| Current manufacturing technologies have to be revolutionized in face of global competition and continuously changing customer demands. In response to this, the concept of agile manufacturing has been proposed. However, in this environment full control and efficient management of information flow in order to integrate process planning and shop floor scheduling have not been obtained due to the lack of functional relationship (functional gap) and data consistencies (data gap) among distributed partners.; The functional gap is caused by the fact that process planning focuses on the technical aspects for specifying machines and tool requirements, whereas shop floor scheduling is concerned with the machines/tools' scheduling and efficient utilization of resources. As a result, iterative adaptations and frequent bottlenecks are inevitable. For the functional gap, this research develops Hybrid Integration-Approach (HIA), which is the mixed approach of interface-oriented integration approach and task-oriented integration approach. These two integration approaches are the most popular integration approaches for integrating process planning and shop floor scheduling. In this research the HIA consists of the two main modules: High Level Process Planning (HLPP) and Low Level Process Planning and Scheduling (LLPPS). Each module contains several sub-modules. The modules have their own objectives and constraints, and conducts its specific tasks.; The data gap is caused by the fact that the process planning system and shop floor scheduling system have respective database systems, and they have different data structure. To solve the data gap, this research develops an integrated data model through object-oriented methodology, which has three components: the object-oriented modeling (OOM), the object-oriented design (OOD), and object-oriented programming (OOP). |
