The purpose of this paper is to extend the optimal design problem of series manufacturing production lines to series‐parallel lines, where redundant machines and in‐process buffers are both included to achieve a greater production rate. The objective is to maximize production rate subject to a total cost constraint.
An analytical method is proposed to evaluate the production rate, and an ant colony approach is developed to solve the problem. To estimate series‐parallel production line performance, each component (i.e. each set of parallel machines) of the original production line is approximated as a single unreliable machine. To determine the steady state behaviour of the resulting non‐homogeneous production line, it is first transformed into an approximately equivalent homogeneous line. Then, the well‐known Dallery‐David‐Xie algorithm (DDX) is used to solve the decomposition equations of the resulting (homogenous) line. The optimal design problem is formulated as a combinatorial optimisation one where the decision variables are buffers and types of machines, as well as the number of redundant machines. The effectiveness of the ant colony system approach is illustrated through numerical examples.
Simulation results show that the analytical approximation used to estimate series‐parallel production lines is very accurate. It has been found also that ant colonies can be extended to deal with the series‐parallel extension to determine near‐optimal or optimal solutions in a reasonable amount of time.
The model and the solution approach developed can be applied for optimal design of several industrial systems such as manufacturing lines and power production systems.
The paper presents an approach for the optimal design problem of series‐parallel manufacturing production lines.
Nahas, N., Nourelfath, M. and Ait‐Kadi, D. (2008), "Ant colonies for structure optimisation in a failure prone series‐parallel production system", Journal of Quality in Maintenance Engineering, Vol. 14 No. 1, pp. 7-33. https://doi.org/10.1108/13552510810861914Download as .RIS
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