Optimising material flows in the pharmaceutical industry: a Lean Six Sigma approach : A case study focusing on critical indirect materials

Sammanfattning

The pharmaceutical industry is a cornerstone of modern society, currently undergoing a digital transformation aimed at replacing manual tasks with automated solutions. Unlike many other sectors, the pharmaceutical industry operates under strict regulatory requirements, ensuring a sustainable and secure production. Resulting in slower implementation of operational changes. Within pharmaceutical production, various materials are handled, among them, by this study defined as Critical Indirect Materials (CIM), which, while not part of the final product, are consumed during the production and are essential for ensuring successful and uninterrupted production. Despite their importance, limited research has addressed the management and optimisation of CIM flows, particularly in this sector. This study addresses this research gap by applying the Lean Six Sigma (LSS) framework in a case company within the pharmaceutical industry. The main research question posed was: How can Lean Six Sigma be applied to identify and optimise the flow of critical indirect materials within the pharmaceutical industry? This was supported by two sub-questions: Which challenges complicate the understanding and assessment of current CIM flows? How can barriers and waste in the flow of CIM be effectively addressed with a single solution to enhance efficiency? The study followed the DMAIC methodology, containing the five steps: Define, Measure, Analyse, Improve, and Control, supported by Value Stream Mapping (VSM) to analyse and improve the current system. This approach enabled the mapping of existing CIM flows, the identification of inefficiencies, and waste within the current system. Consequently, the researchers proposed an integrated barcode-based solution for the automated handling of the CIM flows. The findings underscore the potential of LSS as a valuable framework for improving CIM processes, while also raising questions about the broader applicability of LSS within highly regulated industries such as this.