Search

As the most important part of machining system, machine tools are widely used in industry, and the resource consumption and environmental problems caused by their use are becoming more and more serious. For promoting energy efficiency of machining system, various methods have been developed based on statistical approaches with design of experiments. However, the methods cannot be easily utilized when the optimization target or machine tool design is modified because the optimal solution is determined based on the experimentally measured data. An effective and practical monitoring method is not only the precondition of energy efficiency promoting, but also the basis of the integration with industry 4.0 applications. This paper presents a modelling approach for energy efficiency of machining system which can be used to monitor energy efficiency on-line and without any extra cutting force dynamometer. The approach is proposed based on the energy consumption mechanism of machining system and the dynamic factors (temperature, lubrication, etc.) of machining processes are considered, so that it has a quite high accuracy under various machining conditions. The case study and validation have been carried out and the experimental results indicate that the accuracy of the approach can reach over 90% under various processing conditions. Finally, the static errors and dynamic errors which may affect monitoring accuracy are discussed. [ABSTRACT FROM AUTHOR]

Spindle system is the major mechanical component in machine tools, and its performance is responsible for a significant portion of the total consumed energy of machine tools. Conventional design optimization of spindle system is partially focused on parameter optimization of spindle motor or transmission system, contributing to an increase of the motor efficiency. Given that concurrent interactions among them is complex, very little efforts has been done to conduct integration optimization for optimum energy efficiency. To this end, a new approach of spindle system design is presented with consideration of the above two aspects adequately, to achieve the maximum energy and material efficiency. Firstly, the energy characteristic of spindle system is explicitly modelled on the basis of energy flow analysis. Then, a multi-objective optimization model for parameter optimization of spindle motor and transmission system is developed to take the both maximum energy efficiency and minimum volume as objectives, which is subjecting to a set of constraints with related to the cutting parameters boundary, processing requirements and shifting power losses. Finally, a multi-objective improved teaching-learning based optimization (MO-ITLBO) algorithm is presented to solve the developed optimization model. The performance of the proposed design approach of lathe spindle system is demonstrated through different working conditions. The experimental results indicate that the design of energy and material efficient machine tools can be achieved. [ABSTRACT FROM AUTHOR]