tailieunhanh - Developing agent based heuristic optimisation system for complex flow shops with customerimposed production disruptions

The study of complex manufacturing flow-shops has seen a number of approaches and frameworks proposed to tackle various production-associated problems. | Journal of ICT, 17, No. 2 (April) 2018, pp: 291–322 How to cite this paper: Adediran, T. T., & Al-Bazi, A. (2018). Developing agent-based heuristic optimisation system for complex flow shops with customer-imposed production disruptions. Journal of Information and Communciation Technology, 17(2), 291-322. DEVELOPING AGENT-BASED HEURISTIC OPTIMISATION SYSTEM FOR COMPLEX FLOW SHOPS WITH CUSTOMERIMPOSED PRODUCTION DISRUPTIONS Tunde Victor Adediran & Ammar Al-Bazi Faculty of Engineering, Environment and Computing Coventry University Coventry, United Kingdom adedirat@; ABSTRACT The study of complex manufacturing flow-shops has seen a number of approaches and frameworks proposed to tackle various production-associated problems. However, unpredictable disruptions, such as change in sequence of order, order cancellation and change in production delivery due time, imposed by customers on flow-shops that impact production processes and inventory control call for a more adaptive approach capable of responding to these changes. In this research work, a new adaptive framework and agent-based heuristic optimization system was developed to investigate the disruption consequences and recovery strategy. A case study using an Original Equipment Manufacturer (OEM) production process of automotive parts and components was adopted to justify the proposed system. The results of the experiment revealed significant improvement in terms of total number of late orders, order delivery time, number of setups and resources utilization, which provide useful information for manufacturer’s decision-making policies. Keywords: agent-based simulation, customer production disruptions, flowshops, heuritic optimisation algorithm, manufacturing systems. Received: 2 August 2017 Accepted: 10 February 2018 291 Journal of ICT, 17, No. 2 (April) 2018, pp: 291–322 INTRODUCTION The manufacturing system operations can be challenging to model due to the complex