Nancy Diaz

Energy Consumption Characterization and Reduction Strategies for Milling Machine Tool Use

Since machine tools are used extensively throughout their functional life and consequently consuming valuable natural resources and emitting harmful pollutants during this time, this study reviews strategies for characterizing and reducing the energy consumption of milling machine tools during their use. The power demanded by a micromachining center while cutting low carbon steel under varied material removal rates was measured to model the specific energy of the machine tool. Thereafter the power demanded was studied for cutting aluminum and polycarbonate work pieces for the purpose of comparing the difference in cutting power demand relative to that of steel.

Environmental analysis of milling machine tool use in various manufacturing environments

A life-cycle energy consumption analysis of a Bridgeport manual mill and a Mori Seiki DuraVertical 5060 has been conducted. The use phase incorporated three manufacturing environments: a community shop, a job shop, and a commercial facility. The CO2-equivalent emissions were presented per machined part. While the use phase comprised the majority of the overall emissions, the manufacturing phase emissions were significant especially for the job shop, which is not as efficient as the other facilities due to its inherent need for flexibility. Since the Mori Seiki is heavier, the manufacturing phase of this machine tool had a greater impact on emissions than the Bridgeport. Transportation was small relative to the use phase, which was dominated by cutting, HVAC, and lighting. These results highlight areas for energy reductions in machine tool design as well as the importance of facility type to the manufacture of any product.

Cost and Energy Consumption Optimization of Product Manufacture in a Flexible Manufacturing System

A manufacturing system for discrete part production under flexible process routings is studied for the reduction of cost and energy. Focus is centered on the process planning stage for product manufacture, i.e. machine tool selection. Machine tool scheduling was implemented in a discrete-event simulation environment for the evaluation of several scenarios in which the number of machines tools in a manufacturing cell was varied. Cost was found to be dominated by labor rate and processing time, whereas the energy consumption for the best case scenario was reduced by 8.5% for the production of 1000 parts.