Production data analysis for discrete component manufacture

This thesis reports research into a workshop oriented PC-based machine and inspection facility for a contemporary metalworking SME. It identifies a production data analysis framework, which is supported by the use of order and manufacturing models. A major feature of the framework is the ability to produce rapid manufacturing control through feedback data from both the inspection and manufacturing data analysis activities in order to influence the responsiveness of manufacturing disturbances experienced through the machining of discrete prismatic components. The major contribution of this thesis explores a production data analysis framework, which forms the basis of a prototype computational facility that closes the quality information feedback loop void that exists within manufacturing. The novel approach employed by the production data analysis framework provides both product and manufacturing process control and involves a number of phases in order to close the manufacturing feedback loop. These phases are described and involve the concurrent machine operation and inspection planning, simultaneous production code generation, comparative tolerance analysis and manufacturing data analysis of prismatic components. The information requirements of both the order and manufacturing models to support the functionality of each phase of the production data analysis framework are also examined and discussed. An integrated multi-functional prototype production data analysis software tool supported by information models has been developed for a limited number of manufacturing features. This software tool has been tested through the application of a case study and has proven the production data analysis methodology to be of strong potential for use within a CAE environment.