in this study, the stochastic cell formation problem with developing model within queuing theory with stochastic demand, processing time and reliability has been presented. machine as server and part as customer are assumed where servers should service to customers. since, the cell formation problem is np-hard, therefore, deterministic methods need a long time to solve this model. in this study...

in order to perform preventive maintenance (pm), two approaches have evolved in the literature. the traditional approach is based on the use of statistical and reliability analysis of equipment failure. under statistical-reliability (s-r)-based pm, the objective of achieving the minimum total cost is pursued by establishing fixed pm intervals, which are statistically optimal, at which to replac...

For proper management of life cycle of machines and manufacturing facilities, it is important to perform appropriate maintenance operations, and to keep machine status for better reuse and recycling opportunity. For this purpose, a virtual maintenance system is very effective, where facility life cycle model is constructed in computer, and reliability and availability of machines are predicted ...

Joint optimization models were developed combining group preventive maintenance of a series system and production scheduling. In this paper, we propose a joint optimization model to minimize the total cost including production cost, preventive maintenance cost, minimal repair cost for unexpected failures and tardiness cost. The total cost depends on both the production process and the machine m...

The ELECTRE I is one of the most extensively used methods to solve multiple criteria decision making (MCDM) problems. In this paper, we propose a novel AHPbased ELECTRE I method of reliability design scheme decision for computer numerical control (CNC) machine. Based on the AHP method combined with ELECTRE I, the decision model is built to select the optimal design scheme. The AHP method is app...

In this paper three models derived using Machine Learning techniques (Support Vector Machines, Decision Trees and Shadow Clustering) are compared for approximating the reliability of real complex networks, such as for water supply, electric power or gas distribution systems or telephone systems, using different reliability criteria.

Reliability as a function of failure rate, mode of operation and man-machine interactions, re­ dundancy, and serial and parallel shredding was introduced to provide an analytical approach to the evaluation of a refuse shredding system. Vari­ ous economic factors were combined with the reliability analysis to optimize the selection of system components and arrangement.

This paper proposes an efficient algorithm to evaluate system reliability for many real-life systems such as manufacturing, telecommunication and computers systems. A multicommodity stochastic-flow network is constructed to model a manufacturing system in which each node stands for a machine station, and each arc stands for a transmission medium (shipping machine or conveyor). Four characterist...

Behaviour models are the most commonly used input for predicting the reliability of a software system at the early design stage. A component behaviour model reveals the structure and behaviour of the component during the execution of system-level functionalities. There are various challenges related to component reliability prediction at the early design stage based on behaviour models. For exa...

The cell formation (CF) is one of the most important steps in the design of a cellular manufacturing system (CMS), which it includes machines’ grouping in cells and part grouping as separate families, so that the costs are minimized. The various aspects of the problem should be considered in a CF. The machine reliability and the tool assigned to them are the most important problems which have t...