hamid haghshenas gorgani

Meeting the needs of today’s industry plays a prominent role in the progress and competitive strength of any country. Therefore, it is necessary to align the curriculum of engineering courses with them. In this research, the focus has been on the mechanical engineering curriculum, especially in the universities of Iran. For this purpose, first by surveying the industry owners and reviewing the literature, these expectations have been identified and prioritized. Accordingly, the most important of these needs are creativity, visualization ability, familiarity with manufacturing processes, and agility in learning new concepts. Then, using a two-stage quality function deployment method (QFD), these expectations are translated into curriculum specifications. The results show that the most effective groups of courses in this field are elective courses, skill courses such as engineering graphics (including technical drawing and drawing courses), design of machine components, and practical workshops. In the existing programs, compared to courses in specialized theory and basic courses, some of them have received less considerable attention in quantity and quality.

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.

Engineering education is based on the technical methods in the present form. Information revolution causes to access the technical education materials as a widely spread form by the students. These materials are more effective than the traditional engineering education. Thus, it is necessary to change the engineering education methods from the classical form. General workshop is a first-year course for the engineering students and it is an introduction on the engineering regulations. Nowadays, this course is run to teach the practical training. However, this goal cannot be achieved because of the short period of the course, various topics of the course and improper education methods. In this paper, this course is revised based on the teaching of engineering concepts to the students. Various engineering concepts are explained which can be educated in this course without considerable changes in practice but with magnificent change in the course prospective. It is expected that this new design helps the students more to be familiar with the engineering concepts and methods.

This paper presents a nonlocal strain gradient theory for capturing size effects in buckling analysis of Euler-Bernoulli nanobeams made of three-dimensional functionally graded materials. The material properties vary according to any function. These models can degenerate to the classical models if the material length-scale parameters is assumed to be zero. The Hamilton's principle applied to drive the governing equation and boundary conditions. Generalized differential quadrature method used to solve the governing equation. The effects of some parameters, such as small-scale parameters and constant material parameters are studied.

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.

One of the most important characteristics of a modern product is the extent to which it meets the needs of customers to gain market share. The conceptual design methods of products based on customer requirements are often feature-based, in which several features are identified between different types of a product. According to customer demands, these features are tuned and the closest is selected as the optimum. The great variety of features of a present-day product can often make this difficult because finding these common features is very complicated or even impossible. To solve this problem, choosing the optimal design is divided into two phases: In the first phase, the main product is divided into some basic categories and according to the customers' opinion, one is selected as the "winning category". In the second phase, the selection of common geometrical features between the members of the winning category is made. Then, the optimization process is done based on customer rating and the closest design to the mentioned rating is selected. The house light switch is used as a case study and the proposed algorithm is implemented on it. High customer satisfaction with the optimized final design, high response rate to survey forms, and the low number of incompatible data, all, indicate the suitability of the proposed algorithm with human interface characteristics, simplicity and efficiency in adapting the product to the customers' view. This method can be used for other industrial products and even for non-industrial products or services.

Graphics is a real and complete language used in the engineering design process. Therefore, the engineering drawing has always been considered as a basic and compulsory course in the engineering curriculum. The advances of the digital age and changes in design approach of engineering in recent years, from the step-by-step to concurrent engineering, where all project people work in a unified team, always raise the question of whether There is still a need for engineering graphic training as in the past, and if any, what changes its content should make. The proposed method is a hybrid data processing method based on the use of QFD - as a very simple and efficient method of designing a product to meet customer needs. One of the major weaknesses of the QFD method is the assumption of independence between the product’s technical features. AHP & then DEMATEL technique are combined with QFD, to overcome this problem. The appropriateness of the results with the human mental processes is ensured through the application of fuzzy logic.  The results show that engineering graphics continue to be an essential course in modern engineering education, but its content must be adapted to meet new needs. These changes are suggested in the results section and the new syllabus is presented.

Popular method for assessment of final exam answer scripts in university and among the engineering drawing answer scripts based on absolute true or false judgment and assigning a single number or letter to answer of each problem cannot be so fair. To obtain a fair assessment method, we considered “imagination”, “accuracy”, “drawing” and “innovation” that are objectives of engineering drawing course to be separately assessed for each problem. Flexibility and linguistic properties of fuzzy logic made us use it as the basis of our method. In addition, fuzzy variables and membership functions are easily linguistic explainable, and adjustable to different conditions. “Answering time” was added as a factor with only a positive effect on the final grade. Between these five factors, imagination has special importance because it supports one of seven human intelligences which is spatial ability Finally, however we applied the proposed method to engineering drawing course, it can be applied to other courses with considering their properties.

In this paper, the free vibration behaviors and flexural sensitivity of atomic force microscope cantilevers with small-scale effects are investigated. To study the small-scale effects on natural frequencies and flexural sensitivity, the consistent couple stress theory is applied. In this theory, the couple stress is assumed skew-symmetric. Unlike the classical beam theory, the new model contains a material-length-scale parameter and can capture the size effect. For this purpose, the Euler–Bernoulli beam theory is used to develop the AFM cantilever. The tip interacts with the sample that is modeled by a spring with constant of. The equation of motion is obtained through a variational formulation based on Hamilton’s principle. In addition, the analytical expressions for the natural frequency and sensitivity are also derived. At the end, some numerical results are selected to study the effects of material-length-scale parameter and dimensionless thickness on the natural frequency and flexural sensitivity.

There are mainly two categories for a 3D reconstruction from 2D drawings: B-Rep and CSG that both these methods have serious weaknesses despite being useful. B-Rep method which has been older and have wider function range is problematic because of high volume of calculations and vagueness in answers and CSG method has problem in terms of very limited range of volumes and drawings that it can analyze. Proposed method in this paper is an innovative method based on B-Rep in which optimization of genetic algorithm has been used to identify the relationship among the components of various views in 2D drawings. Using genetic algorithm that is a stochastic algorithm contributes that high volume of calculation that is one of main weaknesses of B-Rep method is solved. Moreover, considering correspondence condition of one to one among response in this method has caused that vagueness problem which is another weakness of B-Rep method to be almost solved so it can be said in addition to having wide range, present method doesn’t have common problems of B-Rep method and it even turns it to an effective method.