Journal of Modern Processes in Manufacturing and Production
Volume:7 Issue: 3, Summer 2018

In this study, the behavior of a composite lattice cylindrical shell is investigated in the buckling deforming. Also, the distribution of shell buckling response and the stress field is studied after making some defects on the ribs.Therefore using ANSYS software, a 3D finite element model of the shell has been created for the analysis. Material properties and geometrical data of the shell are obtained from the some experimental tests. In fact, these parameters have been extracted from the prototypesthat made with filament winding method. The parameters studied in this study include of the kind of ribs defects on buckling response and the geometrical ratios. Composite shells have been tested under axial force and obtained results are compared with the results of FEM. Based on the parametric study, the structural strength-to-weight ratio is increased around %50 by increasing the thickness of the outer shell. It is observed that in each consecutive buckling test, the buckling load is reduced; however the failed sample had reasonably good resistance to the applied load.

Rene-80 nickel-base superalloy as an alloy for production of the jet turbine blades shows high mechanical properties as well as microstructure stability during the high temperature engine operation. In this research, age hardening heat treatment cycle was done on the as-cast Rene-80 superalloy. In the following, microstructure, elemental analysis of phases and macro-hardness of the alloy before and after of heat treatment were compared together with scanning electron microscopy (SEM) observation, X-ray spectrometry (EDS) and hardness test, respectively. The obtained results showed that γ’ carbide particles in the as-cast alloy had cubic morphology, while these particles showed more spherical morphology after heat treatment and also the amount of this phase was reduced after heat treatment. Based on hardness test results, hardness of as-cast sample was reduce from 38.17 to 35.01 HRC after age hardening heat treatment, which can be due to the reduction of carbide particles and their morphological modification.

The Mahalanobis-Taguchi System (MTS) is a relatively new collection of methods proposed for diagnosis and forecasting using multivariate data. It consists of two main parts: Part 1, the selection of useful variables in order to reduce the complexity of multi-dimensional systems and part 2, diagnosis and prediction, which are used to predict the abnormal group according to the remaining useful variables. The main purpose of this research is presenting a new method to select useful variables by using and combining the concept of Mahalanobis distance and Integer Programming. Due to the inaccuracy and the difficulties in selecting the useful variables by the design of experiments method, we have used an innovative and accurate method to solve the problem. The proposed model finds the solutions faster and has a better performance than other common methods.

In this paper, we present a new predictive hybrid model using discrete wavelet transform (DWT), and the artificial neural network (ANN) to reduce the bullwhip effect of demand in supply chain to obtain a real amount of final customer demand. Also, we compare our result with more comprehensive sample of previous research to extend the scope of our study. In this new research our methodology is combine two discrete wavelet transform (DWT), and the artificial neural network (ANN) was used to analyze the data. Results indicated that in comparison with the previous methods of prediction to reduce the bullwhip effect in supply chains, the use of DWT and ANN is more favorable leading to less error against other methods. Moreover, we discrete our data in liner data and nonlinear data because since the combinational method uses nonlinear data and gives importance to these data rather than linear data, it can be concluded that in comparison with linear data, nonlinear data have more importance in predicting the bullwhip effect. According to this new combinational technique, organizations can obtain suitable amounts of demand at all stages of supply chain, which makes a low distance between true and forecasting demands. Therefore, organizations can avoid some costs that playing an inessential role in their products.

Real-time robust adaptive fuzzy fractional-order control of electrically driven flexible-joint robots has been addressed in this paper. Two important practical situations have been considered: the fact that robot actuators have limited voltage, and the fact that current signals are contaminated with noise. Through of a novel voltage-based fractional order control for an integer-order dynamical system and based on a Lyapunov's functions analysis, it is shown that the overall closed-loop system is robust, BIBO stable and the joint position tracking error is uniformly bounded. The satisfactory performance in lower energy consumption of the proposed fractional control scheme is verified in comparison with a standard integer-order controller by experimental results.

Grinding is finishing process aimed at achieving surface quality and dimensional accuracy in workpieces with tight tolerances especially from materials with a high degree of hardness and strength. The grinding process of superalloys is faced with problems and challenges caused by the generation of excessiveheatas well as the adhesion of workpiecematerialon the grinding tool. Therefore, in-depth research is still under way to introduce and develop new techniques for optimization of output parameters in the grinding of superalloys. One of such techniques is to apply minimum quantity lubrication (MQL) using nanofluids. In this research, we study the effect of using a type of mixed nanofluid comprising multiwall carbon nanotubes (MWCNT) and nano-aluminum oxide (Al2O3) on the surface quality in the grinding process of Inconel 600.For this purpose, the input parameters of the process are first determined. Following that, the design of experiments were performed based on full factorial method and the, grinding experiments were conducted accordingly to study the effect of various parameters including the nanoparticles size , volume concentration, and mixing ratio on surface quality of the workpiece.
Based on the results obtained from this study, while using the vegetable oil for MQL with nanofluids, the highest surface quality with Ra=0.15µm is achieved by applying a nanofluid with a mixing ratio of 75% -25% for Al2O3 -MWCNT nanoparticles, volume concentration  of 0.6%, and with size of 20 nm and 15 nm for Al2O3and MWCNT nanoparticles, respectively.