sharif shabani

This article investigates the adverse effects of the COVID-19 pandemic on academic education. Limited time and resources makes it necessary to prioritize negative consequences based on their risk in a preventive manner. An effective tool for this matter is the analysis of potential failure modes and effects (FMEA). The negative consequences of the coronavirus pandemic are categorized and prioritized based on the severity, ways of diagnosis, and the probability of occurrence, using FMEA. In this study, using a survey of 120 participants, common failure modes, severity, occurrence likelihood, and preventive detection methods were investigated, and the intensity and occurrence numbers were assigned based on expert opinions. Finally, the listed breakdowns were ranked in order of deterioration. Also, corrective actions were provided to eliminate or reduce the effects of failure of the mentioned cases, and the risk priority number was re-predicted. At the end, effective solutions were presented as a list.

Following the advances in Computer-Aided Design (CAD) and Additive Manufacturing (AM), with regards to the numerous benefits of the Fused Deposition Modeling (FDM) as a popular AM process, resolving its weaknesses has become increasingly important. A serious problem of the FDM is the dimensional error or size difference between the CAD model and the actual 3D printed part.In this study, the approach is compensating the error regardless of its source. At First, all parameters affecting the dimensional accuracy of FDM are comprehensively identified. Then, multi-input–single-output (MISO) data is prepared by designing experiments using the Taguchi method and obtaining the results from 3D printed samples. Next, a GMDH neural network is applied, which uses a simple nonlinear regression formula in each neuron but can create very complex neuron combinations. So, it is possible to analyze small or even noisy data. Regulatory parameters of the Neural Net have been optimized to increase efficiency. The case study shows a decrease in the RSME for the Nominal CAD Model from 0.377 to 0.033, displaying the compensator's efficiency.