LSS Application to Improve MEC Process in Local Maintenance Firm: A Case Study

Abstract

Lean Six Sigma (LSS) has quickly become the go-to method for many businesses to enhance their business processes. The LSS methodology provides tremendous benefits to businesses due to its real-time emphasis on reducing waste and increasing value by addressing Critical to Quality (CTQ) issues that influence uniformity and consistency in a procedure and product [17]. The Lean methodology focuses on identifying and eliminating all waste in the organization, while the Six Sigma methodology improves the process outputs quality by minimizing the variation. Combining these two methodologies introduces a holistic framework for processes improvement. This paper outlines the execution of an integrated LSS framework by utilizing the DMAIC practices in a local aerospace maintenance firm using a case study approach. The main goal of this project was to reduce the MEC lead time, which means reducing the firm's reaction time to consumer necessities. The MEC is a form generated by the technicians or other requesters in the company to request technical support from the engineering department.

The aim of this study was met by studying the LSS approach in depth, its history, development, and methodology. Furthermore, the performance of the MEC procedure significantly enhanced, by using a variety of LSS tools on the MEC process during the five phases of the DMAIC cycle. The thesis measured the MEC procedure performance represented in the MEC lead time, analyzed the collected data, and found the root causes of the spotted problems in the procedure. It also provided a set of proposals to improve the old process, and control the improved process, in order to ensure the sustainability of the obtained results. The MEC's average lead time was reduced from 18.7 to 5.1 days by implementing LSS methodology. This increased the aircraft serviceability, boosted the performance of the department, and set the organization in the right direction for a holistic Knowledge Management and Continuous Improvement culture.

Date of Award	Apr 2023
Original language	American English
Supervisor	TOUFIC Mezher (Supervisor)