The main objective of this research is to define the best strategies to contribute to the industrialization of the Additive Manufacturing (AM) technology. The industrialization of AM needs to perform several research to deal with the different failure scenarios. The high failure rate leads to arise the total cost which can be a big obstacle to industrialize the AM technology. So, the different failures should be first identified and next treated. The uncertainty should be considered at several levels such as filament material properties, shape complexity, AM process... One of these uncertainty sources is preheating where a failure scenario can be occurred because of preheating issues which related to AM process parameters. In fact, the preheating plays an important role at the adhesion levels, especially at the beginning of the AM process. Considering the preheating uncertainty should lead to increase the reliability level of the AM processes. To highly increase the preheating temperatures, the quality of the products may be affected such as their surface quality and final dimensions. So, there is a need to perform a statistical study considering different preheating parameters. In this work, a complex shape is considered to perform several studies at different preheating temperatures. This complexity of the studied example necessitates to add some supports to obtain the required geometry. An experimental study on PLA (Polylactic acid) material is carried out to define the most reliable preheating parameters for different models. According to the present example and several realistic applications, it is concluded that when manufacturing PLA materials, the best choices of the preheating temperatures are 240°C for the extruder and 100°C for the platform. This way we reduce the likelihood of failure due to adhesion issues. The preheating temperatures largely affect the adhesion levels at the beginning of the AM process. Even for the same conditions, there is no guarantee to obtain the same results which leads to consider the uncertainty concept at each level of the AM process. In addition to the different findings of the preheating effect, this paper provides the newcomers to AM area with some basic concepts and several probable failure scenarios in a simple way.
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.