Turner, Daniel (2017) Investigating the Optimization of the Grinding Process through Software Automation and Thermal Modelling. Masters thesis, University of Huddersfield.

Industrial grinding is a costly process with regards to both time and energy, not only for the machine during the physical grinding process, but also for engineers and machine operators who spend unnecessary time manually making adjustments and modifying parameters in an attempt to optimize the machine performance and work piece accuracy. This research investigates streamlining industry processes through software automation. More specifically, this involves the use of optimization frameworks to produce an optimal series of machine parameters, followed by the utilization of thermal modelling techniques to reduce the likelihood of diminishing the quality of the final work piece. This resulted in the development of an algorithm, which can produce an optimal solution with the potential to reduce cycle time. In addition, this software tool implements a work piece specific thermal model to predict sub-surface temperatures, which can consequently compute a best-case process while maintaining machine precision and work piece integrity. The calculated profits from the use of this new tool, per grinding machine, is in excess of £50 saving per day of machining costs, and a reduction in grinding time of thirty-eight minutes (46%) per day.

FINAL THESIS - TURNER.pdf - Accepted Version
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