Process Improvements to reduce carbon emissions-A Green Lean Six Sigma Approach

Examensarbete för masterexamen
Quality and operations management (MPQOM), MSc
Navaneet, Subbaram
Raghul, Subramanian
In the current situation, carbon emissions are significantly contributing to climate change by trapping heat in the atmosphere through the burning of fossil fuels and producing non-sustainable goods. Because of this, it is important to cut carbon emissions by minimizing waste and finding sustainable ways to distribute goods to clients. Reducing emissions also results in greener earth, more drought resilience, less climate change, and a safer environment. By doing away with waste in its operations and creating environmentally friendly ways to deliver its products to clients, the company studied in this thesis hopes to cut its transportation-related emissions by half by the year 2030. As a result, the goal of this thesis is to enhance the processes by lowering carbon emissions utilizing the green lean six sigma approaches. Understanding the process variations of late materials, 90-Kits, and poor quality which lead to a substantial quantity of carbon emissions in its operations is the focus of this master’s thesis. The authors apply a six-sigma methodology using a multi-phase DMAIC technique to pinpoint the bottlenecks that are responsible for process deviations such as delayed material, 90-Kits, and poor quality. It became clear that the forecasting and sourcing processes were important contributors to the process variations and rising emissions. To decrease process waste and improve accuracy and dependability, forecasting and sourcing models are also integrated. Additionally, a KPI dashboard was created to track the development of various KPIs, which is important for enhancing process performance and reducing or eliminating process variation by taking the appropriate steps when necessary. The final limitation of this study is that because the thesis is restricted to a single area of the supply chain, some of the conclusions cannot be generalized. As a next step to continue the thesis work, suggestions for future projects have also been offered.
Process Improvements , Green lean six sigma , Forecasting methods , KPI dashboard , Carbon emissions , Material tracking
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