Anthony Ikechukwu Anosike

Dynamically Integrated Manufacturing Systems (DIMS)—A Multiagent Approach

Manufacturing businesses in todays market are facing immense pressures to react rapidly to dynamic variations in demand distributions across products and changing product mixes. To cope with the pressures requires dynamically integrated manufacturing systems (DIMS) that can manage optimal fulfillment of customer orders while simultaneously considering alternative system structures to suit changing conditions. This paper presents a multiagent approach to DIMS, where production planning and control decisions are integrated with systems reconfiguration and restructure. A multiagent framework, referred to as a hierarchical autonomous agent network, is proposed to model complex manufacturing systems, their structures, and constraints. It allows the hierarchical structures of complex systems to be modeled while avoiding centralized control in classical hierarchical/hybrid frameworks. Subsystems interact heterarchically with product orders to carry out optimal planning and scheduling. An agent coordination algorithm, operating iteratively under the control of a genetic algorithm, is developed to enable optimal planning and control decisions for order fulfillment to be made through interactions between agents. This algorithm also allows the structural constraints of systems to be relaxed gradually during agent interaction, so that planning and control are first carried out under existing constraints, but when satisfactory solutions cannot be found, subsystems are allowed to regroup to form new configurations. Frequently used configurations are detected and evaluated for system restructure. The approach also enables Petri-net models of new system structures to be generated dynamically and the structures to be evaluated through agent-based discrete event simulation.

Dynamic reconfiguration and simulation of manufacturing systems using agents

Purpose – Conventionally, various levels of decisions with regard to production are made in a number of sequential stages such as system design, production/process planning, production scheduling, system reconfiguration and system restructure. This paper aims to present an integrated approach for modelling, restructuring and simulating manufacturing systems to suit changing manufacturing situations as quickly as possible.Design/methodology/approach – An agent‐based approach is employed where each manufacturing resource is represented by an agent. Simply speaking, the approach enables the machines in a manufacturing system to manage themselves efficiently and effectively.Findings – The agent‐based modelling and interaction approach enables manufacturing resources to be allocated dynamically in an optimal manner. The modelling approach also enables alternative system configurations to be identified and evaluated using distributed discrete event simulation system. Resource allocation and manufacturing system...