In certain industries such as aviation, the different operations are very complex, and a small error may lead to a catastrophe. So, there is a strong motivation to establish an effective maintenance program to avoid any probable error. A concept called Reliability-Centered Maintenance (RCM) was found in the 1960s and initially oriented towards maintaining airplanes. In this work, we first present some existing RCM standards since standardization is considered as an important element of maintainability. Four significant criteria are next selected in order to establish a comparison of four RCM standards. These comparison criteria are: 1) Categories of failure consequences, 2) Treatment of hidden failures, 3) Management of different consequences, and 4) Decision diagrams. Three of them are related to reliability improvement and the last one is related to the RCM process it-self. Here, we present and discuss the similarities and differences considering the selected criteria. In addition, we add new diagrams to combine between the different RCM standards which paves the way to establish a generalized RCM standard in the future works. As a result, NAVAIR is selected to be the most suitable standard to determine the significant functional failures in terms of safety, operations, environment, and economy.
Cover path planning is a fascinating area of study for roboticists, with many studies available in the research literature. During the trajectory planning phase. Since energy consumption is a function of the trajectory it will take, the energy consumption problem will be partially converted to a trajectory optimization problem. For the first phase, we will compress the problem into a 2d design, which is known as the "traveling salesman problem". There is no known method for solving the "traveling salesman problem" that provides accurate answers in a reasonable amount of time for large cases (a large number of cities). Due to the combinatorial explosion, we will often have to make do with approximate solutions for these huge situations. In this paper we will show a heuristic and make a numerical simulation of the flight plan and then characterize the effect of this optimization on the flight time.