Developing Management Diagnostic Tool to Determine Advance Maintenance Management Strategies for Nigerian SMEs Based Upon Industry 4.0 Techniques
Aliyu, Abbas (2025) Developing Management Diagnostic Tool to Determine Advance Maintenance Management Strategies for Nigerian SMEs Based Upon Industry 4.0 Techniques. Doctoral thesis, The University of Sunderland.
Item Type: | Thesis (Doctoral) |
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Abstract
Background: The integration of Industry 4.0 technologies in maintenance management presents significant opportunities for improving operational efficiency in Nigerian manufacturing Small and Medium-sized Enterprises (SMEs). However, these enterprises face unique challenges in adopting advanced maintenance strategies, including infrastructure limitations, resource constraints, skills gaps, and cultural barriers. This study addresses the critical need for a systematic approach to implementing Industry 4.0-enabled maintenance management practices in Nigerian manufacturing SMEs.
Methods: The research employed a qualitative multiple case study approach, conducting in-depth semi-structured interviews with fifteen maintenance managers across diverse manufacturing sectors in Nigeria. Data collection included interviews, document analysis, and direct observations. The study utilized systematic thematic analysis to examine Industry 4.0 readiness dimensions, implementation barriers, and potential impacts on operational performance. Expert validation from twelve industry professionals informed the development and refinement of the Advanced Maintenance 4.0 Implementation Framework (AMIF).
Findings: The analysis identified seven critical dimensions of Industry 4.0 readiness: technological infrastructure readiness, workforce digital readiness, financial resource readiness, leadership commitment, infrastructure support, organizational culture, and knowledge infrastructure. Five interconnected barrier categories emerged: technical implementation barriers, human capital barriers, environmental barriers, organizational barriers, and market-related barriers. The research revealed potential for significant operational improvements including 25-30% enhancement in Overall Equipment Effectiveness (OEE).
Framework Development: The study developed the AMIF framework, providing a structured three-tier implementation approach for Nigerian manufacturing SMEs: Infrastructure Development, Capability Enhancement, and Systems Integration. Each tier incorporates specific implementation strategies tailored to address local challenges including infrastructure constraints, resource limitations, and capability development needs. The framework emphasizes progressive capability building, contextual adaptation, and sustainable advancement while addressing the unique operational realities of Nigerian manufacturing environments.
Implications: This research contributes to both theoretical understanding and practical implementation of Industry 4.0 technologies in maintenance management within developing economic contexts. The AMIF framework offers systematic pathways for Nigerian manufacturing SMEs to enhance maintenance practices while addressing resource constraints and infrastructure limitations. The findings provide valuable insights for policymakers in developing supportive frameworks, industry practitioners in planning technology adoption strategies, and researchers investigating digital transformation in resource-constrained environments.
Conclusion: The study demonstrates that successful Industry 4.0 adoption in Nigerian manufacturing SMEs requires comprehensive approaches addressing technical, organizational, and environmental factors simultaneously. The AMIF framework bridges the gap between theoretical potential and practical implementation requirements, providing contextually appropriate guidance for progressive capability development.
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Depositing User: Delphine Doucet |
Identifiers
Item ID: 19503 |
URI: http://sure.sunderland.ac.uk/id/eprint/19503 |
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Catalogue record
Date Deposited: 22 Oct 2025 09:44 |
Last Modified: 22 Oct 2025 15:20 |
Author: | Abbas Aliyu |
Author: | Abbas Aliyu |
Thesis advisor: | David Baglee |
Thesis advisor: | Derek Dixon |
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