Developing Agent Based Heuristic Optimisation System for Complex Flow Shops With Customer-Imposed Production Disruptions

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.

Agent-based modelling and heuristic approach for solving complex OEM flow-shop productions under customer disruptions

“…However, this work presents an innovative dynamic and adaptive heuristic algorithm that minimises the impact of disruptions imposed by customers, taking into consideration random occurrences of these types of disruption. The work extends that of Adediran and Al-Bazi (2018) by presenting an agent based system which includes a new replenishment strategy that encourages a more sustainable inventory level as a measure for disruption recovery. The description of this disruption problem situation is presented in section 3 below.…”

“…In Adediran and Al-Bazi (2018), disruption problems caused by customers' changing requirements were considered. A simulation-heuristic model was proposed using an inventory replenishment strategy to mitigate impact of disruptions.…”

“…The heuristic algorithm developed in this study is adopted as an extension of the heuristic algorithm proposed in Adediran and Al-Bazi (2017). This extended version is designed to accommodate and adapt to the three types of disruptions in five different possible cases where inventory is applied for production support, as it is in Adediran and Al-Bazi (2018). However, the heuristic algorithm presented in this paper has been applied not only to help adapt to disruption, but to also help maintain sustainable inventory levels.…”

“…In this section, the proposed production-replenishment approach discussed in section 4.1.2 was compared with the sequential replenishment method and the Instantaneous Replenishment method proposed by Adediran and Al-Bazi (2018). Sequential replenishment was selected as one of the approaches for replenishing the inventory, particularly given the nature of the current replenishment.…”

Complex Production-Inventory Replenishment Problem With Uncertainty in Customer Behaviour

“…This is when orders need to be rescheduled for inventory replenishment. While this heuristic targets gradual non-instantaneous inventory replenishment, the heuristics in [34] target a sequential and instantaneous replenishment method. In [34], the production disruption problem caused by customer demand behaviour was considered.…”