Special Issue: Industrial Internet of Things-Enabled Digital Servitization

Submission deadline

31st May 2021

Guest Editors

  • Dr. Pai Zheng, Assistant Professor, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, China. Email: (Managing Guest Editor)

  • Prof. Xun Xu, Professor, Department of Mechanical Engineering, The University of Auckland, New Zealand.

  • Prof. Lihui Wang, Professor, Department of Production Engineering, KTH Royal Institute of Technology, Stockholm 110 44, Sweden.

About the issue

The rapid implementation of the third-wave of IT innovation (e.g. smart, connected products, Internet-of-Things (IoT)) and the fourth Industrial Revolution (e.g. advanced operation technologies (OTs), Cyber-Physical Systems) have enabled the prevailing industrial digital transformation (i.e. digitalization), where OT and IT are integrated in an Industrial IoT environment [1]. Meanwhile, ensured by the advanced digital capabilities (i.e. networking, digitalization and smartness) of Industrial IoT, manufacturing companies are ever increasingly adopting service-oriented business models (i.e. servitization), to offer smart product-service bundles both internally to the industrial engineers/managers and externally to the customers [2]. Such convergence of both digitalization and servitization coined an emerging paradigm, digital servitization [3]. In this paradigm, software-as-a-service plays a dominant role and often replaces the hardware components in a “software-defined X” manner, mainly in fourfold: 1) From physical asset perspectives, digitalized services are generated based on the smart, connected products to perform values in a more flexible manner [4]; 2) From networking perspective, software-defined network together with microservice architecture enables the rapid, frequent, and reliable delivery of large, complex service applications [5]; 3) From digitalization perspective, virtualized products or their digital twins in a software environment can offer types of digitalized services seamlessly (e.g. remote monitoring) [6]; 4) From smartness perspectives, both the cutting-edge knowledge graph and deep learning techniques, as the industrial AI [7], enable the smart functionalities in the digitalized services. To this end, as an emerging and promising research topic, this Special issue aims to present the state-of-the-art and methodologies, tools, systems and cases to enable the readiness and realization of Industrial IoT-enabled digital servitization.


  • Industrial Smart Product-Service Systems

  • Industrial AI-enabled manufacturing servitization

  • Digital Twin-enabled industrial services

  • Industrial big data analytics for digitalized services

  • Microservice-based industrial service management

  • Industrial IoT implementations for digital servitization

  • Case studies on industrial digital servitization

  • Other methodologies, tools and systems towards industrial digital servitization


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  2. P. Zheng, Z. Wang, C.-H. Chen, L. Pheng Khoo, A survey of smart product-service systems: Key aspects, challenges and future perspectives, Adv. Eng. Informatics. 42 (2019) 100973. doi:10.1016/j.aei.2019.100973.

  3. B. Tronvoll, A. Sklyar, D. Sörhammar, C. Kowalkowski, Transformational shifts through digital servitization, Ind. Mark. Manag. 89 (2020) 293–305. doi:10.1016/j.indmarman.2020.02.005.

  4. P. Zheng, T.-J. Lin, C.-H. Chen, X. Xu, A systematic design approach for service innovation of smart product-service systems, J. Clean. Prod. 201 (2018) 657–667. doi:10.1016/j.jclepro.2018.08.101.

  5. A. Theorin, K. Bengtsson, J. Provost, M. Lieder, T. Lundholm, B. Lennartson, A. Theorin, K. Bengtsson, J. Provost, M. Lieder, T. Lundholm, B. Lennartson, An event-driven manufacturing information system architecture for Industry 4.0, Int. J. Prod. Res. 7543 (2017) 1–15. doi:10.1080/00207543.2016.1201604.

  6. M. Ardolino, M. Rapaccini, N. Saccani, P. Gaiardelli, G. Crespi, C. Ruggeri, The role of digital technologies for the service transformation of industrial companies, Int. J. Prod. Res. 56 (2018) 2116–2132. doi:10.1080/00207543.2017.1324224.

  7. J. Lee, H. Davari, J. Singh, V. Pandhare, Industrial Artificial Intelligence for industry 4 . 0-based manufacturing systems, Manuf. Lett. 18 (2018) 20–23. doi:10.1016/j.mfglet.2018.09.002.