مجله مهندسی مکانیک امیرکبیر
سال چهل و دوم شماره 3 (زمستان 1389)

For developing of endoscopic Capsular, a design of legged capsular microrobot with ionic polymer metal composite actuator is suggested in this paper. First locomotion of microrobot is explained then microrobot is modeled by envisage exerting surface forces and microactuator. Surface forces contain slip-friction, surface adhesion and resting adhesion and polymeric microactuator is ionic polymer metal composite. Time variant response of polymeric microactuator is modeled fundamental of coupled electromechanical equation and electric equivalent bulk gel polymeric.
Result simulation of dynamical model microrobot shows that best installation angle of legs is 60 degree, proper mass of microrobot is 2g and speed marching is 1 millimeter per second.

The main concentration of most of the snake robot researches has been on mechanism, control or dynamics. They have rarely focused on snake anatomy to adopt it in design. So far, snake robots are nothing more than an experimental prototype. They have not yet converted to an industrial mobile robot. This paper focuses on snake anatomy to employ its principle in the design of snake robots and increase their chance of being industrial mobile robots. The result was to find the impact of snake anatomy to reduce actuator's torque, as well as the way peg points are established during serpentine motion. This finding will help to remove wheels under snake robots.

The effect of inter-fiber spacing and shape on stress distribution is studied in a composite monolayer. The lamina is subjected to an internal crack while loaded by a force P along the fibers at infinity. Two models are postulated. In the first, fibers have circular cross section while in the second, a triangular shape is considered. By direct application of modified shear – lag model, the differential equations of equilibrium are derived and solved for displacements and stress fields. The results show that the ordinary shear – lag model can not well predict the stress distribution within the lamina. The modified model shows a noticeable decrease in both types of stresses once fiber spacing and shape are changed. This reduction is more pronounced for triangular fibers where a decrease in causes more reduction in maximum shear stresses and no change in fiber normal stresses. The reduction in peak shear stress appears to be 32 percent for volume fraction of one at q = 30o.

Cold roll forming is a sheet metal forming process in whichthe bending occurs gradually in several forming steps from an undeformed strip to a finishedprofile. Althoughsimple appearance, the process is influenced by several parametersthat complicate the process design and control such as springback.
The main purpose in this article is to determine a simple criterion for the springback and to introduce a fast solution to obtain it and therefore artificial neural network was proposed for achiving this goal. Cold roll forming of a channel section in the first station was simulated by a commercial package named “Msc Marc Mentat”. The data obtained from the finite element simulations were used as training and testingsetsfor neural networks. Perfect performance of neural network was proved when the neural network outputs were compared with the testing set that did not exist in the training set.

The need for mirror-finished surfaces has grown rapidly in recent years. This is due to improvements of new products application in high technology industries. New requirements urge new production methods. One of which, in the field of machining technology, is Magnetic Abrasive Finishing. This results in surface roughness of materials in the order of sub-micron and nano level. The technology is based on the magnetic field force, which is exerted on the abrasive powder and runs the powder tool on the surface of work piece.
The process was applied to flat planes. A special apparatus was designed and made for implementation of experiments. Many properties of different factors affecting this process were examined and their influence on the surface roughness was cleared.

Machining of steel inherently generates high cutting temperature, which not only reduces tool life but also impairs the product quality. Further, the lubricant effect deteriorate the working environment and lead to general environmental pollution. In this work, the cutting tool used is uncoated carbide insert with st37 steel as workpiece material to measure the temperature of the tool-chip interface in dry turning. Two different approaches are implemented for temperature measuring: an embedded thermocouple into the cutting tool and infrared camera. Comparisons are made between experimental and FE results. The influence of cutting speed, feed rate and depth of cut on the temperature are investigated. Afterwards, an expression for the effects of cutting conditions on tool temperature are determined using a design of experiment developed by factorial regression method. With the aid of experimental results is concluded that the main factors of the increasing cutting temperature are, cutting speed, feed rate and depth of cut respectively, It is also determined that interaction between cutting speed and feed rate has maximum effect on increasing in cutting temperature.

This paper presents a new, bi-criteria mixed-integer programming model for scheduling cells (part families) and parts within each cell in a manufacturing cellular system. The objective of this model is to minimize the makespan and inter-cell movements simultaneously, while considering sequence-dependent cell setup times. In the CMS design and planning, three main steps must be considered, namely cell formation (i.e., part families and machine grouping), inter and intra-cell layouts, and scheduling issue. Due to the NP-hardness of the proposed model and the scheduling problem in the CMS, a genetic algorithm (GA) as an efficient meta-heuristic method is proposed to solve such a hard problem. Finally, a number of test problems are solved to show the efficiency of the proposed GA and the related computational results are compared with the results obtained by the use of an optimization tool.

In this paper, we consider the problem of simultaneously determining the amount, timing and location of progress payments in projects to maximize NPV of the cash flows. Due to the combinatorial nature of the problem, for the first time, we propose an iterative two-stage heuristics where payment scheduling is determined in the first stage ones activities are fixed, and in the second stage activities are rescheduled to improve contractor NPV by fixing the amount and location of payment scheduling. The two stages iterate up to achieve ideal solutions. In the first stage, two objects are considered; maximization of contractor NPV and maximization of client NPV. Two Meta heuristics; genetic algorithm and simulated annealing are designed and the results are compared. By standard test problems with 120 activities, whole performances of the algorithm is considered and effect of model parameters on NPV and completion time for both objective functions is measured. In addition, effect of the second stage on project feasibility and contractor improvement is considered. The result shows that the proposed algorithm is able to achieve non-dominated solutions in consequential iterations.