Adaptive Manufacturing for SMEs : Digital Retrofitting, Predictive Maintenance, and Servitisation Strategies
Language: English
Published by Institution Of Engineering & Technology Nov 2026, 2026
- Hardcover
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Neuware - Small and medium sized enterprises (SMEs) face growing pressure to modernise in response to volatile market demand, increasing product complexity, and rapid technological change. At the same time, they are expected to improve sustainability performance, strengthen data transparency, and respond more quickly to operational disruption. Although Industry 4.0 has introduced significant opportunities through cyber-physical integration, connectivity, and data-driven decision-making, many SMEs continue to struggle with implementation. Financial constraints, legacy equipment, limited internal capabilities, and the risks associated with poorly sequenced adoption often prevent transformation from progressing beyond isolated initiatives. Flexible and responsive manufacturing systems (FRMS) represent the performance objective of this transition, but for SMEs the central challenge is not simply adopting advanced technologies; it is doing so through a structured and feasible pathway. This book positions that pathway as an incremental and decision-supported transformation process tailored to the operational realities of SMEs. To address this challenge, the book proposes a unified and practical transformation framework built around three interconnected strategies. The first is digital retrofitting, which enables SMEs to incrementally upgrade legacy systems through Industry 4.0 technologies without requiring full-scale replacement. The second is maintenance strategy selection, which applies structured multi-criteria decision-making methods to improve operational reliability, responsiveness, and asset resilience within dynamic manufacturing environments. The third is digital servitisation, which supports the transition from product-based offerings to service-oriented business models capable of generating new value from digitally enabled operations. Taken together, these strategies form a coherent transformation logic in which retrofitting generates data, maintenance strategy converts that data into resilience, and servitisation leverages that resilience for strategic growth. The book also addresses broader themes associated with industry 5.0, including sustainability, organisational readiness, cybersecurity, and human-centred industrial transformation. The book will be key reading for graduate students, educators, and academic researchers in industrial engineering, manufacturing systems and digital transformation.…
Seller Inventory # 9781807050160
- Title
- Adaptive Manufacturing for SMEs : Digital Retrofitting, Predictive Maintenance, and Servitisation Strategies
- Author
- Jiahong Li
- Publisher
- Institution Of Engineering & Technology Nov 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 1807050165
- ISBN 13
- 9781807050160
- Item weight
- 558 grams
- Dimensions
- 234x156x16 mm
Small and medium sized enterprises (SMEs) face growing pressure to modernise in response to volatile market demand, increasing product complexity, and rapid technological change. At the same time, they are expected to improve sustainability performance, strengthen data transparency, and respond more quickly to operational disruption. Although Industry 4.0 has introduced significant opportunities through cyber-physical integration, connectivity, and data-driven decision-making, many SMEs continue to struggle with implementation. Financial constraints, legacy equipment, limited internal capabilities, and the risks associated with poorly sequenced adoption often prevent transformation from progressing beyond isolated initiatives. Flexible and responsive manufacturing systems (FRMS) represent the performance objective of this transition, but for SMEs the central challenge is not simply adopting advanced technologies; it is doing so through a structured and feasible pathway. This book positions that pathway as an incremental and decision-supported transformation process tailored to the operational realities of SMEs.
To address this challenge, the book proposes a unified and practical transformation framework built around three interconnected strategies. The first is digital retrofitting, which enables SMEs to incrementally upgrade legacy systems through Industry 4.0 technologies without requiring full-scale replacement. The second is maintenance strategy selection, which applies structured multi-criteria decision-making methods to improve operational reliability, responsiveness, and asset resilience within dynamic manufacturing environments. The third is digital servitisation, which supports the transition from product-based offerings to service-oriented business models capable of generating new value from digitally enabled operations. Taken together, these strategies form a coherent transformation logic in which retrofitting generates data, maintenance strategy converts that data into resilience, and servitisation leverages that resilience for strategic growth. The book also addresses broader themes associated with industry 5.0, including sustainability, organisational readiness, cybersecurity, and human-centred industrial transformation.
The book will be key reading for graduate students, educators, and academic researchers in industrial engineering, manufacturing systems and digital transformation.
"Synopsis" may belong to another edition of this title.
About the Author
Jelena Milisavljevic-Syed is a senior lecturer in manufacturing systems at the Sustainable Manufacturing Systems Centre, Cranfield University, UK. Jelena is a thought leader in designing evolving cyber-physical-social systems and AI-supported decision-making for sustainable manufacturing and services. Her work bridges mechanical, control and industrial engineering to advance Industry 4.0/5.0 through adaptable, concurrent and human-centric design. She is a member of ASME, ASEE, BFWG, MIET, IEEE and the Design Society.
Abdulrahman Alqoud is head of the Research and Studies Department at a Confidential Government entity in Riyadh, Saudi Arabia. Dr. Alqoud focuses on driving strategic insights and research initiatives to enhance decision-making. Leveraging a PhD in Engineering and certifications such as PMP, C-SBP and C-KPI, he emphasises delivering actionable solutions aligned with organisational goals. With over a decade of experience across academia and industry, his expertise spans Industry 4.0, decision-making and the modernisation of manufacturing systems.
Jiahong Li is a postdoctoral researcher at the Binjiang Institute of Hangzhou Dianzi University, China. He obtained his PhD from Cranfield University, with research focusing on predictive maintenance technologies, decision-making, intelligent enterprise transformation road maps and sustainable reverse supply chains. His current research explores the capability boundaries of AI agents in constrained industrial scenarios and the development of interpretable geological hazard prediction models. Dr. Li's work aims to advance trustworthy and practical AI applications for industrial intelligence and risk prediction.
Mohammed Khan is a Business Analyst at Arcadis, UK, supporting major infrastructure and transport programmes through business analysis, process improvement and project management. He holds a PhD in Engineering Management from Cranfield University, where his research focused on Business Model Innovation, specifically Digital Servitisation and the development of maturity models for manufacturing SMEs. Digital servitisation combines servitisation with emerging digital technologies to enable new and improved services to be delivered more effectively, creating value through technologies such as the Internet of Things, data analytics, artificial intelligence and cloud computing. His research developed a descriptive maturity model to assess servitisation maturity, a prescriptive maturity model providing improvement recommendations, and a DEMATEL-ISM relationship analysis to identify and prioritise relationships between key servitisation factors. His interests span digital transformation, servitisation, maturity models and operational improvement.
"About the title" may belong to another edition of this title.
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