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 main goal of this research was to pinpoint and understand factors that improve performance in automotive industry in North America. Obviously, the most important factor to improve automakers’ productivity is the manufacturing processes itself. However, in general, hours per vehicle (HPV) is a widely recognized and practiced measure that companies use to increase their performance level and raise productivity. Unfortunately, there is a limited understanding of the set of factors that affect HPV across the automotive industry at conceptual and technical levels. Using data from Harbour’s survey of 10 automakers in North America, we have developed the best fitting linear regression model for HPV that include 12 independent variables and some transformations that are controllable by the automakers. The Generalized Linear Model (GLM) was used to analyze the data and derive the HPV regression equations. Stepwise regression procedure was terminated after the inclusion of 9 significant variables (and their transformations) in the model. Automaker brands that supplied the data used in this study are: DCX, Ford, GM, Honda, Cami, Nummi, Auto Alliance, Mitsubishi, Nissan, and Toyota. Independent variables used in the statistical analysis were: vehicle segment, car assembly and capacity utilization, number of models, vehicle variety, platform strategy, production volume, flexible manufacturing, outsourcing, new product launch, annual available working days, salaried employees’ percentage, and year. Regression equations that were formulated in this research may be used effectively to help automakers to set guidelines to improve their productivity with respect to internal and external constraints, strength, and opportunities.

Biography:

N. S. V. Kameswara Rao has done Ph.d Engineering from IIT Kanpur, India. Currently he is working as a professor at School of Engineering and IT Universiti Malaysia Sabah. He has done his M.E. from IISC Bangalore. He is a Member of Editorial Board International Journal for Engineering Analysis and Design, Wiley Eastern Ltd., India. He has about fifty publications to his name. His research area includes Numerical Algorithms, Computational Mechanics, Computer Aided Design, Foundation Dynamics, Finite Element Analysis, Soil-Structure Interaction, Geomechanics, Numerical Methods and Analysis.

Abstract:

Several Scientific, Engineering and Natural Phenomena are complex and are not amenable for exact solutions. These phenomena are broadly classified in terms of the following mathematically different classes of problems: Equilibrium problems; Eigen value problems; Propagation problems and other problems not covered in these categories. Analysis of industrial structures and components of different shapes, sizes operating under diverse environments is the starting step for proper design and subsequent optimization processes. These components usually are in static or dynamic equilibrium besides thermal or other influences. Their analysis falls mostly in one or more of the above categories of problems. With the ready availability of high performance PCs, they are usually analyzed either by Finite Element methods (FEM) or efficient numerical procedures. Suitable algorithms have to be identified and or developed for implementation of these numerical procedures logically for computing the desired solutions. An algorithm is the sequence of logical steps required to perform a specific task such as solving a problem. It is analogous to a recipe. Important phenomena in Science and Engineering pertaining to the above classes of problems are reviewed. Algorithms commonly used for solving these phenomena are highlighted. Application of these phenomena for solving specific problems of industrial structures and components are outlined. Several examples of each of these classes of problems are illustrated. The vastly different and distinctive features of these problems are identified. The various numerical procedures available (besides the above commonly adopted algorithms) for solving these distinctive mathematical equations are presented. The algorithms and their characteristics for possible application to these problems are discussed. The usual shortcomings of these algorithms, error analysis, diagnostic and remedial measures are indicated. The need for developing efficient and accurate algorithms is stressed. Quality control aspects are discussed. Flow charts for these algorithms are presented for ready application in the analysis of Science and Engineering problems in general and industrial structures and components in particular.

Biography:

Volkan Cakir obtained his BSc in Electronics Engineering from Turkish Air Force Academy, Istanbul in 1992. He obtained his MSc in Industrial Engineering from Middle East Technical University, Ankara in 2001. He received his PhD in Engineering Management at the Old Dominion University, Norfolk, Virgina in 2011. His research interest areas are simulation, statistical quality control, system dynamics and risk analysis. He is currently an Assistant Professor and Head of the Industrial Engineering Department at Istanbul Arel University.

Abstract:

One of the alternative investment strategies of large-sized enterprises is to improve the supplier’s processes. Selecting the right suppliers will decrease company’s purchasing cost, increase customer satisfaction and improve the competition capacity. Supplier selection is a complex multi-criteria problem which includes both qualitative and quantitative criteria. In order to select the suppliers, it is necessary to make a tradeoff between these criteria some of which may conflict. Different approaches are suggested to solve the supplier selection problem in the literature. The main purpose of this study is to solve the supplier selection problem of the textile firm by using AHP and TOPSIS. Quality, cost, delivery and service criteria that are mostly used in literature are defined as main criteria in the paper, and also their sub-criteria are defined. AHP method is used to determine the importance degree of main criteria and sub-criteria, TOPSIS method is developed to rank the suppliers.

Biography:

Souraj Salah has completed his PhD from the University of New Brunswick in Canada. He is currently working as a quality manager for Juma Al Majid Group, in the contracting, services and manufacturing sectors. He has published more than 10 papers in reputed journals and has over 15 years of experience as a professional industrial engineer in the field of quality improvement. He is certified as a Black Belt by the Juran Institute and as a Master Black Belt by Alignment Strategies in Canada.

Abstract:

Lean Six Sigma is a well-recognized continuous improvement methodology for achieving operational and service excellence in any organization. The purpose of this paper is to explain how Lean Six can be implemented in real practice resulting in hundreds of thousands of dollars of actual savings (cost reduction and profit increase). This is demonstrated through three practical case studies on utilization of machines and labour, efficiency of production line and margin of sales process. All of these cases studies are real and they follow the structured approach of define, measure, analyze, improve and control (DMAIC). The approach and results of these case studies can be beneficial for managers and continuous improvement practitioners or engineers who can replicate the best practices and lessons learned from these case studies into their similar fields where it can be applicable.

Biography:

Dr. Raid Al-Aomar is a professor of Industrial Engineering and the director of Master of Engineering Management (MEM) program at Abu Dhabi University in the UAE. He holds a PhD in Industrial Engineering/Operations Research from Wayne State University in Detroit, USA. He has over 15 years of experience at companies and universities in Jordan, USA, and UAE with about 50 publications in the field of Industrial Engineering. He is also a professional trainer and a consultant on deploying Lean Six Sigma systems, Supply Chain, & Quality Management. He worked on many projects with the Auto Industry in Detroit and the industrial estates in Jordan and delivered many training courses to professionals in private and public companies in KSA, Bahrain, and the UAE. He is a co-author of "Simulation-based Lean Six Sigma and Design for Six Sigma" book from John Wiley. Dr. Al-Aomar’s research interests include Simulation-based Optimization, Operations Management, and Lean Six Sigma Systems.

Abstract:

Process improvement through downtime reduction is a common buisness practice nowadays. With the intention to improve or bring betterment in the regular processes and timely delivery of products and services, several techniques have been used in the past in a local establishment with differential results. However, almost none of them has proven to be as effective as Six-Sigma. Six-Sigma is one of the commonly practiced approaches with proven results and the quality assurance and is widely used in industries belonging to almost every sector. The theme of Six-Sigma is to minimize the number of defects in a business process context in terms of delays and downtime. A local establishment is a renowned multi-dimensional business establishments ranging from aviation machinery, equipment to travel agencies, tour operation, transportation products to beverages, and the company has a pretty wide business domain. The paper will focus on the technical division and will analyze the need of improvement and what can be done using the Six-Sigma approach. It is believed that the Six-sigma implementation in aviation equipment will significantly reduce the loss by lowering the number of defects. The paper will also discuss significant tools and techniques and their appropriate application for defect reduction and meeting the specifications set as standards.

Biography:

Shoaib Shaikh has completed his PhD in Operations Research at the age of 28 years from Florida Institute of Technology in Melbourne, Florida USA. His dissertation is titled “Design Optimization Using Statistical Techniques”. He is currently an Associate Professor at Florida Polytechnic University, a new state system university located in Lakeland, Florida USA focused on Science, Technology, Engineering and Math (STEM). He has extensive experience working in the Defense Sector and was employed at Lockheed Martin, Harris Corporation and Northrop Grumman, prior to joining Florida Polytechnic University.

Abstract:

In a unique approach, advanced statistical modeling techniques coupled with predictive machine-learning are blended to forecast future stock price movement. From the outset, the stock data is analyzed and “cleansed” for non-stationarity, including any underlying seasonal or trend components. The methods for characterizing the data include detrending and differentiation for normalization purposes. Next, using statistical inference techniques, hypothesis tests and confidence intervals are calculated to provide insight on potential future movement in stock price. This is further enhanced by determining volatility bands above and below the current stock price. These bands measure the variabiltiy of price movement based on historical data. For prediction purposes, two methods applied for this research include Auto Regressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANN). Trained ARIMA models provide greater insight between relationships in the historical stock prices and future stock price movement. ANN will be used as a verificiation and confirming quality measure to the ARIMA forecast.

Biography:

Full Professor in Industrial Design. Second University of Naples/ IDEAS Department of Industrial Design, Environment and History, Italy. He is currently Coordinator of the Ph.D. ADI_Environment, Design and Innovation in which taking place research and experimentation activities within in the science and technology curricula, sustainable for the environment and the territory curricula; Design and innovation for the productive activities of the cultural heritage curricula; Prevention and protection against risks to health and safety curricula.

Abstract:

The contribution sets new design and methodological processes and resulting from integration of different languages and levels, including the traffic system - vehicles, infrastructures and users; safety - active, passive and preventive; intelligent technology and perceptual experience (tactile interactive pathways and surfaces, acoustic signals, luminous contrasts, etc.). An efficient relational system among the sensors, communications system and intelligent applications connected to vehicles and users on the roads, in terms of active, passive and preventive safety, functionality, environmental sustainability, energy efficiency, economic savings and well-being of people. The identification of strategies aimed to develop the richness of spatial implies the introduction of good practices related to the related to the planning, control and management of road safety which fit within the processes of research, design and testing. The aim is to increase the level of "security" of our cities in an innovative and inclusive way so to make it possible that the largest possible number of people with a disability and able-bodied people could improve their life quality in an easier, safer and broader way. The fruition in “real time” of an information network based on “Smart” sensors, according to an adaptive approach, would guarantee the possibility of a correct integration between the various devices already available to provide adequate levels of road safety, in order to increase these levels by using “spot” information associated to the single user and by recognising his “vulnerabilities”. It is necessary to consider the synergies and objectives of the various traffic's components - vehicle - infrastructure - user system, to operate in an integrated, holistic and coherent manner.

Biography:

Pradip Kumar Ray is presently a Professor in the Department of Industrial Engineering and Management, Indian Institute of Technology (IIT), India. He served as the Head of the Department from 2006-2009. He received his PhD and MTech degrees from IIT Kharagpur and Bachelor of Mechanical Engineering degree from Calcutta University, India. He has about more than thirty three years of diversified experience; eight years as Senior Industrial Engineer/Manager at General Electric Company of India in Calcutta and more than twenty five years of teaching and research experience at IIT, Kharagpur. He has also served as Associate Professor at Eastern Mediterranean University, Cyprus and as Visiting Faculty at University of South Pacific, Fiji Islands and trained in Japan on Production Management/JIT-based Manufacturing. He has published one text book titled ‘Product and Process Design for Quality Economy and Reliability’, four book chapters and around 130 papers in international and national journals of repute and conferences. Currently, he is acting as an investigator in UKIERI-sponsored project on ‘Climate Change Issues and Environmental Performance of SMEs in India and UK in collaboration with, Aston University, UK and as the principal investigator in OFB-sponsored project on 130-mm shell process study including its ballistic behavior.

Abstract:

In the fast-changing technology-intensive, innovation-centered and human-focused international scenario, organizations in any sector of a national economy need to improve their performance continually emphasizing on all its critical dimensions and issues in respect of business goals, quality of work life and environmental and social sustainability concurrently. An organization’s knowledge, expertise and effort are required to be directed to plan, assess and control its performance in totality. Robustness of organizational systems, assurance of total performance and sustainable development within the societal framework are three main aspects to be considered at both strategic and operational levels of any organization for development of world-class benchmarked products, processes and work environment. Briefing the current status and practices in some leading countries in respect of relevant issues and factors in this context, details of a total performance assurance system with its implementation potential in organizations are presented in this presentation. Discussing the kinds of problems to be dealt with in establishing sustainable manufacturing processes and systems and the managerial roles and responsibilities in designing such an assurance system with information and technology system support as required in the current scenario, the presentation highlights the research issues and specific challenges to be addressed for assurance of benchmarked performance of any organizations.

Biography:

Despo Ktoridou is currently an Associate Professor and Head of Management & MIS Department at the University of Nicosia in Cyprus. Dr. Ktoridou holds a B.Sc. (1991), M.Sc. (1993) In Computer Engineering and a Ph.D. (2000) in the field of Expert Systems from Saint Petersburg State Electrotechnical University in Russia. Dr. Ktoridou has worked as a Senior Computer Engineer for different organizations in Cyprus (1992 – 1999), from 2000 – 2007 as an Assistant Professor of Educational Technology and currently as an Associate Professor of MIS at the University of Nicosia. Dr. Ktoridou’s research focuses on areas of Information Communication and Social Technology application in education, Innovative Teaching /Learning Pedagogies in Higher Education and Engineering and Technology Management education. Dr. Ktoridou has presented papers in numerous refereed international conferences and has published several papers in refereed journals. Dr. Ktoridou participated in EU and local funded programs and has been invited by foreign universities as a guest lecturer

Abstract:

Continuous technological, economic and social challenges influence higher educational institutions to equip students with the necessary knowledge, skills and competences to work in such challenging context. In the same context, today’s businesses continuously seek innovative engineer-managers not only to design systems but to manage projects/design and development, create strategic plans, handle financing, interface with marketing and recognize and evaluate market opportunities. Management graduate education and Masters in Business Administration (MBA) are considered the most common degree programs offered by business schools worldwide. Even though both degrees serve their purpose well their comparison depends exclusively on the career goals and ways that graduates plan to utilize their degree. For the case of engineering education, engineer graduates tend to undertake management positions within the organizations they are employed with evidence from research showing that engineers who favor a managerial path have considerably stronger wish for promotion while engineers who clearly want to follow the technical path remain committed to system design. This is evidence that postgraduate studies in management are vital for engineers since more and more engineers need to develop management skills. Within this context, the authors describe and explain the philosophy and foundation that underlines the new Master of Science in Engineering Management at the University of Nicosia. They also provide evidence for the program’s evaluation by three experts from industry and academia. The results of this study suggest that higher educational institutions should design such specialized management education programs for engineers who wish to recognize and evaluate market opportunities and understand the enterprise formation process.

Biography:

M Srinivasa Rao is a Professor in GMR Institute of Technology, Rajam, India. He received Doctorate degree in Reliability Engineering from Reliability Engineering Centre at Indian Institute of Technology, Kharagpur, India. He received his BE in Mechanical Engineering and ME in Industrial Engineering from Andhra University, Visakhapatnam, India. He has published his research works in many international journals and presented papers in conferences. His current research interests include condition monitoring, mechanical system reliability, probabilistic risk and system assessment, quality planning and management, reliability and availability analysis and modeling of systems using simulation methodologies.

Abstract:

System reliability and availability are considered as important performance indices. Performance of engineering systems can be assessed by various techniques. The traditional analytical techniques become very complicated and unrealistic especially for modern complex systems. Many researchers have been searching for alternate methodologies for more practical and realistic reliability and availability analysis. There have been attempts in the literature to evolve more realistic techniques using simulation approach for reliability and availability analysis of systems. This research work proposes a hybrid approach called as Markov System Dynamics simulation approach to overcome some of the limitations of Markov process in a simple and efficient way for reliability and availability analysis of systems and to study the dynamic behavior of systems. In this work, various types of complex systems have been considered. The results of the simulation when compared with that obtained by traditional Markov analysis clearly validate the Markov System Dynamics approach as an alternative approach for reliability and availability modeling and analysis. The proposed methodology is applicable for all types of failure and repair rates and it is much simpler compared to traditional approaches.

Biography:

Mohsen Forouzanmehr completed his MSc from Sharif University of Technology, School of Science and Engineering, in the field of Applied Mechanics and Design Engineering. His research interests are residual stresses, FEM method, failure analysis, fracture mechanics, fatigue analysis, shot peening analysis, smart structures and materials and stress analysis.

Abstract:

This paper presents about a numerical investigation on the ability of Abaqus software for simulating CFRP-strengthened beams. In literature, there are several investigations about the failure mode of FRP-strengthened beams, so due to economic issue, lack of time and lack of laboratory facilities, laboratory testing is not always possible. In this research, a numerical solving was introduced for these beams with FEM method analysis. The data obtained from experimental procedure was compared with this work. CFRP-beams were divided into three groups (A, B, C) and in each group different loading was considered on the SENB three points samples in experimental investigation that were available and these results were compared with numerical results that were obtained by commercial code (Abaqus). The curve of loading versus mid span displacement for each type of beams were plotted and the results showed that there is a good agreement between experimental investigation and numerical results , so the response of Abaqus for this type of simulation is so good and it can be used as practical works in civil or mechanical engineering projects.

Biography:

Dr. Nitai Pal received his B.Tech. and M.Tech. from University of Calcutta, Calcutta, India in 1998 and 2000 respectively. He completed his Ph.D. (Engineering) from Jadavpur University, Kolkata, India in the year 2007. He is currently working as an Associate Professor in the Department of Electrical Engineering, Indian School of Mines (Under MHRD, Govt. of India), Dhanbad, Jharkhand, India. He has total experience of approximate fifteen years in teaching. He has total 40 nos. of research publications in various International and National Journals of repute. He has also presented several papers in International & National conferences. He is the peer reviewer of various International Journals like IEEE, IJCEE, IJCTE etc. He is the member of various professional International and National bodies. His specialization is Electrical Machines & Power Systems. His current areas of interest are power electronics applications, application of high frequency converter, renewable energy and its application, energy efficient devices, energy efficient drives, computer aided power system analysis.

Abstract:

In this paper, different issues related to modelling and stability of non-isolated power electronics converter are tried to address by the authors. The stability of different power electronics converters like Buck Converter, Boost Converter and Buck Boost Converter are analysed by using state space analysis in order to obtain the linear model for discontinuous mode of operation. The transfer function of the converters for both ideal and non-ideal converters are obtained.The circuit parameters of the converters are observed from the simulation. Responses of the converters are observed with the change in the internal resistance of the inductor. In addition, simulation is performed and the plots thus obtained shows stabilityof the DC-DC converters. Rise time, peak time, setting time and maximum overshoot of these solid state converters are identified from the simulation.

Biography:

Sanjeev Kumar has completed his PhD at the age of 35 years from National Institute of Technology Kurukshetra and Masters from the same institute. He is the Associate Professor in Department of Mechanical Engineering at YMCA University of Science & Technology, India. He has published more than 40 papers in reputed journals and conferences. He has been serving as an Editorial Board Member of reputed journals.

Abstract:

RCM provides simple, precise and easily understood criteria for deciding technical feasibility of PM/PdM task in the particular context. This means that PM/PdM tasks are only specified for failures which really need them. This in turn leads to substantial reduction in routine workloads. Less routine work also means that the remaining tasks are done properly. This together with the elimination of counter productive tasks leads to more effective maintenance. RCM creates awareness in Maintenance professionals regarding six patterns of failures. A maintenance professional as such comes to terms with the reality of randomness after decades in bathtub. Maintenance professionals thus realise that the idea of age related failures simply does not apply to random failures (Pattern D, E and F). An awareness of these facts has led some organisations to abandon the idea of PM altogether for failures with minor consequences.

Biography:

Zerrouki Hamza graduated in 2013 from the University of Batna with a Master's degree in Industrial Risk Management. Currently, he is completing his PhD at the University of Batna in the Department of Industrial Safety. He is interested in modeling an industrial process using Bayesian networks

Abstract:

Fault tree method has become popular technique that is used widely in safety analysis of process systems. This method aimed to identifying and assessing hazards of complex systems. Fault tree is quantitative analysis that follows the assumptions of logical gates. However, fault tree analysis is not flexible enough to incorporate new knowledge or evidence. Fault tree is difficult to handle with updating probability of basic events, it is also hard to represent the dependency between primary events and multi-states variables. This paper focused on using Bayesian networks to handle with the limitations of fault tree and the uncertainty of the accident and used the ability of Bayesian networks to represent the dependence failure and multi-states variables. A case study of hydrotreater is used to illustrate the application and compare the results of both fault tree and Bayesian networks techniques.

Biography:

Wael Moussa has graduated from the Military Technical College in Cairo in 1996. He works as a System Testing and Maintaining Engineer for the Egyptian Navy. He received Master’s degree from Alexandria University, Egypt in 2004. His Master’s thesis focused on computational fluid dynamics applications for studying and controlling the external flow asymmetry around slender bodies. He obtained PhD degree from Ottawa University, the Canadian Capital University in October 2014. His PhD thesis was titled, “Bearing condition monitoring using both vibration and temperature monitoring methods”.

Abstract:

Passive thermography is a non-contact monitoring approach with a great potential to be used for early bearing fault detection. However, to date, it has only been used to complement vibration-based approaches. However, the vibration-based methods are effective only in detecting physical damages such as bearing cracks and spalls. They cannot be easily used to monitor other unwanted conditions including the lack of lubrication. As such, this paper proposes a method based on temperature rise differences for the detection of both physical bearing damages and lubrication problems based on the mechanisms of the heat sources generated during a bearing operation as well as the mutual effects between these sources and bearing faults. The performance of the proposed method has been examined experimentally. The results have shown that the proposed method has a promising potential to be used for the detection of both physical bearing damages and lubrication related problems.

Biography:

Manoj Parjane is pursuing his PhD from Swami Ramanand Teerth Marathwada University, Nanded. He has completed his PG From SRTMU, Nanded. He is presently working as an Associate Professor in the Mechanical Engineering Department of Pravara Rural Engineering College, Loni which is affiliated to Savitribai Phule Pune University. He has 14 Years of teaching experience. He has published three Papers in international conferences and two in national.

Abstract:

The objective of this article is to understand the concept of Lean Manufacturing, lean implementation benefits and barrier towards lean implementation. Lean Manufacturing by now is a widely discussed and applied manufacturing philosophy in a variety of industries across the globe. The fundamental concept of Lean Manufacturing is to provide a quality product while also ensuring that the product does not cost too much to the customer. Most organizations today are going through a stage where there is a necessity to respond the rapidly changing customer needs. To sustain their place in the market, many organizations have started following the Lean Manufacturing concept. Many factors contribute to lean success not only it is mandatory to implement most of the lean tools but an organization’s culture needs transforming too. Companies following Lean Manufacturing have better flexibility and a good market share. Moreover, Lean Manufacturing produces an operational and cultural environment that is highly conducive to waste minimization.

Biography:

Emir Ali Goze received his BSc and MSc degree with honors in Industrial Enegineering from Yildiz Technical University, Turkey in 2006 and 2008 respectively. He also holds an MSc in International Production Management from Hamburg University of Technology, Germany. He has been working in the field of Revenue Management and He is a PhD candidate in Industrial Engineering with a focus on airline revenue management

Abstract:

Load factor (LF) is a measure of capaticy utilization and has been considered as one of the most commonly used and important performance indicators for passenger airlines. It represents the proportion of the utilized capacity of a flight or the whole airline in general. LF is calculated by dividing the number of paying passengers by the total number of seats for a single flight. Airlines have flights with different distances and having a 90% LF on a long haul flight and %90 on a short haul flight doesn’t have the same impact for the airline. Therefore the capacity utilization of an airline is better represented by an average LF calculation that takes individual flight distances into consideration. Hence, average LF is calculated by dividing Revenue Passenger Kilometers (RPK) by Available Seat Kilometers (ASK). Airlines use LF estimates as a means of planning their actions. For example, if a route’s expected LF is significantly lower for a period of time compared to last year`s same period, then pricing team may consider publishing promotional fares, whereas sales teams may deciede to incrase agency incentives and marketing may decide to make advertisement campaings in order to stimulate demand. Therefore having accurate LF forecasts is of extreme importance for airlines. In this study, an artificial neural network (ANN) approach is presented to forecast LFs and its performace is compared to airline`s current forecasting methodology. It is shown that the proposed ANN approach produce significantly better forecasts compared to the current methodology.

Biography:

A Benbrik is currently Lecturer at the Department of Transport and Hydrocarbon Equipments, Faculty of Hydrocarbons and Chemistry at M’Hamed Bougara University in Boumerdes (Algeria). He earned a Bachelor’s degree in Mechanical Engineering (Major: Drilling Machinery) from the Institute of Hydrocarbons and Chemistry of Boumerdes (Algeria, 1982) and a PhD degree in Technical Sciences from the Gubkin Institute of Petrol and Gas, Moscow, Russia (1987). His research activities mainly concern the modeling and optimization of thermal systems.

Abstract:

In the early years of the oil and gas industry, fire in storage tanks was the common root of most of the incidents. One technique to protect the integrity of neighboring tanks is the water spray curtain, which can provide thermal shielding against fire. This study presents a numerical simulation of radiative heat transfer by the Mont Carlo method through a semitransparent medium (water spray curtain) containing water droplets and gas for the design of an effective thermal shielding system to protect LNG (or combustibles) storage tank from fire. This model will allow us to calculate exactly the attenuation factor of the water curtain as a function of its thickness, density and the size of water droplets. The medium is considered as a non-grey, absorbing and anisotropically scattering. The spectral behavior of the medium is taken into account by the Mie theory and the SNB model is applied respectively to water droplets and gas (H2O, CO and CO2). The calculated results are satisfactorily in agreement with the experimental data.

Biography:

Ibrahim Yusuf is a lecturer at Bayero University, Kano, Nigeria. He have Master's degree, Medical Microbiology and Bacteriology from same university. His skills include Research, Science, Lecturing, Molecular Biology, Microscopy. He has teaching experience of about 6 yrs. In medical laboratory science.

Abstract:

The paper deals with modeling and profit evaluation of a series-parallel system with independent failures using Markov Birth-Death process and probabilistic approach. The system consists of four subsystems with three possible states, working, reduced capacity and failed. Through the transition diagram, systems of differential equations are developed and solved recursively via probabilistic approach. Explicit expressions for busy period of repair men, steady-state availability and profit function are derived. Profit matrices for each subsystem have been developed to provide various performance values for different combinations of failure and repair rates of all subsystems. The results of this paper will enhance the system performance and useful for timely execution of proper maintenance improvement, decision, planning and optimization.

Biography:

M S Khan has completed his PhD from National Institute of Technology, Rourkela, India in 2008. His area of interest includes industrial engineering, operations management, quality engineering and non-conventional manufacturing. Presently, he is serving as Associate Professor in the School of Mechanical Engineering, KIIT University, India. He published more than 20 journal papers and presented in many conferences.

Abstract:

Forecasting of oil prices has always been a matter of great importance due to its influence in driving a country’s economy. As a matter of fact, the petroleum industry is considered to be the biggest contributor in the industrial sector in terms of providing raw materials to the other industries and generating revenues. Due to the non-linear and unpredictable nature of the oil prices, a lot of forecasting techniques have been developed and used to check whether they are capable of forecasting the oil prices satisfactorily. In this paper, two widely used techniques, ARIMA analysis and GMDH neural network has been used to forecast the prices of four petroleum products such as petrol, diesel, LPG and kerosene in India for a three month period (February 2015 to April 2015). The results obtained are compared with the actual prices for the above time period. It is observed that the overall accuracy considering all the four petroleum products shows promising results thus justifying them capable of forecasting the prices of the different petroleum products in India. When both the techniques are compared, ARIMA modelling shows better results (97.99% accuracy) as compared to that of the GMDH neural network method which is 96.97%.

Biography:

Zaki Ahmad is a Professor Emeritus of King Fahad University of Petroleum and Minerals, Dhahran, Saudi Arabia. He obtained his PhD from Leeds University, UK in Metallurgy. He is an Adjunct Professor of Chemical Engineering Department of Comsats Institute of Information and Technology, Lahore, Pakistan. He is a Chartered Metallurgical Engineer (CEngg) of the Engineering Council of UK and a Fellow of Institute of Materials, Minerals and Mining (FIMMM). He is a member of European Federation of Corrosion and a Fellow of Institute of Metal Finishing, Nanotechnology, Professional TMS member USA and member of International Society of Professional Innovation Management. He founded Centre of Excellence Labs at the Institute of Water and Energy at AMUT, Tehran, Iran. He initiated and developed nanotechnology in Saudi Arabia in 2002 and contributed to the development of Centre of Excellence in Nanotechnology. He was a member of a committee to establish a nanotechnology program in KFUPM. He is the Author and Editor of five books published by Elsevier and In-Tech Europe rated highly in the international institutions. He was the Guest Editor to several special issues of Arabian Journal of Science and Engineering. He has written over 120 research papers in international journals, several invited book chapters and over forty papers in international research conferences. He has been an invited speaker at several international forums. He is on the Scientific Editorial Board of INTECH International. He has offered over thirty five short courses and workshops to industry in Saudi Arabia and Middle East

Abstract:

Scandium is a novel alloying element because of its weight strengthening effect, recrystallization, inhabitation, and its ability to improve weld strength and eliminating hot weld cracking. Al 2.5 Mg alloys containing zero to 0.9 wt.% scandium were fabricated by induction melting and chill cast to investigate the influence of scandium on the mechanical strength, microstructure and corrosion behavior. The studies were mainly confined to corrosion which still remains an unexplored area. Experimental alloys containing 0.3-0.6 wt.% scandium with 0.15% wt. Zr showed higher strengths of 290 and 268 MPa respectively, higher than the strength of Al 6061 and Al 2024. The strengthening in scandium added alloys is caused by the pinning of grain boundaries by the formation of nano Al3 (Sc1-x Zr3) precipitates and their uniform distribution. Investigations on the effect of scandium on aluminum magnesium alloys in HCL and NaOH have not been investigated. The Al-Mg alloy containing 0.6 Sc showed the corrosion rate of 10.5 mpy which doubles on decreasing the Sc contained 2.3 Sc (10.22 mpy) due to the formation of Al2O3 and Sc2O3 duplex film. The alloys containing 0.3 Sc showed lower corrosion rate than the alloys containing 0.6 Sc in 0.1 M NaOH. The corrosion rate decreases with age hardening time due to precipitate size, spacing between the precipitate size, spacing between the precipitate and grain and sub-grains sizes. In general, increased aging time increases resistance to corrosion as shown by alloy containing 0.9% scandium with 0.15 Zr. Similar behavior is shown by other alloys containing scandium. It appears that a certain optimum size of precipitates and their distribution affects the rate of corrosion. Studies on open circuit potential vs. time shows that scandium added alloys shows a shift in the potential to more noble values due to formation of a less defective layer of Sc2O3 On top of boehmite ɣ-AlOOH and bayerite Al(OH)3. This shift has a strong influence on the enhancing corrosion resistance. Studies in salt spray chamber show a higher resistance of these alloys. The maximum resistance shown by alloy containing 0.6 wt% Sc with 0.15 Zr may be due to redistribution of β/ and β/-Mg2Al3 phase which generates lattice defects. Precipitates of Al3(Sc1-xZr3) appear to redistribute their phase and enhance corrosion resistance. Elevated temperature studies at 125o C and at rotational velocities of 300 rpm and 700 rpm showed enhanced corrosion as shown by a shift of potential in the negative direction.

Biography:

Abstract:

There is an increased blurring of manufacturing and service activities that impacts on the industrial performance, their business and differentiates their offering. Naturally, services are described as comprising two elements, i.e. process and outcome, where both impact on consumer’s assessment of quality with the involvement of customers in the service delivery process and the well-recognized need to define service quality from the perspective of the consumer. While the manufacturing has been developed by the full cycle of activities from research and development, through design, production, logistics and services, to end of life management, within an economic and social context. In this paper, the authors have identified the gaps between manufacturing and service sectors on the basis of literature. Filling of these gaps will help the better involvement of the industries with each other which offer a rapid growth towards overall market.

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:

A major cause of high manufacturing cost of a product today, is the cost of its rework due to design flaws. Rework cost can rise exponentially during the production phase of a product as compared to catching defects during its design phase. Statistical Process Control techniques that constitute the heart of sound Industrial Engineering practice, assist with the optimum design of a product. In particular, Process Control Charts, Univariate and Multivariate Process Monitoring and Control methods, Full and Fractional Factorial Designs of Experiments avoid rework costs. Beyond these Quality Engineering techniques, optimum product designs can also be secured via other viable Industrial Engineering techniques that include Linear programming, Dynamic Programming, Simulation and Modeling, and Analytic Hierarchy Process, etc. Furthermore, these IE techniques allow an industrial engineer to perform systematic sensitivity analysis by tweaking key system parameters. This type of sensitivity analysis further facilitates the industrial engineer in selecting the most practical design solution from a feasible set. Ultimately, this IE approach of optimum product design reduces the overall product cost.

Biography:

Volkan Cakir obtained his BSc in Electronics Engineering from Turkish Air Force Academy, Istanbul in 1992. He obtained his MSc in Industrial Engineering from Middle East Technical University, Ankara in 2001. He received his PhD in Engineering Management at the Old Dominion University, Norfolk, Virgina in 2011. His research interest areas are simulation, statistical quality control, system dynamics and risk analysis. He is currently an Assistant Professor and Head of the Industrial Engineering Department at Istanbul Arel University.

Abstract:

The label printing and packaging industry has a rapidly growing and evolving market in the world. The most important aim of the companies is to accomplish the demand and expectations of the customers in the market. Label printing houses have to improve their production process to produce fast and good quality products. Aim of this study is identifying bottlenecks, balancing production lines and improving system efficiency by using simulation. Firstly problems are defined in production system then processes are defined and conceptualized in an activity flow diagram. Demand arrival times, demand quantities, lead times, failures, demand product types and production times are observed and analyzed. Product types are divided into groups according to their production technics and also number of colors as they contain. Each process time of product type groups are examined and analyzed separately. Graphical and statistical analysis is done for each data groups by using standard statistical tools. Discrete event simulation model is created at Arena software and based on conceptual model after validation and verification test results, solutions for production problems and improvement of production process are suggested to the company.

Biography:

Abdeelghani had done his Ph.D. in 1978 from north Carolina state university his area of research are Mathematical modeling and optimization in industrial and service facilities, Project scheduling with material, equipment and human resources planning Supply chain and logistics in production and distribution Productivity and quality improvement. His selected papers for publication are: Integration of Equipment Planning and Project Scheduling” European Journal of Operational Research (EJOR), 2008 A WATER RESOURCE PLANNING MODEL FOR AQABA, March 5. United States Agency for International Development, 2007 Project Management: Challenges & Opportunities Published in the proceedings for Egyptian Engineering Management Society, November 20, 2005. Activity Compression, presented in the International INFORMS conference in Puerto Rico, July 8-11, 2007. He is currently working as a professor at The American university in Cairo.

Abstract:

Environmental concerns as well as the continued decline in raw material reserves have intensified the need for Reverse Supply Chains (RSC). In addition RSC could lead to higher profitability by reducing shipping, storage and disposal costs. A RSC Supply chain for product recycling consists of a sequence of activities to collect used products and reprocess them through sorting, disassembly, recovering the valuable recycled material and or disposal. Typically, the top tier of the supply chain would include spent products that are considered for the reverse operations. These products are usually classified depending on their status whether refurbished and reused or disassembled into parts or directly to basic material. The bottom tier would include all parts or basic material recovered as well as all items to be disposed of. The intermediate tiers would include sorter, disassemblers or material recovery plants. The activities in these RSC tiers are modeled into a project network. The relationships among these project activities are then formulated into a Mixed Integer Programming (MIP) model. The model takes into account the shipping, processing and inventory holding costs for all the activities into the network. In addition, the formulation would allow for representing the value of the reclaimed or recycled parts and material. Other criteria including minimizing waste or maximizing a selected type of basic material is also explored. Computational results are presented along with an application of the developed MIP to several real world problems.

Biography:

Dr. Poonam Savsani is working as an assistant professor at Pandit Deendayal Petroleum University, Gujarat, India, in industrial engineering department. She has completed her PhD in robot trajectory optimization using advanced metahuristics. Her research interest includes exploration of different optimization methods for the industrial problems, such as aggregate production planning problem, vehicle routing problem, cutting stock problem, network analysis, robot trajectory planning.

Abstract:

Aggregate production planning (APP) deals with the simultaneous determination of plant’s production, inventory and vocation levels over a finite time horizon. The aim of aggregate planning is to finalize overall output levels in the near to medium future in uncertain demands. This paper presents a Genetic Algorithm approach for solving aggregate production planning with different selection methods and various crossover phenomenons. Combination of four selection methods and five crossover phenomenon are taken and compared to choose the best combination for solving APP in this present work. The problem statement depicts multi-product, multi-period APP with forecasted demand. The proposed approach attempts to minimize the total cost which includes labour cost, backordering cost, subcontracting cost, inventory cost, warehouse cost, overtime cost and machine cost. Results show the outstanding performance of uniform selection procedure and two point crossover combination.