Industrial Engineering
73 theses under this subject heading
Ranking All Units in DEA
Data Envelopment Analysis (DEA) is a methodology to compare efficiency of Decision Making Units (DMUs). DEA is an extension of Charnes, Cooper and Rhodes work by introducing CCR model in 1978. Ranking DMUs is one of the main purposes of DEA in management and engineering. DEA evaluates some DMUs with efficiency score one as efficient DMUs and we therefore need to produce a reliable method for fully ranking DMUs. Some methods have been proposed in this concept and newly Khodabakhshi and Aryavash (2012) ranked DMUs relative to their combined maximum and minimum efficiency scores where efficiency is defined as ratio of weighted sum of outputs to weighted sum of inputs. Due to some obtained weights (multipliers) in DEA may be zero, previous methods have low ability in ranking DMUs because of eliminating the effect of corresponding input and outputs on DEA evaluations. We expand their method by assigning lower bounds on multipliers using facet analysis and then we propose an equitable and precise method for ranking all DMUs based on the modified CCR. Keywords: Data envelopment analysis, decision making unit, rank.
Impact of Supply Chain Strategies on Bullwhip Effect
Changes of today’s firm’s competitiveness strategies from firms level to improved Supply Chain level causes increases in number and importance of Supply Chain studies in the literature. Variation between demand and orders is became the most important problem and most studied Supply Chain topic. This problem named in literature as Bullwhip Effect, is studied in this thesis with possible 11 factors effect on bullwhip. By using the improved Bullwhip Effect formula; lead time, review period, demand distribution, ordering cost, numbers of forecast periods are found as the factors which have significant effect on Bullwhip. In addition to this, for the use of similar Supply Chain researches, or real Supply Chain members, an improved spreadsheet simulation tool is prepared to test the proposed Supply Chain structures effects on different Supply Chain performance measures.
Reconstruction of World Bank Classification of Countries and Moody’s Rating System
This thesis has two main objectives. The first objective is to analyze whether the classification of countries provided by the World Bank (WB) can be reconstructed with a linear and/or integer-programming model known as Multi-Group Hierarchical Discrimination method, using only data published by the WB. The model’s parameters were determined for a collection of 44 countries, and the model was verified using another 39 countries. Moreover, the study examines the relative importance of factors in classification of countries. The second purpose of this study is applying Logical Analysis of Data for country risk rating to provide an approximate rating method. The employed data is available in World Bank and International Monetary Fund and the results are compared with Moody’s rating scale on year 2010. The country risk rating model was established for a collection of 71 countries, and the model was verified using another 34 countries. Furthermore, the study examines the relative importance of economical, environmental, educational, and infrastructure criteria in determining countries risk rating. Keywords: Multi-Group Hierarchical Discrimination, Classification of countries, Country Risk Rating, Logical Analysis of Data
Simultaneous Scheduling of Preventive Maintenance and Production for Single and Parallel Machines
In the last decades, the simultaneous scheduling of production and preventive maintenance has been receiving a considerable attention. Initially, in most researches, maintenance activities were treated as tasks with a fixed period. However, this assumption leads to create a hole in the time horizon. Recently, the variations in maintenance times were addressed, but the starting time is still fixed and known in advance in most of the works. There are few researches that consider the maintenance starting times as decision variables, especially in the non-preemptive case. In this study, the expected total completion time is minimized in the case of a single machine and random failures. The probability of machine failure is an increasing function of the age and the length of the time interval, and preventive maintenance reduces the machine age to zero. The problem is represented by a nonlinear integer programming model which is reduced later to an unconstrained 0-1 optimization problem. Subsequently, a method for solving the unconstrained model by identifying the preventive maintenance decisions is proposed. Moreover, the problem for minimizing the expected makespan on the single machine for the same above mentioned maintenance conditions is addressed and two heuristics methods were proposed to solve the problem. Additionally, the problem of parallel machines which are under the same reliability conditions, but they may have different values of maintenance parameters is discussed. An approximation method based on the bin packing‟s first fit algorithm as well as an exact branch and bound method were introduced to solve the problem. Finally, numerical examples were provided to illustrate each solution procedure of the proposed methods and some analysis was performed. The results show the benefits of integrating both decisions of production and maintenance, because some savings in the values of the discussed performance measures were obtained.
Cyclic Production of Flexible Manufacturing Cells
This thesis deals with two different flexible manufacturing cells. Both cells contain m identical computer numerical control (CNC) machines that are able to perform all the processes to produce a final product. The CNC machines are set up in a line layout. In the both cases, one input station and one output station exists at the beginning and at the end of the line, respectively. The items to be processed are kept in the input station, and the finished items are kept in the output station. In the second case, in addition to the input station, there is an individual input buffers attached to each machine. Using these buffers, each machine can be consecutively loaded twice in a cycle. In the both cells, a robot serves the machines and transports parts from the input station to a machine, loads the machine, and unloads the machine, after finishing its process, and puts the processed part in the output station. In these cells, m different parts will be processed in every cycle. Each part is processed completely by one machine. If the system is at a specific state at the beginning of a cycle, it reaches the same state at the end of the cycle, and then repeats the same actions in the same order in the subsequent cycles. To show all of the possible cycles in such cells, a sequential part production matrix is presented considering a general case. The duration of a cycle is called cycle time. The objective function of both cell types is to find the order of robot operations that minimizes the cycle time which maximizes the long-run average throughput rate of each cell. For the first case, a new mathematical model is presented to optimize the system. A reduced version of the new model is also provided. The reduced version is still an exact model of the minimization of the cycle time, however it does not determine the waiting times of the robot directly. These two models are more effective than the previous existed exact models in the literature. The solution of the reduced model requires significantly less CPU time comparing to the other models. A metaheuristic algorithm based on simulated annealing algorithm is proposed. In order to compute the minimum cycle time in each iteration of the algorithm, a linear programming model is needed to be solved which is the first case in the literature to the best of our knowledge. A new proof is provided for the lower bound of cycle time. This new proof facilitates the optimality analysis of several sequences of the robot movements. For the second case, a mathematical model is presented to optimize the cyclic production. A two-machine cell is discussed in details. In addition to some lower bounds of the cycle time for different orders of robot movements, the optimal cycles and upper bounds for the cases with different activities are also investigated.
Failure Modes and Effects Analysis (FMEA) Method Based on Data Envelopment Analysis (DEA) Approach for the Efficiency Measurment of Radio Frequency Identification (RFID)
There are many papers which emphasize on the benefits of radio frequency identification (RFID) technology implementation in the management and the production. This technology is used in many fields such as inventory, logistics, return management, order picking in a warehouse, assembly and testing and health care Etc. The existing literature examined the efficiency of RFID based on one of the following factors: accuracy, reliability, service enhancement, cost, time, work efficiency, flexibility, interactivity, risk management, emergency, privacy, energy and big Data. In this research, we will shed the light on the failure modes of this technology by using FMEA Approach, then we will measure the efficiency of solving each of these failures according to their severity, occurrence, detection, cost and time; using data envelopment analysis (DEA). DEA is a non-parametric method that evaluates the efficiency of the collection of decision making units (DMUs) when all of them consume and produce the same inputs and outputs respectively. A DMU can be efficient when it is able to produce more outputs by consuming fewer inputs. This economical point of view transforms the issue into a linear programming problem. Based on DEA concept, each failure mode of the RFID technology will be considered as a DMU, and the above mentioned criteria as inputs/outputs. Then the efficiency of these DMUs will be evaluated by DEA models.
An Evaluation of Efficiency, Productivity and Sustainability of the Hotel Industry in Tunisia using a Two-stage DEA method
Hotel industry is a very important domain of the tourism industry that is known for its large presence and growth. This service industry does not only consume a huge amount of resources (water, electricity, fuel…) but also intensifies the environmental problems. There have been very little work directed towards sustainability in the hotel industry. An understanding of the situation of the hotel industry and its relationship to sustainability may help improve the performance of this industry while taking into account the economic, social and environmental concerns of sustainability. To investigate the performance of the hotel industry, first, two-stage data envelopment analysis (DEA) method is used to evaluate the efficiency of the hotel industry in the tourist regions of Tunisia for the period 2014-2015. Next, the impact of a number of independent sustainability variables on the efficiency of hotel industry is tested using Tobit regression model. Finally, the Malmquist productivity index is assessed to examine the level of productivity in hotel industry of the tourist regions in Tunisia. The results reveal that the average efficiency of the hotel industry in Tunisia is 66.83% for 2014 and 61.41% for 2015, and the average productivity is 57.18%. The results conclude that sustainability has a positive impact of the efficiency of the hotel industry. The results of this thesis provide understanding on ways to improve the performance of the hotel industry and the sustainable development. Keywords: Bootstrapping, DEA, Efficiency, Hotel industry, Malmquist productivity index, Productivity, Sustainability, Tobit regression model.
Stochastic Facility Location Problem with Distributed Demands along the Network Edges
Since 1960s, facility location problem (FLP) has been studied by a myriad number of researchers. Nowadays, it is one of the most prominent branches of operations research which is applied in different fields such as determining the location of warehouses, hazardous materials sites, automated teller machines (ATMs), coastal search and rescue stations, etc. Also, the application of FLP in emergency logistics for choosing the best location of service centers has become rampant recently. On the premise that demands are uniformly distributed along the network edges, two network location problems are investigated in this study. For both problems, some of the candidate locations will be selected to establish the facilities. The first problem is a multiple-server congested facility location problem. It is assumed that demands are generated according to the Poisson process. Furthermore, the number of servers in each established facility is considered as a decision variable and the service time for each server follows an exponential distribution. Using queuing system analysis, a mathematical model is developed to minimize the customers’ aggregate expected traveling times and the aggregate expected waiting times. The second problem is a combined mobile and immobile pre-earthquake facility location problem. Each facility is used in the relief distribution operation. It’s incontrovertible that due to earthquakes, some network edges collapse and corresponding areas may lose their accessibility. Thus, it’s assumed that people on intact and accessible edges travel to the location of the distribution centers to receive the relief. For those who are located on collapsed or inaccessible network edges, the medium-scale Unmanned Aerial Vehicle (UAV) helicopters are utilized in the relief distribution operation. The mathematical model developed for this problem minimizes the aggregate traveling time for both people and UAVs over a set of feasible scenarios. In order to demonstrate the applicability of the model developed, a case study based on Tehran earthquake scenarios is presented. Since network location problems are NP-hard, three metaheuristic algorithms including genetic algorithm, memetic algorithm, and simulated annealing are investigated and developed to solve the proposed problems.
An Extension of Smart Failure Modes and Effects Application for Wind Turbines
Energy is a critical part of socio-economic growth and financial expansion. Wind energy, for instance, is a RE source that is native to the area and may assist in reducing reliance on fossil fuels. Electricity production from wind energy has increased dramatically in recent years all around the earth. The most critical challenge for the wind business is effectively predicting the dependability and availability of newly constructed WT. Furthermore, the FMEA approach has been utilized to investigate the dependability of a variety of power production systems. We suggest evaluating the windmill system technique using Smart FMEA, which is a mix of standard FMEA, DEA, and AHP. The components of WT are the focus of the failure mechanisms, impacts, and analyses. As components of WT, time and costs criticalities are gained. Several crucial choice criteria are validated under this study, in addition to weather (temperature, wind speed, wind direction, and so on) and wind turbine type. It also examines the interaction between components of wind farms that will be presented as downtime, cost criticalities are examined with a type of WT using AHP and DEA with crisp linguistic modeling and analyzes the impacts of decision factors while applying Smart FMEA on WT. Keywords: Data Envelopment Analysis, Wind power, Wind turbine, Renewable Energy, Feasibility Study of Wind Farm, Smart FMEA, Analytical Hierarchy Process.
A Real Life Feasibility Analysis in a Delivery Service System
Online food ordering is an emerging field in recent years in the restaurant industry. The availability of this platform provides customers with convenient food shopping and restaurants with increased productivity and order accuracy. Feed Me Cyprus (FMC) is an online food ordering application, that has been in progress since the beginning, now it is considering to start the delivery service by itself. For this purpose, the feasibility of establishing the own distribution network for a real-life service system which is FMC was analyzed in this research. Two strategies have been developed, one with considering the restaurants separately and the other with grouping restaurants according to their locations. All related data and information are obtained from several resources and the problem was formulated as a mixed-integer programming model. The developed model was used to find the expected annual profit of FMC for all alternative scenarios. Both of the strategies, by trying different service prices: 6, 7,…,10 Turkish lira (TL) and delivery units were profitable. The second strategy is developed to increase the utilization of the delivery units and the expected profit of FMC by combining restaurants in groups based on their locations. By applying a comparison between the results of the two strategies, the second one was more profitable. In this way, some useful information and guiding comments for FMC are obtained by implementing several economic analyses based on the found numerical results of the second strategy. Except for some cases in price 6 TL, the results for the rest of the prices in economic analyses were acceptable based on their net profit and payback period. Keywords: Feasibility analysis, Distribution, Online food delivery, Economic analysis, Mixed-integer programming
Investigating Gap between Customers’ Taste and Market Variety and its Impact on the Customer Satisfaction: An Empirical Study in the Automotive Industry
This study investigates and examines the gap between customer preferences and market variety in the Iranian automobile market and its impacts on customer satisfaction. A linear approximation is used for the utility function of customers of the Iranian carmaker (Iran Khodro Co). Also the SERVQUAL model for measuring customer satisfaction is used to determine, the gap between customer expectation and perceived quality. The moderator variable called “Role of car in the customer life” is introduced and its effect on the relationships between customer expectation, perceived quality and customer satisfaction is evaluated. The results show that considering the history of car sales over the past five years compared with the value predicted by the existing car market share, a significant gap between the current sales of IKCO and a product assortment ideally adapted to the customers is detected. The highest gap occurred between the level of expectation and the perceived quality of factors, respectively belonging to sale, car accessories, technical and physical aspects and the after-sale services. In this way, companies can elaborate better strategies and production plans and can increase their market share. As a contribution, this study provides a method for identifying customer behavior based on choices among options consisting of a set of qualitative and quantitative factors. So the method presented in this study can be used to empower automakers corporations to increase their competitive advantage and create the readiness to enter and compete in global market. This could prevent decline in automakers share and increase their profitability through achieving customer satisfaction. We live in a dynamic and changing environment. Changes in customer tastes and purchasing power; Changes in technical standards specifically regulations related to polluting potential of cars and tariff regulations; Changes in market structure toward openness to global market and increasing competition, could reduce the applicability of this research results. So these are open questions for future researches. Also as a topic for further research, the number of vehicles and factors types can be changed to evaluate the market share. Also, the effect of the moderator variable on customer satisfaction for other useable products and services may be investigated.Öz:Bu çalışma İran otomobil piyasasındaki müşteri tercihleri ve pazar çeşitliliği arasındaki boluğu ve bunun müşteri memnuniyeti üzerindeki etkisini araştırmakta ve incelemektedir. İranlı otomobil üreticisi (İran Khodro Co) müşterilerinin yarar fonksiyonu için doğrusal bir yaklaşım kullanılmıştır. Ayrıca müşteri beklenti ve algılanan kalite arasındaki boşluğu belirlemek ve müşteri memnuniyetini ölçmek için SERVQUAL modeli kullanılmıştır. "Müşteri hayatında arabanın rolü" adlı moderatör değişken olarak tanıtılarak müşterinin beklentisi, kalite algısı ve müşteri memnuniyeti üzerindeki etkisi değerlendirilmiştir. Sonuçlar, son beş yıl içerisindeki otomobil satışlarıyla mevcut araç pazar payı içerisindeki değeri karşılaştırıldığında, IKCO’nun mevcut satış ve ideal müşterilerine uyarlanmış bir ürün yelpazesi arasında anlamlı bir fark tespit edilmiştir. En büyük fark, satış, araba aksesuarları, teknik be fiziksel donanım ve satış sonrası hizmetlerin beklenti düzeyi ve kalite faktör algıları arasında meydana gelmiştir. Bu şekilde, şirketler daha iyi strateji ve üretim planlarını hazırlayarakmak pazar paylarını artırabileceklerdir. İleri bir araştırma konusu olarak, araç ve faktör türlerinin sayısı değiştirilerek pazar payı değerlendirilmesi önerilmektedir. Ayrıca, diğer kullanışlı ürün ve hizmetler için müşteri memnuniyeti moderatör değişkenin etkisi araştırılabilir.
Supplier Selection in Service Industry Using Analytical Hierarchy Process
Every production system including the tourism industry which creates services to customer satisfaction is directly part of supply chain must have its contractor and decisions about the appropriate suppliers. For hotels are a major issues of concern since its assumption will deploy an inclusive choice of scientific co-operation extended within a particular era. For as we all know that, every firm hugely depends on a reliable supplier for their products, therefore suppliers play vital role to make any organization reach the peak of cost efficient and profitable. Supplier selection (SS) has a great impact on integration of the Supply Chain Relationship (SCR), and the best supplier will greatly help to enterprises efficiency between supply chain (SC) partners and consequently enhance organizational performance. To the best of our knowledge, there are many studies regarding supplier selection for various industries, most of them are good production systems and only few are related to service industry. However, there is no study for hotel business. In this study we are considering some significant factors to determine which of them is the most important to be accepted when making a selection for the right supplier in hotel business. Via evaluating the weight of each factor using Analytic Hierarchy Process (AHP), through Pair-wise Comparison Matrix’s (PWCMs) of a given criteria and the weight of the numerical scale of judgment are used to represent the relative important among the Multiple-Criteria Decision Makings (MCDMs). For evaluating and selecting the best supplier in hotels was a realistic attempt by implementing a survey questionnaire which was sent to the top managers in various hotels through a well-designed internet web-site which was used to justify the AHP judgment from the decision makers (DM) or experts. For assigning the efficacy and accuracy of the identified criteria and their weights the real life application is applied to a hotel in Cyprus. The landscape and geography of Cyprus gives potential to run a hotel business, and therefore this part of touristic industry has succeed high degree of competitiveness. The facilitated and determined weights of criteria in real life may provide a privilege for hotels to analyze alternative suppliers and make the best decision. The main contribution of this study is that utilize weight of the criteria is used to enhance the efficiency and flexibility of the supply network and selection process for continuous improvement of hotel business.
Minimization of Emergency Response Time by Incorporating Aerial Transportation
In this thesis, we deal with two different real-life medical emergency service problems. In these problems, we consider a city in which the locations of all the hospitals, medical service centers, and the other emergency care centers are known. In both problems the emergency services are deployed using aerial and ground vehicles for moving towards patients in their locations after receiving a call, performing the initial emergency medical care, and transporting the patients to the hospitals or other medical care facilities. For this reason, the accidents or demands are classified into two types the severity accidents which need aerial vehicles and normal accidents which are operated by ground vehicles. According to the average number of the accidents in each location (node) and the severity of the accident, a weight is assigned to each node. In the first problem, we assume that the ground emergency services are optimal and we just deal with assigning a given number of the aerial vehicles to the hospitals or the medical care centers for the severity accidents or emergency medical demands in a way that the total response time by the aerial vehicles is minimized. In another words, this type of the demands for ground and aerial services are different in this type of the problem. In the second problem, we are dealing with both ground and aerial medical services together and at the same time. As the number of the accidents or the demands for both ground and aerial services are known and separate. In this type of the problem we are aiming to assign a given number of the aerial and ground vehicles to the hospitals or the medical care centers in a way that the total response time by all the aerial and ground vehicles is minimized.
Logistic design and facility location for organ transplantation centers
[Abstract Not Available]
Cyclic Scheduling Problem of a Flexible Robotic Cell with a Self-Buffered Robot
Extensive usage of automatic processing in industries has created Flexible Manufacturing Systems (FMSs). In a robotic FMS there are some Computer Numerical Control (CNC) machines for processing the parts, there is an input buffer for keeping unprocessed parts and an output buffer for finished parts, and at least one robot for transporting the parts in the system and loading/unloading the machines, and a central computer controlling the system. Such systems provide advantage in flexibility and standardization in production systems and they have been employed in recent years in order to keep up with the market competition. In order to use the system efficiently the system should be scheduled carefully. In this content, the order of the robot actions such as robot movements and loading/unloading activities should be determined for maximizing the system’s efficiency. When the system repeats a cycle in its run maximizing the efficiency is equivalent to minimizing the cycle time. This thesis considers a robotic FMS in which there is a single self-buffered robot which has the ability to carry more than one part at a time in an inline robotic cell where parts produced are identical. The system repeats a cycle in its long run. The problem is to determine the schedule of the system for minimizing the cycle time. A Mixed Integer Programming (MIP) model of the problem is developed to find the optimal solutions. Since the developed MIP model could not solve the large size problems a Simulated Annealing meta-heuristic algorithm is developed to solve those problems. Performances of the proposed methods and considered robotic FMS cells are evaluated on several numerical instances. Numerically, it has been shown that the performances of the proposed methods are satisfactory and the performance of the robotic FMS increases significantly by using a self-buffered robot up to some robot buffer capacity. After a point more robot buffer capacity becomes useless. Keywords: Flexible Manufacturing Systems, Cyclic Robotic FMS Scheduling, Self-Buffered Robot.
Performance Efficiency Evaluation of European Countries Healthcare Systems during the Pandemic (Covid-19) Using the Data Envelopment Analysis
In this paper, a non-parametric method known as Data Envelopment Analysis was used to analyse the efficiency of the healthcare systems of 48 European countries in managing the covid-19 pandemic. Using the constant returns to scale model of Charnes, Cooper and Rhodes (CCR) on input and output variables like total population, total covid-19 cases, total tests performed, total recoveries etc, the results showed that only 10 out of the 48 countries were optimally efficient in their management of the pandemic with some of the richest countries like France and Belgium being some of the poorest performers. Minimally developed countries like the Czech Republic, Andorra and Moldova were some of the best performers with Moldova being the most referenced optimal country in the benchmark test. It was shown that the inefficient countries like France and Belgium had to reduce the number of cases via distancing and lockdown measures to improve efficiency. The same goes for minimally efficient countries like the United Kingdom. The results finally indicate that developmental indices like gross domestic product (GDP) had an insignificant impact on the efficiency of countries in managing the pandemic as very rich countries were poor performers, although their high populations likely skewed the efficiency ratios in comparison to high performing countries with low populations. Keywords: Data Envelopment Analysis, DEA, CCR, European, Countries, Healthcare, Efficiency, Gross Domestic Product, Total Population, Covid-19, Tests
Performance Evaluation of Iranian Private Banks Using Data Envelopment Analysis (DEA)
Assessing performance of any organizations is necessary in guiding their future strategic decisions. Banks also are no exception. The purpose of this study is to evaluate the performance of 15 Iranian private banks using data envelopment analysis in 5 years period using Data Envelopment Analysis (DEA). The result will help these banks to improve their performances by focusing on inadequate factors and evaluate their efficiency among the competitors. In the process of evaluating the banks, all of the important indicators are verified and inputs and outputs have been selected in order to assess the efficiency of the banks based on previous studies and the views of experts in this field. Then, the efficient and inefficient banks and their operational rank were determined. Also, reasons for inefficiency of banks would have been detected and proposal for improvements would be discussed. Keywords: Private Banks, Banking efficiency, DEA, Iranian Banks, Privatization
The Impact of Musculoskeletal Discomfort on Traditional Education System and Tablet-Assisted Education System: A Comparative Study
With the advances in the technology, computers are more involved in education, with various forms. Especially tablet computers are actively used for educational purposes. Given the fact that musculoskeletal development of children and adolescents is still continuing, potential musculoskeletal problems resulting from usage of such technologies must not be disregarded. The aim of this research is to investigate posture and musculoskeletal system of students during traditional and tablet assisted education activities. Descriptive analysis of the literature was conducted to discuss the impact of traditional education on students. To determine the impact of tablet assisted education system, a survey was conducted on to 406 students, and Logistic Regression Analysis was carried out to identify the correlation between musculoskeletal discomfort and tablet computer use. The validation of the risk factors determined in the model was tested by applying Analysis of Variance to the Surface Electromyogram records for the control and experimental groups. The results of the statistical analysis revealed that the physical discomforts due to tablet computer use are intensively experienced in neck, upper back, lower back, and shoulder regions, which are very similar to those experienced in traditional education. Reading and writing activities have an impact on the shoulders, upper back, and left upper arm. The developed risk assessment model shows that both educational and extra-curricular activities create significant risk factors for physical discomfort. Keywords: physical discomfort, risk assessment model, tablet-assisted education, traditional education, children/adolescent.
Transport the Injured People to Hospitals on the Post-Disasters
The objective of thesis is to propose better design of EMU Library by assessing its furniture and its impact on the understudy stance, execution and consideration. We discovered that the EMU library furniture (Chairs and Tables) are not suitable for students' health. One hundred and fifty seven undergraduate and postgraduate were used as a subject. They were between 16 to 45 years old. Twelve measurements of anthropometry of the students were measured including: Shoulder Height (SDH), Stature, Shoulder Elbow Height, Popliteal Height, Knee Height, Forearm Length, Buttock-to-Popliteal Length, Elbow Sitting Height(EH), Hip Width, Sitting Height, Sitting, Overhead Stretch Height, and Eye Height. Standard deviation, mean, percentiles, least and greatest estimation of measurements were figured. Arrangement of the present light of the library was assessed by recording the illumination level on every table on second floor of library. The present light system was found to neglect to consent to ergonomic configuration criteria. Another configuration of furniture and recommendation of light system proposed to enhance the level of solace for students. Keywords: Ergonomic design criteria, Anthropometric data, Mismatch, Percentile
Application of Data Envelopment Analysis by the Evaluation of the Quality and Operational Factors
In the last decade, soft drink products among FMCG (Fast Moving Consumer Goods) industry have been facing serious problems due to the change in the consumer preferences. Health concerns towards these products had risen and companies keep making strategies to cope with this change. Since, the condition of the market shares getting narrower, maintaining efficient operations throughout the industry supply chain became an essential matter. The study focuses on the efficiency evaluation of soft drink company’s production lines between 2010 and 2015 located in Köprülüköy Cyprus, since the production phase is one of the most essential part of the whole operation. Data Envelopment Analysis is a widely known technique used for the evaluation of technical efficiencies of decision making units where multiple inputs and multiple outputs were under concern. Here, production lines of the production facility have chosen as DMUs and among the models of DEA, standard CCR and standard BCC models were utilized. Since the study was being performed in FMCG sector, where perishable food products were under concern, quality factors were also taken into consideration besides operational factors in the operation. Especially for the food production process, efficiency of the whole operation is definitely affected by the efficiency of the quality operations. In this study a general procedure for the evaluation of the production line efficiencies for the perishable goods had built that could easily adapted to the whole industry. Findings of the models can help management in decision making process, budget planning purposes, categorize production lines, future plans, and help to build a corporate memory for the efficiency of the lines. Keywords: Data Envelopment Analysis, FMCG, Quality Factors, Operational Factors, Efficiency, CCR Model, BCC Model, Food Production, Soft drink.
Application of Fuzzy AHP and Fuzzy TOPSIS in Selecting Proper Contractors: Case of Sistan and Baluchistan Province Gas Company
ABSTRACT: The selection of contractors is, counted to be the most substantial decision of an employer before the execution of a project. During the recent years there have been many problems during the execution of projects leading to waste of lots of capitals. Yet, there is always a significant risk during the selection of contractors. In this research, legal limits and requirements in connection with the organization of governmental tenders are studied to determine effective factors on the selection of contractors by Sistan & Baluchistan Province Gas Company in Iran, and to present proper solutions to choose the most appropriate contractor. A descriptive - measurement method is used for this research to gather information from experts of the company to analyze them in order to design a fuzzy model to assess if contractors are qualified or not. In this context, a fuzzy method of AHP (Analytic Hierarchy Process) is applied to determine weights of criteria and sub-criteria in selection of contractors. Then, the fuzzy method of TOPSIS (Technique for Order Preference by Similarity to Ideal Situation) is used to classify the top three contractors who achieved highest points of evaluation. By applying fuzzy AHP method, the relative weight of executive records, good records, financial powers, technical and planning capacities, and equipment and machinery criteria are determined to be 0.215, 0.216, 0.205, 0.186, and 0.178 respectively. Three best qualified liable contractors are then selected based on the given scores in three conditions as the pessimistic, most likely and optimistic to the above criteria using fuzzy TOPSIS technique. The proposed model in this research, offers a systematic method to identify effective measures for evaluating competence of contractors and selection of contractors that involve and consider the employer's goals; as well as the type of project, available resources and executive constraints. Keywords: Contractor selection, analytic hierarchy process, TOPSIS, fuzzy set, triangular fuzzy numbers. …………………………………………………………………………………………………………………………
Work Related Musculoskeletal Discomfort among Iranian Heavy Truck Drivers
Musculoskeletal Disorders (MSDs) are the common health problems among individuals in different occupations. Heavy truck drivers are exposed to various psychological, psychosocial and physiological factors such as Whole Body Vibration (WBV), awkward positioning, bad eating habits and etc. which some of them cause the prevalence of musculoskeletal discomfort in different body regions. In Iran, the prevalence of musculoskeletal discomfort among the heavy truck drivers is a mutual concern. Thus, investigation related to association of different factors with prevalence of musculoskeletal discomforts is necessary. Cross sectional study method is applied in order to assess association of factors with the occurrence of musculoskeletal discomforts. 384 Iranian heavy truck drivers are interviewed by an updated Nordic Musculoskeletal Questionnaire (NMQ). Furthermore, hypothesis testing is used to assess the associations of different factors and musculoskeletal discomfort reported by participants. Logistic regression method is used to investigate the different correlations among questions of the survey and different body sections that Interviewees experience trouble as well. Moreover, Rapid Entire Body Assessment (REBA) technique is applied for various positions of drivers whom used in order to fulfill different job tasks. Results demonstrate that 57% of the drivers are suffering from discomfort in their lower back region. Additionally, neck, left shoulder, right shoulder, knees and upper back, are among the high prevalence region that musculoskeletal discomfort has been reported. Hours of exposure to vibration were associated with discomfort of neck (p- value=0.00) and shoulders area (p-value=0.00); though, such a relation was not found for the discomfort of lower back (p-value=0.30). In addition 24 mathematical equations have been illustrated with significant predictors‟ questions and their correlations with the prevalence musculoskeletal discomfort of different body regions of truck drivers. REBA method improved three different positions of the truck drivers; however, seating position behind the steering wheel is remains at high risk position category (REBA score=10). Keywords: Musculoskeletal disorders, WRMSD, REBA, Logistic regression, Nordic Musculoskeletal Questionnaire
Musculoskeletal Activities and Possible Musculoskeletal Discomfort Among Students Using Desktop / Laptop / Tablet Computers: A Case Study with a Special Emphasis to the Use of Tablets for Educational Purposes
[Abstract Not Available]
Modified Data Envelopment Analysis of Multiple Response Experiments in the Robust Parameter Design Procedures
Selecting the optimum process parameter level setting for multi-quality processes is cumbersome. Robust parameter designs procedure that utilizes different strategies for improving performance/productivity during product and process design so that quality response can be obtained efficiently and optimally. An inevitable problem that is associated with the product and process design is in appropriating process variables that will yield optimal response. The complexity of the problem is peculiar with multiple response experiments (processes) where different factor level combinations yield varying responses. Previous methods are plagued with complex computational search, unrealistic assumptions, ignoring the interrelationship between responses and failure to select optimum process parameter level setting. This thesis proposes the implementation of modified variable return to scale (VRS) data envelopment analysis in the Robust Parameter Design (RPD) procedures to estimate and optimize responses of all non-dominated (significant) factors level combinations in multi-response experiments. This study also enhances the discriminatory tendency of the model by imposing VRS partitioning within the model. The model is conducted in a manner that with an adequate BPNN topology, experiment with incomplete, missing or censored data whenever encountered, could be investigated. Here, standard DEA modes are allowed to self-assess, the upper bound is restricted and the VRS penalization coefficient is adopted to determine the optimum process parameter level setting. The proposed procedures are applied to seven different case studies and the results were compared with existing methods of principal component analysis (PCA), DEA based ranking approach (DEAR), genetic algorithm (GA), grey relational analysis (GRA) and benevolent formulation (BF). The effectiveness of the proposed model measured by the total anticipated improvement yielded the highest total improvement over the existing methods. In overall, many inefficient DMUs that would have been promoted as efficient by the standard DEA models were revealed. The discriminative tendency further gives insight to DMUs that are within the convex set of the factor level settings and those that are not, thereby making the computation search for the optimal easy and simple.