Analysing Lean 4.0 Adoption Factors Towards Manufacturing Sustainability in SMEs: A Hybrid ANN-Fuzzy ISM Framework DOI
Karishma M. Qureshi, Bhavesh G. Mewada, Alok Yadav

и другие.

Опубликована: Апрель 10, 2025

Abstract Manufacturing industries across the globe are undergoing a digital transformation that demands both efficiency and sustainability. Industry 4.0 (I4.0) Lean (L4.0) methodologies have become focal points in these efforts. Despite widespread recognition of benefits integrating L4.0 I4.0, more studies need to address practical challenges this integration, especially key factors influence its successful implementation. Small medium-sized enterprises (SMEs) emerging economies often face significant practices due resource limitations complex operational challenges. This study bridges critical research gap by proposing an integrated framework combines Artificial Neural Networks (ANN) with fuzzy Interpretive Structural Modeling (FISM) identify prioritise success (CSFs) for adoption. A survey 216 manufacturing SMEs was used validate CSFs through Exploratory Factor Analysis (EFA). The ANN analysis revealed Process Factors highest normalised importance (NI) 100%, followed Organizational (NI = 60.46%), Human 58.93%), Technological 43.21%), External 42.13%), Environmental 39.63%). Complementary FISM Cross-Impact Matrix Multiplication Applied Classification (MICMAC) analyses further structured relationships, underscoring roles Change Management, Culture, Waste Reduction, Regulatory Compliance. These findings offer theoretical advancement understanding CSF interactions guidance striving achieve sustainable practices.

Язык: Английский

Analysing Lean 4.0 Adoption Factors Towards Manufacturing Sustainability in SMEs: A Hybrid ANN-Fuzzy ISM Framework DOI
Karishma M. Qureshi, Bhavesh G. Mewada, Alok Yadav

и другие.

Опубликована: Апрель 10, 2025

Abstract Manufacturing industries across the globe are undergoing a digital transformation that demands both efficiency and sustainability. Industry 4.0 (I4.0) Lean (L4.0) methodologies have become focal points in these efforts. Despite widespread recognition of benefits integrating L4.0 I4.0, more studies need to address practical challenges this integration, especially key factors influence its successful implementation. Small medium-sized enterprises (SMEs) emerging economies often face significant practices due resource limitations complex operational challenges. This study bridges critical research gap by proposing an integrated framework combines Artificial Neural Networks (ANN) with fuzzy Interpretive Structural Modeling (FISM) identify prioritise success (CSFs) for adoption. A survey 216 manufacturing SMEs was used validate CSFs through Exploratory Factor Analysis (EFA). The ANN analysis revealed Process Factors highest normalised importance (NI) 100%, followed Organizational (NI = 60.46%), Human 58.93%), Technological 43.21%), External 42.13%), Environmental 39.63%). Complementary FISM Cross-Impact Matrix Multiplication Applied Classification (MICMAC) analyses further structured relationships, underscoring roles Change Management, Culture, Waste Reduction, Regulatory Compliance. These findings offer theoretical advancement understanding CSF interactions guidance striving achieve sustainable practices.

Язык: Английский

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