International Journal of Industrial Engineering & Production Research

---

---

Abstract The purpose of this article is to present a system dynamics (SD) model for studying the ‎interconnections among human being weight, eating habit, exercise, body fat, take-in medication, drugs-uses, and the health problems in general. Due to the fact that all of these factors have direct and indirect impacts on the expenses that insurance company have to pay this author is proposing a systems thinking approach for determining the interconnections among the factors and uses the concept of system dynamics to simulate and determine the behavior of the system. To do so, this author has reviewed key point ‎about the system thinking, related theories, and system dynamics. Next, models in ‎the form of causal loops presenting the interconnections between weight factor ‎and health problems are developed and discussed. Thereafter, a flow diagram of ‎model is constructed and the overall expenses are studied. Expense rates are classified as: operational expenses (OE), treatment expenses (TE), Medication expenses (ME), Hospitality expenses (HE), and Drug treatment expenses (DE). This article makes a significant contribution to the health ‎study issues due to the fact that it shows how a factor such as weight can have ‎impacts on hearth attack, blood pressure, and blood sugar, to mention a few, and how relate all these to the overall expenses that an insurance company have to pay at last. ‎Since, to the best of this author's knowledge, this is the first study that relates ‎weight to health problem using systems thinking concepts and system dynamics approach ‎it makes significant contribution to health literature.‎

---

Job Satisfaction (JS) plays important role as a competitive advantage in organizations especially in helth industry. Recruitment and retention of human resources are persistent problems associated with this field. Most of the researchs have focused on the job satisfaction factors and few of researches have noticed about its effects on productivity. However, little researchs have focused on the factors and effects of job satisfaction simultanosly by system dynamics approaches.In this paper, firstly, analyses the literature relating to system dynamics and job satisfaction in services specially at a hospital clinic and reports the related factors of employee job satisfaction and its effects on productivity. The conflicts and similarities of the researches are discussed and argued. Then a novel procedure for job satisfaction evaluation using (Artificial Neural Networks)ANNs and system dynamics is presented. The proposed procedure is implemented for a large hospital in Iran. The most influencial factors on job satisfaction are chosen by using ANN and three differents dynamics scenarios are built based on ANN's result. . The modelling effort has focused on evaluating the job satisfaction level in terms of key factors which obtain from ANN result such as Pay, Work and Co-Workers at all three scenarios. The study concludes with the analysis of the obtained results. The results show that this model is significantly usfule for job satisfaction evaluation Keywords: Job Satisfaction, system dynamics, Artificial Neural Network (ANN), healthcar field.

---

Abstract: In order to evaluate the relationship between Organizational Strategies and Organizational results, a comprehensive model is required, which should be able to capture all aspects of business excellence. The EFQM model is suitable tool to observe these factors. The EFQM model consists of two main domains: Enablers and Results. The first domain which includes processes and systems in general, "enable" the organization to have higher performance or "results". On the other hand, the feedback from the results makes the organization to correct the system. Hence, a dynamic model could be appropriate in analyzing the interrelated behavior of the two main domains as well as those within the criteria and sub-criteria. This research is an effort to find the relationship between Strategies and results through system dynamics tool based upon EFQM model. In other words, this research exploits system dynamics in order to measure the effects of Strategies on Organizational results using a dynamic model. The advantage is that by changing one parameter in the Strategies, one can find how it could affect key results especially financial outcomes. Keywords: Organizational Strategies, Organizational results, Business Excellence Model, EFQM, System Dynamics

---

---

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

---

Because of electricity subsidies, electricity price in Iran is much lower than its real value, and the growth of electricity demand is much more than its rational rate, which in turn implies ever increasing investment in the electricity section by the Government. Therefore, the recent Government policies are based on elimination of electricity subsidies, followed by commissioning complete electricity market to attract investors in the power industry. In this paper, a model is developed for electricity demand prediction and evaluating Iran's current electricity market and complete market to deal with optimistic and pessimistic electricity demand. Hence, a system dynamics framework is applied to model and generate scenarios because of its physical capability and information flows that allow understanding the of behavior nonlinear dynamics in uncertain conditions. To validate the model, it was compared with the available actual data within 21 years, since (1988-2008). After model validation, two scenarios are evaluated based on the influence of eliminating electricity subsidies on electricity demand in short-term and long-term and then commissioning of the probable complete electricity market is evaluated. For this purpose, first, the electricity demand is estimated for the target years and then changing dynamics in transition of Iran’s electricity market is analyzed.

---

Abstract Purpose of this paper: This paper presents an analysis toward understanding the business value components that a health care organization can drive by adopting RFID technology into its system. This researcher proposes a framework for evaluating the business value of RFID technology. To do so, emphasis is put on delivering business value through refining business processes and expanding the business model. Author illustrates the concepts drawing on the experience of nine case studies already presented on the health care topics and service industries. Thereafter, a framework, as a set of propositions based on relevant literature, case studies from the field, and author's intuition, is formulated. The proposed propositions need to be validated through empirical evidence. To fully understand this topic some applications of radio frequency identification in health care management and other industries are briefly discussed and nine cases from health care industry are studied. Design/methodology/approach: Identifies key elements of radio frequency identification through the review of healthcare management literature and case studies. For this purpose, nine cases are reviewed from the health care industry and then key features of those cases are employed to determine four proposals for further studies. Findings: To make healthcare management systems functional and successfully operational we can use radio frequency identification solutions to reduce operating costs through decreasing the labor costs, including automation, improving tracking and tracing, and preventing the lost of materials under any circumstances. Practical implications (if applicable): What is original/value of paper: The emphasis is put on delivering business value through refining business processes and expanding the business model. A framework, as a set of propositions based on relevant literature, case studies from the field, and author's intuition is formulated and presented for further studies using true case studies.

---

Abstract Firms no longer compete as autonomous entities and prefer to joinin a supply chain alliance to take advantage of highly competitive business situation. Supply chain coordination has a greatimpact on Firm’sstrategic partnering and success in competitive business environment. In this paper, we propose a system dynamics simulation model for strategic partner selection in supply chain. Our model addresses a supply chain including suppliers and retailers. It presents an approach to simulateeach supplier’s (retailers) tendency to select downstream (upstream) partner selection and the impact of their policies in the whole supply chain.

---

The present research aims at investigating feasible improvements by determining optimal number of stations and required workforce using a simulation system, with the ultimate goal of reaching optimal throughput while respecting the problem constraints in an attempt to achieve maximum feasible performance in terms of production rate. For this purpose, similar research works were investigated by reviewing the relevant pieces of the literature on simulation model, car signoff station, and techniques for optimizing the station, and the model of the car signoff unit was designed using data gathering tools, existing documents, and actual observations. Subsequently, the model was validated by means of descriptive statistics and analysis of variance (ANOVA). Furthermore, available data was analyzed using ARENA and SPSS software tools. In a next step, potential improvements of the unit were identified and the model was evaluated accordingly. The results indicated that some 80% of the existing problems could be addressed by appropriately planning for human resources, on-time provision of the required material at reworking units, and minimization of transportation at the stations that contributed the most to the working queue. Thus, the waiting time per station could be minimized while increasing the production rate.

---

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.

---

The selection of an appropriate cutting tool for the production of different jobs in a flexible manufacturing system (FMS) can play a pivotal role in the efficient utilization of the FMS. The selection procedure of a cutting tool for different production operations becomes more significant with the availability of similar types of tools in the FMS. In order to select and allocate appropriate tool for various production operations in the FMS, the tool selection rules are commonly used. The application of tool selection rules is also observed to be beneficial when a system demands two or more tools for the production operations at different work centers at the same time in the FMS. In this paper, investigations are carried out to evaluate the performance of different tool selection rules in the FMS. The performance of the tool selection rules is evaluated by simulation with respect to different performance parameters in the FMS namely makespan, mean work center utilization (%) and mean automatic tool transporter (ATT) utilization (%).
 

---

The present study is focused to investigate the effect of the various machining input parameters such as cutting speed (v_c), feed rate (f), depth of cut, and nose radius (r) on output i.e. surface roughness (R_a and R_q) and metal removal rate (MRR) of the C40 steel by application of an artificial neural network (ANN) method.  ANN is a soft computing tool, widely used to predict, optimize the process parameters. In the ANN tool, with the help of MATLAB, the training of the neural networks has been done to gain the optimum solution. A model was established between the computer numerical control (CNC) turning parameters and experimentally obtained data using ANN and it was observed from the result that the predicted data and measured data are moderately closer, which reveals that the developed model can be successfully applied to predict the surface roughness and material removal rate (MRR) in the turning operation of a C40 steel bar and it was also observed that lower the value of surface roughness (R_a and R_q) is achieved at the cutting speed of 800 rpm with a feed rate of 0.1 mm/rev, a depth of cut of 2 mm and a nose radius of 0.4 mm.

---

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.

---

To respond to the urgent call for preventive action against COVID-19 pandemic implications for societies, this research is carried out. The main aim of our research is providing a new insight for the effects of the newly emerged restrictions by COVID-19 on the SD Goals (SDGs). This research applied a qualitative approach for supporting the SDGs achievement post-COVID in Iran, as a developing country in the Middle East, in two phases. In the first phase, using a fuzzy Delphi method, the SDGs affected by COVID-19 were identified. In the next phase, a fuzzy cognitive map, as a qualitative system dynamics modeling, was conducted to specify the key interconnections among the SDGs post COVID-19. Finally, three strategies including focus on people in vulnerable situation, support for industrial units and small and medium-sized enterprises, and national aggregation to Fight COVID-19 were examined. As a result, different scenarios associated with the three proposed strategies were tested based on the identified interconnections among the SDGs to reduce the potential negative effects of COVID-19 crisis on the achievement of the SDGs. The results provide a decision support for stakeholders and policy makers involved in SD action plan.