Streamlining LCA process using Simplification and DMAIC framework for process improvisation and cycle time reduction: A pragmatic LCA approach for engineering organizations

Main Presenter: Nayan Sonawane 

Co-Authors: Heinz Huesmann Sachin Nande

In recent years, manufacturing organizations are increasingly looking beyond the financial aspects of their operations to integrate environmental (ecological) concerns into the decision-making process. Accordingly, the need to embed sustainability in the value chain has become indispensable. Life Cycle Assessment (LCA) is one such tool that is most widely used for environmental impact quantification considering all life cycle stages of product/services. The results from LCA studies eventually help in making verified, transparent and credible environmental performance claims. However, being resource and time-intensive, efforts are underway to streamline the LCA process. The end objective of streamlining is to reduce the complexity of the task, simplify it, and make it more efficient to reduce time and cover a broad product portfolio.

In this project, we aimed to streamline the LCA process using the DMAIC framework and various streamlining methods reported in literature thus applying it to our products identified for Environmental Product Declaration (EPD) labels. In brief, we amalgamated the three principles of standardization, automation, and substitution as suggested by Beemsterboer et al. 2020, with the DMAIC framework to simplify the LCA process (without compromising on quality) and achieve cycle time reduction. Tools like thought maps, SIPOC, process flow charts, and value stream maps were used in the Define (D) and Measure (M) stages to benchmark current LCA practices within the organization. In the Analyse (A) stage, we leveraged fellow LCA practitioners’ inputs through why-why/route cause analysis and Pareto Charts. In the Improve (I) stage, we developed a systematic approach through a controlled engineering process-DMAIC aiming to adopt the three principles mentioned above to accelerate the LCA process. In
the last phase, i.e., Control (C), we established a control plan to sustain proposed improvement processes.

Through this approach, we were successful in replacing repetitive and manual steps, which were time consuming, with various levels of automation and standardization. This resulted in reducing about 60% of our time as compared to conducting a full LCA study, without compromising on the quality and credibility of the findings. We also proved how traditional quality control tools (e.g., DMAIC, LEAN), which are predominantly applied in manufacturing setups for enhancing productivity or turnaround time, can be utilized to streamline the complex LCA processes. This unique approach can be easily adopted by other engineering and manufacturing organizations where DMAIC or similar tools are used for quality and process improvisation. It offers a significant advantage over employing only simplification or DMAIC methods, which poses risk of simplification or standardization at the expense of potential accuracy loss.

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