A hybrid push/pull system in assemble-to-order manufacturing environment
A hybrid push/pull system of an assemble-to-order manufacturing environment is investigated in this paper. In this environment, raw material can be transformed into common semi-finished products at a point where next downstream operations are triggered by customer orders. The production of the earlier upstream stations is controlled by push-type production, while the production of the later downstream stations is controlled by pull-type production. The hybrid system often compromises the conflicting performance characteristics of the push and the pull environments. In the push type, high inventory cost is anticipated in the return of low delivery leadtime. On the contrary, in the pull type, high delivery leadtime is expected in the return of low inventory cost. The objective function for the presented hybrid model is to minimize the sum of inventory holding cost and delivery leadtime cost, which is the cost of the time period since customers have placed an order until it is fulfilled. The model is applied to solve the inventory and late delivery problems in an assemble-to-order manufacturer. A genetic algorithm (GA) is used. A discrete event simulation model is used to evaluate the objective function for each chromosome in the GA. The pure push and pull systems are also simulated in order to compare their performance with the hybrid system. Sensitivity analysis on the coefficient of variation (CV) of time between actual customer order arrivals and on various cost ratios of delivery leadtime and inventory are carried out. In most cases, the hybrid performs the best. Results show that the hybrid production system would save the company significantly compared to the pure push or pure pull production systems.
hybrid push/pull assemble-to-order genetic algorithms pull production system production delay