INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION MANAGEMENT (IJIE) (INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE) (PERSIAN)
Year:2008 | Volume:19 | Issue:1|Papers Count:13

Today, firms increasingly rely on technology transfer (TT) to establish competitive postures in the global marketplace. Therefore, pinpointing the factors affecting technology assimilation is of great importance for technology transfer success. One of the most important factors associated with technology transfer success is the organizational competence of firms receiving imported technologies. Organizational competence encompasses the consistency and alignment between the new technology and the firm's organizational structure, organizational culture and organizational resources. This article examines the role of the aforementioned organizational factors on technology transfer effectiveness in Iranian firms. To do so, we first identify the variables that measure organizational competence and the variables that measure TT effectiveness in Iranian firms. Then we test the effect of organizational competence on TT effectiveness in these firms. The findings of this research show that organizational competency significantly influence TT effectiveness in Iranian firms. An organizational structure providing lower control levels, lower hierarchy levels, multifunctional teams, and higher emphasis on individual rewards is found to influence TT effectiveness positively. An organizational culture providing high degree of trust, lower degree of uncertainty avoidance, and high degree of discipline is also found to positively influence TT effectiveness in Iranian firms.

In this research, a new model for cost-oriented assembly line balancing problem has been presented that consists of labor and equipment cost. The approach of this model for these costs is coincided with real condition of assembly lines and yield possibility of using common equipment among tasks. The objective function and constrains of this model has been shown by mathematical relations and also some relations for lower and upper bounds of objective function have been presented. Genetic algorithm has been used for solving the problems of this model and the best parameters of this algorithm for different size of problems have been found. Also the performance of suggested genetic algorithm has been compared by a famous method named RTA (Random Task Assignment) and lower bound of objective function. The results of these experiments indicate better performance of the genetic algorithm in quality of solution and computing time.

Iran is one of the top five important countries in the world that have rich oil reserves. Exchange incomes produced by oil exports play an important role in country's budget. Therefore, the studies and researches in fields that are related to oil economics have great privilege. Today, there is a plentiful interest in use of artificial intelligence methods especially neural networks for improving financial decision-making procedures. The main advantage of neural networks is their ability for learning from past experiments. They improve their efficiency by network training. So in this research, a neural network model is developed for forecasting monthly crude oil price using supervised learning.In development process of this model, effect of network structure types, technical inputs types, fundamental inputs, number of input layer neurons, number of hidden layers and neurons, transfer function of layers, data preprocess, divide of data to train and test sets and improved learning algorithm types are investigated.A three layers feed forward network with N9-2-8-1 structure is selected as the best price-forecasting model. This network has mean absolute error equal to 0.74$ on train set and 0.71$ on test set.

A primary assumption of many procedures in statistical process control and in process capability analysis is that the observations taken from the process are independent. However many processes exhibit a certain degree of autocorrelation.In this paper we discuss the effects that autocorrelation may have on process variance and capability indices and we show that when autocorrelation exists, variance estimate ceases to be unbiased. Also two simple approaches are developed to calculate process capability indices in the presence of autocorrelation. The first approach is based on the assumption of rational subgroups of means and variance analysis. The second approach is based<on the calculating process capability from an autoregressive model.

Supply chain management in second half recent century extended 'so much and in current century this extension is continued. One of the scopes that to be interested is extension and adaptation of production and inventory control policy, under just in time philosophy, for material and production control in supply chain. Hence in this paper we will adapt pull-push CONWIP (constant work in process) policy in supply chain context and model this Strategy. Demand rate, production, setup and transportation time are uncertain. In optimization process, concerning supply chain complexity, we will use simulation optirilization procedure that has more flexibility for solving problem. Objective function is summation of total work in process, hack log and supply raw material that will be minimized. At last, model result will be studied and analyzed.

In this paper, a comprehensive approach for performance assessment and ranking of the electricity distribution companies is presented. In this approach, in order to obtain exact ranks of the electricity distribution companies, Data Envelopment Analysis (DEA) as a non-parametric model and Corrected Ordinary Least Squares (COLS) as a parametric model are combined by Principal Component Analysis (PCA). First, the efficiency scores .of the electricity distribution companies are calculated by DEA and COLS. Then, the efficiency generated by DEA and COLS ate used as indicator in PCA model in this paper, thirty eight electricity distribution companies are ranked by proposed approach and the results are validated and verified by geometric mean approach.

A great number of organizations have adopted e-commerce as one of the most vital innovations in carrying out their business processes across the globe. Every country's economy encompasses small and medium sized enterprises (SMEs) that play a fundamental role in development and improvement of that country's economic induces thus the prosperity of such enterprises is dependent on adopting new innovative ways. E-commerce is certainly an innovative way of performing business processes. In this study, taking advantages of literature review, the different models of e-commerce adoption by SMEs are surveyed and so analyzed in order to identify the most common and important components of them which are most effective on the SMEs performance. Basing on the prior researches and the studies conducted by the other researchers, the primary model of e-commerce adoption by SMEs has been attempted to be defined. Technical implications, organizational factors, and inter-organizational systems have been recognized as the key components of the cited model. As the next step, the questionnaires have been designed according to the both model description and also expert opinions in order to gathering the related data from the statistical sample which encompasses both academician and also professional people familiar to the related subjects. By analyzing the gathered data, the effective variables with significant correlations with the e-readiness and performance indicators have been identified as the result of the study. With the help of such a model, the SMEs could be able to identify their performance weaknesses and strengths and also formulation proper strategies and guidelines in order to enhance their performance key indicators related to adopted e-commerce. In this study the IT balanced score card (ITBSC) approach and its criteria have been leveraged in order to appraisal the e-commerce performance.

Multi-choice knapsack problem is a branch of regular knapsack problem where the objects are classified in different classes and each class has one and only one representative in final solution. Although it is assumed that each object belongs to just one class, sometimes this assumption is not valid in real problems. In this case an object may belong to the several classes. In fuzzy multi-choice knapsack problem (FMCKP), fuzzy sets are applied to show that each object is a member of each class with a membership grade. In this paper we proposed two new models for fuzzy multi-choice knapsack problem. These models have a fuzzy constraint and so we applied the fuzzy linear programming (FLP) approach to solve them. Typical examples show the capability and efficiency of the proposed models.

Shewhart charts are the main tools for statistical process control. They are used for detecting assignable causes which affect quality of process output. From them, X and MR charts are two univariate control charts for monitoring mean and variation of measurable quality characteristics. The main drawbacks of these charts are: weakness of X chart against non-normal distribution of process data, autocorrelation of consecutive MR values, and inability of MR chart in detecting decrease in process variation, These drawbacks have declined their effectiveness. This paper presents a simple method for monitoring two parameters of normal distribution, based on fuzzy logic, resolving above drawbacks, the proposed method can detect non-random patterns of the process data. Here a fuzzy expert system is developed to assess individual measurements, This results in considerable improvement in decreasing out-of-control average run length versus the traditional control charts, Moreover, performance of fuzzy control chart for recognizing unnatural process behaviors has investigated using Mont-Carlo simulation and advantages of this novel method have been investigated.

The IT value measurement model proposed to evaluate the business value of IT. This model utilizes some different tools and techniques such as: Benchmarking, Balanced Scorecard, qualitative and quantitative measurement techniques. The basis of this model is a link between 3- layer IT classification and IT planning with a combinatorial approach. Connecting these three layers with effectiveness and efficiency concepts led this model from a conceptual to a practical framework various effects of different IT levels on the organization performance were analyzed by using secondary data. In each layer a balanced scorecard framework was setup and some measures were selected in each zone; and then compared with the historical trends, reference values which carried out by benchmarking and relative' cost ratios. The outcome will show deviations and weame's Spoints of IT planning and activities which should be studied by creative problem solving techniques in order to find roots of the problems, the last step of a typical IT value measurement program is planning and running an improvement project. This study will propose a framework to measure IT value both before and after planning and implementation.

The success in a business requires a complicated communication Management System. The Main objective of this research paper we are developing an optimization approach when there is one producer and several distribution centers. The model comprised of several parameters such as transport type, route specification, and transport capacities. Also we imposed several limitation such as capacity, number of storage facilities, transport capacity, .etc.

Packing rectangular shapes into a rectangular space is one of the most important discussions on Cutting & Packing problems (C&P); such as: cutting problem, bin-packing problem and distributors pallet loading problem, etc. Assume a set of rectangular pieces with specific lengths, widths and utility values. Also assume a rectangular packing space with specific width and length. The objective function is, to pack the pieces into the space in Order to get the maximum sum of utility value of the packed pieces. To generate the related packing pattern this paper proposes a new formulation metl10dbased on the column generation, approach. In this method one each cycle of the algorithm; a one-dimensional pattern is generated based on the shadow prices 'Of the Simplex method. The set of generated one-dimensional patterns are used: to construct the two-dimensional packing pattern. Also, the proposed model and the present models in the.state-of-1beart have been compared.

There is numerous research papers published on the impact of autocorrelation on Shewhart control charts. The subject of data autocorrelation becomes more important considering recent advances in automated inspection procedures, which let product or process quality characteristics, be measured in time order of production. Therefore, it is necessary for engineers and practitioners to know substitute methods for conventional control charts to monitor autocorrelated processes. On the other hand, widely use of time series techniques for modeling autocorrelatd data has entailed inadequate attention to other statistical methods and ignorance of the properties of autocorrelated processes. Concerning this issue, this paper explains and compares several important theoretical approaches for monitoring autocorrelated processes and presents some related demonstrating examples. The comparison is made based on the sensitivity of each method to detect mean shifts of an autoregressive process. Finally, we propose guidelines for choosing most appropriate method and analyze the corresponding situation for employing different methods.