Fu-Kwun Wang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Fu-Kwun Wang has a total of 75 co-authors. Here are the top co-authors by number of shared publications:
- Jia-Hong Chou
Department of Industrial Management, National Taiwan University of Science and Technology, Taipei, Taiwan
10 shared publications Xiao‐Bin Cheng
Intelligence Center Shanghai Electric Wind Power Group Shanghai China
10 shared publicationsYeneneh Tamirat
Department of Business Administration, Asia University, Taichung, Taiwan
10 shared publications- Berihun Bizuneh
Bahir Dar University Apparel Faculty, Ethiopian Institute of Textile and Fashion Technology Bahir Dar
6 shared publications - Shih-Che Lo
National Taiwan University of Science and Technology
6 shared publications William Gomez
6 shared publications
Latest Publications
- 5 November 2026
- Published by Emerald Publishing in International Journal of Lean Six Sigma
- p. 1-30
A new framework for linking process-level sustainability performance to economic loss in manufacturing
Purpose: This study presents a framework that links process-level sustainability performance and economic loss analysis in manufacturing by integrating the triple bottom stream method (TBSM), a value-stream-oriented process-flow assessment framework, into the Lean Six Sigma-define–measure–analyze–improve–control (LSS-DMAIC) cycle. The purpose of this study is to provide a structured method for identifying how operational, environmental and social inefficiencies relate to financial outcomes and to support sustainable process improvement. Design/methodology/approach: The proposed framework uses TBSM to evaluate operational, environmental and social sustainability performance. These dimensions are integrated into a Composite Performance Index (CPI) that represents overall manufacturing sustainability performance. A diagnostic sustainability-loss indicator is further used to assess sustainability-related deficiencies, while economic performance is evaluated through economic-loss analysis based on observed process and problem costs. The framework enables the identification of process-level inefficiencies across the operational, environmental and social dimensions while providing a separate assessment of economic consequences at the process level. It is subsequently operationalized through the LSS-DMAIC cycle to support structured process improvement. Findings: In an Indonesian manufacturing SME, the initial TBSM assessment yielded a CPI of 64.17%, indicating acceptable overall sustainability performance; however, detailed process-level assessment and economic-loss evaluation revealed that several manufacturing processes still exhibited substantial operational, environmental and social deficiencies. After implementing improvement actions, the CPI increased to 78.92%, reflecting improvement across operational, environmental and social dimensions. The improvements generated an estimated gross monthly saving of US$4,807.38 and a net monthly financial benefit of US$3,780.49 after deducting operational costs. Originality/value: Prior approaches often evaluate selected dimensions without providing an integrated assessment of operational, environmental and social sustainability performance alongside process-level economic consequences. To address this gap, this study introduces the TBSM, which integrates operational, environmental and social sustainability assessments into the CPI while examining economic loss through a separate economic-consequence analysis path. This framework enables a more structured assessment of sustainability performance and economic consequences at the process level. The proposed framework supports broader sustainability objectives, including Sustainable Development Goal (SDG) 9 and SDG 12 while advancing integrated and system-oriented sustainability practices in manufacturing.
- 5 November 2026
- Published by Emerald Publishing in International Journal of Lean Six Sigma
- p. 1-30
A new framework for linking process-level sustainability performance to economic loss in manufacturing
Purpose: This study presents a framework that links process-level sustainability performance and economic loss analysis in manufacturing by integrating the triple bottom stream method (TBSM), a value-stream-oriented process-flow assessment framework, into the Lean Six Sigma-define–measure–analyze–improve–control (LSS-DMAIC) cycle. The purpose of this study is to provide a structured method for identifying how operational, environmental and social inefficiencies relate to financial outcomes and to support sustainable process improvement. Design/methodology/approach: The proposed framework uses TBSM to evaluate operational, environmental and social sustainability performance. These dimensions are integrated into a Composite Performance Index (CPI) that represents overall manufacturing sustainability performance. A diagnostic sustainability-loss indicator is further used to assess sustainability-related deficiencies, while economic performance is evaluated through economic-loss analysis based on observed process and problem costs. The framework enables the identification of process-level inefficiencies across the operational, environmental and social dimensions while providing a separate assessment of economic consequences at the process level. It is subsequently operationalized through the LSS-DMAIC cycle to support structured process improvement. Findings: In an Indonesian manufacturing SME, the initial TBSM assessment yielded a CPI of 64.17%, indicating acceptable overall sustainability performance; however, detailed process-level assessment and economic-loss evaluation revealed that several manufacturing processes still exhibited substantial operational, environmental and social deficiencies. After implementing improvement actions, the CPI increased to 78.92%, reflecting improvement across operational, environmental and social dimensions. The improvements generated an estimated gross monthly saving of US$4,807.38 and a net monthly financial benefit of US$3,780.49 after deducting operational costs. Originality/value: Prior approaches often evaluate selected dimensions without providing an integrated assessment of operational, environmental and social sustainability performance alongside process-level economic consequences. To address this gap, this study introduces the TBSM, which integrates operational, environmental and social sustainability assessments into the CPI while examining economic loss through a separate economic-consequence analysis path. This framework enables a more structured assessment of sustainability performance and economic consequences at the process level. The proposed framework supports broader sustainability objectives, including Sustainable Development Goal (SDG) 9 and SDG 12 while advancing integrated and system-oriented sustainability practices in manufacturing.
- 12 October 2026
- Published by Emerald Publishing in International Journal of Quality & Reliability Management
- p. 1-25
A multi-dimensional performance framework for industry 5.0 manufacturing: integration of lean six sigma with human-centric, sustainability and resilience metrics
Purpose: This study examines how Lean Six Sigma (LSS) can support the implementation of Industry 5.0 and its three pillars to improve progress toward Sustainable Development Goals (SDGs). It seeks to clarify the overlaps between LSS and Industry 5.0, develop an integrated conceptual model connecting both frameworks to SDGs 8, 9, 12 and 13, and demonstrate its practical use through a Define-Measure-Analyze-Improve-Control (DMAIC)-based case study in manufacturing. Design/methodology/approach: A structured conceptual literature review was conducted to synthesize and critically analyze existing studies on LSS, Industry 5.0, and SDGs. The review was used to identify conceptual synergies and research gaps that informed the development of the proposed human-centric, sustainable, and resilient enhancement (H-SURE) framework. The proposed framework was subsequently illustrated through a DMAIC-based single-company case study to demonstrate its practical implementation within an Industry 5.0 manufacturing environment. Findings: The analysis shows that LSS and Industry 5.0 strongly align in strategic orientation, waste reduction, human engagement and continuous improvement, while differing in regulatory readiness and technological integration. The conceptual H-SURE framework indicates that LSS offers a structured pathway to operationalize Industry 5.0 and advance SDGs 8, 9, 12 and 13. The case study demonstrates that integrating both frameworks reduces defects and energy use, strengthens human-machine collaboration, increases employee empowerment and enhances operational resilience. Originality/value: This study offers a comprehensive model linking LSS, Industry 5.0 and the SDGs, addressing a significant gap in the literature on how continuous improvement methodologies can enable human-centric and sustainable industrial transformation. By integrating a conceptual H-SURE framework with empirical insights from a DMAIC-driven case study, the study provides both theoretical advancement and practical guidance for organizations seeking to transition from Industry 4.0 to Industry 5.0 while strengthening their contributions to global sustainability goals.
- 12 October 2026
- Published by Emerald Publishing in International Journal of Quality & Reliability Management
- p. 1-25
A multi-dimensional performance framework for industry 5.0 manufacturing: integration of lean six sigma with human-centric, sustainability and resilience metrics
Purpose: This study examines how Lean Six Sigma (LSS) can support the implementation of Industry 5.0 and its three pillars to improve progress toward Sustainable Development Goals (SDGs). It seeks to clarify the overlaps between LSS and Industry 5.0, develop an integrated conceptual model connecting both frameworks to SDGs 8, 9, 12 and 13, and demonstrate its practical use through a Define-Measure-Analyze-Improve-Control (DMAIC)-based case study in manufacturing. Design/methodology/approach: A structured conceptual literature review was conducted to synthesize and critically analyze existing studies on LSS, Industry 5.0, and SDGs. The review was used to identify conceptual synergies and research gaps that informed the development of the proposed human-centric, sustainable, and resilient enhancement (H-SURE) framework. The proposed framework was subsequently illustrated through a DMAIC-based single-company case study to demonstrate its practical implementation within an Industry 5.0 manufacturing environment. Findings: The analysis shows that LSS and Industry 5.0 strongly align in strategic orientation, waste reduction, human engagement and continuous improvement, while differing in regulatory readiness and technological integration. The conceptual H-SURE framework indicates that LSS offers a structured pathway to operationalize Industry 5.0 and advance SDGs 8, 9, 12 and 13. The case study demonstrates that integrating both frameworks reduces defects and energy use, strengthens human-machine collaboration, increases employee empowerment and enhances operational resilience. Originality/value: This study offers a comprehensive model linking LSS, Industry 5.0 and the SDGs, addressing a significant gap in the literature on how continuous improvement methodologies can enable human-centric and sustainable industrial transformation. By integrating a conceptual H-SURE framework with empirical insights from a DMAIC-driven case study, the study provides both theoretical advancement and practical guidance for organizations seeking to transition from Industry 4.0 to Industry 5.0 while strengthening their contributions to global sustainability goals.
- 18 September 2026
- Published by Elsevier in Advanced Engineering Informatics
- Vol. 77
An improved iTransformer framework for health prediction of proton exchange membrane fuel cells
- 18 September 2026
- Published by Elsevier in Advanced Engineering Informatics
- Vol. 77
An improved iTransformer framework for health prediction of proton exchange membrane fuel cells
- 7 March 2026
- Published by Elsevier in Electric Power Systems Research
- Vol. 256
Predicting medium-term wind speed using a hybrid deep learning model with a transfer learning approach
- 7 March 2026
- Published by Elsevier in Electric Power Systems Research
- Vol. 256
Predicting medium-term wind speed using a hybrid deep learning model with a transfer learning approach
- 13 February 2026
- Published by Elsevier in ISA Transactions
- Vol. 175, 58-72
A prediction framework for the state of health of an electric vehicle battery pack
- 13 February 2026
- Published by Elsevier in ISA Transactions
- Vol. 175, 58-72
A prediction framework for the state of health of an electric vehicle battery pack