The present investigation presents a stochastic model for a flexible Manufacturing system consisting of flexible machine, loading/unloading robot and an automated pallet-handling device. We consider unreliable flexible Manufacturing cell (FMC) wherein machine and robot operate under individual as well as common cause random failures. The pallet-handling system is completely reliable. The pallet operation times, loading/unloading times and material handling times are considered to be random and exponentially distributed. By constructing governing equations for various system states at equilibrium, the steady-state probabilities are obtained. Some system characteristics namely utilization rate of the handling system, utilization rate of the production machine and utilization rate of the robot etc. are obtained. Some special cases are also discussed for reliable and unreliable cells. Sensitivity analysis is facilitated to examine the effect of parameters on system performance by taking numerical illustration.

One of the important challenges that in today's business environment managers are faced with is managing supply chain in an efficient and effective way. Supply chain management is a multidisciplinary subject, but despite of attentions that some disciplines pay to SCM, strategic management didn’t pay enough attention to this subject. But strategic management can play an important role to help supply chain in achieving strategic goals. In this research, after complete study of literature, new model for formation supply chain strategy is recommended, and this model is applied in real case. After recommending this model and clarifying supply chain strategy of case study organization, Manufacturing system that is compatible with this strategy is selected by AHP approach.Information for decision making gathered from experts and owners of case study organization.

Cellular Manufacturing system (CMS) is highly important in modern Manufacturing methods. Given the ever increasing market competition in terms of time and cost of Manufacturing, we need models to decrease the cost and time of Manufacturing. In this study, CMS is considered in condition of dynamic demand in each period. The model is developed for facing dynamic demand that increases the cost of material flow. This model generates the cells and location facilities at the same time and it can move the machine (s) from one cell to another cell and can generate the new cells for each period. Cell formation is NP-Complete and when this problem is considered in dynamic condition, surly, it is strongly NP- Complete. In this study, genetic algorithm (GA) is used as a meta-heuristic algorithm for solving problems and evaluating the proposed algorithm, Branch and Bound (B & B) is used as a deterministic method for solving problems. Ultimately, the time and final solution of both algorithms are compared.

Mechanisms of assistive mechanical-movement and therapeutic devices are derived from treadmill, walker and manual sliding and sliding movements, where a person is placed on a skeleton of a cubic-shaped rod and rotates the front wheels by 180 degrees by moving and sliding one of the handles and by moving the second batch, the remaining 180 degrees of forward rotation is made and the device moves in successive motion. The technical background of the invention is in the field of rehabilitation engineering or assistive devices for people with movement disorders and disabilities. The wheels are elastic, and the electronic eye in front of the walker collides with the brakes. The lower part is mounted independently of the treadmill for each leg, with the simultaneous application of different loading mechanisms for the lower limbs, which allows the person to move through the rear wheels and move the machine forward. In addition to ease of movement for the person with a variety of disabilities and lower extremity abnormalities, this device does not apply pressure to the injured foot or both legs.

In the cellular industry, the components of products are manufactured by multiple companies that are distributed across di erent regions, hence increasing production costs. In this regard, the present study aims to introduce a cooperative cellular Manufacturing system to decrease these costs. To this end, a mathematical programming model was proposed to estimate the production cost in the case of companies working independently, and the model was then extended to consider coalitional conditions in which the companies cooperated as an integrated cell formation system. A key question that arises in this scenario is how to arrange the cells and machines of multiple companies when their cell formation systems are designed cooperatively. Through a realistic case study of three high-tech suppliers of Mega Motor Company, we demonstrated that these companies could reduce the costs using a cooperative cellular Manufacturing system. Then, the cost savings of each coalition of companies obtained from cooperation was computed to get a fair allocation of the cost savings among the cooperating  rms. Four cooperative game theory methods including Shapley value, -value, core-center, and least core were then proposed to examine fair sharing of cost saving. A comprehensive analysis of the case study revealed signi cant managerial insights.

In recent years, flexible Manufacturing system as a response to market demands has been proposed to increase product diversity, optimum utilization of machines andperiods of short-term products. The development of computer systems has provided the ability to build machines with high functionality and the necessary flexibility to perform various operations. However, due to the complexity and the random nature of these problems, deterministic algorithms are not highly accurate andefficient enough. In this paper, computer simulation models are used to optimize flexible Manufacturing system FMS). The objectives of this paper are included: the optimal time served in each unit, the optimal number of servers in each unit, and the optimum number of domestic transportation fleet based on type. At the first step, source-destination traffic matrix is presented for development, including: service time and traffic volume are used. The computational results show the accuracy and efficiency of using simulation tools in these problems.