Industrial Management Journal
Year:2015 | Volume:7 | Issue:2 |Papers Count:9

Maintenance is one of the Inseparable parts of each Industry and relations between this part and others consist of many dynamics and feedbacks. By this regard systems dynamic is a tool that can be used to analyze this part. In this paper for a company that produces Wire and cable, cause and effect (feedbacks) between maintenance and others part are modeled. After creating stock-flow diagram, model validation analyzed with Behavior Reproduction, Extreme Condition, and Sensitivity test. Also after model validation, effect of changing companies attitude from corrective maintenance to preventive maintenance, discussed. Results show this shifting is beneficial for company from different views and increase sales and customers. By this regard company managers should increase their Attention to preventive maintenance.

Increasing of energy demand and decreasing of water resources, could make the future energy production as a big challenge. Climate change is one of the main reasons for water resources limitation. Future precipitation and air temperature, change hydrological conditions and directly effect on the hydropower production. For showing the future condition and making it possible to manage the hydropower, a mathematical model is developed and is run under Lingo optimization package. Climate changes are evaluated by establishing a group of scenarios of hydrological parameters. In this research a 30 years historical data of Karun4 basin is used to establish the monthly temperature-evaporation models and series of multi-variable discharge models. By using these models, future discharge scenarios are computed by the downloaded scenarios data. The results show a 17.2% reduction on precipitation, a 22.6% increasing on air temperature and a 26.1% increasing on the evaporation. These all cause a 10.9% reduction on the river discharge at the dam entrance. By managing the PF and taking it equal to 0.2, production optimization results a range of reduction between 12 and 46 percent with the average amount of 20% in energy production under a series of restrictions from climate change, plant characteristics and future energy demand.

Nowadays, customers ask for high quality products with less cost. So, the organizations such as Iran Transfo Rey are looking for a solution to survive longer. Implementation of lean production can lead the company to its target. The main goal of this research is evaluating the readiness of Iran Transfo Rey Co. for performing the Lean Production System through dimensional analysis model. In this regard, 8 components and 66 factors have been recognized through conducted studies and their conformity to Lean Production was studied. The current research methodology is survey model including one main question and 8 sub-questions. Data was gathered through interview to experts and completing the questionnaires. Paired comparison technique was used for analyzing data. Validity of questionnaires approved by Experts and respectively final assessment was done through test re test. Findings show that Iran Transfo Rey Co. was 49% away from full conformity to lean production; and components including organization and leadership, human resource management and production process management had the most importance for lean production achievement.

This prioritization of the projects in the organization is a multi-criteria decision making (MCDM) that because of the uncertainties existing in experts judgments, these cannot be represented accurately with numbers. The scope of this research is the introduction of the Grey system theory (Grey Possibility Degree Method) and application in ranking strategic organizational projects in an uncertain environment. First, qualitative indicators, which were extracted from the company’s strategic documents (strategic indicators), are weighted using Grey verbal variables. Subsequently, the effect of each indicator on the projects was investigated. After that, using the GPD algorithm, the projects under study were ranked by looking at the probability of how close each choice was to the preferred choice. Based on the probabilities found from studying each project, the choice that was closest to the preferred choice was ranked higher and using the above method, have been judged by the company executives as logical and acceptable.

In today's competitive world, establishıng a proper system of evaluating firms performance is essential. The purpose of this study is to evaluate the financial performance of pharmaceutical, basic metals and automotive parts companies using a new method. The fuzzy AHP is used for weighting the performance evaluation measures and Fuzzy TOPSIS and fuzzy Vikor is also used to rank the companies in this study. A combination of traditional performance evaluation measures and value-based me measures to evaluate the performance and ranking of pharmaceutical, basic metals and automotive parts companies are used in 1388. The population of this study includes pharmaceutical, the manufacturer of basic metals and automotive parts companies listed in Tehran stock exchange market. Ranking fuzzy approach to ranking of the companies listed in stock exchange significantly enhances the accuracy of the input data to the ranking softwares. The results presented two new accurate models of performance evaluation. These models can be useful to variety of groups such as investors, stock market and other users.

In the last two decades due to globalization of supply chain, enormous changes occurred in chains. Leaders in this field, always facing new risks and disorders that should prepare themselves to deal with them. In the recent years, sanctions as one of the most serious risks have damaged the supply chains. However, in the research related to global supply chains, modeling of disruption has been neglected. The purpose of this study was the modeling of drug supply chain at the tactical level in terms of sanction impairing. Physical and financial flow and their disruption in the term of sanction have been modeled simultaneously. To complete the financial flow, financial statements have also been modeled. One of the newest approaches named Robust Possibilistic Programming has been used for the modeling of the uncertainty of the problem. The model has been implemented on a drug organization called Atra and the results have been analyzed and validated by the optimization software Gams. The results show a robust and resistant system in the case of sanction disruption that without violating the constraints of the problem shows the appropriate measures to deal with the problem.

The scheduling problems are the non-polynomial problems-hard (NP-Hard), is to solve it, and meta-heuristic innovative method compared with the exact method require less time and memory. In this research, developed imperialistic competitive algorithm used to solving the single-mode resource-constrained project scheduling problem. also the basic feasible solution algorithm used in order to increase the rate of developed imperialist competetive algorithm by remove the unfeasible search space. The proposed algorithm is tested on a set of standard problems PSPLIB Library and the performance is compared with some existing methods. Test results of the proposed algorithm show effectiveness and feasibility of algorithm to solve standard problems. To evaluate the performance of algorithms for solving problems in real field, two projects that carried out by the Quds Force (supplies petrochemicals project in Kermanshah, Kermanshah Petrochemical Project Setup Utility) are modeling in RCPSP and solved by using the proposed algorithm.

Rough set theory is a new mathematical approach to analyze the imperfect knowledge. It does not need any preliminary or additional information about data and provides efficient methods, algorithms and tools for finding hidden patterns in uncertain data. In this study, RST has been used to extract the rules from the data of energy audits of buildings. Since part of building energy audit data related to assessment of occupants comfort level and other data related to the technical analysis of the buildings so in this research, a decision attribute and eleven conditional attributes have been selected and rules inference have been done using ROSETTA software. Due to the different algorithms of data complement, discretization, reduction and rule generation, four rule models have been constructed based on the conditions of this study. Cross validation is used for evaluation of the model results. Finally the best model was chosen with fourteen rules and 99.8 percent of accuracy. The model demonstrate that the core attribute of buildings is "uncontrolled area of buildings". It means that if the value of this attribute is calculated the 14 rules can be used to accurately predict the level of employees comfort in the buildings.

Suitable supplier selection is the most important factor in supplier chain management; so that correct decisions in this phase, caused to reduce costs, make permanent relationship with suppliers and strong competitive strategy in market. In this paper, by reviewing the past articles, important related criteria found and then weighting of criteria and evaluation of alternatives were done with fuzzy Delphi. By ranking the alternatives in fuzzy TOPSIS, five thresholds obtained for grouping in the future. The results that obtained from these computations, converted to knowledge base (KB) of Expert System for Supplier Evaluation (ESSE). The ESSE was designed in Java Expert System Shell (Jess), so that its KB could be updated in the future. To make a user friendly interface, java language was used. The proposed system and experts individually evaluated some sample alternatives and by compare the results, they were very close.