Review of Health Prognostics and Condition Monitoring of Electronic Components

To meet the specifications of low cost, highly reliable electronic devices, fault diagnosis techniques play an essential role. It is vital to find flaws at an early stage in design, components, material, or manufacturing during the initial phase. This review paper attempts to summarize past development and recent advances in the areas about green manufacturing, maintenance, remaining useful life (RUL) prediction, and like. The current state of the art in reliability research for electronic components, mainly includes failure mechanisms, condition monitoring, and residual lifetime evaluation is explored. A critical analysis of reliability studies to identify their relative merits and usefulness of the outcome of these studies' vis-a-vis green manufacturing is presented. The wide array of statistical, empirical, and intelligent tools and techniques used in the literature are then identified and mapped. Finally, the findings are summarized, and the central research gap is highlighted

Exploring the impacts and contributions of maintenance function for sustainable manufacturing

This investigation studies advanced practitioners of maintenance management and seeks to uncover the related impacts and contributions of best practice maintenance toward sustainable manufacturing operations. This exploratory research conducted a novel empirical analysis focused on maintenance functions in nine manufacturing companies from diverse sectors. The analysis uncovered insights related to the economic, environmental, and social benefits of deeper involvement of maintenance function in plant operations and decision-making. We observed links of maintenance function with product competitiveness and with energy management activities that were unexpected. We confirmed benefits from keeping machinery in good working conditions and restoring promptly good working conditions when an issue happens. The depth of maintenance contribution on each area identified in this study will depend on the operational and business context of the manufacturing company; thus, companies need to reflect on these based on their specific processes, business needs and goals. Ultimately, this work can inspire managers in manufacturing companies to organise maintenance functions strategically toward fostering long-term competitive, responsible and sustainable performance

Intelligent decision support for maintenance: an overview and future trends

The changing nature of manufacturing, in recent years, is evident in industry’s willingness to adopt network-connected intelligent machines in their factory development plans. A number of joint corporate/government initiatives also describe and encourage the adoption of Artificial Intelligence (AI) in the operation and management of production lines. Machine learning will have a significant role to play in the delivery of automated and intelligently supported maintenance decision-making systems. While e-maintenance practice provides aframework for internet-connected operation of maintenance practice the advent of IoT has changed the scale of internetworking and new architectures and tools are needed. While advances in sensors and sensor fusion techniques have been significant in recent years, the possibilities brought by IoT create new challenges in the scale of data and its analysis. The development of audit trail style practice for the collection of data and the provision of acomprehensive framework for its processing, analysis and use should be avaluable contribution in addressing the new data analytics challenges for maintenance created by internet connected devices. This paper proposes that further research should be conducted into audit trail collection of maintenance data, allowing future systems to enable ‘Human in the loop’ interactions

Service-Oriented Computing for intelligent train maintenance

The purpose of this work is to apply the servicization of enterprise information systems in maintenance, particularly in the management of the maintenance process of the component parts of trains. Service Oriented Architecture (SOA) is an architectural approach that permits servicization since it provides a flexible set of design principles used during the modeling practices (abstraction and realization). With a view to supporting the model-driven engineering of software systems, Mode Driven Architecture (MDA) is a design approach delivering a set of guidelines for the configuring of specifications in systems development. Therefore, the combination of these two approaches can be fruitful to address the challenging issues the enterprise information system is facing today. Our study is based on a methodological approach using the MDA models for the automatic generation of web service. The case study concerns a Railways Maintenance Workshop (RMW) at Sidi Bel Abbes (Algeria). Finally, the information system for the management of maintenance of the component parts of passengers and baggage railcars, using the generated solution, is realized and deployed. This software helps to have better management of the RMW by the effective planning of interventions, improve performance by increasing reliability, traceability, and availability of the equipment (parts)

How Kano’s Performance Mediates Perceived SERVQUAL Impact on Kansei

Through Kansei Engineering (KE) methodology in services, the perceived service quality shows a direct impact on Kansei response. In order to strengthen the KE methodology, Kano model is embedded considering the attractive [A] and one-dimensional [O] performances. However, to what extent the Kano performance brings significant impact on Kansei is questionable and has not been explored yet. It is beneficial to measure the effort spent to improve a certain service attribute, considering the Kano performance and its impact on Kansei. This study on logistics services confirms that the Kano’s attractive category [A] shows the highest impact on Kansei (with loading of 0.502), followed by one-dimensional [O] and must-be [M] ones (with loadings of 0.514 and 0.507), respectively. The service provider should prioritize Kano’s [A] service attributes first for improvement. Keywords - Kano, logistics services, Kansei, SERVQUA

Integrated Frameworks for Effective Multi-criteria Decision Making in Reliability Centred Maintenance of Industrial Machines

No abstract availabl

How Blockchain Facilitates the Transition toward Circular Economy in the Food Chain?

Food loss and waste are two of the many problems that modern society is facing. To date, among many solutions, the circular economy is the one prevailing. A successful transition toward a circular economy (CE) requires the food sector to overcome the challenges of today's complex food supply chains such as information asymmetry, poor cooperation among stakeholders, and concerns about food safety. Blockchain, a form of distributed ledger technology, has been progressively gaining traction in supply chains in areas like data management, certifying product provenance and tracking products. Despite its importance, knowledge around the potential of the blockchain technology in facilitating the transition towards a circular economy in the agri-food sector is fragmented. This review provides evidence-based insights into the blockchain implementations in the food supply chains and the implications for CE. Our findings indicated four major areas that blockchain could accelerate CE in the agri-food sector: improving data utility; supply chain management efficacy; enhanced eco-efficiency; and superior traceability

The Application of Industry 4.0 Technologies in Sustainable Logistics: A Systematic Literature Review (2012-2020) to Explore Future Research Opportunities

Nowadays, the market competition becomes increasingly fierce due to diversified customer needs, stringent environmental requirements, and global competitors. One of the most important factors for companies to not only survive but also thrive in today’s competitive market is their logistics performance. This paper aims, through a systematic literature analysis of 115 papers from 2012 to 2020, at presenting quantitative insights and comprehensive overviews of the current and future research landscapes of sustainable logistics in the Industry 4.0 era. The results show that Industry 4.0 technologies provide opportunities for improving the economic efficiency, environmental performance, and social impact of logistics sectors. However, several challenges arise with this technological transformation, i.e., trade-offs among different sustainability indicators, unclear benefits, lifecycle environmental impact, inequity issues, and technology maturity. Thus, to better tackle the current research gaps, future suggestions are given to focus on the balance among different sustainability indicators through the entire lifecycle, human-centric technological transformation, system integration and digital twin, semi-autonomous transportation solutions, smart reverse logistics, and so forth