A Novel Approach Towards Energy-efficient Machining

Abstract

Manufacturing, being the backbone of an industrialised country’s economy, is facing many challenges through resource shortages, environmental deterioration, and everintensifying global competition. With the widespread adoption of Computer Numerical Control (CNC) machine tools, the machining industry has been revolutionised by soaring productivity, excellent quality and unbeatable prices. However, from a sustainability perspective, this has placed heavy burdens on the eco-system. The need for energy consumption efficiency has thus been widely recognised. The energy required by this industry will continuously increase with the advancement of CNC machine tools. Therefore, sizeable efforts from both industry and academics are being made to improve this situation. The work presented in this study deals with improving energy-efficient machining systems by providing an open, interoperable and holistic solution built upon a comprehensive framework of Global Energy-efficient Machining Systems (GEMS), a novel energy consumption modelling approach, and integrated energy data models. Four activity modules in the framework, namely, energy monitoring, analysis, energy-based optimal control and databases, were designed. Three key issues in creating GEMS have been identified and carefully studied in this research. Firstly, the model-based characteristics of GEMS give rise to an accurate, comprehensive, yet practical energy consumption model. The energy model developed here attempts to combine specific theoretical and/or empirical models of individual components with state-based models of systematic behaviour. The resulting hybrid energy model has proved feasible and effective in modelling two different machining systems. Subsequently, the function block technique was introduced to model energy consumption for the first time, and facilitate model implementation. This supports the idea of creating a shared pool of modular energy models for maximum reusability, fast construction and flexibility, so that the machine/process-specific characteristics of energy consumption behaviour can be addressed. Secondly, to facilitate communication and collaboration between different activities, tighter integration of energy data with machining systems is a prerequisite. This energy data integration envisages a standardised, unambiguous data representation, exchange and maintenance mechanism, which can support various energy-efficient activities. The dated but still dominant CNC part programming G-code fails to meet such requirements. Hence, energy data models have been developed in compliance with STEP/STEP-NC standards, providing an enhanced ability to describe product information through an entire life cycle. In this research, four groups of energy data model were proposed to define data structure and holders for automated monitoring, energy modelling, online optimisation and energy data archiving. Useful information for potentially improving energy performance is thereby captured and preserved. Thirdly, to implement the aforementioned hybrid energy model and data models, two systems were investigated, namely, a unified energy analysis system – iGEMS, and a mobile application – GEMS-IIMS. Utilising the latest IT and computing technology, a Cloud-based architecture was adopted. It aims to provide a service-oriented and practicable energy-efficient machining system, with the intention of improving industrial practices. Easily accessible energy monitoring, prescribed energy analysis and online energy optimisation, and a comprehensive energy data repository have been provided to meet user requirements. An energy analysis and machine tool energy database were created to demonstrate that the energy consumption of a machining system can be effectively analysed based on high-level production data. Furthermore, it was noticed during this research that having an energy evaluation system helps users to understand energy consumption data, and guides them in improving energy efficiency. Hence, an energy rating schema, taking information at different levels of detail into account, is proposed. The schema avoids pointless comparison between different types of machine tools, but concentrates on improving actual operations. All in all, the importance and necessity of this research lies in the fact that it views energy-efficient machining systems as a whole, which paves the way to reducing overall energy consumption and the corresponding environmental impact in the future.