Prescriptive Analytics for finding the optimal manufacturing practice based on the simulation models of Lean Manufacturing and Total Quality Management

The manufacturing practices such as Lean Manufacturing (LM) and Total Quality Management (TQM) will take several years for the implementation at the operational level. There is a requirement of huge investment for the implementation of LM and TQM. Hence, most of the companies are unable to implement the LM and TQM at the operational level. The key obstacles of huge investment and time consumption for finding the optimal manufacturing practice can be overcome by using Prescriptive analytics. In the field of analytics, the prescriptive analytics can be performed using the simulation to find the optimal manufacturing practice. This paper aims at finding the optimal manufacturing practice from the prescriptive models such as LM and TQM simulation models. The simulation model of LM and TQM is evaluated to find the optimal manufacturing practice according to the variables and mean key performance indicators (KPIs). Based on the simulation analysis, the mean utilization found to be better for both LM and TQM. But it indicates that TQM are unable to produce more throughputs due to more time needed for processing. Hence the LM is found to be the optimal manufacturing practice because of lean principles such as Muda for reduction in unnecessary time and Pull system for reduction in mean WIP inventory that leads to increase in mean throughput. The sustainable framework of LM implementation needs to be developed based on the lean principles such as Muda and Pull system.