The application of Lean Six Sigma to build operational excellence in steel manufacturing: Case study from India

Abstract

Measuring and controlling dimensional accuracies are very critical in steel manufacturing to meet high specification requirements of customers and to provide competitiveness. MPL Steels, being one of the major steel producers in India, have been experiencing great scrap rates of 9-11% in the context of dimensional inconsistency amidst roller wear, mill instability and cutting errors, a fact that has caused massive loss of finances and Occasional operational difficulties. The purpose of the study was to design and institute an integrated Lean Six Sigma system with the increased predictive maintenance and digital optimization capability to methodically minimize defects and improve process capability in MPL Steels in a sequential manner. Applying the DMAIC Six Sigma approach, the identification of the root causes was fulfilled by means of Pareto, regression, and cause-effect tools applied to a big amount of production data. The important interventions were taken such as monitoring of roller wear using IoTs, auto-adjustment of cutting parameters using an AI program, a prediction-based maintenance schedule, and thorough training of operators, and the pain points were monitored using a statistical process control chart. After its implementation, MPL steels realized 55.4% reduction in its thickness-related scrap, which reduced the scrapping rates to 4.1% downturn 9.2%, whereas process capability (Cpk) also improved up to 1.33 up turned 0.82. Reduction in machine downtimes was 66.7%, the total defects decreased by 61.5%, and the annual saving was much more than half a million dollars. The findings show that a combination of Lean Six Sigma and Industry 4.0 technologies can be used to make significant improvements in quality, operational efficiency, and sustainable competitiveness in a mid-sized steel manufacturing that will serve as a basis of long-term, data-driven continuous improvement.