Umudike Journal of Engineering and Technology

This research work is concerned with modeling a scheduling operation for production of aluminum roofing sheet. The model involves three sequential machines through which every order must pass followed by one out of three finishing machines used one per finishing type. Agent-oriented analysis that adjusts to the dynamics of the stochastic order processes is used in the analysis of the proposed agent-based model for the job shop scheduling. A well-crafted scheduler agent carries out bunching of sorted jobs either in 1 or 2 or 3 days bunche(s) per finishing type and selects the best out of the three approaches. The scheduling of order arrival for ten months was carried out by the scheduler agent using the bunching technique developed. The result of the agent-based job shop scheduling model was validated with D.G. Kendall, classical method for poisson arbitrary distribution with nonpreemptive discipline where the agent-based model (ABM) compared favorably with the classical model. ABM had better results in orders for months 4,6, 8, 9, 10 and approximately equal to the classical method in orders for months 1, and 3. The classical method is only better in orders for months 2, 5 and 7. The comparative result shows that the modelled agent-based job shop scheduling is an improvement to the existing model and should be applied in an industrial set up for optimum machine usage and customer satisfaction.