Showing 27 results for Fer
Mohammad Ali Shafia, Arnoosh Shakeri,
Volume 20, Issue 4 (4-2010)
Abstract
This paper aims at emphasizing the importance of establishing a Project Management (PM) system in Technology Transfer (TT) processes and developing a conceptual framework for it. TT is an important process in Technology Management affairs for all enterprises. Most of the time, lack of a particular concentration on technical, commercial and legal aspects of TT process, leads to mismanagement of other aspects of transferring project, like Time and Project Integration. This situation may lead to failure and loss of many opportunities in transfer process. To overcome this problem, inputs, outputs and activities of a typical TT processes are identified and based on these components, a conceptual framework for managing this project & prevent the loss is developed using Project Management models and methodologies.
J. Jassbi, S.m. Seyedhosseini , N. Pilevari,
Volume 20, Issue 4 (4-2010)
Abstract
Nowadays, in turbulent and violate global markets, agility has been considered as a fundamental characteristic of a supply chain needed for survival. To achieve the competitive edge, companies must align with suppliers and customers to streamline operations, as well as agility beyond individual companies. Consequently Agile Supply Chain (ASC) is considered as a dominant competitive advantage. However, so far a little effort has been made for designing, operating and evaluating agile supply chain in recent years. Therefore, in this study a new approach has been developed based on Adaptive Neuro Fuzzy Inference System (ANFIS) for evaluating agility in supply chain considering agility capabilities such as Flexibility, Competency, Cost, Responsiveness and Quickness. This evaluation helps managers to perform gap analysis between existent agility level and the desired one and also provides more informative and reliable information for decision making. Finally the proposed model has been applied to a leading car manufacturing company in Iran to prove the applicability of the model.
Iman Nosoohi , Seyed Nader Shetab-Boushehri,
Volume 22, Issue 2 (6-2011)
Abstract
Selection of appropriate infrastructure transportation projects such as highways, plays an important role in promotion of transportation systems. Usually in evaluation of transportation projects, because of lack of information or due to long time and high expenditures needed for gathering information, different effective factors are ignored. Thus, in this research, regarding multi criteria nature of transportation projects selection and using fuzzy logic, an appropriate conceptual framework for ranking and selecting transportation projects is proposed. Also, unlike the previous researches, we've applied a fuzzy inference system (FIS) to account value of each project with respect to each criterion, in the proposed methodology. The FIS helps us to set rule-based systems for paying attention to expert's experience and professional knowledge in decision making. The proposed methodology is explained in detail through an applicable example. We've considered most common criteria including effect of transportation project on traffic flow, economical growth and environment beside budget constraint, in the descriptive example.
Mohammad Saber Fallah Nezhad, Ali Mostafaeipour,
Volume 25, Issue 1 (2-2014)
Abstract
In order to perform Preventive Maintenance (PM), two approaches have evolved in the literature. The traditional approach is based on the use of statistical and reliability analysis of equipment failure. Under statistical-reliability (S-R)-based PM, the objective of achieving the minimum total cost is pursued by establishing fixed PM intervals, which are statistically optimal, at which to replace or overhaul equipments or components. The second approach involves the use of sensor-based monitoring of equipment condition in order to predict occurrence of machine failure. Under condition-based (C-B) PM, intervals between PM works are no longer fixed, but are performed only “when needed”. It is obvious that Condition Based Maintenance (CBM) needs an on-line inspection and monitoring system that causes CBM to be expensive. Whenever this cost is infeasible, we can develop other methods to improve the performance of traditional (S-R)-based PM method. In this research, the concept of Bayesian inference was used. The time between machine failures was observed, and with combining Bayesian Inference with (S-R)-based PM, it is tried to determine the optimal checkpoints. Therefore, this approach will be effective when it is combined with traditional (S-R)-based PM, even if large number of data is gathered.
Fernando Antonio Moala,
Volume 25, Issue 4 (10-2014)
Abstract
The Weibull distribution has been widely used in survival and engineering reliability analysis. In life testing experiments is fairly common practice to terminate the experiment before all the items have failed, that means the data are censored. Thus, the main objective of this paper is to estimate the reliability function of the Weibull distribution with uncensored and censored data by using Bayesian estimation. Usually it is assigned prior distributions for the parameters (shape and scale) of the Weibull distribution. Instead, we assign prior distributions for the reliability function for a fixed time, that is, for the parameter of interest. For this, we propose different non-informative prior distributions for the reliability function and select the one that provides more accurate estimates. Some examples are introduced to illustrate the methodology and mainly to investigate the performance of the prior distributions proposed in the paper. The Bayesian analysis is conducted based on Markov Chain Monte Carlo (MCMC) methods to generate samples from the posterior distributions
![\"AWT](\"./files/site1/images/24.png\")
Hadi Mokhtari , Ashkan Mozdgir,
Volume 26, Issue 2 (7-2015)
Abstract
Assembly lines are special kinds of production systems which are of great importance in the industrial production of high quantity commodities. In many practical manufacturing systems, configuration of assembly lines is fixed and designing a new line may be incurred huge amount of costs and thereby it is not desirable for practitioners. When some changes related to market demand occur, it is worthwhile to re-balance an existing line rather than balancing a new one. Hence, in this paper we suggest a re-balancing model of an existing assembly line in which a new demand related cycle time (CT) is embedded to the traditional assembly line balancing problem (ALBP) as a new parameter. It does not focus on balancing a new line instead it considers a more realistic problem which is re-balancing an existing line. The objective is to re-schedule the tasks in order to reduce the current CT to the new required one such that two criteria are optimized: (i) minimization of the incurred costs and (ii) minimization of non-smoothing of reconfigured line. To solve the considered problem, an effective differential evolution algorithm is developed. Furthermore, to enhance the performance of algorithm, its parameters are optimized by the use of Taguchi method which is a conventional statistical technique for parameter design. The obtained results from computational experiments on benchmark instances show the effectiveness of suggested algorithm against other methods.
![\"AWT](\"./files/site1/images/3(2).png\")
Emad Sane-Zerang, Reza Tavakkoli-Moghaddam, Hossein Heydarian,
Volume 27, Issue 3 (9-2016)
Abstract
This paper considers a bi-objective mathematical model for locations of landfills, transfer stations and material recovery facilities (MRFs) in order to serve the entire regions and simultaneously identify the capacities of landfills. This is a mixed-integer programming (MIP) model, whose objectives are to minimize the total cost and pollution simultaneously. To validate the model, a numerical example is solved an augmented ε-constraint method and the associated computational results are presented to show the number of solid waste facilities and location of sites for solid waste facilities.
Mohammad Mehdi Dehdar, Mustafa Jahangoshai Rezaee, Marzieh Zarinbal, Hamidreza Izadbakhsh,
Volume 29, Issue 4 (12-2018)
Abstract
Human-based quality control reduces the accuracy of this process. Also, the speed of decision making in some industries is very important. For removing these limitations in human-based quality control, in this paper, the design of an expert system for automatic and intelligent quality control is investigated. In fact, using an intelligent system, the accuracy in quality control is increased. It requires the knowledge of experts in quality control and design of expert systems based on the knowledge and information provided by human and equipment. For this purpose, Fuzzy Inference System (FIS) and Image Processing approach are integrated. In this expert system, the input information is the images of the products and the results of processing on images for quality control are as output. At first, they may be noisy images; the pre-processing is done and then a fuzzy system is used to be processed. In this fuzzy system, according to the images, the rules are designed to extract the specific features that are required. At second, after the required attributes are extracted, the control chart is used in terms of quality. Furthermore, the empirical case study of copper rods industry is presented to show the abilities of the proposed approach.
Mostafa Soltani, R. Azizmohammadi, Seyed Mohammad Hassan Hosseini, Mahdi Mohammadi Zanjani,
Volume 32, Issue 2 (6-2021)
Abstract
The blood supply chain network is an especial case of the general supply chain network, which starts with the blood donating and ends with patients. Disasters such as earthquakes, floods, storms, and accidents usually event suddenly. Therefore, designing an efficient network for the blood supply chain network at emergencies is one of the most important challenging decisions for related managers. This paper aims to introduce a new blood supply chain network in disasters using the hub location approach. After introducing the last studies in blood supply chain and hub location separately, a new mixed-integer linear programming model based on hub location is presented for intercity transportation. Due to the complexity of this problem, two new methods are developed based on Particle Swarm Optimization and Differential Evolution algorithms to solve practical-sized problems. Real data related to a case study is used to test the developed mathematical model and to investigate the performance of the proposed algorithms. The result approves the accuracy of the new mathematical model and also the good performance of the proposed algorithms in solving the considered problem in real-sized dimensions. The proposed model is applicable considering new variables and operational constraints to more compatibility with reality. However, we considered the maximum possible demand for blood products in the proposed approach and so, lack of investigation of uncertainty conditions in key parameters is one of the most important limitations of this research.
Mahdi Rahimdel Meybodi,
Volume 32, Issue 3 (9-2021)
Abstract
Today, one of the most important concerns of production units is the evaluation, analysis and risk management in the production process. In this research, based on the fuzzy control approach, a scientific and logical method for evaluating, analyzing and managing risk in the production process is presented. Based on the proposed method of this research, after identifying the risks in the production process of products, according to the three criteria of failure severity, probability of failure and detectability, as well as using the best - worst method, evaluation and determining the importance of these risks, is done. Then, with the fuzzy rules, fuzzy inference system is designed. The final result is the classification and prioritization of identified risks. Finally, the proposed research model for an applied sample is used and its final results are analyzed.
Katiryna Sheludko, Iryna Koshkalda, Olena Panukhnyk, Dmytro Hoptsii, Liudmyla Makieieva,
Volume 33, Issue 1 (3-2022)
Abstract
The article analyzes the ecological condition of the soil and identifies the main problems of the environmentalization of land use in Ukraine in the case of the Kharkiv region. Deterioration of the ecological condition of agricultural land, weakening of their erosion resistance, violation of the optimal structure of land, reduction of the content of humus and basic nutrients lead to a decrease in land productivity. In general, the current state of environmental safety of land is quite unsatisfactory, so it significantly reduces the quality and volume of agricultural production.
The analysis of the situation and the forecast of the efficiency of soil fertility show that due to the sharp decrease in the application of organic and mineral fertilizers, insufficient implementation of forest reclamation, and anti-erosion measures, degradation processes have intensified in all areas. The problem with the balance of nutrients has become more acute, the acidity of the soil solution is increasing, the humus content is reducing, and the intensity of erosion processes has significantly increased.
The main tasks of the environmentalization of agricultural land use involve measures for increasing soil fertility by limiting the use of intensive chemicalization of agriculture; measures for the application of the organic fertilizer to ensure a deficit-free balance of humus in the soil; measures for mechanization, chemicalization, land reclamation using the latest methods; anti-erosion measures and the use of new methods of tillage, liming, soil, and minimization of tillage. Thus, to ensure the formation of environmentally friendly agricultural land use, an important condition is the creation of a scientifically sound structure and optimization of the ratio of productive (arable land) and environmentally friendly (hayfields, pastures, wooded areas) land use. The main environmentally friendly elements of this structure include agro-ameliorative and forest-ameliorative measures that form the ecological framework of agro-landscapes and are the basis for providing favorable agro-environmental parameters for agricultural land.
Fatima Zohra Allam, Latifa Hamami-Mitiche, Hicham Bousbia-Salah,
Volume 33, Issue 1 (3-2022)
Abstract
For several years, considerable efforts have been made in the field of biometric research. The major interest of this line of research is linked, among other things, to the recognition of the individual because the security needs are becoming increasingly important, and the economic stakes are colossal. There are many and diverse biometric applications that provide a substantial level of security.
Unimodal biometric systems allow a person to be recognized using a single biometric modality, but cannot guarantee correct identification with certainty. While multimodal biometric systems, using several biometric modalities, guarantee better recognition.
In this article, we are interested in the study of evaluation tools for biometric systems. For this, we will first calculate three essential parameters, namely: False Rejection Rate (FRR), False Acceptance Rate (FAR) and Equal Error Rate (EER). Second, we will determine the performance curves, in this case, the ROC curve (Receiver Operating Characteristic) and the DET curve (Detection Error Tradeoff). The calculation of these metrics allows the evaluation of unimodal and bimodal biometric systems to compare the benefit of merging the biometric modalities.
Ali Fallahi, Mehdi Mahnam, Seyed Taghi Akhavan Niaki,
Volume 33, Issue 2 (6-2022)
Abstract
Integrated treatment planning for cancer patients has high importance in intensity modulated radiation therapy (IMRT). Direct aperture optimization (DAO) is one of the prominent approaches used in recent years to attain this goal. Considering a set of beam directions, DAO is an integrated approach to optimize the intensity and leaf position of apertures in each direction. In this paper, first, a mixed integer-nonlinear mathematical formulation for the DAO problem in IMRT treatment planning is presented. Regarding the complexity of the problem, two well-known metaheuristic algorithms, particle swarm optimization (PSO) and differential evolution (DE), are utilized to solve the model. The parameters of both algorithms are calibrated using the Taguchi method. The performance of two proposed algorithms is evaluated by 10 real patients with liver cancer disease. The statistical analysis of results using paired samples t-test demonstrates the outperformance of the PSO algorithm compared to differential evolution, in terms of both the treatment plan quality and the computational time. Finally, a sensitivity analysis is performed to provide more insights about the performance of algorithms and the results revealed that increasing the number of beam angles and allowable apertures improve the treatment quality with a computational cost.
Motahare Gitinavard, Parviz Fattahi, Seyed Mohammad Hassan Hosseini, Mahsa Babaei,
Volume 33, Issue 4 (12-2022)
Abstract
This paper aims to introduce a joint optimization approach for maintenance, quality, and buffer stock policies in single machine production systems based on a P control chart. The main idea is to find the optimal values of the preventive maintenance period, the buffer stock size, the sample size, the sampling interval, and the control limits simultaneously, such that the expected total cost per time unit is minimized. In the considered system, we have a fixed rate of production and stochastic machine breakdowns which directly affect the quality of the product. Periodic preventive maintenance (PM) is performed to reduce out-of-control states. In addition, corrective maintenance is required after finding each out-of-control state. A buffer is used to reduce production disturbances caused by machine stops. To ensure that demand is met during a preventive and corrective maintenance operation. All features of three sub-optimization problems including maintenance, quality control, and buffer stock policies are formulated and the proposed integrated approach is defined and modeled mathematically. In addition, an iterative numerical optimization procedure is developed to provide the optimal values for the decision variables. The proposed procedure provides the optimal values of the preventive maintenance period, the buffer stock size, the sample size, the sampling interval, and the control chart limits simultaneously, in a way that the total cost per time unit is minimized. Moreover, some sensitivity analyses are carried out to identify the key effective parameters.
Komeil Fattahi, Ali Bonyadi Naeini, Seyed Jafar Sadjadi,
Volume 34, Issue 1 (3-2023)
Abstract
Venture capital (VC) financing is associated with the challenges of double-sided moral hazard, and uncertainty, which leads to the difficulty in estimating the venture's value accurately and consequently the impossibility of determining the optimal equity sharing between the entrepreneur and investor. Traditionally, convertible preferred equity mechanisms used to be implemented as an incentive to decline moral hazard. However, despite the emphasis on investor risk-taking, such mechanisms transfer the investor risk to the entrepreneur and do not mitigate the incentive of opportunistic behaviors. Furthermore, according to the literature review, and to the best of the authors’ knowledge, there has not been developed any practical mechanism for equity sharing in VC financing up to now. This paper proposes a fair equity sharing mechanism, which alleviates the above-mentioned deficiencies. It adjusts both parties' share during the equity dilution in each stage of financing, regarding the difference between the venture's ex-ante and ex-post values. Moreover, it manages uncertainty by applying staged financing and the option of abandonment at the end of each stage. The proposed mechanism has been verified by using the mathematical tools and drawing its curves for a case study.
Laila Refiana Said, Zainal Arifin, Meldasari Said,
Volume 34, Issue 2 (6-2023)
Abstract
Numerous studies have examined the increasing number of virtual team communication usage, especially during the Covid-19 pandemic. However, little research has been conducted on the factors affecting its effectiveness in improving task performance, seeing the virtual team's rapid development today. Therefore, this study examines the effect of direct and indirect employee preferences and organizational support on task performance through virtual teamwork communication. The research method used was a survey of 156 employees in the fields of education, telecommunications, transportation, and health in Banjarmasin city, who work from home, interact with colleagues who also work from home, and with colleagues who work in the office. The analysis was carried out using path analysis. The results showed that employee preferences and organizational support directly affected task performance. Virtual team communication can mediate the influence of employee preferences and organizational support on task performance. The research implies that virtual team communication that runs well can improve work performance. Therefore, it requires collaborative support, both from individuals and the organization.
Qurtubi Qurtubi, Muhammad Suyanto, Anas Hidayat, Elisa Kusrini,
Volume 34, Issue 3 (9-2023)
Abstract
Various of studies on firm’s performance have been performed by reserachers involving many variables as antecedents, logistics performance is one of them. Aside from significantly supporting the firm, it also identifies firm’s performance as standard to keep up in short and long-term competition. There are several types of criteria in logistics performance, however they are all only classified in three dimensions which are efficiency, effectiveness and differentiation. From the literature review, it was suggested that halal certification could affect logistics performance. This article proposes research model that integrates logistics efficiency, logistics effectiveness, logistics differentiation and halal certification as the dimensions of logistics performance. . It is expected to provide theoretical contribution by explaining causal relationship among variables and provide intact knowledge by considering the firm’s performance that is determined by dimensions of logistics performance. Literature review is applied for this research. Based on the result and discussion, it can be concluded that halal certification potentially could become a new dimension for logistics performance in addition to other existing three dimensions, yet it takes empirical research support strengthen this proposed model.
Yuvaraj M, Jothi Basu,
Volume 35, Issue 3 (9-2024)
Abstract
Refrigerated trucks in the cold chain enhance the shelf-life of food. In the fruit supply chain (FSC), if each different fruit necessitates its dedicated fleet of refrigerated vehicles, the total cost of the supply chain would increase. On the other hand, if there are several fruits in a single compartment, the quality and freshness of the fruits will be impacted since each fruit requires a different operating temperature. Therefore, partitions are necessary within the container. While the use of cold chain infrastructure will result in a reduction in food loss and an enhancement in food security, it will also incur an increase in the overall cost of the supply chain. Therefore, this paper aims to create a mixed integer non-linear programming (MINLP) mathematical model considering multi-compartment reefer trucks (MCRTs) to minimize the total cost in the FSC. To assess the efficiency of the model, a case study is carried out in India, and the formulated mathematical model is solved using a heuristic approach. The findings indicate that utilizing MCRTs leads to a reduction in the number of vehicles required and a drop in total supply chain cost. Three-compartment reefer trucks offer a more significant cost-saving advantage in the FSC compared to two-compartment reefer trucks. Furthermore, it is noted that operating three distribution centers (DCs) results in a reduction in the overall cost. The decrease in total supply chain costs enhances the affordability of fruits for low-income populations and contributes to the enhancement of food security. In addition to cost reduction, implementing MCRT has also beneficial environmental impacts such as decreased emissions due to a decrease in the number of trucks utilized and reduced food waste.
Maryam Ghasemi, Mehdi Seifbarghy, Nezir Aydin, Wichai Chattinnawat,
Volume 36, Issue 1 (3-2025)
Abstract
One of the most important issues regarding community health is animal health, followed by the health of animal products. Providing a sustainable environment for production facilities like livestock centers is essential. In this study, we have proposed designing four fuzzy inference systems for managing the sustainability of livestock centers. The first, second, and third systems are applied for the economic, social, and environmental dimensions. The fourth is for a system whose output is the sustainability level while its inputs are the three addressed sustainability dimensions. The data source was experts' judgment, and the major limitation of this research was access to a limited number of experts in making system rules. The validation is made by cross-checking with other experts. Considering a maximum of 10 points for each sustainability dimension and supposing that the economic dimension is 5.05, the social dimension is 7.77 and the environmental dimension is 8.12, the sustainability level turns out to be 7.92
Sakineh Alizadeh Latrei, Seyed Ali Nabavi Chashmi, Iraj Mahdavi,
Volume 37, Issue 2 (6-2026)
Abstract
Pricing is the core of every business plan and directly affects the components and marketing strategies of industrial companies. The present study was conducted with the aim of achieving product pricing patterns in industrial markets with a customer-oriented approach based on the Fuzzy Delphi method. The method considered for conducting the present study is the qualitative method. The statistical population of the qualitative part of this study consists of experts, managers, assistants, and senior experts in the petrochemical industry. The data collection tool in the qualitative stage is in-depth and semi-structured interviews with experts, and in the quantitative part, a researcher-made questionnaire, which was used to confirm its validity by using content validity and construct validity. In order to measure the reliability of the study, Cronbach's alpha coefficient was used, the value of which was calculated to be above 0.7 for the total research variables. In the first part, using the data-based approach, the 6 main categories of the model were identified and presented in the form of a strategic pricing model for petrochemical products. The results confirm the positive and significant relationships between the research variables. Therefore, it can be stated that the relationships considered in the model are correct and logical and the presented model is confirmed.
