Abstract
Efficiency and the reduction of energy consumption in the manufacturing industry are crucial issues for green and sustainable manufacturing. In particular, the machine tool field, which is a representative resources of the manufacturing industry and consumes a large amount of energy, requires the development of a technology capable of monitoring and analyzing data from an energy point of view in addition to existing manufacturing indicators such as productivity improvement and processing quality; however, existing studies have focused on one-dimensional areas such as monitoring energy consumption or developing predictive models in an experimental environment. Therefore, it is necessary to establish a practical and integrated environment by developing more systematic methodologies and supporting systems. In this paper, an integrated approach to the energy consumption of machine tools based on a data analysis is introduced. During the development of the approach, the real-time data processing methods of various sources, such as sensors and computer numerical control interfaces were investigated in a real environment, and the energy consumption models of the target machine’s tools and feeds were defined. An energy data-based comparative analysis method for diagnosing an abnormal state was also developed. In addition, practicality was confirmed through the implementation of the developed approach and the actual application process. Through the results of this paper, a more efficient energy data management and consumption plan can be established, and the convergence of advanced information communication technology can be expected to be the basis for green and sustainable manufacturing.
Highlights
To date, various researches have been conducted on the effective operation and control of machine tools, which are core manufacturing resources in various industries
The need to monitor and to manage the energy consumption of machine tools has already been confirmed by many studies; due to the nature of machine tools and analytical processes, there is a lack of practical analytical and system-related technologies
In terms of the research aspect, the contribution is the unification of the energy consumption data analysis process, including prediction, data collection/process-based monitoring, comparative analysis, and abnormal state diagnosis
Summary
Various researches have been conducted on the effective operation and control of machine tools, which are core manufacturing resources in various industries. There is a need for a technology and system that can be effectively utilized for monitoring, analyzing, and predicting the energy consumption of such machine tools and improving their use according to their purpose, such as optimal energy use and active control of energy-based machinery [6]. Based on this study, we propose an integrated data analytics-based approach to predict, collect, process, and analyze the energy consumption of machine tools and to diagnose abnormal states. To this end, we first defined the energy data monitoring for each component unit by subdividing the machine tool energy consumption units (ECUs). Based on the results of this study, it was confirmed that advanced research, such as the optimization of the energy consumption of machine tools and the implementation of a dynamic operation and control system in terms of the energy consumption of machine tools, is expected to provide a foundation for sustainable manufacturing in the era of green manufacturing
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