Industrial Management Journal
Year:2019 | Volume:11 | Issue:3 |Papers Count:10

Objective: The choice of suppliers is one of the important issues in the design of industrial systems, which must be done with due regard to cost, reliability, repairability and delivery time of parts supplied and their effect on the total cost of the manufacturing system. Provide a template for selecting suppliers of a multi-state industrial system, taking into account the cost, reliability, and repairability of the system. Methods: A nonlinear integer programming model has been developed using Markov's network results and solved for a case study in two different ways and the results have been compared: (1) accurate resolution, using GAMS software, and (2) complete counting. Results: By solving this model, the order of parts of the system is selected so that the total cost of construction and operation of the system; including the cost of purchasing the components as well as the cost of reducing the capacity and the complete system shutdown during operation be minimized. The results show that taking into account the effect of components similarity on the purchase price, the delivery time and the speed of repair of components can be effective in choosing the supplier. Conclusion: In conclusion, the effect of choosing the same components is emphasized when assessing the availability and cost of the entire system.

Objective: Today, one of the most important concerns of managers is to find a way to measure the maturity level of Business Process Management (BPM) and to recognize improvement conditions. Hence, the aim of this research is to measure and plan various scenarios in order to develop business process management. A Maturity Model has three dimensions: Levels, factors and measurement tools. In this paper, the dimensions are recognized via a comprehensive literature review. Finally, they are conceptualized, measured and a scenario planning is developed. Methods: In this research, the extracted factors and indices form the basic approach of the conceptual model and are validated by a confirmatory factor analysis. Regarding the structure of the conceptual model, factors and indices of all levels of process maturity, a causal loop has been developed based on a fuzzy cognitive map that illustrates the maturity aspects and their relationships to provide scenario planning for developing maturity. Results: The developed BPM maturity model classifies the maturity levels into the following stages, primary, managed, standardized, predictable and innovative. Also, the findings show that there are 33 process concepts that lead to the development of a business process maturity level. Furthermore, by the result of this research, if the deployment level of concepts in the organization is determined, organizations can measure the level of their BPM maturity and provide scenario planning. Conclusion: 33 BPM maturity concepts can support organizations as a road map to promote maturity level from 0 to 100. In addition, the implementation of the results of this research into case study show that the current status of business processes is graded as level 3 of the maturity level and its score is 36 of 100.

Objective: This research was carried out with the aim of simultaneously examining the two categories of the most commonly encountered issues in the field of production and operations including the redundancy allocation and the buffers allocation. The study sought to optimize goals such as accessibility, system costs, and buffer capacity and for this purpose, variables such as the optimum capacity of buffers between machines, the number of high-reliability machines and their allocation, and the appropriate time schedule for maintenance and repair were investigated. Methods: Considering the categorization of emergency and preventive failures for machinery, taking into account the cost of any failure for machinery, and considering the non-exponential and increasing distribution function for a variety of failures, it is very difficult to obtain and calculate mathematical functions related to the objectives of Availability and Cost explicitly. Therefore, a combination of simulation, experimental design, and neural network approach was used to estimate these two objective functions. In order to solve the proposed model, the NSGA-II algorithm was coded in MATLAB. Also, in order to analyze the efficiency of the suggested Algorithm, the MOPSO Algorithm was used and the Algorithms were compared with each other based on the performance measures of the algorithms. Results: After applying the numerical example with the approach used, the results of the research indicate the validity of the proposed methodology for the problem under study. Conclusion: Based on the set of solutions obtained from the algorithms used, different combinations of variables (including the number of machines per station, buffer capacity and duration of repairs) can be used to achieve the appropriate level of objectives.

Objective: Technology Development Funds (TDFs) are one of the most important innovations and so financing institutions must prioritize identifying and funding technological projects, due to the limitation of financial resources. The objective of this paper is to present a Multi-Criteria Decision-Making model (MCDM) for evaluation and selection of appropriate projects in TDFs and their resource allocation. Methods: In this paper a combination of qualitative and quantitative methods is used. In the first step, important criteria for evaluating technological projects are identified by reviewing literature, reviewing documents and interviewing experts and by using the factor analysis method, the most important criteria in evaluating knowledge-based projects are determined. Then a multi-criteria decision-making model based on the Best-Worst Method (BWM) is presented considering financial, firm, technology, and market analysis and risk criteria. Results: In this study, the results of the evaluation of 20 knowledge-based projects of the applicant for the interest-free loans and industrial production loans from the Innovation and Prosperity Fund (IPF) are presented. The results of the study indicate that the weight of the evaluation criteria has a significant effect on the results of the evaluation and the approval or rejection of projects. Conclusion: A multi-criteria decision-making model based on the Best-Worst Method is presented in this study, that by using it, technology development funds can carefully evaluate the technological projects and accurately allocate limited national financial resources to the best projects. Knowledge-based companies can also focus their strategies and initiatives on critical and important issues, considering important criteria in the evaluations.

Objective: Traditional DEA models cannot determine the source of inefficiency for structures with more than one stage (network structures). Continuous two-stage structures are one of the most applicable and basic network structures, and one of their main challenges is determining the relationship between the total efficiency and the efficiency of the stage and also determining the optimum amount of intermediate variables. The available models in solving the challenges and calculating the efficiency have orib or aren’ t applicable for all two-stage structures. The purpose of this study is developing a multi-objective network DEA model that doesn’ t have the weaknesses of the previous model. Methods: In this study, it is attempted to develop a multi-objective model with a composition approach that considers the efficiency of the stages simultaneously, and also to interpret the results geometrically and compare it with the available models. The presented model was developed to multi-optimal and VRS conditions. Results: In all the models, efficiencies are between zero to one and a unit is network efficient only and only when it is efficient in both stages. Conclusion: The presented model was used in an applicable example to evaluate the sustainability of 17 supply chains and the results showed that the model does a realistic evaluation in comparison to the traditional models. In the end, the model priority over the literature review models was mentioned with examples.

Objective: The selection of an optimal investment portfolio for a long-term period does not seem logical. So the investors should update their investment portfolios over specific time periods if needed. Since the problem dimensions significantly increase after the periods, a definitive solution to the problem is not achievable. Methods: In this regard, the Multistage Approximate Stochastic Dynamic Programming has been used to make the best portfolio over each period by using a stochastic return rate. The Monte Carlo was used for scenario development, and GlueVar was selected as a risk measurement criterion. The approximation technique was used to resolve for large dimensions; however, some optimized solutions may be eliminated so we used the Genetic Algorithm for the rapid search around the optimal solution to obtain a better one, if possible. Results: Top 100 companies listed in the Tehran Stock Exchange between 2011 and 2017 were investigated. This study investigated and compared the return and risk of investment portfolios based on the proposed method, Genetic Algorithm, and stock portfolio with equal weights. The modeling was done with MATLAB and tests were carried out with SPSS. Conclusion: The results indicated a higher performance of the proposed method in comparison with the other mentioned methods.

Objective: The SWOT technique has been used to formulate strategies of a raw materials pharmaceutical producer in Iran. Methods: One of the main weaknesses of the SWOT method is that it does not rank the strategies, especially if there is a dependency between the criteria. The study also provides flexibility in the model for contribution of data such as knowledge, experience and human judgment which results in operational strategies and precise responses in the model we applied fuzzy analytical network process (FANP). Results: The priorities of the strategies in this case study are: 1-Adding high-profit margin products, 2-Increasing product efficiency and capacity, 3-Focusing on marketing and allocating a portion of sales percentage-4-Focusing and investing on exports 5-Improving the R&D process 6-Reducing the cost of sales and ultimately selling price 7-Removing products that have no economic justification. Conclusion: Applying the Analysis Network Process (ANP) causes the assumption of dependency among factors, sub-factors, and options in the Analytical Hierarchy Process, and the application of fuzzy theory eliminates the inaccuracy of the decision makers' inaccurate views.

Objective: Performance evaluation (PE) is one of the critical activities in the assessment and improvement of management systems. Performance evaluations are done with different aims and approaches. Self-Assessment (SA) is considered as one of the most important performance evaluation methods. And, learning focus is one of the strengths of SA compared to the other performance evaluation methods. Like the other PE methods, SA has some weaknesses such as human error during performance measurement. Consequently, researches have been trying to identify the human effect on the selfassessment process. Methods: To achieve the mentioned goal, the results of the sustainable excellence (H3SE) model between 121 experts of 42 Petrochemical companies have been analyzed. The role of the intervening variables in performing self-assessment tests (e. g. age, gender, educational degree, and related experience) have been investigated. Results: Result of research reveals that the mentioned variables do not have a significant intervening impact on excellence. Conclusion: Since the present research uses a biographical variable as an intervening variable, it seems that there are unknown variables that weren’ t considered. In addition because of the statistical population (Petrochemical Industries) generalizability of research finding to the other research is impossible.