Reducing the scrap rate in an electronic manufacturing SME through Lean Six Sigma methodology

Alireza Shokri, Gareth Bradley, Farhad Nabhani

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    Purpose – The aim of this project was to reduce the level of scrap rate in the production of a product known as the “Remote Acceleration Sensor (RAS)” that is used for Air Bags through Lean Six Sigma (LSS) methodology. Design/methodology/approach – This is an action research that was conducted in a single case study and used the LSS methodology of DMAIC concentrating on one fully automated sub-process of the production called the “Overmould line”. Finding – It was found that implementing DMAIC methodology had an effective impact on the production and scrap rate was reduced achieving the 99.03% First Run Yield (FRY) from 98.4% FRY before implementation. This was the improvement from 3.65 to 3.85 in the Sigma scoring term with significant financial impact at this scale. Research Limitations/Implications – This action research could be deployed in other sub- processes of the production line, other processes of the company and could also be conducted in more than one single case study from the same sector. The research investigation needs to be fully controlled by the team in order to correctly gauge the effect of any changes made to the process. Practical Implications – This project adds further evidence of effectiveness of the LSS methodology in manufacturing SMEs through adding value to the process and reducing the scrap rate and waste. The project had greater saving than expected by the managers at £98,000 per annum. This saving could even be higher when the company is expanded. Originality/Value- The approach of this research project combines proven statistical tools with some basic but effective lean tools to be applied in an original sequence in order to design robust product and match manufacturing capabilities. Key Words – Lean Six Sigma, Six Sigma, DMAIC, Manufacturing, SMEs, Scrap Rate


    ConferenceSixth International Conference on Lean Six Sigma
    Period30/05/16 → …
    Internet address

    April 2024 testing of classification propagation

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