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Showing 20 results for Assessment

F.d. Javanroodi , K. M. Nikbin ,
Volume 17, Issue 3 (9-2006)
Abstract

There is an increasing need to assess the service life of components containing defect which operate at high temperature. This paper describes the current fracture mechanics concepts that are employed to predict cracking of engineering materials at high temperatures under static and cyclic loading. The relationship between these concepts and those of high temperature life assessment methods is also discussed. A model for predicting creep crack growth initiation and growth in terms of C* and the creep uniaxial ductility is presented and it is shown that this model gives good agreement with the experimental results. The effects of cyclic loading on crack growth behaviour are considered and fractography evidence is shown to back a simple cumulative damage concept when dealing with creep/fatigue interaction. Finally a discussion is presented which highlights the important aspect of life assessment methodology for high temperature plant.


M. Haghpanahi, H. Pirali ,
Volume 17, Issue 3 (9-2006)
Abstract

Finite element analysis of a tubular T-joint subjected to various loading conditions including pure axial loading, pure in-plane bending (IPB) and different ratios of axial loading to in-plane bending loading has been carried out. This effort has been established to estimate magnitudes of the peak hot spot stresses (HSS) at the brace/chord intersection and to find the corresponding locations as well, since, in reality, offshore tubular structures are subjected to combined loading, and hence fatigue life of these structures is affected by combined loading. Therefore in this paper, at the first step, stress concentration factors (SCFs) for pure axial loading and in-plane bending loading are calculated using different parametric equations and finite element method (FEM). At the next step, the peak HSS distributions around the brace/chord intersection are presented and verified by the results obtained from the API RP2A Code procedure. Also the locations of the peak hot spot stresses which are the critical points in fatigue life assessment have been predicted. 


F. Sanati , S.m. Seyedhoseini,
Volume 19, Issue 1 (3-2008)
Abstract

Abstract: At the last decade of the 20th century, Womack et. Al introduced Lean concept to the industrial world. Since 1990 up to now, existed studies mostly have focused on lean production in the step of manufacturing, but in this research leanness concept has developed in the plant life cycle. In this paper leanness concept will be described as elimination of wastes in the phases of investment, plant design & construction(hardware), organization & systems design (software) and these three steps will be added to, elimination of previously described seven wastes in production step. For this purpose at first, the types of wastes in the above mentioned phases are defined by using Axiomatic Design methodology. After defining the types of wastes, a model for assessment of leanness is submitted. In this quantitative model, amount of leanness in each phase will be determined and combined to make a unique measure for total leanness. Dimensions of leanness are shown for quick understanding, by using a spider diagram. In the last section of the paper, the results of an example of the application of this model in fan industry are brought. This example shows the simplicity and powerfully of the model to determine the leanness in before production phases. © 2008 Authors all rights reserved.

 


H. Arabi, M.t Salehi, B. Mirzakhani, M.r. Aboutalebi , S.h. Seyedein , S. Khoddam,
Volume 19, Issue 5 (7-2008)
Abstract

Hot torsion test (HTT) has extensively been used to analysis and physically model flow behavior and microstructure evolution of materials and alloys during hot deformation processes. In this test, the specimen geometry has a great influence in obtaining reliable test results. In this paper, the interaction of thermal-mechanical conditions and geometry of the HTT specimen was studied. The commercial finite element package ANSYS was utilized for prediction of temperature distribution during reheating treatment and a thermo-rigid viscoplastic FE code, THORAX.FOR, was used to predict thermo-mechanical parameters during the test for API-X70 micro alloyed steel. Simulation results show that no proper geometry and dimension selection result in non uniform temperature within specimen and predicted to have effects on the consequence assessment of material behavior during hot deformation. Recommendations on finding proper specimen geometry for reducing temperature gradient along the gauge part of specimen will be given to create homogeneous temperature as much as possible in order to avoid uncertainty in consequent results of HTT.


, , ,
Volume 20, Issue 1 (5-2009)
Abstract

Fuzzy Cognitive Maps (FCMs) have successfully been applied in numerous domains to show the relations between essential components in complex systems. In this paper, a novel learning method is proposed to construct FCMs based on historical data and by using meta-heuristic: Genetic Algorithm (GA), Simulated Annealing (SA), and Tabu Search (TS). Implementation of the proposed method has demonstrated via real data of a purchase system in order to simulate the system’s behavior.
S.m. Mohammad Seyedhoseini , M. Ali Hatefi,
Volume 20, Issue 1 (5-2009)
Abstract

  Selecting an effective project plan is a significant area in the project management. The present paper introduces a technique to identify the project plan efficient frontier for assessing the alternative project plans and selecting the best plan. The efficient frontier includes two criteria: the project cost and the project time. Besides, the paper presents a scheme to incorporate Directed Acyclic Graph (DAG) into the project risk analysis.

This scheme is used to estimate the expected impacts of the occurrence of the project risks on the project cost and the project time. Also, a theoretical model is defined to provide integration between project risk analysis and overall project planning using the breakdown structures. We believe that applying the proposed technique helps the company’s managers in most effective manner dealing with his complicated project plan assessment and selection problems. The application of the technique was implemented in the companies in construction industry in which represented a considerable cost and time improvements.
F. Bagheri , M. J. Tarokh,
Volume 21, Issue 1 (6-2010)
Abstract

Assessment and selection of suppliers are two most important tasks in the purchasing part in supply chain management. Supplier selection can be considered to be a single or multi-objective problem. From another point of view, it can be a single or multi-sourcing problem. In this paper, an integrated AHP and Fuzzy TOPSIS model is proposed to solve the supplier selection problem. This model makes the decision-maker to be able to solve this problem with different criteria and different weight for each criterion with respect to the purchasing strategy. Finally, the proposed model is illustrated by an example.
Mir. B. Aryanezhad, M.j. Tarokh, M.n. Mokhtarian, F. Zaheri,
Volume 22, Issue 1 (3-2011)
Abstract

  Multiple criteria decision making (MCDM) problem is one of the famous different kinds of decision making problems. In more cases in real situations, determining the exact values for MCDM problems is difficult or impossible. So, the values of alternatives with respect to the criteria or / and the values of criteria weights, are considered as fuzzy values (fuzzy numbers). In such conditions, the conventional crisp approaches for solving MCDM problems tend to be less effective for dealing with the imprecise or vagueness nature of the linguistic assessments. In this situation, the fuzzy MCDM methods are applied for solving MCDM problems. In this paper, we propose a fuzzy TOPSIS (for Order Preference by Similarity to Ideal Solution) method based on left and right scores for fuzzy MCDM problems. To show the applicability of the proposed method, two numerical examples are presented. As a result, our proposed method is precise, easy use and practical for solving MCDM problem with fuzzy data. Moreover, the proposed method considers the decision makers (DMs) preference in the decision making process. It seems that the proposed fuzzy TOPSIS method is flexible and easy to use and has a low computational volume .


F Etebari, M. Abedzadeh , F. Khoshalhan,
Volume 22, Issue 1 (3-2011)
Abstract

Improvement in supply chain performance is one of the major issues in the current world. Lack of coordination in the supply chain is the main drawback of supply chain that many researchers have proposed different methodologies to overcome it. VMI (Vendor-managed inventory) is one of these methodologies that implementing it has some obstacles. This paper proposes new model that is agent-managed SC. This paper is trying to use intelligent agent technology in the supply chain. In this paper supply chain assessment performance measure indicators have been divided into three categories cost, flexibility and customer responsiveness indicators. In the first category we use holding and backordered inventory costs, for second category, bullwhip effect are used and for the last one customer responsiveness indicator has been applied. Bullwhip effect is one of the main phenomena’s that has been tried to reduce it with the agent-based systems.
Abbas Saghaei, Hoorieh Najafi,
Volume 22, Issue 2 (6-2011)
Abstract

 

  Six sigma,

  Rolled throughput yield, Organizational performance

Six Sigma is a well- established approach to improve the capability of business processes in order to gain satisfaction of customers. The performance assessment of a given process is essential to some phases of six sigma methodology. So far, different indicators are used to demonstrate the performance of a process, while many organizations tend to report their organizational performance level. Unfortunately there have been few methods on calculating overall performance. This paper introduces a quantitative model that is formulated by focusing on process features. In addition, a number of numerical examples illustrate the performance of our proposed method in comparison to other methods .


Gholam Reza Jalali Naieni, Ahmad Makui, Rouzbeh Ghousi,
Volume 23, Issue 1 (3-2012)
Abstract

Fuzzy Logic is one of the concepts that has created different scientific attitudes by entering into various professional fields nowadays and in some cases has made remarkable effects on the results of the practical researches. However, the existence of stochastic and uncertain situations in risk and accident field, affects the possibility of the forecasting and preventing the occurrence of the accident and the undesired results of it.

In this paper, fuzzy approach is used for risk evaluating and forecasting, in accidents caused by working with vehicles such as lift truck. Basically, by using fuzzy rules in forecasting various accident scenarios, considering all input variables of research problem, the uncertainty space in the research subject is reduced to the possible minimum state and a better capability of accident forecasting is created in comparison to the classic two-valued situations. This new approach helps the senior managers make decisions in risk and accident management with stronger scientific support and more reliably.


, ,
Volume 23, Issue 2 (6-2012)
Abstract

Nowadays, project selection is a vital decision in many organizations. Because competition among research projects in order to gain more budgets and to attain new scientific domain has increased. Due to multiple objectives and budgeting restrictions for academic research projects have led to the use of expert system for decision making by academic and research centers. The existing methods suffer from deficiencies such as solution time inefficiency, ineffective assessment process, and unclear definition of appropriate criteria. In this paper, a fuzzy expert system is developed and improved for decision making in allocating budgets to research projects, by using the analytic network process(ANP). This has led to fewer rules and regulation, faster and more accurate decision-making, fewer calculations, and less system complexity. The rules of the expert system exacted in C# environment, consider all of the conditions and factors affecting the system. We describe the results of proposed model to measure its advantages and compare to existing selection processes for 120 projects. We also discuss the potential of proposed expert system in supporting decision making. The implementation results show that this system is significantly valid in selecting high-priority projects with respect to the known criteria , decision making regarding the determination of the assessment factors, budget allocation, and providing the appropriate initiatives for the improvement of the low-priority projects.
Nasim Nahavandi, Ebrahim Asadi Gangraj,
Volume 25, Issue 1 (2-2014)
Abstract

Flexible flow shop scheduling problem (FFS) with unrelated parallel machines contains sequencing in flow shop where, at any stage, there exists one or more processors. The objective consists of minimizing the maximum completion time. Because of NP-completeness of FFS problem, it is necessary to use heuristics method to address problems of moderate to large scale problem. Therefore, for assessment the quality of this heuristic, this paper develop a global lower bound on FFS makespan problems with unrelated parallel machines.
Dr. Yahia Zare Mehrjerdi, Ehsan Haqiqat,
Volume 26, Issue 4 (11-2015)
Abstract

Abstract Project management in construction industry, in many cases, is imperfect with respect to the integration of Occupational Health and Safety (OHS) risks. This imperfection exhibits itself as complications affecting the riskiness of industrial procedures and is illustrated usually by poor awareness of OHS within project teams. Difficulties on OHS regularly came about in the construction industry. The integration of OHS risk is not systematic in construction areas in spite of progressing laws and management systems. As project safety and risk evaluation in construction industry is an important issue, thus, the way on doing evaluation and liability of estimation is necessary. In this paper, we propose a new systematic approach based on Latin Hypercube Sampling (LHS) for integrating occupational health and safety into project risk evaluation. This approach tries to identify and evaluate reinforcement effects in a systematic approach for integrating OHS risks into project risk assessment. Furthermore, the proposed method allows evaluating and comparing OHS risks before and after the mitigation plan. A case study is used to prove the workability, credibility of the risk evaluation approach and uncomplicated integration of OHS risks at a construction project. This approach enables continual revaluation of criteria over the direction of the project or when new information is obtained. This model enables the decision makers such as project managers to integrate OHS risks toward schedule plan and compare them before and after the mitigation plan. The mentioned model is found to be useful for predicting OHS risks in construction industries and thus avoiding accidents over the path of the project.

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Abdollah Eshghi, Mehrdad Kargari,
Volume 29, Issue 1 (3-2018)
Abstract

In this paper a fraud detection method is proposed which user behaviors are modeled using two main components namely the un-normal trend analysis component and scenario based component. The extent of deviation of a transaction from his/her normal behavior is estimated using fuzzy membership functions. The results of applying all membership functions on a transaction will then be infused and a final risk is gained which is the basis for decision making in order to block the arrived transaction or not. An optimized threshold for the value of the final risk is estimated in order to make a balance between the fraud detection rate and alarm rate. Although the assessment of such problems are complicated, we show that this method can be useful in application according to several measures and metrics.
Arezoo Jahani, Parastoo Mohammadi, Hamid Mashreghi,
Volume 29, Issue 2 (6-2018)
Abstract

Innovation & Prosperity Fund (IPfund) in Iran as a governmental organization aims to develop new technology-based firms (NTBF) by its available resources through financing these firms. The innovative projects which refer to IPfund for financing are in a stage which can receive both fixed rate facilities and partnership in the projects, i.e. profit loss sharing (PLS). Since this fund must protect its initial and real value of its capital against inflation rate, therefore, this study aims to examine the suitable financing methods with considering risk. For this purpose we study on risk assessment models to see how to use risk adjusted net present value for knowledge based projects. On this basis, the NPV of a project has been analyzed by taking into account the risk variables (sales revenue and the cost of fixed investment) and using Monte Carlo simulation. The results indicate that in most cases for a project, the risk adjusted NPV in partnership scenario is more than the other scenario. In addition to, partnership in projects which demand for industrial production facilities is preferable for the IPfund than projects calling for working capital.
Ali Vaysi, Abbas Rohani, Mohammad Tabasizadeh, Rasool Khodabakhshian, Farhad Kolahan,
Volume 29, Issue 3 (9-2018)
Abstract

Nowadays, the CNC machining industry uses FMEA approach to improve performance, reduce component failure, and downtime of the machines. FMEA method is one of the most useful approach for the maintenance scheduling and consequently improvement of the reliability. This paper presents an approach to prioritize and assessment the failures of electrical and control components of CNC lathe machine. In this method, the electrical and control components were analyzed independently for every failure mode according to RPN. The results showed that the conventional method by means of a weighted average, generates different RPN values ​​for the subsystems subjected to the study. The best result for Fuzzy FMEA obtained for the 10-scale and centroid defuzzification method. The Fuzzy FMEA sensitivity analysis showed that the subsystem risk level is dependent on O, S, and D indices, respectively. The result of the risk clustering showed that the failure modes can be clustered into three risk groups and a similar maintenance policy can be adopted for all failure modes placed in a cluster. Also, The prioritization of risks could also help the maintenance team to choose corrective actions consciously. In conclusion, the Fuzzy FMEA method was found to be suitably adopted in the CNC machining industry. Finally, this method helped to increase the level of confidence on CNC lathe machine.
Monireh Jahani Sayyad Noveiri, Sohrab Kordrostami,
Volume 30, Issue 4 (12-2019)
Abstract

Sustainability performance assessment is a significant aspect of making sustainable decisions for organizations. Measuring sustainability performance of firms in a time span, covered in several periods, leads to more rational decision-making and planning by managers. Furthermore, in many application fields, there are discrete and bounded measures. However, there has been no systematic effort to analyze sustainability performance of Decision-Making Units (DMUs) in multiple periods of time when discrete and bounded factors are presented. Therefore, approaches based on Data Envelopment Analysis (DEA) are proposed in this paper to tackle this problem. To illustrate this issue in more detail, the performance of systems is measured for all dimensions, including economic, social, and environmental ones and for each period. Moreover, the overall multi-period sustainability performance and sustainability performance of each period are estimated using the suggested one-stage methods. Then, the sustainability performance is investigated for conditions in which internal relationships among economic, social, and environmental indicators are presented. Moreover, sustainability performance changes and performance changes of dimensions are addressed. An example and a case study are provided to explain our proposed approach. Results show that the introduced ideas are practical and effective.
K.v.k Sasikanth,
Volume 31, Issue 3 (5-2020)
Abstract

The Today’s interconnected world generates huge digital data, while millions of users share their opinions, feelings on various topics through popular applications such as social media, different micro blogging sites, and various review sites on every day. Nowadays Sentiment Analysis on Twitter Data which is considered as a very important problem particularly for various organizations or companies who want to know the customers feelings and opinions about their products and services. Because of the data nature, variety and enormous size, it is very practical for several applications, range from choice and decision creation to product assessment. Tweets are being used to convey the sentiment of a tweeter on a specific topic. Those companies keeping survey millions of tweets on some kind of subjects to evaluate actual opinion and to know the customer feelings. This paper major goal would be to significantly collect, recognize, filter, reduce and analyze all such relevant opinions, emotions, and feelings of people on different product or service could be categorized into positive, negative or neutral because such categorization improves sales growth about a company's products or films, etc. We initiate that the Naïve Bayes classifier be the mainly utilized machine learning method for mining feelings from large data like twitter and popular social network because of its more accuracy rates. In this paper, we scrutinize sentiment polarity analysis on Twitter data in a distributed environment, known as Apache Spark.

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