Energy consumption modeling of machining transient states based on finite state machine

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• 作者：Shun Jia ; Renzhong Tang ; Jingxiang Lv…
• 关键词：Transient state ; Energy consumption modeling ; Finite state machine (FSM) ; State transition chart ; Sustainable machining
• 刊名：The International Journal of Advanced Manufacturing Technology
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：88
• 期：5-8
• 页码：2305-2320
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design;
• 出版者：Springer London
• ISSN：1433-3015
• 卷排序：88

文摘

Energy-saving and emission reduction are urgently vital tasks of the manufacturing industry. Energy optimization of machining processes provides an important approach leading to the energy-saving of the manufacturing industry. Energy modeling of machining processes is the key technology and foundation of energy optimization. Energy consumption of machining processes can be decomposed into two parts: energy consumption of steady state and energy consumption of transient state. Transient state is the transition process between two steady states, which may lead to the peak power. Transient states frequently occur during a machining process and their energy consumptions should not be ignored. However, research that specifically focuses on these energies is rare. Therefore, a finite state machine (FSM)-based energy consumption modeling method of machining transient state is proposed in this paper. FSM is introduced to describe the transient states during machining. The key transient state processes are identified according to Pareto principle, and energy consumption models of these key transient state processes are established. State transition chart is then constructed to determine key transient states and their execution times during machining process. Based on the state transition chart and energy consumption models of the key transient states, an energy consumption model of machining process is established. Finally, a case study is conducted to show the effectiveness and feasibility of the proposed modeling method. The proposed method can improve the integrity and accuracy of the energy consumption model of machining process.