The Pro-t-con project : the development of a system for continuous process improvement using Pro-t-con process optimisation software at AEP Filmpac Ltd : a thesis submitted to the Faculty of Technology and Engineering, Massey University, in partial fulfilment of the requirements for the degree of Master of Technology in Quality Systems

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Date
2000
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Massey University
Abstract
This project details the work done to develop a methodology for process improvement at AEP Filmpac in Auckland, New Zealand. The company had purchased a process optimisation software package called Pro-t-con which they intended to use to improve the operating conditions for each product on each machine in the plant. Early use of the Pro-t-con software produced a number of questions as to its ability to optimise processes as effectively as expected. Thus research was done to test the effectiveness of the package and analyse its strengths and weaknesses. The results of this work suggest that Pro-t-con although very easy to use is limited in its ability to effectively optimise processes. Statistically it lacks the rigor of Classical and Taguchi design of experiment methods and cannot resolve processes with interactions or non-linear factors. At the outset of the project the plant did not possess a system for suitably storing and retrieving machine setup information, thus any improvements made to the settings one day would not be available for use the next time that product was run. Consequently in order to longitudinally develop process settings it was also necessary to develop a setting sheet system to support the process improvement initiatives. The combination of a methodology for continuously improving processes and one for actually undertaking experiments to exploit such a process produced a coherent 10 step method for general process improvement This method was used successfully on a variety of processes at plants in Auckland and Sydney.
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Appendix M removed due to copyright restrictions. Consult print copy held in the Library
Keywords
Process control, Data processing, Production engineering
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