The paper proposes an approach that combines reliability analyses and multi-criteria decision methods to optimize maintenance activities of complex systems. A failure mode, effects, and criticality analysis (FMECA) is initially performed and the fuzzy TOPSIS (FTOPSIS) method is then applied to rank previously identified failure modes. For prioritization, failure modes are assessed against three evaluation criteria that differ from those traditionally involved in risk priority number (RPN) computation (i.e. severity, occurrence and detection). Two criteria refer to the maintenance management reflecting the operational time taken by the maintenance activity performed after the occurrence of a specific fault, and the way such an action is executed. The third criterion reflects the classical frequency of the occurrence of faults. To further develop previous research, the analytic hierarchy process (AHP) is herein applied to weight evaluation criteria and a group of experts is involved with aspects associated with the considered criteria. The approach is applied to a real-world case study, showing that the obtained results represent a significant driver in planning maintenance activities. To test the influence of criteria weights on ranking results, a sensitivity analysis is carried out by varying the vector of criteria weights obtained from the group decision process.

Supply chains are complex networks that receive assiduous attention in the literature. Like any complex network, a supply chain is subject to a wide variety of risks that can result in significant economic losses and negative impacts in terms of image and prestige for companies. In circumstances of aggressive competition among companies, effective management of supply chain risks (SCRs) is crucial, and is currently a very active field of research. Failure Mode, Effects and Criticality Analysis (FMECA) has been recently extended to SCR identification and prioritization, aiming at reducing potential losses caused by lack of risk control. This article has a twofold objective. First, SCR assessment is investigated, and a comprehensive list of specific risks related to the automotive industry is compiled to extend the set of most commonly considered risks. Second, an alternative way of calculating the Risk Priority Number (RPN) is proposed within the FMECA framework by means of an integrated Multi-Criteria Decision-Making (MCDM) approach. We give a new calculation procedure by making use of the Analytic Hierarchy Process (AHP) to derive factors weights, and then the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) to evaluate the new factor of “dependence” among the risks. The developed joint analysis constitutes a risk analysis support tool for criticality in systems engineering. The approach also deals with uncertainty and vagueness associated with input data through the use of fuzzy numbers. The results obtained from a relevant case study in the automotive industry showcase the effectiveness of this approach, which brings important value to those companies: When planning interventions of prevention/mitigation, primary importance should be given to (1) supply chain disruptions due to natural disasters; (2) manufacturing facilities, human resources, policies and breakdown processes; and (3) inefficient transport.

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Nowadays, optimal sensor placement (OSP) for leakage detection in water distribution networks is a lively field of research, and a challenge for water utilities in terms of network control, management, and maintenance. How many sensors to install and where to install them are crucial decisions to make for those utilities to reach a trade-off between efficiency and economy. In this paper, we address the where-to-install-them part of the OSP through the following elements: nodes’ sensitivity to leakage, uncertainty of information, and redundancy through conditional entropy maximisation. We evaluate relationships among candidate sensors in a network to get a picture of the mutual influence among the nodes. This analysis is performed within a multi-criteria decision-making approach: specifically, a herein proposed variant of DEMATEL, which uses fuzzy logic and builds comparison matrices derived from information obtained through leakage simulations of the network. We apply the proposal first to a toy example to show how the approach works, and then to a real-world case study.

Reliability and availability analyses are recognized as essential for guiding decision makers in the implementation of actions addressed to improve the technical and economical performance of complex systems. For industrial systems with reparable components, the most interesting parameter used to drive maintenance is the stationary availability. In this regard, the present paper proposes an exact formula for computing the system stationary availability of a k-out-of-n system. Such a formula is proved to be in agreement with the fundamental theorem of Markov chains. Then, a multiobjective mathematical model is formulated for choosing the optimal system configuration design. The Pareto front is developed using the Lexicographic Goal Programming (LGP) method, and the TOPSIS method is successively implemented to choose the k-out-of-n configuration that represents the best compromise between the considered objective functions. A numerical example is provided.

Decision-making is frequently affected by uncertainty and/or incomplete information, which turn decision-making into a complex task. It is often the case that some of the actors involved in decision-making are not sufficiently familiar with all of the issues to make the appropriate decisions. In this paper, we are concerned about missing information. Specifically, we deal with the problem of consistently completing an analytic hierarchy process comparison matrix and make use of graph theory to characterize such a completion. The characterization includes the degree of freedom of the set of solutions and a linear manifold and, in particular, characterizes the uniqueness of the solution, a result already known in the literature, for which we provide a completely independent proof. Additionally, in the case of nonuniqueness, we reduce the problem to the solution of nonsingular linear systems. In addition to obtaining the priority vector, our investigation also focuses on building the complete pairwise comparison matrix, a crucial step in the necessary process (between synthetic consistency and personal judgement) with the experts. The performance of the obtained results is confirmed. KEYWORDSAHP, decision-making, graph theory, incomplete information, layout reorganization a solid scientific basis that is capable of managing the intrinsically subjective and partially informed nature of decisions. This formulation should aim to make decisions as objective as possible, even if the decision-making process cannot be totally objective. Flexible decision-making methods are required that consider a wide variety of J Multi-Crit Decis Anal. 2019;26:3-15.wileyonlinelibrary.com/journal/mcda

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 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. Multi-criteria 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.

Human factors are intrinsically involved at virtually any level of most industrial/business activities, and may be responsible for several accidents and incidents, if not correctly identified and managed. Focusing on the significance of human behaviour in industry, this article proposes a multi-criteria decision-making (MCDM)-based approach to support organizational risk assessment in industrial environments. The decision-making trial and evaluation laboratory (DEMATEL) method is proposed as a mathematical framework to evaluate mutual relationships within a set of human factors involved in industrial processes, with the aim of highlighting priorities of intervention. A case study related to a manufacturing process of a real-world winery is presented, and the proposed approach is applied to rank human factors resulting from a previous organisational risk evaluation from which suitable inference engines may be developed to better support risk management.