In a multi-pass face milling process, cutting parameters for each pass and the total number of passes dramatically affect the electrical energy consumption and production cost of the final product. In this paper, the electrical energy consumption characteristics of multi-pass face milling are firstly analyzed. Then a multi-objective parameter optimization model for maximizing energy efficiency and minimizing production cost is proposed and solved by the Adaptive Multi-objective Particle Swarm Optimization algorithm. Finally, a case study is carried out to validate the proposed model and search for the trade-off solutions between maximum energy efficiency and minimum production cost. From the results of the case study, significant interaction effects between cutting parameters and number of passes are revealed. Moreover, it also can be found that the traditional multi-pass parameter optimization for minimizing production cost does not necessarily satisfy the maximum energy efficiency criterion. Simultaneously optimizing the cutting parameters of each pass and the total number of passes achieves a trade-off between maximum energy efficiency and minimum production cost. Based on the work presented in this paper, manufacturers can easily improve energy efficiency and reduce production cost in the multi-pass face milling process.
All Science Journal Classification (ASJC) codes
- Renewable Energy, Sustainability and the Environment
- Environmental Science(all)
- Strategy and Management
- Industrial and Manufacturing Engineering