Six Sigma is a well-liked technique for raising productivity and quality of output in industrial processes and process improvement initiatives. In the Six Sigma methodology, abnormalities in the operational process are reviewed and examined using the Define, Measure, Analyze, Improve, and Control (DMAIC) cycle. Corrective action is then taken to reduce bottlenecks to enhance productivity, ensure stable product quality, and create a tightly connected production cycle. This study proposes the use of integrating statistical hypotheses into the DMAIC cycle of the Six Sigma method and proposes the use of Enterprise Resource Planning (ERP) modules to monitor production processes at a major mechanical processing company. Lean tools are also suggested by the author to be used in the analysis phase. The research results show a reduction in the rate of late product delivery to users from 6.28% to 0.02% per month. The lean tool application model, statistical hypotheses, and industry 4.0 system are integrated into the EPR system at the company's improvement department and are considered a model for manufacturing companies to refer to in implementing improvements for their products. Production processes in different companies.