hasan haleh

Developing a robust platform architecture can give companies a competitive edge and enhance product future generations and customer satisfaction. However, in order to develop a product platform architecture, there is a need for some kind a product variety design that concurrently manages costs and the supply chain process, and focuses on ease of use and improved availability to components. In this research, the design for variety (DFV) approach and two indices, generational variety index (GVI) and coupling index (CI) are used to measure a product architecture. Using the quality function deployment (QFD) and design structure matrix (DSM), design indices for product diversity are identified and ranked. Additionally, the design for variety approach is modeled simultaneously with the concepts of design for cost (DFC), design for availability (DFAv), and design for supply chain (DFSC) to yield a practical mathematical model for the development of the product platform architecture, which aims for product diversity, improved availability, reduced costs, and supply chain management. The case study of the current research is a phased array radar, which is optimized using the latest techniques (genetic algorithm) and MATLAB software to solve the problem. After implementing the model, considering four objectives including total cost, availability, supplier evaluation score (competency) and replaceability (variety), and seven main parameters of the model, sensitivity analysis and other comparisons and results are presented, which analyzes the relationships between objectives, the impressment and affectability of objectives and model parameters on each other. Regarding the comparison of objectives, the results generally show the inverse relationship between the total cost objective and the other objectives, and the direct relationship between the other objectives with each other. Additionally, the results of the sensitivity analysis performed indicate that the availability objective had the highest effect and replaceability (variety) and the evaluation score of suppliers (competency) and total cost also took next place.

In this research, a combined statistical process control model is presented to identify factors affecting efficiency and quality in manufacturing and component manufacturing industries, and then controlling and optimizing these processes is considered. Manufacturing and component industries are considered as the main body of the country's industries for case study and implementation. Clustering techniques are used to discover factors affecting efficiency. And then using decision tree algorithms to predict efficiency and quality in these industries, and in the final stage, control charts of dispersion and average variables are used to draw control charts. The comparison table of the parameters is prepared by the output of the Clementine software, and RapidMiner software is used in the neural network section. The results obtained from the identification of influencing and forecasting factors are close to the target values from a technical point of view, and the control charts are consistent with the technical control limits of the characteristics and are useful for optimizing the target value, which is efficiency and quality.

The current study aims to provide a framework for evaluating the large projects based on the sustainability dimensions and with agility approach using data envelopment analysis.

To this end, sustainability indicators, agility indices in project management and project management critical success factors are identified. By calculating the large projects efficiency numbers in each of attitudes include financial, social and environmental, three dimensions of sustainability and by drawing a regional graph based on the projects’ efficiency numbers in both attitudes of agiliy and project management critical success factors, the project performance is studied in both attitudes. 

Graphs and efficiency results in sustainability attutudes show that among 27 projects, just three projects are efficient in all three attitudes. In addidtion, to deliver product/service in the shortest time is the meaning of delivering value to the customer with extending the agility in project management. Also, to protect the resources for the next generation, project manager can dedicate the financial and social resources in order to control the environmental impacts of the projects in parallel with the sustainable development principles which which can be translated to be responding efficiently and effectively to the customers while meeting the requirements of the sustainable development. 

The project as a temprory organization should be managed in such a way that while adapting to the changes and being agile in responsiveness, it also keeps the time range, cost and qulity for delivering the created product/service. Agility has been proposed as an approach to gain and keep the competitiveness in a changing and unpredictable environment and it focuses on meeting customers needs while sustainability attitude does focus on the reduction of the udesireable affects of the meeting customers demands. To integrate these two concepts in the field of project management leads to the efficiency and success of the project, comprehensively.

In the modern world of business which is based on competing and delivering the best performance to achieve the organizational goals. The commercial growth development and natural resources usage can’t be gained without considering their effects. Thus, in line with the sustainable development principles, project-oriented organizations aim to be successful in project management, gain the profit and satisfy the customers. Profitability and be successful in the project performance are based on creating value for the customers, adapting to market changes, environmental constraints and to be responsive to the customers’ needs. Therefore, to successful implementation of the project management in parallel with the sustainability principles will be possible by creating the agility parameters. For this purpose, the current study, has provided an approach to identify and rank the agility factors in project-oriented organizations, based on project management critical success factors and sustainability factors, applying quality function deployment. To this end, firstly, project management critical success factors and then, agility and sustainability factors in project-oriented organizations, have been identified. Thereafter, the importance of the project management critical success factors and agility factors have been evaluated from the Isfahan Municipality’s experts’ and academia experts’ viewpoints. Afterward, Agility factors’ weights in project-oriented organizations have been calculated based on the project management critical success factors using quality fuction deployment. Finally, on the basis of the calculated weights, agility factors in project oriented organizations have been ranked.

In the real world, businesses with hybrid flow-shop manufacturing environment have faced the constraints in machinery, human resource constraints and increasing salary and have tried to use their human resource better. Given the limitations of these resources, customer delivery requirements have made the job rejection essential in order to meet distinct customer requirements. Therefore, this paper considers the dual resource constrained hybrid flow-shop scheduling problem with job rejection in order to minimize the total net cost (the sum of the sum of costs obtained from rejected jobs and total penalty cost) which has high practical and operational relevance in many industries. The present study is developed a new mixed integer linear programming model for the problem. In addition, a new improved sooty tern optimization algorithm (STOA) is proposed to solve large-size problems as well as a new decoding method due to the NP-hardness of the problem. In order to evaluate the proposed optimization algorithm, 5 well-known algorithms in the literature including (Immunoglobulin-based artificial immune system (IAIS), Genetic algorithm (GA), Novel discrete artificial bee colony algorithm (DABC), Fruit fly optimization (IFFO), Effective modified migrating birds optimization (EMBO)) are adapted with the proposed problem and finally the performance of the proposed optimization algorithm is investigated against the adapted algorithms. All results and evaluations show the good performance of the new improved sooty tern optimization algorithm.

Bank lending is one of the most important Bank activities but they have many problems by Customer credit risks or inability to repay the principal and interest on loans granted. Thus the design of scoring models to manage and control credit risk known as one of the largest bankruptcy factor of banks is necessary. Various methods such as parametric models as logistic regression and nonparametric methods as neural networks have been used to rank banking customers until now, but in this paper provide a model in scoring of Corporate client applying for credit In terms of credit risk by using hybrid ANP-Promethee method that one the hand need not to get the distribution and assumptions such as parametric models and unlike methods such as neural networks and logistic regression ranked Bank Customer by using actual data and in the other hand consider impact of expert opinions. The application of the proposed method22 index criteria is extracted 5C model validation and the weight of each was determined using ANP and the end step scoring on a sample of 25 corporate customers bank were being Promethee method.

This paper presents a new approach which is based on quality control in order to optimize supplier selection. Using inspections, removing the defected materials and considering penalties for low quality materials are the main factors which we have considered in modeling. In this model costs are divided to three parts: 1- costs of purchasing 2- costs of inspection policy 3- costs of quality and defective items. The aim of modeling is to minimizing the total cost during the planning horizon. At the end two numerical examples will be presented to explain the proposed approach.

Tendency to optimization in last decades has resulted in creating multi-product manufacturing systems. Production planning in such systems is difficult, because optimal production volume that is calculated must be consistent with limitation of production system. Hence, integration has been proposed to decide about these problems concurrently. Main problem in integration is how we can relate production planning in medium-term timeframe with scheduling in short-term timeframe. Our contribution creates production planning and scheduling framework in flexible job shop environment with respect to time-limit of each machine in order to produce different parts families in automotive industry. Production planning and scheduling have iterative relationship. In this strategy information flow is transformed reciprocative between production planning and scheduling for satisfying time-limit of each machine. The proposed production planning has heuristic approach and renders a procedure to determine production priority of different part families based on safety stock. Scheduling is performed with ant colony optimization and assigns machine in order of priority to different part families on each frozen horizon. Results showed that, the proposed heuristic algorithm for planning decreased parts inventory at the end of planning horizon. Also, results of proposed ant colony optimization was near the optimal solution. The framework was performed to produce sixty four different part families in flexible job-shop with fourteen different machines. Output from this approach determined volume of production batches for part families on each frozen horizon and assigned different operations to machines.

In this paper, the system reliability in the design stage and before production is improved. The proposed algorithm is based on the fact that the chosen structure should be practical in reality. First, possible structures for the system of interest are designed then the optimum structure is chosen for production. The proposed approach to select the optimal alternative is to determine the effective criteria for selecting process, then using analytic network process as a robust and useful technique for multi-attribute decision making.