Design of robust energy consumption model for manufacturing process considering uncertainties

In view of environment degradation, sustainable manufacturing has become a major focus in the production industry. Energy consumption is one of the key factor in sustainable manufacturing and also responsible for an increase in production cost. It is found that machining parameters have a considerable influence on both energy consumption and product quality. One way to optimize the energy consumption is to establish the relationship between the machining parameters. Thus, developing robust and accurate energy consumption models for manufacturing process is an urgent need to ease negative environmental impacts. In this context, an evolutionary approach of Gene Expression Programming considering uncertainties is proposed. Two case studies are carried out to validate the effectiveness of proposed approach. Uncertainties during the modeling process are considered and handled with a designed set of experiments. Experiments are further performed to validate the robustness of the models. Further, 2D and 3D plots are employed to analyze the relationship between the given machining parameters. Optimization of the designed models is then carried out to determine the optimum set of inputs that minimizes the energy consumption.