Antonella Certa

An Analytic Hierarchy Process for the Evaluation of Transport Policies to Reduce Climate Change Impacts

Transport is the sector with the fastest growth of greenhouse gases emissions, both in developed and in developing countries, leading to adverse climate change impacts. As the experts disagree on the occurrence of these impacts, by applying the analytic hierarchy process (AHP), we have faced the question on how to form transport policies when the experts have different opinions and beliefs. The opinions of experts have been investigated by a means of a survey questionnaire. The results show that tax schemes aiming at promoting environmental-friendly transport mode are the best policy. This incentives public and environmental-friendly transport modes, such as car sharing and car pooling.

Determination of Pareto frontier in multi-objective maintenance optimization

Abstract The objective of a maintenance policy generally is the global maintenance cost minimization that involves not only the direct costs for both the maintenance actions and the spare parts, but also those ones due to the system stop for preventive maintenance and the downtime for failure. For some operating systems, the failure event can be dangerous so that they are asked to operate assuring a very high reliability level between two consecutive fixed stops. The present paper attempts to individuate the set of elements on which performing maintenance actions so that the system can assure the required reliability level until the next fixed stop for maintenance, minimizing both the global maintenance cost and the total maintenance time. In order to solve the previous constrained multi-objective optimization problem, an effective approach is proposed to obtain the best solutions (that is the Pareto optimal frontier) among which the decision maker will choose the more suitable one. As well known, describing the whole Pareto optimal frontier generally is a troublesome task. The paper proposes an algorithm able to rapidly overcome this problem and its effectiveness is shown by an application to a case study regarding a complex series–parallel system.

Multi-objective human resources allocation in R&D projects planning

In a R&D department, several projects may have to be implemented simultaneously within a certain period of time by a limited number of human resources with diverse skills. This paper proposes an optimisation model for the allocation of multi-skilled human resources to R&D projects, considering individual workers as entities having different knowledge, experience and ability. The model focuses on three fundamental aspects of human resources: the different skill levels, the learning process and the social relationships existing in working teams. The resolution approach for the multi-objective problem consists of two steps: firstly, a set of non-dominated solutions is obtained by exploring the optimal Pareto frontier and secondly, based on further information, the ELECTRE III method is utilised to select the best compromise with regards to the considered objectives. The uncertainty associated to each solution is modelled by fuzzy numbers and used in establishing the threshold values of ELECTRE III, while the weights of the objectives are determined taking into account the influence that each objective has on the others.

ELECTRE III to dynamically support the decision maker about the periodic replacements configurations for a multi-component system

The problem tackled by the present paper concerns the selection of the elements of a repairable and stochastically deteriorating multi-component system to replace (replacements configuration) during each scheduled and periodical system stop within a finite optimization cycle, by ensuring the simultaneous minimization of both the expected total maintenance cost and the system unavailability. To solve the considered problem, a combined approach between multi-objective optimization problem (MOOP) and multi-criteria decision making (MCDM) resolution techniques is proposed. In particular, the @e constraint method is used to single out the optimal Pareto frontier whereas the ELECTRE III multi-criteria decision support method is proposed to support the selection of the replacements configuration that represents the best compromise among the considered objectives. The proposed approach is sequentially applied at each scheduled system stop by allowing the dynamic updating of the information about the decisional context in which the decision maker has to operate. To illustrate the whole procedure a numerical case study is solved for different hypothesized scenarios related to the importance attributed by the decision maker to the system unavailability and the maintenance cost objectives.

A Dempster-Shafer Theory-based approach to the Failure Mode, Effects and Criticality Analysis (FMECA) under epistemic uncertainty: application to the propulsion system of a fishing vessel

Failure Mode and Effects Analysis (FMEA) is a safety and reliability analysis tool widely used for the identification of system/process potential failures, their causes and consequences. When aimed at the failure modes prioritization, FMEA is named Failure Mode, Effects and Criticality Analysis (FMECA). In the latter case, failure modes are commonly prioritized by means of the Risk Priority Number (RPN) that has been widely criticized to have several shortcomings. Firstly, in the presence of multiple experts supplying different and uncertain judgments on risk parameters, RPN is not able to deal with such a kind of information. Therefore, the present paper proposes the Dempster-Shafer Theory (DST) of evidence as a proper mathematical framework to deal with the epistemic uncertainty often affecting the input evaluations on risk parameters. In particular, such evaluations are supposed to be elicited from experts in an interval or crisp form, and then opportunely propagated to obtain a multiple-values characterization of the RPN associated with each analyzed failure mode. In order to synthesize the available information and make them useful for failure modes prioritization aims, Belief and Plausibility distributions are used. The methodology is finally applied to the propulsion system of a fishing vessel operating in Sicily.

A Multi-Objective Approach to Optimize a Periodic Maintenance Policy

The present paper proposes a multi-objective approach to find out an optimal periodic maintenance policy for a repairable and stochastically deteriorating multi-component system over a finite time horizon. The tackled problem concerns the determination of the system elements to replace at each scheduled and periodical system inspection by ensuring the simultaneous minimization of both the expected total maintenance cost and the expected global system unavailability time. It is assumed that in the case of system elements failure they are instantaneously detected and repaired by means of minimal repair actions in order to rapidly restore the system. A nonlinear integer mathematical programming model is developed to solve the treated multi-objective problem, whereas the Pareto optimal frontier is described by the Lexicographic Goal Programming and the e-constraint methods. To explain the whole procedure, a case study is solved and the related considerations are given.

ELECTRE TRI-based approach to the failure modes classification on the basis of risk parameters

Proposing an ELECTRE TRI-based approach for the failure modes classification into predefined and ordered risk classes.Direct identification of failure modes on which performing the corrective actions with priority.Easy definition of risk classes on the basis of DMs expertise and perception of the industrial context considered.Application to dairy manufacturing processes. Failure Mode and Effects Analysis (FMEA) is an engineering technique aimed at the detection of potential failures, their causes and consequences on the system/process under investigation. When used for the failure modes prioritization, FMEA is also referred to as Failure Mode, Effects and Criticality Analysis (FMECA). In traditional FMECA, risk priorities of failure modes are determined through the Risk Priority Number (RPN), which is a function of the three risk parameters Occurrence (O), Severity (S), and Detection (D). In the present paper, an alternative approach to the RPN is proposed for the criticality assessment of process/system failure modes. Particularly, the Multi-Criteria Decision Making (MCDM) method ELECTRE TRI is employed to assign failure modes to predefined and ordered risk classes, from the highest to the lowest risky one. Contrarily to the traditional RPN, the method allows the Decision Maker (DM) at taking into account the relative importance of risk parameters as well as his/her uncertainty in assigning each failure mode to a specific risk class. The ELECTRE TRI-based approach is implemented on the applicative case proposed by Kurt and zilgen (2013) with reference to Turkish dairy manufacturing industries. A sensitivity analysis is finally performed in order to test the influence of the input parameters on the classification results.

A Multistep Methodology for the Evaluation of Human Resources Using the Evidence Theory

The paper aims at proposing a model for the human resources evaluation as regards to a set of skills. Specifically, it starts sfrom the judgments expressed by a team of experts on the basis of their previous working experiences with the resource to be evaluated. Information arising from experts is successively handled by the analyst and aggregated to determine the resource suitability or unsuitability. The Dempster–Shafer theory is proposed here as an appropriate tool to deal with both the uncertainty of experts due to the incomplete knowledge about resources to be evaluated and that of the analyst to convert expert judgments in terms of resource suitability/unsuitability. Furthermore, the Yager rule is used to aggregate the available information simultaneously taking into account the uncertainty and the eventual conflict among the information sources. In addition, a parameter synthesizing the expertise of each candidate is suggested.

A combined multi-criteria approach to support FMECA analyses: A real-world case

Abstract 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.

A Synthetic Measure for the Assessment of the Project Performance

The present paper aims to offer a synthetic project performance indicator (PPI) that aggregates two input parameters obtained by the Earned Value Analysis. The PPI is calculated by using a Fuzzy Inference System (FIS) able to single out a measure based on the input parameters, instead of formulating a mathematical model that could be a troublesome task whenever complex relations among the input variables exist. The purpose is to communicate the project performance to the stakeholders in a clear and complete way, for example, describing the PPI by means of contour lines.