Criticality Analysis Techniques Applied to Optimize Maintenance Management Processes

The techniques of criticality analysis are tools that allow identifying and hierarchy for their importance the assets of an installation on which it is worth directing resources (human, economic, and technological). In other words, the process of criticality analysis helps determine the importance and consequences of potential failure events of production systems within the operational context in which they perform. Taking as reference the maintenance management model (MMM) of the eight phases, this chapter related to techniques of prioritization and criticality is part of Phase 2 of the MMM. In the following chapter, the most important theoretical aspects of equipment hierarchical analysis techniques are explained, based on the qualitative and quantitative risk model (failures frequencies and consequences). Finally, two case studies in the oil refining industry are developed; the first case uses the tool qualitative risk matrix (QRM), and the second case uses the tool risk analytic hierarchy process (RAHP).

SPACECRAFT RELIABILITY CALCULATIONS USING STATISTICAL REGULARITIES IN OCCURRENCES OF FAILURES IN DEVICES, UNITS AND ASSEMBLIES DURING THEIR OPERATION

The paper addresses reliability analysis of manned spacecraft with the use of statistical regularities in in-flight failures of their devices, units and assemblies. It formulates validity criteria for using a device failure in reliability analysis, proposes a method for analyzing and classifying failures which enables factoring in different types of failures in reliability analyses. It considers a hypothesis of the absence of statistically significant differences in probabilities of individual valid failures and demonstrates the feasibility of its adoption with the use of dispersion analysis. A method is developed for evaluating product reliability using a functional relationship between reliability and the number of failures occurring in flight which makes it possible to significantly simplify reliability analysis for complex products, to establish the number of in-flight failures that is acceptable from the standpoint of the product reliability requirements, to study various product architectures from the standpoint of reliability criteria. It proposes a method for evaluating the lower boundary for the probability of manned spacecraft completing their missions based on the failure modes, effects and criticality analysis, and demonstrates the feasibility of optimizing the product redundancy scheme based on the fault tolerance requirements. Key words: manned spacecraft, flight, failure, fault tolerance, classification of failures, reliability, probability of failure-free operation, statistical analysis, dispersion analysis.

A New Hybrid Dynamic FMECA with Decision-Making Methodology: A Case Study in an Agri-Food Company

The Failure Mode and Effect Analysis (FMEA) is often used to improve a system's reliability. This paper proposes a new approach that aims to overcome the most critical defects of the traditional FMEA. This new methodology combines the Entropy and Bwm methodology with the EDas and System Dynamics, FMECA: The EN-B-ED Dynamic FMECA. The main innovation’s point of the proposed work is the presence of an unknown factor (Cost) in order to take into consideration the economic aspect; the evaluation of the four-factor through both an objective method (Entropy method) and a subjective method (BWM); the ranking method used (EDAS method), much more accurate than RPN; the development of a dynamic criticality analysis to take in consideration the dynamic aspect of the system. This work aims to give manufacturing companies an easy and replicable method to analyze the possible failure modes and prevent the fault.

Unusual Surface Latent Heat Flux Variations and Their Critical Dynamics Revealed before Strong Earthquakes

We focus on the possible thermal channel of the well-known Lithosphere–Atmosphere–Ionosphere Coupling (LAIC) mechanism to identify the behavior of thermal anomalies during and prior to strong seismic events. For this, we investigate the variation of Surface Latent Heat Flux (SLHF) as resulting from satellite observables. We demonstrate a spatio-temporal variation in the SLHF before and after a set of strong seismic events occurred in Kathmandu, Nepal, and Kumamoto, Japan, having magnitudes of 7.8, 7.3, and 7.0, respectively. Before the studied earthquake cases, significant enhancements in the SLHF were identified near the epicenters. Additionally, in order to check whether critical dynamics, as the signature of a complex phenomenon such as earthquake preparation, are reflected in the SLHF data, we performed a criticality analysis using the natural time analysis method. The approach to criticality was detected within one week before each mainshock.

Reliability degradation prediction of photovoltaic modules based on dependability methods

PurposeThe reliability prediction is among the most important objectives for achieving overall system performance, and this prediction carried out by anticipating system performance degradation. In this context, the purpose of this research paper is to development of methodology for the photovoltaic (PV) modules' reliability prediction taking into account their future operating context.Design/methodology/approachThe proposed methodology is framed by dependability methods, in this regard, two methods of dysfunctional analysis were used, the Failure Mode and Effects Criticality Analysis (FMECA) method is carried out for identification of the degradation modes, and the Fault Tree Analysis (FTA) method is used for identification the causes of PV modules degradation and the parameters influencing its degradation. Then, based on these parameters, accelerated tests have been used to predict the reliability of PV modules.FindingsThe application of the proposed methodology on PWX 500 PV modules' in different regions of Algeria makes it possible to predict its reliability, taking into account the future constraints on its operation. In this case, the temperature and relative humidity vary from one region to another was chosen as constraints. The results obtained from the different regions confirms the reliability provided by the designer of the Saharan cities Biskra, In Salah, Tamanraset, and affirms this value for the two Mediterranean cities of Oran and Algiers.Originality/valueThe proposed methodology is developed for the reliability prediction of the PV modules taking into account their future operating context and, the choice of different regions confirms or disproves the reliability provided by the designer of the PV modules studied. This application confirms their performance within the framework of the reliability prediction.

FMECA and MFCC-Based Early Wear Detection in Gear Pumps in Cost-Aware Monitoring Systems

Gear pump failures in industrial settings are common due to their exposure to uneven high-pressure outputs within short time periods of machine operation and uncertainty. Improving the field and line clam are considered as the solutions for these failures, yet they are quite insufficient for optimal reliability. This research, therefore, suggests a method for early wear detection in gear pumps following an extensive failure modes, effects, and criticality analysis (FMECA) of an AP3.5/100 external gear pump manufactured by BESCO. To replicate this condition, fine particles of iron oxide (Fe2O3) were mixed with the experimental fluid, and the resulting vibration data were collected, processed, and exploited for wear detection. The intelligent wear detection process was explored using various machine learning algorithms following a mel-frequency cepstral coefficient (MFCC)-based discriminative feature extraction process. Among these algorithms, extensive performance evaluation reveals that the random forest classifier returned the highest test accuracy of 95.17%, while the k-nearest neighbour was the most cost efficient following cross validations. This study is expected to contribute to improved evaluations of gear pump failure diagnosis and prognostics.

Digital Twin-Driven Process and Equipment FMECA Generation for Smart Manufacturing Applications

Qualtech Systems, Inc. (QSI)’s integrated tool set, consisting of TEAMS-Designer® and TEAMS-RDS® provides a comprehensive digital twin-driven and model-based systems engineering approach that can be deployed for fault management throughout the equipment life-cycle – from its design for fault management to condition-based maintenance of the deployed equipment. In this paper, we present QSI’s approach towards adapting and enhancing their existing model-based systems engineering (MBSE) approach towards a comprehensive digital twin that incorporates constructs necessary for development of a Process Failure Modes and Criticality Analysis (P-FMECA) and integrates that with an Equipment FMECA. The paper will discuss the various levels of automation towards incorporation of these model constructs and their reuse towards automation of the development of the different digital twins and subsequently the automatic generation of the combined Process and Equipment FMECA. This automated ability to develop the integrated FMECA that incorporates both Process-level Failure Modes and Equipment-level Failure Modes allows the system designer and operators to correlate and identify process failures down to their root causes at the equipment-level and thereby producing a comprehensive actionable systems-level view of the entire Smart Manufacturing facility from a fault management design and operations perspective. The paper will present the application of this novel technology for the Advanced Metal Finishing Facility (AMFF) at the Warner-Robins Air Logistics Complex (WR-ALC) in Robins Air Force Base, Georgia, as part of WR-ALC’s initiative towards model-based enterprise (MBE) and smart manufacturing.

Identification and Assessment of Obsolescence in the Early Stages of System Design

Obsolescence is the fact that an entity (physical or logical) is becoming outdated or no longer possesses the required level of performance. The objectives of this article are twofold. First, it is intended to contribute to the understanding of obsolescence propagation. Secondly, two supporting approaches for the Identification and Assessment phases are proposed: the House of Obsolescence and the System Obsolescence Criticality Analysis. The former allows the mapping of obsolescence propagation via dependencies, whether imposed changes are desired or imposed, by external actors to the system architecture. Whereas, the objective of the latter is to assign an obsolescence criticality index to the identified risks in order to prioritize them for solution or mitigation determination during the analysis phase. The tools make extensive use of the modeled system knowledge through the application of Systems Engineering. The application of these approaches is presented through an illustrative study.