Planning and sequencing heuristics for feature-based control of holonic machining equipment

The intelligent manufacturing system program was proposed by Japan in 1989. Five participating regions-Australia, Canada, the European Community, Japa n, and the United States-currently are involved in developing 21st century manufacturing technology through an investment of US $1.2 billion over 10 y ears. Korea joined the program and will start work on one of the six ongoin g projects, holonic manufacturing systems (HMSs). The objective of the pape r is to develop the control architecture of the holonic machining unit (HMU ) for construction of the HMSs and to present some planning and sequencing heuristics for feature-based control of the HMU. Further, the paper provide s the HMU's functionality using the IDEF0 function modeling method. The bas ic operation of the decision maker among the HMU's functions is to determin e an efficient feature sequence in real time from the nonlinear feature gra ph used to represent a process plan. To this end, two methodologies are app lied sequentially to managing a nonlinear process plan: removal of the OR n odes and then grouping and sequencing the features in the feature graph. Ma rkov chain theory is used to compute the path preference indicator for remo ving the OR nodes, that is, for selecting the best path among those surroun ded by OR nodes. The resulting graph is the AND graph, from which the featu re type nodes are formed into sequenced groups. The CNC codes associated wi th the features in each group are combined and downloaded to the CNC machin e. The development of the methodologies can help manufacturers efficiently cope with unexpected failures encountered during computer-automated machini ng.