The electrical generation industry is looking for techniques to precisely determine the proper maintenance policy and schedule of their assets. Reliability-centered maintenance (RCM) is a methodology for choosing what maintenance activities have to be performed to keep the asset working within its designed function. Current developments in RCM models are struggling to solve the drawbacks of traditional RCM with regards to optimization and strategy selection; for instance, traditional RCM handles each failure mode individually with a simple yes or no safety question in which question has the possibility of major error and missing the effect of a combinational failure mode. Hence, in the present study, a hybrid RCM model was proposed to fill these gaps and find the optimal maintenance policies and scheduling by a combination of hybrid linguistic-failure mode and effect analysis (HL-FMEA), the co-evolutionary multi-objective particle swarm optimization (CMPSO) algorithm, an analytic network process (ANP), and developed maintenance decision tree (DMDT). To demonstrate the effectiveness and efficiencies of the proposed RCM model, a case study on the maintenance of an electrical generator was conducted at a Yemeni oil and gas processing plant. The results confirm that, compared with previous studies, the proposed model gave the optimal maintenance policies and scheduling for the electrical generator in a well-structured plan, economically and effectively.

The oil and gas industry is looking for ways to accurately identify and prioritize the failure modes (FMs) of the equipment. Failure mode and effect analysis (FMEA) is the most important tool used in the maintenance approach for the prevention of malfunctioning of the equipment. Current developments in the FMEA technique are mainly focused on addressing the drawbacks of the conventional risk priority number calculations, but the group effects and interrelationships of FMs on other measurements are neglected. In the present study, a hybrid distribution risk assessment framework was proposed to fill these gaps based on the combination of modified linguistic FMEA (LFMEA), Analytic Network Process (ANP), and Decision Making Trial and Evaluation Laboratory (DEMATEL) techniques. The hybrid framework of FMEA was conducted in a hazardous environment at a power generation unit in an oil and gas plant located in Yemen. The results show that mechanical and gas leakage FM in electrical generators posed a greater risk, which critically affects other FMs within the plant. It was observed that the suggested framework produced a precise ranking of FMs, with a clear relationship among FMs. Also, the comparisons of the proposed framework with previous studies demonstrated the multidisciplinary applications of the present framework.

Rotational Piezoelectric Energy Harvesting (RPZTEH) is widely used due to mechanical rotational input power availability in industrial and natural environments. This paper reviews the recent studies and research in RPZTEH based on its excitation elements and design and their influence on performance. It presents different groups for comparison according to their mechanical inputs and applications, such as fluid (air or water) movement, human motion, rotational vehicle tires, and other rotational operational principal including gears. The work emphasises the discussion of different types of excitations elements, such as mass weight, magnetic force, gravity force, centrifugal force, gears teeth, and impact force, to show their effect on enhancing output power. It revealed that a small compact design with the use of magnetic, gravity, and centrifugal forces as excitation elements and a fixed piezoelectric to avoid a slip ring had a good influence on output power optimisation. One of the interesting designs that future works should focus on is using gear for frequency up-conversion to enhance output power density and keep the design simple and compact.

In the present study, a rotational piezoelectric (PZT) energy harvester has been designed, fabricated and tested. The design can enhance output power by frequency up-conversion and provide the desired output power range from a fixed input rotational speed by increasing the interchangeable planet cover numbers which is the novelty of this work. The prototype ability to harvest energy has been evaluated with four experiments, which determine the effect of rotational speed, interchangeable planet cover numbers, the distance between PZTs, and PZTs numbers. Increasing rotational speed shows that it can increase output power. However, increasing planet cover numbers can increase the output power without the need to increase speed or any excitation element. With the usage of one, two, and four planet cover numbers, the prototype is able to harvest output power of 0.414 mW, 0.672 mW, and 1.566 mW, respectively, at 50 kΩ with 1500 rpm, and 6.25 Hz bending frequency of the PZT. Moreover, when three cantilevers are used with 35 kΩ loads, the output power is 6.007 mW, and the power density of piezoelectric material is 9.59 mW/cm³. It was concluded that the model could work for frequency up-conversion and provide the desired output power range from a fixed input rotational speed and may result in a longer lifetime of the PZT.