Multi-objective teaching–learning-based optimization algorithm for reducing carbon emissions and operation time in turning operations

Abstract

2014): Multi-objective teaching-learning-based optimization algorithm for reducing carbon emissions and operation time in turning operations, Engineering Optimization, In addition to energy consumption, the use of cutting fluids, deposition of worn tools and certain other manufacturing activities can have environmental impacts.All these activities cause carbon emission directly or indirectly; therefore, carbon emission can be used as an environmental criterion for machining systems. In this article, a direct method is proposed to quantify the carbon emissions in turning operations. To determine the coefficients in the quantitative method, real experimental data were obtained and analysed in MATLAB. Moreover, a multi-objective teaching-learning-based optimization algorithm is proposed, and two objectives to minimize carbon emissions and operation time are considered simultaneously. Cutting parameters were optimized by the proposed algorithm. Finally, the analytic hierarchy process was used to determine the optimal solution, which was found to be more environmentally friendly than the cutting parameters determined by the design of experiments method.

A method integrating Taguchi, RSM and MOPSO to CNC machining parameters optimization for energy saving

“…• Given that optimal parameters are selected directly from experimental combinations, the result is highly dependent on experimental settings of the parameters, and has a high risk of being trapped into local optimal points (Lin et al, 2014).…”

Dynamic Acquisition and Real-Time Distribution of Carbon Emission for Machining Through Mining Energy Data

“…For instance, Liu et al [19] proposed a method to identify and manage cutting status though real-time emission source. Lin et al [20] analyzed the relationship between carbon emissions (i.e., use of cutting fluids, deposition of worn tools and material consumption) and turning operations, and presented a approach to determine operation time of lathe. The research by Hu et al [21] on spindle power in operating state also shown that running statues of machine tools can be acquired though carbon emissions as power consumption is the main carbon source for a machine tool.…”

Multi-Objective Parameter Optimization Dynamic Model of Grinding Processes for Promoting Low-Carbon and Low-Cost Production

“…Jiang et al [22] proposed a method to predict the remanufacturing cost based on dates. Lin et al [23] proposed a method to directly quantify carbon emissions during the entire turning process and established a low-carbon, efficient turning model. Yan et al [24] built a model to improve the thermal efficiency of the arc welding process, reducing energy consumption as a result.…”