TY - GEN
T1 - The Integration of Lean Six Sigma Solutions and Emerging Technologies for Resilient Manufacturing in the Rail Transportation Sector in South Africa
AU - Bakam, Genevieve
AU - Mpofu, Khumbulani
AU - Mbohwa, Charles
AU - Nenzhelele, T.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026
Y1 - 2026
N2 - Promoting manufacturing excellence relies on the synergy between existing operations techniques and future technology as the cornerstone of digital manufacturing restructuration. This paper investigates the integration of Lean Six Sigma (LSS) solutions and emerging technologies for resilient manufacturing in the rail transportation sector in South Africa. This study applies cause-effect and technology-organisation-environment analyses to support the LSS methodologies namely Define, Measure, Analyze, Improve, Control (DMAIC) and Define, Measure, Analyze, Design, Verify (DMADV) for existing and innovative processes. The case study of Gibela-Rail Consortium is applied using its integrated manufacturing reports. Findings revealed that smart technologies like big Industrial Internet of Things (IIoT), advanced analytics, sensors, manufacturing systems, Artificial Intelligence (AI), blockchain and digital twin enable connectivity, automation, process streamlining, green practices, quality control, Just-in-time production, embedded policies, and integrated descriptive, prescriptive and predictive analytics for enhanced decision-making processes. Applying LSS and smart technologies enhances cost reduction, zero-waste, production increase enhanced maintenance, lightweight and energy-efficient trains, operational efficiency, passenger satisfaction and competitive advantage. The proposed Smart LSS (LSS4.0)-enabled Resilient Manufacturing Model combines lean techniques and smart technologies to enable resilient manufacturing and continuous improvement. Transport manufacturing companies should adopt a digital change culture enabling process revitalisation and the SA government should upgrade regulations and infrastructure to support digital and green transformation for long-term value creation.
AB - Promoting manufacturing excellence relies on the synergy between existing operations techniques and future technology as the cornerstone of digital manufacturing restructuration. This paper investigates the integration of Lean Six Sigma (LSS) solutions and emerging technologies for resilient manufacturing in the rail transportation sector in South Africa. This study applies cause-effect and technology-organisation-environment analyses to support the LSS methodologies namely Define, Measure, Analyze, Improve, Control (DMAIC) and Define, Measure, Analyze, Design, Verify (DMADV) for existing and innovative processes. The case study of Gibela-Rail Consortium is applied using its integrated manufacturing reports. Findings revealed that smart technologies like big Industrial Internet of Things (IIoT), advanced analytics, sensors, manufacturing systems, Artificial Intelligence (AI), blockchain and digital twin enable connectivity, automation, process streamlining, green practices, quality control, Just-in-time production, embedded policies, and integrated descriptive, prescriptive and predictive analytics for enhanced decision-making processes. Applying LSS and smart technologies enhances cost reduction, zero-waste, production increase enhanced maintenance, lightweight and energy-efficient trains, operational efficiency, passenger satisfaction and competitive advantage. The proposed Smart LSS (LSS4.0)-enabled Resilient Manufacturing Model combines lean techniques and smart technologies to enable resilient manufacturing and continuous improvement. Transport manufacturing companies should adopt a digital change culture enabling process revitalisation and the SA government should upgrade regulations and infrastructure to support digital and green transformation for long-term value creation.
KW - Advanced analytics
KW - Digital twin
KW - Gibela-Rail
KW - Lean Six Sigma
KW - Smart-to-green
KW - Sustainable manufacturing and South Africa
UR - https://www.scopus.com/pages/publications/105023137665
U2 - 10.1007/978-3-032-07675-5_34
DO - 10.1007/978-3-032-07675-5_34
M3 - Conference contribution
AN - SCOPUS:105023137665
SN - 9783032076748
T3 - Lecture Notes in Mechanical Engineering
SP - 355
EP - 362
BT - Flexible Automation and Intelligent Manufacturing
A2 - Srihari, Krishnaswami
A2 - Khasawneh, Mohammad T.
A2 - Yoon, Sangwon
A2 - Won, Daehan
PB - Springer Science and Business Media Deutschland GmbH
T2 - 34th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2025
Y2 - 21 June 2025 through 24 June 2025
ER -