Concetta Manuela La Fata

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.

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.

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.

k-out-of-n systems: An exact formula for the stationary availability and multi-objective configuration design based on mathematical programming and TOPSIS

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 multi-objective 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. Stationary availability formula proposed for k-out-of-n systems.Validation of the proposed formula by Markov chains.Design of a k-out-of-n system.Selection of Pareto solution by means of TOPSIS multi-criteria method.

Service quality benchmarking via a novel approach based on fuzzy ELECTRE III and IPA: an empirical case involving the Italian public healthcare context

A novel fuzzy-based approach which combines ELECTRE III along with the Importance-Performance Analysis (IPA) is proposed in the present work to comparatively evaluate the service quality in the public healthcare context. Specifically, ELECTRE III is firstly considered to compare the service performance of examined hospitals in a noncompensatory manner. Afterwards, IPA is employed to support the service quality management to point out improvement needs and their priorities. The proposed approach also incorporates features of the Fuzzy Set Theory so as to address the possible uncertainty, subjectivity and vagueness of involved experts in evaluating the service quality. The model is applied to five major Sicilian public hospitals, and strengths and criticalities of the delivered service are finally highlighted and discussed. Although several approaches combining multi-criteria methods have already been proposed in the literature to evaluate the service performance in the healthcare field, to the best of the authors’ knowledge the present work represents the first attempt at comparing service performance of alternatives in a noncompensatory manner in the investigated context.