Call for Papers: Special Issue on Intelligent Asset Management, Industry 4.0 and Beyond

Assets, core or non-core, are essential constituents of any business enterprises. These assets generally contribute through their roles as factors of production. In the information age, digital and information driven assets are coming up as major contributors. Industrial assets have a number of systems and subsystems, hardware, sensors and software including rotating and sliding parts. It is well known that failure mechanism and degradation behaviour of these parts and subsystems influences life of those systems. Sector specific assets do have specific treatment, but have the scope for standard measurements to ensure continued lifecycles.

Emergence of digital and disruptive supply chains have showcased may bets practices globally. These assets need transformative approach for sustainable lifecycle centric maintenance. Intelligent maintenance through systematic and systemic approaches have a better leverage in optimizing the cost, productivity and returns on investment. This approach of optimization needs competence and informed decisions of maintenance, reliability and asset management professionals. It is imperative that such competencies of managers need to reflect in the machine behaviour, performance of overall enterprise systems. But there are issues and challenges in understanding these by maintenance, reliability and asset management professionals.

In particular, information driven decisions of asset lifecycle management do have support of appropriate and innovative technologies including industry 4.0. Industry 4.0 has comprehensive association with emerging computing environment including IoT and IIoT, Machine learning, Artificial Intelligence, augmented and virtual reality (AR/VR); Cloud, Fog and Edge Computing; to generate, access and analyze the machine behaviour and enhance predictability and traceability of machine behaviour. The related digital infrastructure has real-time and online interfaces with machines allowing efficient processing of data locally and close to the source. Industry 4.0 has created opportunities for the industrial sector to create assets and related infrastructure to benefit form digital twins and threads to make fast and confident decisions — and to create best-in-class products through efficient production, managing the factory and plant lifecycles.

The emerging technologies, systems and processes to support intelligent asset management activities by merging Operational Technology (OT) and Information Technology (IT). This merger offers opportunities for creating efficient and predictive optimization models for predictive maintenance, smart designing and creating autonomous systems, condition monitoring and quality management.

This special issue of the journal seeks to bring a comprehensive view on the intelligent asset management and maintenance. This issue is primarily interested in knowing what makes intelligent asset management and maintenance approaches more responsive to the sectoral demand and what should be done to make managers involved more informed. The issue shall in particular encourage submissions to the ICMIAM 2022, thrugh not limited to, with the unit of analysis central to the theme related to industry 4.0, intelligent assets, smart maintenance of asset lifecycles. The articles which are strong in interdisciplinary, theoretical, conceptual and empirical research shall be more acceptable. The intended outcome of the articles should primarily lead to contribute to the extant literature on assort management, and intelligent maintenance of asset lifecycles. The outcome of the research articles may also contribute to policies related to quality standards and protocols. The related areas considered for inclusion in the special issue are as follows, but are not limited to:

  • Asset Management (AM), ISO 55000/55001 and related standards certification and beyond,
  • Intelligent management of critical assets, e.g., water, power, smart grids, energy management, intelligent traffic system, rural asset management, regulations and compliance environment, Internet of Things (IoT),
  • Industry 4.0 in AM, analytics and applications in AM, risk management, 
  • Cyber Physical Systems, process modelling, digital twins, machine learning in AM,
  • AM for oil and gas industry,
  • Bat environment asset management, low cost sensing for asset management,
  • New advancements in reliability, maintenance engineering, preventive and predictive maintenance,
  • Life-cycle cost analysis, remaining useful life analysis,
  • Tribology, Artificial Intelligence (AI) and IoT in RAM,
  • Condition Monitoring (CM), Condition Based Maintenance (CBM) and efficiency, RAM in Industry 4.0, resilience, rolling stock maintenance, reliability and resilience, risk and performance assessment, risk-based maintenance,
  • Safety analytics, occupational health, integrated safety management systems, Prevention through Design (PtD)
  • Probabilistic risk assessment & uncertainty analysis,
  • Human factors & cognitive ergonomics, process safety, workplace safety, safety economics,
  • Industry 4.0 technologies in safety management,
  • Digital asset management, asset integrity, cyber security challenges and risk to management,
  • AI and ML applications in safety & security,
  • Smart transportation and logistics,
  • Cyber Supply Chain Risk Management (CSRM)


Guest Editors:
Professor Raghuvir Pai,
Manipal Academy of Higher Education, India
Dr. Gopinath Chattopadhyay, Federation University, Australia
Professor Harekrishna Misra, Institute of Rural Management Anand, India
 

Submissions Process:
Primarily, full papers submitted to the ICMIAM2022, shall be considered for further reviews to be accepted for publications in the special issue of the journal. But this process is not limited to ICMIAM2022. Authors who did not submit to ICMIAM2022, are invited to submit their original work as well.
Please follow the instructions of the journal while preparing your manuscript. A guide for authors can be found at: https://www.springer.com/journal/13198/submission-guidelines
Please submit your manuscript through the Journal’s homepage at https://www.springer.com/journal/13198
For questions, please contact: raghuvir.pai@manipal.edu or hkmishra@irma.ac.in


Time Line:
Submission of manuscript: 28 February 2023
Acceptance notification: 15 May 2023
Publication: 31 August 2023

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