The design and development of an intelligent planning and scheduling holarchy system for flexible manufacturing systems

Abstract

This research study is concerned with the design and development of an intelligent planning and scheduling holarchy (IPSH) system for a holonic flexible manufacturing workstation (HFMW) which is a type of a flexible manufacturing system (FMS) built on holonic manufacturing concepts. The disadvantages and limitations of conventional manufacturing control architectures result in the evolution of a holonic architecture which is a hybrid type of hierarchical and heterarchical architecture. The Holonic Manufacturing Systems (HMS) exhibits the attributes of an autonomous and a cooperative system which has recently attracted many research interests; for example, the Product-Resources-Order-Staff Architecture (PROSA) developed at PMA/K.U. Leuven in 1998. The basic building blocks of PROSA are called the "basic holons". The main part of this research is the design and development of an intelligent planning and scheduling holarchy (IPSH) which is a decision supporting holon to the "basic holons" of the HFMW. The IPSH is constructed into three problem domains where they are mapped into three sub-holons, namely: the Process Selection Sub-holon; the Master Scheduling Sub-holon; and the Job Sequencing Sub-holon. These sub-holons are designed, developed and experimented in a hierarchical form while they can also function independently. In the analysis and modeling of the IPSH, it is made up of a functional model, a structural model, and a mathematical model. The functional model identifies the functions of sub-holons being performed in the IPSH. The structural model delineates the interactions of the sub-holons to the "basic holons". The mathematical model presents the programming formulation of the functions of the IPSH. Moreover, the IPSH is implemented using a genetic-based coordinator. After comparison and evaluation of different heuristic techniques, Genetic Algorithms (GA) was proposed and implemented within the IPSH architecture. A prototype IPSH system had been developed to test the proposed concepts. The experimental results confirmed that the genetic-based coordinator, which consists of three GA solution methodologies, is powerful and robust to solve the three problem domains in the IPSH architecture. The completion of this research has contributed to bridge the gap between the planning and scheduling of manufacturing to the holonic shop floor control.