tools have been developed for FMaS and FAS design using simulation and/or analytical tools (e.g., Borenstein 1998a, b;Lee and Stecke 1996;Mellichamp et al 1990). …”

Section: Literature Reviewmentioning

confidence: 99%

A framework for capacity planning and machine configuration in flexible assembly systems

Lee

Srinivasan

Yano

2006

Int J Flex Manuf Syst

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We consider the problem of simultaneously determining the number of machines (and/or workers), the assignment of tasks (and related tools and components) to these machines, and the number of jobs circulating in a flexible assembly system (FAS), to satisfy steady-state throughput requirements for a family of similar products at minimum cost. We focus on situations where there are precedence relations among the various tasks, as is common in assembly systems. We present a framework for solving this problem based on a heuristic decomposition approach which involves the solution of only a few types of sub-problems. We demonstrate the efficiency and effectiveness of the overall procedure using a number of example problems.

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FMS Designer: An expert system for flexible manufacturing system design

Cited by 32 publications

References 5 publications

An integrated methodology for manufacturing systems design using manual and computer simulation

An integrated methodology for manufacturing systems design using manual and computer simulation

A model for co-evolution in manufacturing based on biological analogy

A framework for capacity planning and machine configuration in flexible assembly systems

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