Two-stage decision support for production ramp-up
Y.M.J. Chen, Tzong‐Ru Lee, Jau Wen Wang
Abstract
Y.M.J. Chen, Tzong‐Ru Lee, Jau Wen Wang
Abstract
The goal of this paper is to provide guidance for a critical production ramp-up process by a two-stage decision approach, which incorporates human expertise with a computerised multi-objective optimisation problem. We develop a compound approach that aims to resolve ramp-up production challenges. We employ analytic network process and analytic hierarchical process to integrate soft issues in optimised decision making for production ramp-up. The outcome provides clear guidance for the critical production ramp-up process. Practitioners may benefit from the outcomes of this paper in that the complicated and time-pressed ramp-up processing can be handled swiftly. Since a human expert often possesses the ability or the talent of resolving unforeseen problems, our approach is able to allow the intervention of human experts and fosters the automatic decision, which is optimal and can avoid future problems. This paper offers a unique feature in proving an opportunity for human intervention in a computerised optimisation process.
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The goal of this paper is to provide guidance for a critical production ramp-up process by a two-stage decision approach, which incorporates human expertise with a computerised multi-objective optimisation problem. We develop a compound approach that aims to resolve ramp-up production challenges. We employ analytic network process and analytic hierarchical process to integrate soft issues in optimised decision making for production ramp-up. The outcome provides clear guidance for the critical production ramp-up process. Practitioners may benefit from the outcomes of this paper in that the complicated and time-pressed ramp-up processing can be handled swiftly. Since a human expert often possesses the ability or the talent of resolving unforeseen problems, our approach is able to allow the intervention of human experts and fosters the automatic decision, which is optimal and can avoid future problems. This paper offers a unique feature in proving an opportunity for human intervention in a computerised optimisation process.
Key concepts: Production (economics), Process (computing), Risk analysis (engineering), Computer science, Decision support system, Outcome (game theory), Intervention (counseling), Feature (linguistics)