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.
A Doctoral Thesis. Submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy of Loughborough University.