Abstract :
The infrastructure of separation between data and process has evolved as basis of computer integration manufacturing system (CIMS), in which case many corresponding techniques are emerging in multitude for designing an CIMS system, such as OLE for process control (OPC), grid service etc. Generally speaking, a data model is used to describe and represent storage and a process model is used to define production flow, including structure, categorization and classification of data operations that deal with the operations of data such as drawing, simulation, cost calculation, report, visualization etc. Although there have been standardization efforts for data model and process model (for example, BPEL4WS defines both abstract and executable processes and ER Modeling defines the data model), how to bride the gap between them is still a challenge due to its complication. In the paper, a few prevalent infrastructures are discussed; furthermore an automatic middleware-based technique for bridging the gap between them is presented.
Keywords :
computer integrated manufacturing; data models; grid computing; middleware; process control; OLE; automatic middleware-based technique; computer integration manufacturing system; data categorization; data classification; data model; grid service; process control; process model; production flow; Bridges; Computer aided manufacturing; Computer integrated manufacturing; Costs; Data models; Data visualization; Flow production systems; Grid computing; Manufacturing systems; Process control;
