Raw material release time control for complex make-to-order products with stochastic processing times

This paper considers a make-to-order manufacturing system producing complex products with multiple resource constraints, multiple levels of product structures, and stochastic processing times. The objective is to find the optimal raw material release times by minimising the expected sum of work-in-progress holding costs, product earliness costs and product tardiness costs. An evolution strategy-based planning tool is developed, in which the performance measure is evaluated by stochastic discrete event simulation. The tool is applied to an illustrative example that includes wide, deep and complex product structures and to a case study using data obtained from an industrial company that manufactures capital goods. It is demonstrated that the solutions produced perform substantially better than those produced by the backward scheduling based on infinite capacity, and also significantly better than those produced by the same search method based on deterministic processing times. More benefit can be achieved if the system has a higher degree of uncertainty.