Implications for sustainability in supply chain management and the circular economy using machine learning model

The definition of “Industry 4.0” would contribute to that distributed manufacturing systems, real-time information and inevitably a lot more product information. In this case, the optimization of capabilities goes beyond the conventional goal often adds to the competitiveness and efficiency of the company. Lean management and continuous development strategies, in turn, suggest an enhancement rather than maximization of energy. Furthermore, the analysis of Power Optimization and Costing Models is an important area of research that needs functional theoretical feedback. Hence in this paper, a statistical approach for power control based upon multiple costing frameworks using a machine learning model (SCM–MLM) has been designed and developed for power optimization and cost factor. This paper introduces and addresses a generalized model that has been built to evaluate idleness and create techniques to optimize the profitability of the enterprise. The maximization of trade-off capacity against organizational performance is demonstrated and it is seen to be organizational inefficiency by power optimization has been validated in this paper.