The development of a sustainable manufacturing process requires a comprehensive evaluation method and fundamental understanding of the processes. Coolant application is a critical sustainability concern in the widely used machining process. Cryogenic machining is considered a candidate for sustainable coolant application. However, the lack of comprehensive evaluation methods leaves significant uncertainties about the overall sustainability performance of cryogenic machining. Also, the lack of practical application guidelines based on scientific understanding of the heat transfer mechanism in cryogenic machining limits the process optimization from achieving the most sustainable performance.
In this dissertation, based on a proposed Process Sustainability Index (ProcSI) methodology, the sustainability performance of the cryogenic machining process is optimized with application guidelines established by scientific modeling of the heat transfer mechanism in the process. Based on the experimental results, the process optimization is carried out with Genetic Algorithm (GA).
The metrics-based ProcSI method considers all three major aspects of sustainable manufacturing, namely economy, environment and society, based on the 6R concept and the total life-cycle aspect. There are sixty five metrics, categorized into six major clusters. Data for all relavant metrics are collected, normalized, weighted, and then aggregated to form the ProcSI score, as an overall judgment for the sustainability performance of the process. The ProcSI method focuses on the process design as a manufacturer’s aspect, hoping to improve the sustainability performance of the manufactured products and the manufacturing system.
A heat transfer analysis of cryogenic machining for a flank-side liquid nitrogen jet delivery is carried out. This is performed by micro-scale high-speed temperature measurement experiments. The experimental results are processed with an innovative inverse heat transfer solution method to calculate the surface heat transfer coefficient at various locations throughout a wide temperature range. Based on the results, the application guidelines, including suggestions of a minimal, but sufficient, coolant flow rate are established.
Cryogenic machining experiments are carried out, and ProcSI evaluation is applied to the experimental scenario. Based on the ProcSI evaluation, the optimization process implemented with GA provides optimal machining process parameters for minimum manufacturing cost, minimal energy consumption, or the best sustainability performance.
| Identifer | oai:union.ndltd.org:uky.edu/oai:uknowledge.uky.edu:me_etds-1045 |
| Date | 01 January 2014 |
| Creators | Lu, Tao |
| Publisher | UKnowledge |
| Source Sets | University of Kentucky |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations--Mechanical Engineering |
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