2002
DOI: 10.1016/s0360-8352(02)00127-4
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Evaluation and optimisation of integrated manufacturing system operations using Taguch's experiment design in computer simulation

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Cited by 46 publications
(20 citation statements)
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“…Using OA design, the effects of multiple process factors on the performance characteristics can be determined while minimizing the number of experiments. The selection of an appropriate OA depends on the total degrees of freedom (DOF) of process parameters [23]. In this research work, the squeeze casting process parameters namely squeeze pressure (A), melt temperature (B), and die preheating temperature (C) at three levels were selected as the control factors.…”
Section: Experimental Methodologiesmentioning
confidence: 99%
“…Using OA design, the effects of multiple process factors on the performance characteristics can be determined while minimizing the number of experiments. The selection of an appropriate OA depends on the total degrees of freedom (DOF) of process parameters [23]. In this research work, the squeeze casting process parameters namely squeeze pressure (A), melt temperature (B), and die preheating temperature (C) at three levels were selected as the control factors.…”
Section: Experimental Methodologiesmentioning
confidence: 99%
“…Computer simulation have applied and proposed in order to deal with the problems and variations in the integrated manufacturing systems. It is very useful to analyze, design, and schedule the manufacturing systems and apply simulation instead of using complex mathematical model equations (Tsai, 2002).…”
Section: Literature Reviewmentioning
confidence: 99%
“…Tsai (2002), focused on assessment and optimization of joined manufacturing system operations with the aim of experimental design in computer simulation. The results show that this approach could consider the assessment and optimization of operating situations in multifaceted systems concurrently.…”
Section: Literature Reviewmentioning
confidence: 99%
“…PSO is a developmental algorithm that was suggested by James Kennedy and Russell Eberhart in 1995 to determine the best solution of problems [18]. It is comprised of Swarm Intelligence and Collective Intelligence and is a sub-field of Computational Intelligence.…”
Section: Particle Swarm Optimization (Pso) Algorithmmentioning
confidence: 99%