Day 1 :
Keynote Forum
Majid Jaridi
West Virginia University, USA
Keynote: Analysis of the potential of renewable energy development in Saudi Arabia
Time : 10:15 - 11:00
Biography:
Dr. Majid Jaridi is a Professor of Industrial and Management Systems Engineering at West Virginia University. He earned his PhD in Industrial and Operations Engineering from the University of Michigan in 1983. He teaches courses in the areas of Statistical Design of Experiments, Quality Engineering, Forecasting, and Decision Analysis. He also serves as the Director of West Virginia Space Grant Consortium, a consortium of 12 colleges and several high technology companies in West Virginia. Dr. Jaridi’s research areas include forecasting and time series analysis, transportation planning, design of experiments, and decision analysis.
Abstract:
Saudi Arabia is a nation that has been exploring the potential of renewable energy for many years. Saudi authorities, scientists and researchers view renewable energy as a preferable long-term energy strategy. Despite this, because Saudi Arabia is one of the leading oil producing nations and relies heavily on it as a form of energy, solar energy has not been given much serious consideration. Solar and wind energy are the best sources of renewable energy in Saudi Arabia; however, because of the large amount of oil in the country, most do not want to explore the option of renewable energy. Hence, it is essential to explore the alternative sources to insure reliable supply for potential future need. The main objectives of this research were to: Establish the potential of solar and wind energy generation as a suitable, cost-effective alternative to petroleum products and; to establish the potential for maximizing renewable power generation to support the grid supply to Saudi cities. We developed three different forecasting models for 32 Saudi cities: the decomposition method, multiple linear regressions (linear trend model) and multiple linear models (seasonal model). We then selected a preferred model that can best forecast the amount of renewable energy capacity in the forecasting horizon. Using software written for this research, we developed an economic model to evaluate the cost of generation and transmission of solar as well as wind energy at the selects cities in Saudi Arabia.
- Industrial Engineering
Location: 1
Chair
Hamed Fazlollahtabar
Mazandaran University of Science and Technology, Iran
Session Introduction
Muzaffar A Shaikh
Florida Institute of Technology, USA
Title: A fast plant-location heuristic using influencing factors
Biography:
Muzaffar A Shaikh completed his PhD in Industrial Engineering from the University of Illinois, Urbana Champagne. Currently, he is Associate Vice President for International Partnerships, Distinguished Professor, and Head of the Engineering Systems Department at Florida Institute of Technology, Melbourne, Florida, USA.
Abstract:
Globalization today has made the problem of locating a new plant extremely difficult due to a myriad of extra factors that did not possess high priority in the past. First, multinational corporations are engaged more than before in manufacturing parts of the same end product in different countries to minimize the cost of production. This contributes to considering additional factors (e.g., local culture, political stability, economic stability, safety and security, etc.) while evaluating plant location. Second, complexities arise when it comes to assembling parts together into the end product due to differing manufacturing standards of various countries. This abstract presents a numerical heuristic that uses pertinent influencing factors, computes their ratings to square grids formed by dividing the given area of interest (AoI). The heuristic starts with first evaluating larger grids (e.g., 100x100 miles) against influencing factors. Next, it utilizes initial results and reduces the larger AoI into smaller focused areas with a smaller set of grids. Grid sizes are reduced at the discretion of the industrial engineer to perform more focused analysis ofthe new AoI. This iterative process of grid evaluation continues until the engineer is satisfied with the most acceptable overall grid score. A key advantage of the heuristic is the ability to tweak input parameters to both determine the sensitivity of grid score to critical environmental factors and to attempt ‘what if’ scenarios.
Hamed Fazlollahtabar
Mazandaran University of Science and Technology, Iran
Title: Scheduling of multiple robots for a parallel assembly line using minimum cost network flow
Biography:
Hamed Fazlollahtabar is an Assistant Professor at the Faculty of Management and Technology of Mazandaran University of Science and Technology, Iran. He has done his BSc and MSc in Industrial Engineering from Mazandaran University of Science and Technology, Babol, Iran in 2008 and 2010, respectively. He has received his PhD in Industrial and Systems Engineering from Iran University of Science and Technology, Tehran, Iran in 2015. He is in the Editorial Board of WASET (World Academy of Science Engineering Technology) Scientific and Technical Committee on Natural and Applied Sciences, International Journal of Information and Decision Sciences, International Journal of Humanities and Social Sciences, and Member of the International Institute of Informatics and Systemics (IIIS). He has published over 200 research papers in international book chapters, journals and conferences. He has also published 5 books out of which three of them are internationally distributed to the academicians.
Abstract:
This research proposed a parallel automated assembly line system to produce multiple products having multiple autonomous guided vehicles (AGVs). Several assembly lines are configured to produce multiple products in which the technologies of machines are shared among the assembly lines when required. The transportation between the stations in an assembly line (intra assembly line) and among stations in different assembly lines (inter assembly line) are performed using AGVs. Scheduling of AGVs to service the assembly lines and the corresponding stations are purposed. In the proposed problem the assignment of multiple AGVs to different assembly lines and the stations are performed using minimum-cost network flow (MCF). It optimizes weighted completion time of tasks for each short-term window by formulating the task and resource assignment problem as MCF problem during each short-term scheduling window.
Amrita Jain
Manipal University, Dubai Campus, UAE
Title: Supercapacitors: Types, materials and applications
Biography:
Amrita Jain completed her PhD in 2014 from Department of Physics, Jaypee University of Engineering and Technology, India. She is working as an Assistant Professor in School of Engineering and IT, Manipal University, Dubai Campus. She has published more than 11 papers in peer reviewed journals. She is also co-author of books published with German publishers. She is also recipient of Young Scientist Award for her outstanding work in the field of energy storage devices by Govt. of Madhya Pradesh, India in 2012.
Abstract:
Supercapacitors or ultracapacitors are considered as one of the most upcoming and promising candidates for power devices in future generations. Because of its appealing properties, it is suitable for many advanced applications like hybrid electrical vehicles and similar other power devices and systems. In order to use this device in power applications, its energy and power density needs to be maximized. A lot of results from published work in the form of research and review papers, patents and reports are available this time. The purpose of this article is to re-look the journey of the materials used for supercapacitors with focus on the energy storage capability for practical applications. Moreover article also addresses the principal technological challenges which the research society is facing in the field of supercapacitors.
Biography:
Ahmet Feyzioglu has completed his PhD in 2012 from Marmara University and Post-doctoral studies from University of Manchester, Institute of Innovation Research. He has been working in the Department of Mechanical Engineering of the Marmara University since 2013.
Abstract:
The manufacturing processes are realized with effective implementation of automation. In this study, optimum revolution and feed rate values for different kinds of metals undergoing spinning manufacturing process are given. Spinning which is a chipless forming process used to produce axisymmetric parts, is one of the difficult manufacturing process to implement automation. If the process is done without any caution, some defects such as wrinkling, tearing or cracking, could be present in the spinning part. These are caused by applying unacceptable feeds and rpms to material and diameter. In order to reduce defects the material needs to be spun using appropriate feed rates and revolution per minutes. These values differ for each alloy of different diameter. There have been methods used to predict the behavior of the material in spinning. One example is in shear spinning surface roughness where required force can be determined by regression analysis. In this paper, scalar values for some of the parameters will be provided so that they can be applied directly to the forming process. The optimum values for some metals along with the related diameter are given for implement automation to spinning process.
Zin Eddine Dadach
Higher Colleges of Technology, UAE
Title: Effect of summer weather conditions on the environmental impact of a power plant in the UAE
Biography:
Zin Eddine Dadach obtained his Bachelor’s degree in Refining and Petro-chemistry from the Algerian Institute of Petroleum in 1980. He received his Master’s degree in Chemical Engineering from Stevens Institute of Technology (Hoboken, NJ; USA) in 1984. He obtained his PhD degree in Chemical Engineering from Laval University (Quebec, Canada) in 1994 and conducted a research in enzymatic degradation of biomass at the Osaka National Research Institute (Osaka, Japan) for two years. Since he joined the Higher Colleges of Technology (Abu Dhabi, UAE) in 2005, he has developed active learning strategies to enhance the intrinsic motivation of students. He supervised a number of students’ final industrial projects including the exergy analysis of power generation plants.
Abstract:
This work investigates the effect of summer weather conditions on the environmental impact of an Open Cycle Gas Turbine in Abu Dhabi (UAE) using an exergoenvironmental analysis. The results are used to suggest measures for reducing the calculated impact. Actual operational data are verified with simulation data using commercial software. Compared to standard weather conditions, the summer weather conditions in Abu Dhabi decrease the overall exergetic efficiency of the plant by 4.3% and increase the total environmental impact per generated KWh by 7.9%. The addition of a heat recovery steam generator could increase the net power output and decrease the total environmental impact of the plant. The main contributor to the environmental impact of exergy destruction is the combustion chamber. Summer conditions increase this impact by 21.5%. The compressor has the second highest environmental impact, increased by 14.6% for summer conditions. A process control system for continuous measurement of exhausted O2 and CO can help to reduce the excess air and, consequently, the associated environmental impact. This may also decrease the power required by the compressor. Lastly, a cooling system for the ambient air may also help to increase the power output of the plant by decreasing the power required by the compressor.
Majid Jaridi
West Virginia University, USA
Title: A comparative study of e-tail service quality scale in USA and India
Biography:
Majid Jaridi is a Professor of Industrial and Management Systems Engineering at West Virginia University. He earned his PhD in Industrial and Operations Engineering from the University of Michigan in 1983. He teaches courses in the areas of Statistical Design of Experiments, Quality Engineering, Forecasting, and Decision Analysis. He also serves as the Director of West Virginia Space Grant Consortium, a consortium of 12 colleges and several high technology companies in West Virginia. His research areas include forecasting and time series analysis, transportation planning, design of experiments, and decision analysis.
Abstract:
The purpose of this research is to measure the e-tail service quality of online retailers by considering survey responses from two different geographical locations, USA and India. This research focuses primarily on (i) Collecting data and performing factor analysis to refine initial scale items, developed by Qianqian, followed by reliability tests for checking the scale’s validity by considering responses received from survey participants in two different geographical regions; (ii) Testing of hypothesis based on the construct of the scale items of the initial scale and the scale obtained in this research; (iii) Performing regression analysis to demonstrate the impact of factors on the overall e-tail service quality. Based on Qianqian's initial scale items, the questionnaire was slightly modified to accommodate changes related to mobile e-tailing. Data was collected and analyzed further through item analysis and exploratory factor analysis. The scale is later tested for its reliability and validity, followed by regression analysis. Results revealed a variation in scale parameters when a global sample is considered. This research is based on the assumption that the key to improving customers’ online purchasing decisions is improving e-service quality, which in turn has a significant effect on transaction results. This research is purely theoretical, with basis on exhaustive literature review.
Muzaffar A. Shaikh
Florida Institute of Technology, USA
Title: A fast plant-location heuristic using influencing factors
Biography:
Dr. Muzaffar Shaikh completed his Ph.D. in Industrial Engineering from the University Of Illinois, Urbana Champagne. Currently, he is Associate Vice President for International Partnerships, Distinguished Professor, and Head of the Engineering Systems Department at Florida Institute of Technology, Melbourne, Florida, USA.
Abstract:
Globalization today has made the problem of locating a new plant extremely difficult due to a myriad of extra factors that did not possess high priority in the past. First, multinational corporations are engaged more than before in manufacturing parts of the same end product in different countries to minimize the cost of production. This contributes to considering additional factors (e.g., local culture, political stability, economic stability, safety and security, etc.) while evaluating plant location. Second, complexities arise when it comes to assembling parts together into the end product due to differing manufacturing standards of various countries. This abstract presents a numerical heuristic that uses pertinent influencing factors, computes their ratings to square grids formed by dividing the given area of interest (AoI). The heuristic starts with first evaluating larger grids (e.g., 100x100 miles) against influencing factors. Next, it utilizes initial results and reduces the larger AoI into smaller focused areas with a smaller set of grids. Grid sizes are reduced at the discretion of the industrial engineer to perform more focused analysis of the new AoI. This iterative process of grid evaluation continues until the engineer is satisfied with the most acceptable overall grid score.
Majid Jaridi
West Virginia University, USA
Title: A comparative study of e-tail service quality scale in USA and India
Biography:
Majid Jaridi is a Professor of Industrial and Management Systems Engineering at West Virginia University. He earned his PhD in Industrial and Operations Engineering from the University of Michigan in 1983. He teaches courses in the areas of Statistical Design of Experiments, Quality Engineering, Forecasting, and Decision Analysis. He also serves as the Director of West Virginia Space Grant Consortium, a consortium of 12 colleges and several high technology companies in West Virginia. Dr. Jaridi’s research areas include forecasting and time series analysis, transportation planning, design of experiments, and decision analysis.
Abstract:
The purpose of this research is to measure the e-tail service quality of online retailers by considering survey responses from two different geographical locations, USA and India. This research focuses primarily on (i) Collecting data and performing factor analysis to refine initial scale items, developed by Qianqian, followed by reliability tests for checking the scale’s validity by considering responses received from survey participants in two different geographical regions; (ii) Testing of hypothesis based on the construct of the scale items of the initial scale and the scale obtained in this research; (iii) Performing regression analysis to demonstrate the impact of factors on the overall e-tail service quality. Based on Qianqian's initial scale items, the questionnaire was slightly modified to accommodate changes related to mobile e-tailing. Data was collected and analyzed further through item analysis and exploratory factor analysis. The scale is later tested for its reliability and validity, followed by regression analysis. Results revealed a variation in scale parameters when a global sample is considered. This research is based on the assumption that the key to improving customers’ online purchasing decisions is improving e-service quality, which in turn has a significant effect on transaction results. This research is purely theoretical, with basis on exhaustive literature review.