# PAL-VMEA: A Novel Method for Enhancing Decision-Making Consistency in Maintenance Management
###### Abstract
The merits of using performance-based weighting schemes to combine judgments of different individuals (rather than assigning equal weights to individual experts) and the way that interaction between experts should be handled are still ongoing research topics [22]. The expert opinion aggregation can become more challenging if the information provided by experts is contradictory. A family of so-called heterodox nonclassical logics, namely, Paraconsistent Logic (PL), whose main feature is the withdrawal of the principle of noncontradiction can aid in decision-making when the analyst is confronted with contradictory opinions [23]. One of the techniques that belongs to such a family and deserves special attention is the Paraconsistent Annotated Logic (PAL) that allows a better decision-making when there are contradictory values or opinions through the attribution of favorable and unfavorable values (the degrees of belief and disbelief) in relation to any proposition, generating a logic that presents results in four states: true, false, inconsistent, and indeterminate [23; 24; 25]. The method has been applied in qualitative and quantitative approaches, such as logic programming for robotics, artificial intelligence and automation, analysis of environmental problems, decision-making in industrial quality and logistics, logical-philosophical reasoning, applied mathematics in decision-making in matters of medicine and law, and complexity of computational systems (mainly assisting in inconsistent data mining). With this technique it is possible to obtain greater consistency and reduce the epistemic uncertainties (obtained by extractors of belief and disbelief in values) for the weights attributed by decision-makers in many decision processes. A relatively new method proposed to improve quality and reliability of products and process is the Variation Mode and Effect Analysis (VMEA), which has been mainly used in the areas of project development and prototype testing in controlled environment. VMEA is a statistically based method used to analyze the effect of different sources of variation on a specific system. One of the main advantages of VMEA is to assist in the comprehension of these variations and to highlight the areas of the product or process in which improvement efforts should be directed. The method systematically assesses how Noise Factors (NF) affect the Key Product Characteristics (KPC) of a system's components. The VMEA result is an index, the Variation Risk Priority Number (VRPN), which indicates the transfer of the variation of these NFs to the analyzed system, supporting the proposal of solutions that could minimize such effects and increase the robustness of the system [26; 27; 28]. Considering the DMP context, these characteristics make the method a strong candidate for application in the maintenance management decision-making process. However, despite the favorable performance of both methods in the aforementioned areas, the lack of application of such techniques in maintenance and reliability engineering decision-making processes, added to the difficulty in assertive decision-making in maintenance activities associated with infrastructure systems, such as power generation and petrochemical plants, are motivating factors for this research. In this way, the present work aims to adapt the VMEA method to analyze the sensitivity of the KPCs of the main items of an equipment, according to the potential and functional failure modes, which are considered as NFs. Due to the importance of the weight assignment process in the VMEA analysis, the Paraconsistent Bi-Annotated Logic (PAL2v)--Paraconsistent Annotated Logic with annotation of two values--is applied as a weight assignment tool for the variables involved in this analysis, which make up the indicators that measure the impact of failure modes on the variation of the key characteristics (main function) of the components of an equipment.