An intelligent concurrent design task planner for manufacturing systems

Product design is an integral component of manufacturing systems. This paper presents a prototype intelligent concurrent design task planner, which combines the strength of genetic algorithms and an iterative design analyser for the scheduling of a complex design process of a manufacturing system. It accounts significantly for shortening the time-to-market of a product, and hence, improves the agility of a manufacturing system. The proposed prototype attempts to schedule the design process inherently containing iteration, which is caused by the interdependencies among tasks and leads to prolonged lead-time and increased cost on the whole time-span of introducing a product. Genetic algorithm (GA), as one of the effective optimisation techniques, is embodied in the prototype to search for the optimal schedule for a design process for the goal of satisfying the managerial objective under resource constraints. The iterative design analyser, which is basically an analytical tool for design iteration, is utilised to estimate the time and engineering cost spent on the design process for each candidate schedule. Considering the unpredictable length of a schedule for iterative design process, a novel chromosome representation scheme and unique crossover and mutation operators have been introduced. A case study conducted on a burn-in system of a manufacturing company has illustrated the effectiveness of the proposed prototype.