Alberto Martinetti

Background: The convergence of information technology (IT) and operational technology (OT) in physical assets offers significant benefits but also presents challenges, particularly in aligning the lifecycles of IT and physical assets. A review of 24 serious games related to asset management and rail revealed a research gap in synchronising the separate IT and OT lifecycles, highlighting the need for a serious game specifically addressing this issue. Consequently, a serious game has been developed to educate professionals on lifecycle alignment within IT/OT convergence. Aim: This study aims to iteratively design and evaluate an artefact, the IT/OT Railway Game, to address IT/OT convergence challenges, with an emphasis on understanding the potential of IT/OT lifecycle alignment, assessing strategies, and applying them in a simulated railway context. Method: The game was developed using the Design Science Research Methodology (DSRM) and evaluated using the Framework for Evaluation in Design Science (FEDS). Four design iterations and three evaluation cycles were conducted, with 118 participants across 14 sessions. The evaluation focused on playability, game mechanics, and achievement of intended learning outcomes. Results: The study designed and evaluated a serious game to educate practitioners on IT/OT lifecycle alignment. A three-step evaluation assesses playability, game mechanics, and learning outcomes to measure learning effectiveness. Findings show a measurable improvement in participants’ knowledge and ability to apply IT/OT lifecycle alignment strategies in practice. Furthermore, the study suggests that participatory design can be used not only in serious game development but also as a learning strategy. Conclusion: The IT/OT Railway Game demonstrates the potential of serious games as practical tools for addressing sociotechnical challenges, such as IT/OT lifecycle alignment. While developed for the railway industry, its principles are transferable to other sectors. Future research should explore its adaptability and effectiveness in broader industrial and academic contexts.

Recently, the global landscape of public transportation has witnessed a transformative shift towards sustainable and efficient modes of mobility, with particular emphasis on electric vehicles (EVs) and their integration into industrial applications. The mining industry, including the underground mining of the mineral resources sector is following this trend. However, underground mines are critical environments and the adoption of EVs needs to be carefully analysed. This study investigates the associated hazards and risks of adopting EVs (such as dumpers and loaders) focusing on the swapping battery operations. First, current hazards related to battery swapping are identified—21 in total, occurring in 25 instances. After, risks are assessed and associated with specific hazards. Finally, possible measures and solutions for reducing the impacts of these risks on the performance of the EVs are offered.

Maintenance and troubleshooting contribute to the overall economic efficiency of rolling stock throughout its lifecycle, yet these activities are resource-intensive and incur significant costs. In the era of Industry 4.0 implementation, the escalating complexity of rolling stock poses challenges in troubleshooting and maintenance decision-making. Recognizing this, there is a pressing need for a structured solution that empowers maintenance operators with tools for effective organization, analysis, and real-time presentation of rolling stock system failures, facilitating streamlined troubleshooting and maintenance guidance. Functional blocks, providing systematic structuring of processes, and Augmented Reality (AR), offering enhanced visualization and decision support, emerge as solutions to navigate and streamline these challenges in the evolving industrial landscape. The intricacies of existing fault-diagnosing systems, particularly interconnected transmission of functional blocks for troubleshooting and AR integration, lack detailed explanation, hindering effective solutions. To address these challenges, this work leverages AR for troubleshooting rolling stock failures, introducing functional blocks to (1) collect maintenance and fault data, (2) integrate maintenance information based on failure diagnostics and maintenance patterns, and (3) deliver this information to maintenance operators through AR. The developed Sequential Augmented Reality Assist (SARA) method, demonstrates the sequential implementation of AR troubleshooting functional blocks in an industrial context, providing a systematic solution to the complexities involved.

Purpose: Providing a comprehensive literature review to consolidate existing knowledge, advancements and future directions in the field. By synthesizing the state of research, this work enhances the understanding of Prescriptive Maintenance (PsM) methodologies, applications and potential benefits to assist researchers in identifying fruitful avenues for further investigation, and guide practitioners in implementing PsM strategies to improve maintenance outcomes in their industries.Design/methodology/approach: Through a systematic, multistage, specialists audited analysis of peer-reviewed articles, conference papers, books sections, thesis, magazines and industry reports, this work provides a literature review analyzing PsM origins, definitions, enablers, outputs and emerging trends.Findings: PsM concept evolved in recent years representing a shift from traditional maintenance, leveraging prescriptive analytics, data-driven modeling and optimization techniques to enable proactive decision-making and optimal resource allocation. By harnessing PsM, organizations can anticipate and mitigate failures, optimize maintenance actions and enhance asset reliability.Research limitations/implications: Existing literature points out the following challenges for PsM implementation: prescriptive analytics improvement, scalability of frameworks, development of prototypes, processes integration; PsM maturity assessment; asset health prognostics assertiveness, real-time data availability and adoption of cost functions to grasp business and environmental, social and governance (ESG) costs.Practical implications: Optimal deployment of resources with little or no human intervention in the maintenance decision process and the creation of new services improving reliability and operational performance.Social implications: By optimizing maintenance, not only direct costs diminish but also environmental, social and governance (ESG) related costs decrease by reducing energy waste during equipment’s operating phase, assessing the ecological impact of providing maintenance to operators and line maintenance stakeholders and, consequently, minimizing or even eliminating harmful effects on the environment and the human.Originality/value: Work consolidating existing PsM-related knowledge and indicating future work is a gap in the literature. This paper fills this gap.

This paper analyses the planning of operation for underground mining trucks powered by Lithium-ion batteries. Trucks supplied by the companies Epiroc and Sandvik are used as examples, comparing their characteristics with equivalent diesel-engine models. These trucks have similar payload capacities and dimensions, but significant differences in available energy, demonstrating that battery-powered trucks have substantially lower autonomy. The paper describes a method for estimating the autonomy of battery-powered trucks, considering motor efficiency, energy losses, and regenerative braking. A procedure is presented for determining the energy consumption for truck movement along a known route, considering the total resistance. It is demonstrated that the lower available energy of battery-powered trucks is a major factor necessitating a different approach to planning their operation in underground mining.

The convergence of information technology (IT) with operational technology (OT), within physical assets can enhance performance but also presents challenges due to higher performance expectations and increased complexity. This study reviews the research that has been conducted to address these convergence and integration challenges by using an in-depth review of academic papers, industry standards, and reports published during the last three decades. Our investigation reveals that about a third of the existing IT/OT research really focuses on the convergence of IT/OT, by including organizational aspects into the study. Three key research domains were identified: maintenance, cybersecurity, and configuration management. The introduction of IT in assets has necessitated changes in maintenance practices, as current approaches are not suitable for these converged lifecycles. Cybersecurity risks have received the most attention in the IT/OT domain. The integration requires the management of these changes; therefore, configuration management has become more crucial than it already is to keep of actual configuration of both the IT and the OT parts of the asset. This research hereby provides relevant observations for practitioners in industry and academics in the IT and the physical asset management domain. The identified gaps suggest the need for tools and methods to better align IT and OT standards, policies, tools, processes, and people throughout the lifecycle of an IT/OT converged physical asset in a sustainable way.

Wearable sensors for psychophysiological monitoring are becoming increasingly mainstream in safety critical contexts. They offer a novel solution to capturing sub-optimal states and can help identify when workers in safety critical environments are suffering from states such as fatigue and stress. However, sensors can differ widely in their application, design, usability, and measurement and there is a lack of guidance on what should be prioritized or considered when selecting a sensor. The paper aims to highlight which concepts are important when creating or selecting a device regarding the optimization of both measurement and usability. Additionally, the paper discusses how design choices can enhance both the usability and measurement capabilities of wearable sensors. The hopes are that this paper will provide researchers and practitioners in human factors and related fields with a framework to help guide them in building and selecting wearable sensors that are well suited for deployment in safety critical contexts.