1,721,235 research outputs found
Feedback-Based Algorithm for Negotiating Human Preferences and Making Risk Assessment Decisions
No full textWork equipment risk assessment is essential for guaranteeing health and
safety of workers in industrial contexts.Many and varied hazards are involved in the
use of equipment,which have to be periodically subject to thorough controls required
by law. This research proposes a novel hybrid decision-making framework aimed at
integrating flexible negotiation on human preferences. This goal will be achieved by
establishing effective feedback exchanges with expert(s) familiarwith the field of risk
and maintenance of work equipment. We extend a previous research that proposed
a user-friendly negotiation procedure to increase consistency of judgments provided
by experts about relevant risk factors. The proposed algorithm has been built within
the framework of the Analytic Hierarchy Process (AHP), a widely popular Multi-
Criteria Decision-Making (MCDM) method. After negotiation of the evaluations
of preference with experts to weight the main risk factors of interest, the obtained
priorities will be used as a part of the body of input data required for a further
MCDM application. This application will use the ELimination Et Choix Traduisant
la REalité (ELECTRE) I method as a structured way for planning and implementing
maintenance interventions. A real world application will lead towards the selection
of the work equipment with associated higher level of risk under diverse risk factors,
differently weighted by means of the negotiation process. Apart from the industrial
field of reference, our theoretical framework can be applied to solve a wide range of
practical decision-making problem
PageRank vs. ANP: A Comparative Analysis for Prioritizing Maintenance Activities in Industrial Water Distribution Systems.
Full text linkThis paper proposes the implementation of the PageRank algorithm as an alternative to the Analytic Network Process (ANP) for prioritizing maintenance activities in water distribution systems. We demonstrate the comparable performance of the PageRank algorithm to the ANP by comparing the results obtained from a previous conference paper that utilized the ANP for decision-making in sustainability-related problems involving water distribution systems feeding manufacturing industries. The ANP is commonly used for decision-making
in complex systems, but has limitations such as subjective weighting and handling large datasets. In contrast, the PageRank algorithm, originally designed for web page ranking, offers a scalable and objective approach for analyzing complex systems. To showcase the effectiveness of the PageRank algorithm, we compare the results obtained from the ANP in our previous conference paper with the PageRank algorithm. Our findings reveal that the PageRank algorithm yields identical results to the ANP, while addressing its limitations. The results of this study demonstrate the viability and effectiveness of the PageRank algorithm in achieving identical outcomes as the ANP, with potential advantages in scalability and objectivity. The proposed implementation of the PageRank algorithm as an alternative to the ANP offers a
promising approach for prioritizing maintenance activities in water distribution systems, as similar considerations can be extended to any sector of activity
Digital Transformation in Maintenance Management
No full textThe relationship between technology and maintenance is mutually beneficial since technology is continuously improving with consequent substantial advancements in the field of maintenance. Maintenance management may be effectively modernized through digitalization. Developing advanced technologies promotes indeed the possibility of maintaining a competitive and long-term position in this field. Digitalization is consistently transforming organizations by allowing them to use suitable technologies for collecting data automatically. Various equipment and components are nowadays capable of collecting their operating data over an extended period, which may yield a plethora of intriguing insights employing digitalization. However, to achieve effective prediction of any type of failure, maintenance management requires several smart technologies which offer wider applications for digitalization, including artificial intelligence (AI), big data, Internet of Things (IoT), digital twins, novel sensor technologies, data collection and distribution from various smart sensors, and investigating a lot of data utilizing machine/deep learning. Smart sensors facilitate the collection of large amounts of data to be effectively evaluated for enabling maintenance management and decision-making of more complex systems. The focus of this study is to investigate which type of data should have to be digitally collected for effectively implementing predictive maintenance policies. This can be identified by studying the latest trends of digitalization in maintenance management. Moreover, this study aims to elaborate a decision-making model supporting the implementation of maintenance management policies. This will be done by first identifying critical factors for maintenance management and secondly analyzing their mutual relationships in a structured way. In detail, a Fuzzy Cognitive Map (FCM) will be built to model such relations, in order to identify those factors having a greater influence on all the other ones. In this direction, this study may have positive impacts on economic, social, and environmental factors
Managerial decision making for complex service systems Optimization
No full textThe present paper deals with managerial decisions for Predictive Maintenance (PrdM) of complex service systems. We propose a Multi-Criteria Decision-Making (MCDM) approach aimed at sorting those failure modes potentially involving critical components into risk classes for interventions prioritisation and maintenance control. In this context, the sorting technique ELimination Et Choix Traduisant la REalité (ELECTRE) TRI is applied to support in finding the root causes that can be eliminated for failure prevention and/or minimization. This methodology presents the advantage to not rely on comparisons (as well as on their transitivity) between pairs of elements, simplifying computations for complex systems. To be sorted, decision elements are indeed compared with single reference profiles and the final assignment may constitute a valid alternative to the traditional ranking of failures achievable by other MCDM techniques and, among others, consistency-based methodologies. The proposed approach will be eventually applied to a case study from the industrial reality
How sustainability factors influence maintenance of water distribution systems feeding manufacturing industries
Full text linkThis work aims to analyse the role played by relevant sustainability factors towards the implementation of maintenance interventions
in the manufacturing industrial sector. In this context, we focus on industrial water distribution systems, on whose effective work
depends the functioning of core plants as well as general industrial facilities. In detail, we propose aMulti-Criteria Decision-Making
(MCDM) application based on the use of the Analytic Network Process (ANP) as amethodological way to prioritise maintenance
interventions while considering the influence of some of themost relevant sustainability factors identified in literature. The main
advantage of such an approach consists in the elaboration of a flexible maintenance procedure for companies based on a well-known
and reliablemulti-criteria application. The novelty of our work refers to the development of a structured link between sustainability
factors and maintenance management of industrial water distribution systems, something that is fundamental in manufacturing but
also in other fields of application
An integrated methodological approach for optimising complex systems subjected to predictive maintenance
No full textThe present paper addresses the relevant topic of maintenance management, widely recognised as a fundamental issue involving complex engineering systems and leading companies towards the optimisation of their assets while pursuing cost efficiency. With this regard, our research aims to provide companies with a hybrid methodological approach based on Multi-Criteria Decision-Making (MCDM) capable to deal with the main failures potentially involving complex systems subjected to predictive maintenance. Such an approach is going to be integrated within the framework of traditional Failure Mode Effects and Criticality Analysis (FMECA), whose strengths and weaknesses are considered. In particular, the ELimination Et Choix Traduisant la REalité (ELECTRE) TRI is suggested to sort failure modes into risk priority classes while the Decision Making Trial and Evaluation Laboratory (DEMATEL) is proposed to highlight the most influencing failures within each risk class. The approach is applied to a real service system, whose critical components are monitored by sensors and subjected to predictive maintenance. Final results clearly demonstrate as highlighting the elements impacting the occurrence of other failures within specific risk classes is a significant driver towards the implementation of effective maintenance, maximising the whole level of performance of the analysed system over its lifecycle
Flexible negotiation process to adhere to human preferences; A case of work equipment risk assessment
No full textMaking structured and reliable decisions on relevant business problems often requires expert assistance. In decision making practice, experts are frequently required to pairwise compare elements to support the decision made. This paper proposes a user-friendly negotiation procedure to establish an effective feedback relation with experts to globally increase the consistency of their pairwise comparisons judgments, where necessary. To this aim, we develop a flexible tool, which makes use of an algebraic consistency-improving algorithm and a sensitivity analysis technique to identify which judgments contribute most to inconsistency. The framework pursues friendliness for the involved decision makers, as they are asked to reconsider only a few a priori judgments, instead of rethinking the entire set of previously elicited comparisons. A real-world case study on risk assessment in industry is implemented to demonstrate the practical applicability of the proposed approach
Balancing sustainability and occupational health in airport operations
No full textThe interconnections among sustainability factors in airports
and their effects on occupational health are of paramount importance.
Not only are airports key drivers of economic growth, employment, and
tourism, but they also have significant and far-reaching environmental
and social impacts. Therefore, achieving sustainable airport operations
requires a delicate balance between economic, environmental, and social
factors. To this end, collaboration among stakeholders is crucial for de veloping innovative solutions that protect workers’ health and promote
sustainability. Mathematical models play a key role in decision-making
and policy development to ensure sustainable airports while safeguarding
workers’ well-being. In this context, this contribution proposes the use
of Fuzzy Cognitive Maps (FCMs) to evaluate the most significant Occu pational Stress Risks (OSRs) for an Italian airport. The analysis aims to
assess the subset of OSRs whose potential occurrence may likely impact
the occurrence of other related OSRs. The study concludes by proposing
potential prevention/reduction strategies for each of these OSRs
A Feasible Framework for Maintenance Digitalization
Full text linkThe entire industry is changing as a result of new developments in digital technology,
and maintenance management is a crucial procedure that may take advantage of the opportunities
brought about by industrial digitalization. To support digital innovation in maintenance management,
this study intends to meet the cutting-edge necessity of addressing a transformation strategy in
industrial contexts. Setting up a customized pathway with adequate methodologies, digitalization
tools, and collaboration between the several stakeholders involved in the maintenance environment
is the first step in this process. The results of a previous conference contribution, which revealed
important digitalization variables in maintenance management, served as the foundation for the
research approach herein suggested. We lead a thorough assessment of the literature to categorize
the potential benefits and challenges in maintenance digitalization to be assessed in conjunction
with the important digitalization aspects previously stated. As a starting point for maintenance
management transformation, we offer a feasible framework for maintenance digitalization that
businesses operating in a variety of industries can use. As industrial processes and machines have
become more sophisticated and complex and as there is a growing desire for more secure, dependable,
and safe systems, we see that this transition needs to be tailored to the specific application context
A multifunctional plant for a sustainable reuse of marble waste toward circular economy
No full textThe marble processing cycle involves the production of large quantities of wastes whose disposal represents an economic and environmental concern for marble companies due to the difficulty of identifying suitable landfills and the high transfer costs. In this context, the design of a sustainable industrial plant that allows the reuse of the calcium carbonate (CaCO3) contained in the marble waste is extremely challenging. With this recognition, the main industrial applications of CaCO3 are firstly analyzed in the present work to identify the physical–chemical properties required to CaCO3 in these contexts. Later, different plant solutions are suggested to recover CaCO3 from marble sludge in order to allow its use in industrial applications. The designed industrial plant includes an energy efficient drying phase, which exploits the thermal waste of the exhaust gases produced in a cogeneration section, and a subsequent milling phase. Since marble wastes currently constitute an economic burden for companies and an environmental emergency for the Public Administration, the performed technical–economic analysis shows that its recovery may represent an opportunity of sustainable development for the marble sector
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