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

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.

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

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 manufacturers decision-making policies

Developing agent based heuristic optimisation system for complex flow shops with customer-imposed production distruptions

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

Developing agent based heuristic optimization system for complex flow shop with customer-imposed production disruptions

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

The application of the agent-based simulation approach in the flow-shop production environment has recently gained popularity among researchers. The concept of agent and agent functions can help to automate a variety of difficult tasks and assist decision-making in flow-shop production. This is especially so in the large-scale Original Equipment Manufacturing (OEM) industry, which is associated with many uncertainties. Among these are uncertainties in customer demand requirements that create disruptions that impact production planning and scheduling, hence, making it difficult to satisfy demand in due time, in the right order delivery sequence, and in the right item quantities. It is however important to devise means of adapting to these inevitable disruptive problems by accommodating them while minimising the impact on production performance and customer satisfaction. In this paper, an innovative embedded agent-based Production Disruption Inventory-Replenishment (PDIR) framework, which includes a novel adaptive heuristic algorithm and inventory replenishment strategy which is proposed to tackle the disruption problems. The capabilities and functionalities of agents are utilised to simulate the flow-shop production environment and aid learning and decision making. In practice, the proposed approach is implemented through a set of experiments conducted as a case study of an automobile parts facility for a real-life large-scale OEM. The results are presented in term of Key Performance Indicators (KPIs), such as the number of late/unsatisfied orders, to determine the effectiveness of the proposed approach. The results reveal a minimum number of late/unsatisfied orders, when compared with other approaches

Agent-Based Heuristics Model for Measuring Customer Disruption Impact on Production and Inventory Replenishment

Agent-based simulation approach in production and inventory environment is capable of responding and adapting to disruptions caused by customers’ changing requirements. The impacts of disruptions in production and inventory systems can be measured through learning and decision-making ability of system agents. In this paper, agent-based modelling integrated with heuristic optimisation approach is presented as embedded within a scheduling and rescheduling framework. The proposed approach is implemented in a disrupted OEMs parts manufacturing system. The integration of the framework modules in connection with inventory control helped production planners to manage disruptions by tracking order processing times and quantities and for performance measurement. The proposed approach is compared with the few existing related methods like the sequential method. The proposed approach not only revealed the impact of disruptions in terms of process times and order quantities but offered ‘available times’ which were applied for production support and inventory replenishment. This demonstrates a valuable and viable resolution strategy responding and adapting to disruptions caused by customers