# PAL-VMEA: A Novel Method for Enhancing Decision-Making Consistency in Maintenance Management
## 2 Variation Mode and Effect Analysis (VMEA)  
The concept of a robust product significantly contributed to the establishment of the Robust Design Methodology (RDM) as a methodology to improve product and process quality during the second half of the last century [29]. Although the use of RDM-related methods is quite disseminated, it is clear that only to a limited extent, some systematic techniques are used in the industry for the original purpose, which indicates that there are lack of some elements for successful implementation [30; 31; 32]. As a response to this gap and considering that variations in the manufacturing process affect the quality and performance characteristics of the final product in several ways and, also, that some of that characteristics are more sensitive to that variations than others, [PERSON], [PERSON], and [PERSON] [32] introduced an engineering method, VMEA, developed to systematically look for NFs affecting KPCs in early product development phases. Although it can be considered a derivation of Failure Mode and Effect Analysis (FMEA), a failure-oriented approach, VMEA emphasizes the assessment of risks related to excessive variations in the analyzed system. Originally focused on product design and analysis, in this work its objective is to identify and prioritize NFs that contribute significantly to the variability of KPCs and could generate undesired consequences in terms of safety, compliance with government regulations, and functional system requirements. The resulting index of the analysis, VRPN, directs the attention of analysts and maintainers to areas where reasonably predicted variations may be harmful. Based on the results obtained from VMEA, a design or maintenance strategy that seeks to prioritize actions that minimize or eliminate the causes of the observed variations can be formulated, facilitating the subsequent efforts to obtain a more robust and reliable system. [PERSON] et al. [26] presented a statistically based VMEA that, as the authors put it, could be used in situations where the transfer function, i.e., the relationship between the KPCs and the factors affecting them, is unknown. When the analytical expression of the transfer function is known, VMEA would correspond to the well-known method of moments. The VMEA procedure would be particularly useful to grasp information on the transfer function usually mastered by experts on the product under study. The results of the VMEA would then serve as a basis for attaining robust designs using traditional Design of Experiments (DoE) in the phases of parameter and tolerance design. Carrying out a study about a jet engine components' fatigue life in order to obtain a safety margin that would take into consideration all identifiable causes of uncertainty, [PERSON] et al. [33] used the probabilistic branch of VMEA implemented as a first-order, second-moment reliability method. In their conclusions they stressed the fact that in addition to the use of both basic and enhanced VMEA in the early design stages for the identification of critical components, whenever either scatter or uncertainty need to be quantified, a more sophisticated probabilistic VMEA is required. [PERSON], [PERSON], and [PERSON] [34] included VMEA among the most usual engineering tools that have been used to improve and optimize processes. The authors reasoned that VMEA provided a scientific method to discover the actual main causes of variation, as opposed to the fact that often in process innovation engineers believe that they are instinctively aware of the main causes of variation, while in many cases, it is one of the unsuspecting parameters which is not high on the list of offenders that is the main cause of process problems and variation. [PERSON] et al. [28] stated that the possibility of predicting the reliability of hardware for both components and systems is important in engineering design. So VMEA was used to investigate how different sources of variation affected the reliability of a wheel loader automatic transmission clutch shaft.