Increasing attention has been paid toward enhancing energy retrofitting in machine tools due to its enormous energy consumption and high energy-saving potential. Developing energy-efficient machine tools and selecting appropriate machine tools in procurement processes are two effective approaches for saving energy. However, existing studies on the evaluation of energy performance to support the design and selection of machine tools, rarely consider various process controls, which have considerable impact on the energy performance of machine tools. This study proposes a group of key performance indicators, which are referred to as ‘inherent energy performance’ (IEP) indexes, to support the design and selection of machine tools with the consideration of the main process controls in the usage phase and their interaction. A systematic method is introduced to acquire the IEP indexes. The method involves a simplified measurement of basic data and the calculation of the indexes from the data. A case study indicates that the proposed indicators succeed in obtaining the energy demand information of almost all machine system activities and can be used to provide basic data for developing energy information labels, selecting matching machine tools, and designing energy-efficient machine tools.
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Tuo et al. (2018) studied this question.
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