How sustainability factors influence maintenance of water distribution systems feeding manufacturing industries

This 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

A Feasible Framework for Maintenance Digitalization

The 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

Improved pairwise comparison transitivity using strategically selected reduced information

The research is financially supported by the Czech Science Foundation, Grant No. 19-06569S.Benítez López, J.; Carpitella, S.; Izquierdo Sebastián, J. (2021). Improved pairwise comparison transitivity using strategically selected reduced information. Universitat Politècnica de València. 106-110. http://hdl.handle.net/10251/182210S10611

Managing expert knowledge in water network expansion project implementation

The implementation of expansion projects of water networks supplying growing cities is deemed to be a complex decision-making problem involving both technical aspects and expert knowledge. Management and control processes must rely on experts in the field whose knowhow must be coupled with techniques able to deal with the natural subjectivity that affects input evaluations. Given the presence of many decision-making elements, the choice of proper hydraulic technical parameters may be linked to the main aspects of analysis requiring formal expert evaluation. In this contribution, the simulation of hydraulic indicators is integrated with a multi-criteria approach able to eventually determine those areas of a water network through which organising the expansion may be more beneficial. The software EPAnet 2.0 is first used for hydraulic simulations, whereas the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) will eventually rank network's nodes. A case study is solved to demonstrate the applicability and effectiveness of the proposed approach. Copyright (C) 2021 The Authors

District metered area design through multicriteria and multiobjective optimization

The design of district metered areas (DMA) in potable water supply systems is of paramount importance for water utilities to properly manage their systems. Concomitant to their main objective, namely, to deliver quality water to consumers, the benefits include leakage reduction and prompt reaction in cases of natural or malicious contamination events. Given the structure of a water distribution network (WDN), graph theory is the basis for DMA design, and clustering algorithms can be applied to perform the partitioning. However, such sectorization entails a number of network modifications (installing cut-off valves and metering and control devices) involving costs and operation changes, which have to be carefully studied and optimized. Given the complexity of WDNs, optimization is usually performed using metaheuristic algorithms. In turn, optimization may be single or multiple-objective. In this last case, a large number of solutions, frequently integrating the Pareto front, may be produced. The decision maker has eventually to choose one among them, what may be tough task. Multicriteria decision methods may be applied to support this last step of the decision-making process. In this paper, DMA design is addressed by (i) proposing a modified k-means algorithm for partitioning, (ii) using a multiobjective particle swarm optimization to suitably place partitioning devices, (iii) using fuzzy analytic hierarchy process (FAHP) to weight the four objective functions considered, and (iv) using technique for order of preference by similarity to ideal solution (TOPSIS) to rank the Pareto solutions to support the decision. This joint approach is applied in a case of a well-known WDN of the literature, and the results are discussed

Decision-making tools to manage the microbiology of drinking water distribution systems

This paper uses a two-fold multi-criteria decision-making (MCDM) approach applied for the first time to the field of microbial management of drinking water distribution systems (DWDS). Specifically, the decision-making trial and evaluation laboratory (DEMATEL) was applied removing the need for reliance on expert judgement, and analysed interdependencies among water quality parameters and microbiological characteristics of DWDS composed of different pipe materials. In addition, the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) ranked the most common bacteria identified during trials in a DWDS according to their relative abundance while managing vagueness affecting the measurements. The novel integrated approach presented and proven here for an initial real world data set provides new insights in the interdependence of environmental conditions and microbial populations. Specifically, the application shows as the bacteria having associated the most significant microbial impact may not be the most abundant. This offers the potential for integrated management strategies to promote favourable microbial conditions to help safeguard drinking water quality

Prioritization of maintenance actions in water distribution systems

[EN] Industrial water distribution systems are paramount in many manufacturing systems to optimise the related industrial plant availability and consequently the level of production. They also play an important part in keeping right standards of hygiene of workplaces and machines. A strategic action of planning and implementing of suitable maintenance activities is necessary to assure the standards previously described. The present contribution proposes the prioritization of maintenance actions for industrial water distribution systems through a multi-criteria decision making approach, since some of the elements integrated in maintenance-related aspects are not easily quantifiable and, on the contrary, may be classified as subjective and intangible. This prioritization seeks to pursue technological innovation and may represent a long-term strategy for the organization based on personnel expertise. The AHP technique is suggested to obtain a ranking of maintenance actions. Actions with a lower degree of priority will be postponed on the basis of appropriate time planning. A case study on the real industrial water distribution system belonging to a manufacturing firm is finally presented.Carpitella, S.; Carpitella, F.; Benítez López, J.; Certa, A.; Izquierdo Sebastián, J. (2017). Prioritization of maintenance actions in water distribution systems. International Center for Numerical Methods in Engineering (CIMNE). 1656-1664. http://hdl.handle.net/10251/1798601656166

Prioritization of maintenance actions in water distribution systems

[EN] Industrial water distribution systems are paramount in many manufacturing systems to optimise the related industrial plant availability and consequently the level of production. They also play an important part in keeping right standards of hygiene of workplaces and machines. A strategic action of planning and implementing of suitable maintenance activities is necessary to assure the standards previously described. The present contribution proposes the prioritization of maintenance actions for industrial water distribution systems through a multi-criteria decision making approach, since some of the elements integrated in maintenance-related aspects are not easily quantifiable and, on the contrary, may be classified as subjective and intangible. This prioritization seeks to pursue technological innovation and may represent a long-term strategy for the organization based on personnel expertise. The AHP technique is suggested to obtain a ranking of maintenance actions. Actions with a lower degree of priority will be postponed on the basis of appropriate time planning. A case study on the real industrial water distribution system belonging to a manufacturing firm is finally presented.Carpitella, S.; Carpitella, F.; Benítez López, J.; Certa, A.; Izquierdo Sebastián, J. (2017). Prioritization of maintenance actions in water distribution systems. International Center for Numerical Methods in Engineering (CIMNE). 1656-1664. http://hdl.handle.net/10251/179860S1656166

Fuzzy cognitive maps for knowledge-oriented human risk management in industry

This contribution proposes an integrated approach making use of Fuzzy Cognitive Maps (FCMs) to organise in a flexibleway human knowledge about decision-making (DM) problems of interest in industry. By modelling human reasoning, FCMs allow to represent real phenomena on the basis of spontaneous human brainstorming on relations between pairs of relevant DM elements. Because of its characteristics, the use of FCMs can be effective to model DM problems such as human risk management, particularly critical in the industrial business sector. After identifying human risks in the existing literature, FCMs will be used to define relations among risks, which will be later prioritised by means of a modified Failure Modes, Effects and Criticality Analysis (FMECA). A case study on the sector of automotive industry is eventually implemented and solved to provide practical insights for risk management

Digital Transformation in Maintenance Management

The 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