جستجوی مقالات مرتبط با کلیدواژه « ریسک » در نشریات گروه « صنایع »

The ability to monitor supplier performance is a critical capability to maintain a strong organization-supplier relationship, especially for organizations where the supplier plays a significant role in their end product and market retention. In this article, a multi-variable multi-profile monitoring model is presented, taking into account the risk conditions in two stages for monitoring the quality of parts and supplier products. In the first step, the criteria and indicators for evaluating the quality process as well as the risk function are extracted according to the library resources and the opinion of experts and elites of the relevant industry. In the next phase, in the first phase of monitoring, using the Hotelling’s  Statistic Based on the Successive Differences, the parameters of the model are calculated and monitored, and in the second phase, the likelihood ratio method is used to monitor the supplier's quality process over time, so that if the presence of a warning will show the control chart in the shortest possible time. This model has been implemented in the automotive industry of Iran Khodro Company and the supplier of gearbox parts by Niro Travezah Company.

Knowing the real costs of a project, correctly estimating them and identifying the risks involved in resource allocation for projects such as the construction of a petrochemical unit whose resources are expensive or difficult to access, is of particular importance. By using costing methods in conditions of risk and uncertainty, more reliable cost information can be obtained. By examining past studies and researches in the field of costing, it was found that their focus was mostly on carrying out activities, and less attention was paid to the risk factor. In this article, the use of the ABC approach, which focuses on identifying activities and cost centers, has been discussed in the form of a mathematical model whose purpose is to minimize the risk of resource allocation to activity centers based on the desired limitations in costs and resources. Due to the fact that the numerical values of the parameters in the general model, such as cost and time, have uncertainty, risk-based resource allocation modeling has been considered. To test the proposed model, the main activities of the construction and installation stage of a petrochemical unit were considered, and after collecting the necessary data, the steps of the compiled model for resource allocation and the steps of the activity-based costing approach have been implemented. The results show that there is a difference between the costs calculated based on the allocation of resources of the proposed model for the activity centers and the costs estimated according to the past data.

The production routing problem is created by combining the two problems of lot sizing and vehicle routing. Previous research has examined the effectiveness of this combination in reducing costs. In this paper, the production routing problem is considered with the aim of minimizing the risk of production and distribution of hazardous materials. Attention to social and environmental criteria related to sustainability is being increased by researchers today. Hazardous materials are harmful to human health and the environment. Accidents related to these materials often have far-reaching adverse consequences. Risk is a danger measurement criterion for operations related to these materials.

The problem is modeled as a mixed integer program. The risk function in the proposed model is nonlinear and depends on the load of the machine, the population risk, and the type of hazardous material. Given that solving the mathematical model with the nonlinear objective function is more difficult, this function is approximated by a piecewise linear function.

In this research, 8 standard instances have been used to evaluate and solve the model and compare the two nonlinear and linear models. The results show that by using the approximate model, a better answer can be achieved at the same time. Through sensitivity analysis, the effect of changes to production capacity and warehouses on risk has also been looked into.

Originality/Value:

 This research proposed the production routing problem for hazardous materials according to sustainability criteria using a nonlinear mathematical model and uses a piecewise linear approximation to solve the model.

simulation method. According to the reports, the cost of fatalities and serious injuries is estimated to be 1.8 trillion per year, with an average of 3% of GDP per country. Besides, the enormous costs of accidents have caused governments to reduce their consequences and losses by investing in this area. Consequently, reducing the cost of crashes requires an effective strategy and one of the effective strategies is identifying and eliminating Hot Spots. However, they are often prioritized due to financial constraints and so, their immunization is delayed. Using the capacity of the private sector, especially insurance companies interested in this investment, can be very helpful in reducing the constraints. Today, insurance companies' cooperation in promoting road safety is well known in most developed and even developing countries. Roads condition play a key role in road safety and the geometrical features, road design, and infrastructure have a significant impact on accidents. As a result, one of the most important areas of cooperation between government and insurance companies can be defined in road safety projects. On the other hand, studies show that the design, construction and management of highways under PPP has a positive relationship with the results of road safety and the number of annual accidents and the number of fatalities in the Public-private partnerships is less. To this end, a model based on the Public-Private Partnership (PPP) approach is developed for the partnership of government and private sector in immunization projects and assessment of investment risk. This model helps in deciding on investment and risk assessment by calculating the value at risk of IRR for the insurance company and the public sector. In the end, the specifications and cost information of a Hot Spot is taken into account and the IRR for each party is calculated according to the level of confidence desired.

Increasing the population, followed by increasing human needs and problems related to transportation, has led managers to seek for solutions by the goal of increasing economic profitability and reducing costs. Therefore, in this study, a set of location decisions, vehicle routing and inventory management has been used as the main tools to face with these problems.

model has been solved and validated by Gams software using Epsilon method in small scale. Since this is one of the NP-Hard problems, meta-heuristic algorithms, MOPSO, MOFF, MOIWO, NSGA-II have been used to solve large-scale problems.

The results of all comparative criteria show the superiority of the MOIWO algorithm over other algorithms and the appropriate efficiency of these methods in solving the mathematical model, especially in high dimensions and short times.

 In this study, the design of hazardous materials transportation network is considered by considering the decisions related to location, routing, inventory. For this purpose, a new multi-objective mathematical model with the objectives of minimizing cost, minimizing travel time and maximum social responsibility is presented. This mathematical model can be used in different areas and different dimensions.

The failure probability and establishment risk of startups is high due to the required high technical knowledge and added value, new product developments, lack of financial sources and need for specialists. By the use of risk management approaches, one can systematically evaluate the risks related to the decisions and improve the success probability by studying the corresponding opportunities and treats. In this paper, we consider the development phase of Nanotechnology startups as a project and propose a quantitative framework for analyzing the risk response strategies based on the PMBOK standard and a combination of FMEA, TOPSIS, and optimization model. Using FMEA, we can study the effect of risks and risk responses on the startup goals. TOPSIS helps to analyze the impact of risk responses on all the risk factors. The bi-objective optimization model is formulated subject to the prevailing constraints such as budget, time, production capacity and incompatibility of strategies. The proposed optimization model is for determining the Pareto frontier of risk and profits that as a decision tool may help managers to select the appropriate risk response strategies. The validation and sensitivity of proposed framework is analyzed applying it for a Nanotechnology startup in Yazd science & technology Park. Although the complete enumeration can be used to solve the small and medium instances, we propose the Epsilon constraint method successfully in order to solve the large-sized problems. The validation of framework confirm that it can apply to identify, evaluate and select of optimal risk response strategies. Also, the sensitivity analysis results show that the estimation quality of the model parameters particularly costs has a great impact of the outcomes. Therefore, developing the quantitative methods such artificial neural network to estimate the key parameters such as costs, revenues and risk levels is as a direction for the future study.

The automotive industry is one of the country's most important industries, and in fact, it is economic stimulant of many other industries. The purpose of this study is to identify and investigate the impact of supply chain’s risk factors on financial performance of IranKhodro Khorasan Company, identifying the major and important supply chain risks, required questionnaires have been prepared by relying on the literature of the case and involving the valuable comments of Iran Khodro Khorasan's supply chain specialists and according to that the relative importance and ranking of each risk in Iran Khodro Khorasan Co. is determined.(using MCDM techniques including AHP techniques for weighting the measurements craiterian, VIKOR and TOPSIS techniques were used to ranking the risks.)
Considering the fact that in this research the specialists from all party of Iran Khodro Khorasan’s supply chain of have been consulted, the results of this study provide the possibility for senior company managers to have better capabilities in identifying and dealing with risks specially with unexpected risks and, by effective coping and timely response, eliminates or minimizes the negative and destructive effects of risks, and can also help to make strategic decisions and develop operational plans to deal with risks.
According to the results of this study the risks of: inappropriate material planning, inventory updating failure, truck drivers strikes, delayed delivery of raw materials and parts from suppliers, and financial problems,are as the most important and influential risks of Iran Khodro supply chain considering the effection on financial performance.

The rapid growth of technology, increased risk-taking in global markets and the ever-increasing changes in customer needs have put pressure on new product development teams.There are many risks in the process of developing new products in all industries intrinsically. Therefore, understanding, identifying and ranking the risks is of strategic importance for companies. The purpose of this study is identifying and ranking the risks in the process of developing a new product in Iran's automotive industry, based on the literature of research and specialized interviews conducted with experts, the main indicators have been identified. The main risk indicators in the new product development process are (organizational, managerial, financial, manufacturing, marketing, and technical) and related to the phases of new product development. Therefore, these indicators will be ranked in this study. Regarding to the relationship between the criteria and the sub-criteria, the DEMETL technique will be used to identify the relationship model, and based on the network of identified relationships, the network analysis process (ANP) technique has been used for ranking the criteria And Sub-criteria with Super Decision software. The result of these techniques suggests that organizational risk is the most important parameter in risk management of the new product development process and the technical risk is the least important. On the other hand, sub-criterion of incorrect planning of resources has the highest importance and sub-criterion of lack of sufficient communications is the least important in the automotive industry in Iran.

Risk management is a significant issue in supply chain management. Improving the ability to control and manage the risk, enables the companies to be more successful in competing with other companies and decrease the expected long-term loss. In this manuscript, a mixed integer linear programming model for designing the green supply chain is presented. This model aims to minimize the cost, greenhouse gas emissions, and risk. Risk of supplying the raw materials and transportation in all levels of supply chain are under uncertainty. Furthermore, cost of raw materials is suggested by suppliers to producers with an incremental discount. The initial modelling is turned into a deterministic one using Bertsimas and Sim budget of uncertainty approach and consequently solved by GAMS software to manage risk. Furthermore, the uncertain parameter is analyzed and using various amounts the obtained result has been assessed and evaluated. The results show that the risk function is the most important factor in objective function, because parameters of risk function are subject to uncertainty.

Nowadays, Organizational survival depends on the tendency toward new products and the use of new ways to create them. Developing new product is a process through which a new product or a service is offered to the customers. More precisely, the new product development process involves using resources and capabilities to create a new product or improve an existing product. Given the shorter life cycle of products and technology developments, new product development process in the growth, survival, and competitiveness of the utmost importance. There are several risks during new product development process; that in general, are divided into three major categories: technological risks, organizational risks, and marketing risks. According to studies, the technological risks are one of the most important risks. Perceived technological risk refers to a firm’s inability to completely understand or accurately predict some aspects of the technological environment as it relates to NPD projects. Hence identifying and reducing these risks helps to increase the success rate of the new product development process. In this research, by reviewing the literature on the areas of the new product development process, risk and risk management, 20 types of common technological risks in new product development process are extracted from the literature and using a number of experts from Malek Ashtar University of Isfahan who are specialized in this field, they are prioritized by the Analytical Network Process (ANP).

Iran's carpet market in the past has been great. But in recent years we observe a decline in the market for this product and the lack of proper investment in this industry. Identifying risks in this industry can make a lot of contribution in order to better manage these risks. In the first stage of these research, we interview carpet industry experts in order to modify the parameters of risk assessment using the Delphi method. In the second phase of the study we distributed questionnaire among hand-made carpet producers in the cities of Kashan, Nain, Isfahan, Najaf Abad and Qom. The first sample size is 15 and the second sample size is 264. In this research, the FMEA method has been used to investigate the risks. In order to improve the methodology, Delphi was used to identify the risks, and in the second step, TOPSIS was used to rank the risks. According to the rating of risks, knowledge of financial management, knowledge of customer's needs, using the pull production system and familiarity with customs laws are the main recommendations mentioned in this research.

In the electric power industry, as one of the key energy industries, the electrical energy generated in power plants is transmitted to distribution substation via electric power transmission lines. Finally, it is delivering to consumers. The purpose of construction of the transmission lines and distribution substations is to meet the needs of customers, increase stability and reliability of the system, and exchange with neighboring countries. Iran's overhead lines projects (transmission and sub-distribution) are monitored by regional electric companies of the country with the aim of supplying electricity to different provinces in order to meet energy requirements and customer satisfaction. The main phases of the projects are Initial phase, Design and Engineering phase, Procurement phase, Implementation phase, and the Final phase. In each phase, projects can be faced with specific and effective risks that can affect their aims. These risks caused the majority of the mentioned projects to face with events that each of them can increase the amount of time, cost, and decrease the quality in turn. Perhaps, if risk management is done effectively, the success of these projects, at least in terms of time and cost, will increase. However, with project managers that act only on the basis of their taste and knowledge, the risk management will not have the proper output. Risk identification of these projects on one hand and their ranking on the other hand as parts of complex process of risk management are the major steps of a proper evaluation and timely and appropriate response to these risks. Therefore, in this study, risks are identified based on the librarian studies, semi-structured interviews with experts, and work breakdown structure (WBS). List of identified risks contains 385 risks. Then, according to developed methodology based on PMBOK standard, flexible qualitative analysis was performed, and risk scores in each of areas of ``Time'', ``Cost'', ``Quality'', ``Time-Cost'', ``Time-Quality'', ``Quality-Cost'', and ``Time-Cost-Quality'' were accomplished. After analyzing, the 84 key risks are identified. At the end, the key risks are ranked using "Time-Cost-Quality" score and clustered using K-Means method. The results showed Execution and Contractor Management category include the most number of risks.

In the recent decades, environmental concerns have been attracted more attentions of researchers because of hazardous eects that create by logistics networks on the human's environment. Nowadays, customers are interested in products that are amicable with environment and can be recovered. Therefore, manufacturers are forced by customers not only to supply environmentally amicable products but also to be responsible for the returned products. On the other hand, natural and political conditions (e.g., natural disaster, disease, sanctions and wars) cause risk and indemnify the structure of logistic networks. The risks can be could be divided in two groups. Internal risks (e.g., delay, interrupt and failure) can be controlled by the prediction of managers; however, external risk (e.g., ood, earthquake and thunder) cannot be controlled by managers. Hence, in this paper, we develop a two-stage stochastic model for an integrated forward/reverse logistics network with eight echelons considering risk and environmental conditions. Three echelons in forward logistics (i.e., suppliers, plants and distribution centers) and four echelons in revers logistics (i.e., collection centers, repairing centers, dismantle centers and disposal centers). First, a deterministic mixed-integer linear programming (MILP) model is developed for the integrated logistics network to avoid sub-optimality caused by the separated design of the forward and revers networks. Then, the two-stage stochastic model of the presented MILP model is developed by using a scenario-based approach. After that we analyze the eect of changes in demand of customers in both deterministic and stochastic models and compare them in each scenarios. Both models have been solved by GAMS software considering each scenarios. Furthermore, he numerical results show that the stochastic model can handle the uncertainty data as well and both models can be feasible for all scenarios. Finally, the conclusion is provided. We can consider multiple periods, pricing, routing and other meta-heuristic algorithms in the represented model for future studies.

The Boilers as a group of pressure vessels have a great importance In terms of occurrence catastrophic events in Process industries. The aim of this study Determination of critical activities in the exploitation of the boilers and safety analysis of exploitation of steam boilers. In this study after viewing the critical activities of operation practices boilers, Imaging, interviews and reviewing the documents Determined by the Expert Working Group and by using the job safety analysis method Implementation trend of these activities was evaluated. After identification of hazardous activities during the operations, the risk assessment was done. Finally According to the results, it was determined that the most risky activity is carried out, For Installation of Tower crane and safest activity is for boiler commissioning. The important point is that selection of an appropriate technique plays an important role in identifying a higher number of hazards.