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Reducing energy demand in manufacture is an urgent challenge. This challenge is driven by higher consumer demand for manufactured products, increasing electricity and energy prices, volatility and uncertainty in energy supply and national policy. These factors, together with a need to reduce energy consumption derived carbon dioxide emissions, strategically call for energy efficient manufacturing. In manufacturing processes, especially mechanical machining, more than 90% of environmental impact arises from direct electrical energy demand in machine tools. At the machine tool level, the biggest share of the electrical energy associated with mechanical machining is required to bring the machine to a ready state and support non-cutting operations such as spindle torque requirements, auxiliary units and movements. These activities are controlled and related to machine commands such as NC codes. In this paper comprehensive information on energy intensity in machining process, including the influence of tool wear, was studied. Key energy states were identified to build up an energy demand for machining components. The paper defines the essential power constants for a database that can assist energy prediction for any available machines and workpiece materials. The assessment of alternative toolpaths identified major opportunities for energy demand reduction. [ABSTRACT FROM AUTHOR]

Abstract: Machining tasks are performed on machine tools with enormous amount of energy consumption in manufacturing system. Understanding and characterizing task-oriented energy consumption is significantly essential to explore the potential on energy-saving in production management. To achieve it, this paper proposes a modeling method of task-oriented energy consumption for machining manufacturing system. The energy consumption characteristics driven by task flow in machining manufacturing system are analyzed, which describes that energy consumption dynamically depends on the flexibility and variability of task flow in production processes. Based on the task-oriented energy consumption characteristics, an event graph methodology has been exploited to model the energy consumption driven by tasks in production processes of machining manufacturing system. The proposed modeling method is solved in Simulink simulation environment, and applied to select the flexible processes of tasks for optimizing energy consumption. The results show a valuable insight of energy consumption in machining manufacturing system so as to make robust decisions on the potential for improving energy efficiency. [Copyright &y& Elsevier]