Title: Advancing sustainability through efficient production processes: integrating ISO standards, Lean Six Sigma and artificial intelligence

Authors: António Rocha; Edit Sule; Fernando Romero; Ricardo Simões

Addresses: 2Ai – Applied Artificial Intelligence Laboratory, School of Technology, Polytechnic Institute of Cávado and Ave, Vila Frescainha, Campus do IPCA, 4750-810, Barcelos, Portugal; ALGORITMI Research Centre, University of Minho, Campus de Azurém, 4800-058 Guimarães, Portugal ' Szechenyi Istvan University, Győr, Egyetem tér 1, 9026, Hungary ' ALGORITMI Research Centre, University of Minho, Campus de Azurém, 4800-058 Guimarães, Portugal ' School of Design, Polytechnic Institute of Cávado and Ave, Vila Frescainha, Campus do IPCA, 4750-810, Barcelos, Portugal; Institute for Polymers and Composites IPC/I3N, University of Minho, Campus de Azurém, 4800-058 Guimarães, Portugal

Abstract: In a circular economy, products must be designed and produced to a high standard of quality, durability, and reliability, to be easy to maintain and repair, and manufacturing processes must be efficient to minimise waste, information, and energy losses. Our research focuses on sustainable business success while addressing environmental concerns. Data from the European Environmental Agency's PRTR database has been analysed to identify industries contributing the most to air and water pollution and whether emissions have decreased over time. Findings highlight the need for stronger commitment and investment to achieve net-zero greenhouse gas emissions. As a contribution to this end, a baseline for an integrated management system for industrial sustainability (IMSIS) is proposed, combining ISO standards, Lean Six Sigma, and artificial intelligence (AI), making use of advanced technologies. This approach aims to address productivity and sustainability challenges, leading to reduced manufacturing waste and improved energy and information use.

Keywords: sustainability; process efficiency; management systems; artificial intelligence; Lean Six Sigma; advanced technologies.

DOI: 10.1504/IJPQM.2026.152584

International Journal of Productivity and Quality Management, 2026 Vol.47 No.3, pp.275 - 304

Received: 07 Dec 2023
Accepted: 17 Dec 2023
Published online: 30 Mar 2026 *

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