Abstract
Some asynchronous production systems can never be truly balanced. This phenomenon demands the incorporation of asynchronism and unreliability in buffer allocation problems (BAPs). This paper reports a BAP in an asynchronous serial production system with Bernoulli machines. A profit-based integer programming model is formulated to maximise the throughput and minimise the buffer capacity simultaneously. Because the production run is finite in the current mass customisation environment, a transient analysis is used to estimate the system performance. Piecewise closed-form expressions are derived for a two-machine case based on Markovian structures. For M > 2 machine lines, an efficient recursive algorithm based on aggregation is developed. Considering the nonlinear characteristic of this BAP, a dynamic-objective particle swarm optimisation with neighbourhood searching is developed. This approach is verified by a case from an assembly plant. The results demonstrate that the programming method can increase the system profit by 1.85%.
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