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Identifying Meaningful Targets for Complex Lean 4.0 Manufacturing Using Business Analytics: A Case Study in Biopharmaceutical Manufacturing

Year: 2025

Type: article

Abstract: Traditional Lean manufacturing material waste and immaterial (time and effort) reduction targets may not be of significant value for complex manufacturing. A competitive advantage in complex manufacturing lies in the accumulation of process knowledge and leveraging this knowledge to improve performance metrics such as yield. The study demonstrates how Business Analytics using CRISP-DM can extract process knowledge from human experts and historical manufacturing data to provide actionable insights. The study explores how established Lean manufacturing tools, such as Standard Work and 5s, can be adapted to deploy the Business Analytics recommendations on the manufacturing floor, leading to Lean 4.0. The proposed approach is validated on a case study in biopharmaceutical manufacturing, resulting in a 6% increase in product yield. The study discusses how the successful combination of Business Analytics and Lean manufacturing can provide useful process knowledge insights in complex manufacturing through an adapted Lean 4.0 framework to target non-traditional performance measures such as yield.

Source: IEEE Transactions on Engineering Management

DOI: 10.1109/tem.2025.3575692

Authors: William Fahey, Gareth Thornton, Eimear O'Brien, Olivia McDermott, Paula Carroll

Institutions: Pfizer (United Kingdom), Pfizer (Ireland), University of Leeds, Ollscoil na Gaillimhe – University of Galway, University College Dublin

Language: English

Topic: Digital Transformation in Industry

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Responsible consumption and production, Industry, innovation and infrastructure

Open Access status: green

Funder: Irish Research Council