International Journal of Industrial and Systems Engineering http://www.inderscience.com/browse/index.php?journalID=188&year=2012&vol=10&issue=2 Inderscience Publishers Ltd en-uk International Journal of Industrial and Systems Engineering 1748-5037 1748-5045 © 2012 Inderscience Publishers Ltd editor@inderscience.com https://www.inderscience.com/images/files/coverImgs/ijise_scoverijise.jpg http://www.inderscience.com/browse/index.php?journalID=188&year=2012&vol=10&issue=2 http://www.inderscience.com/link.php?id=45177 The analysis of the multivariate dynamic information contained in the observed data of automobile build has been one of the significant and interesting topics. In this paper, we present a new approach to dynamic statistical analysis of multidimensional quality characteristics in automobile body assembly. An analytic procedure combining the principal component analysis with the time-series method is given to investigate the multivariate dynamic problems in automotive industry. An application study using real data in automobile body build is illustrated in detail. An approach to dynamic analysis of multidimensional quality characteristics in automobile body-in-white assembly
Yinzhong Jiang; Kai Yang
International Journal of Industrial and Systems Engineering, Vol. 10, No. 2 (2012) pp. 135 - 152
The analysis of the multivariate dynamic information contained in the observed data of automobile build has been one of the significant and interesting topics. In this paper, we present a new approach to dynamic statistical analysis of multidimensional quality characteristics in automobile body assembly. An analytic procedure combining the principal component analysis with the time-series method is given to investigate the multivariate dynamic problems in automotive industry. An application study using real data in automobile body build is illustrated in detail.

]]> 10.1504/IJISE.2012.045177 International Journal of Industrial and Systems Engineering, Vol. 10, No. 2 (2012) pp. 135 - 152 Yinzhong Jiang; Kai Yang Beijing Automotive Technology Center, Peng Long Building 1012, No. 10 Hua Wei Li, Chao Yang District, Beijing 100021, China ' Department of Industrial and Manufacturing Engineering, Wayne State University, Detroit, MI 48202, USA multidimensional quality control PCA principal component analysis time series automobile industry car body assembly automotive body-in-white. 2012-01-31T23:20:50-05:00 10 2 135 152 2012-01-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=45178 Fully adjustable, ergonomically designed assembly workstations could be expensive for companies to adopt. Therefore, an alternative low-cost, ergonomically designed adjustable assembly workstation was designed, developed and evaluated in a manufacturing company. Experiments were conducted on the existing and on the low-cost, ergonomically designed assembly workstation using ten industrial assembly operators. Operator performance on the low-cost, ergonomically designed workstation was 27% higher compared to the existing non-ergonomically designed assembly workstation. The increased performance was due to flexibility and ergonomic design features incorporated in the workstation. The cost of the workstation was three times less compared to the cost of a fully adjustable, ergonomically designed assembly workstation (smart assembly workstation) designed earlier. Evaluation of a low-cost ergonomically designed adjustable assembly workstation
Ashraf A. Shikdar; Mohamed A. Al-Hadhrami
International Journal of Industrial and Systems Engineering, Vol. 10, No. 2 (2012) pp. 153 - 166
Fully adjustable, ergonomically designed assembly workstations could be expensive for companies to adopt. Therefore, an alternative low-cost, ergonomically designed adjustable assembly workstation was designed, developed and evaluated in a manufacturing company. Experiments were conducted on the existing and on the low-cost, ergonomically designed assembly workstation using ten industrial assembly operators. Operator performance on the low-cost, ergonomically designed workstation was 27% higher compared to the existing non-ergonomically designed assembly workstation. The increased performance was due to flexibility and ergonomic design features incorporated in the workstation. The cost of the workstation was three times less compared to the cost of a fully adjustable, ergonomically designed assembly workstation (smart assembly workstation) designed earlier.

]]> 10.1504/IJISE.2012.045178 International Journal of Industrial and Systems Engineering, Vol. 10, No. 2 (2012) pp. 153 - 166 Ashraf A. Shikdar; Mohamed A. Al-Hadhrami Department of Mechanical and Industrial Engineering, Sultan Qaboos University, P.O. Box 33, Al-Khod 123, Muscat, Sultanate of Oman ' Department of Mechanical and Industrial Engineering, Sultan Qaboos University, P.O. Box 33, Al-Khod 123, Muscat, Sultanate of Oman adjustable workstations ergonomic design assembly tasks worker performance low-cost workstations assembly workstations ergonomics manufacturing industry flexibility workstation design. 2012-01-31T23:20:50-05:00 10 2 153 166 2012-01-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=45179 The changing economic conditions have challenged many organisations to search for more efficient and effective ways to manage their supply chain. During recent years supplier selection decisions have received considerable attention in the supply chain management literature. There are four major decisions that are related to the supplier selection process: what product or services to order, from which suppliers, in what quantities and in which time periods? Data envelopment analysis (DEA) has been successfully used to select the most efficient supplier(s) in a supply chain. In this study, we introduce a novel supplier selection model using chance-constrained DEA with non-discretionary factors and stochastic data. We propose a deterministic equivalent of the stochastic non-discretionary model and convert this deterministic problem into a quadratic programming problem. This quadratic programming problem is then solved using algorithms available for this class of problems. We perform sensitivity analysis on the proposed non-discretionary model and present a case study to demonstrate the applicability of the proposed approach and to exhibit the efficacy of the procedures and algorithms. Supplier selection using chance-constrained data envelopment analysis with non-discretionary factors and stochastic data
Majid Azadi; Reza Farzipoor Saen; Madjid Tavana
International Journal of Industrial and Systems Engineering, Vol. 10, No. 2 (2012) pp. 167 - 196
The changing economic conditions have challenged many organisations to search for more efficient and effective ways to manage their supply chain. During recent years supplier selection decisions have received considerable attention in the supply chain management literature. There are four major decisions that are related to the supplier selection process: what product or services to order, from which suppliers, in what quantities and in which time periods? Data envelopment analysis (DEA) has been successfully used to select the most efficient supplier(s) in a supply chain. In this study, we introduce a novel supplier selection model using chance-constrained DEA with non-discretionary factors and stochastic data. We propose a deterministic equivalent of the stochastic non-discretionary model and convert this deterministic problem into a quadratic programming problem. This quadratic programming problem is then solved using algorithms available for this class of problems. We perform sensitivity analysis on the proposed non-discretionary model and present a case study to demonstrate the applicability of the proposed approach and to exhibit the efficacy of the procedures and algorithms.

]]> 10.1504/IJISE.2012.045179 International Journal of Industrial and Systems Engineering, Vol. 10, No. 2 (2012) pp. 167 - 196 Majid Azadi; Reza Farzipoor Saen; Madjid Tavana Faculty of Economic and Management, Islamic Azad University – Sciences and Researches Branch, Tehran, Iran ' Department of International Business and Asian Studies, Griffith University – Gold Coast Campus, Gold Coast, Queensland 4222, Australia ' La Salle University, Philadelphia, PA 19141, USA supplier selection SCM supply chain management chance-constrained DEA data envelopment analysis chance-constrained programming non-discretionary factors stochastic data quadratic programming. 2012-01-31T23:20:50-05:00 10 2 167 196 2012-01-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=45180 This paper is motivated by a firm that manufactures two main types of products. In an effort to increase their throughput, the company created a production scheme using takt times. To achieve a smooth flow of production, they desired low work-in-process inventory in order to make all components move simultaneously. However, the process includes parallel assembly lines that converge to or diverge from common resources. A simple takt time calculation cannot provide enough information to achieve the desired throughput. The authors identify solutions that improve throughput. One solution, based on takt times or each station's processing times (PTs) for a zero waste schedule, can be used in many other scheduling problems. With the aid of Little's Law and simulation, the authors also show how the system flow can be influenced via managerial settings. Across all production configurations, a 10-15% increase in throughput over the original design can be achieved. Production capabilities using takt times, requirements analysis and simulation
Jun Duanmu; Kevin Taaffe
International Journal of Industrial and Systems Engineering, Vol. 10, No. 2 (2012) pp. 197 - 216
This paper is motivated by a firm that manufactures two main types of products. In an effort to increase their throughput, the company created a production scheme using takt times. To achieve a smooth flow of production, they desired low work-in-process inventory in order to make all components move simultaneously. However, the process includes parallel assembly lines that converge to or diverge from common resources. A simple takt time calculation cannot provide enough information to achieve the desired throughput. The authors identify solutions that improve throughput. One solution, based on takt times or each station's processing times (PTs) for a zero waste schedule, can be used in many other scheduling problems. With the aid of Little's Law and simulation, the authors also show how the system flow can be influenced via managerial settings. Across all production configurations, a 10-15% increase in throughput over the original design can be achieved.

]]> 10.1504/IJISE.2012.045180 International Journal of Industrial and Systems Engineering, Vol. 10, No. 2 (2012) pp. 197 - 216 Jun Duanmu; Kevin Taaffe Old Dominion University, Virginia Modeling Analysis and Simulation Center, 1030 University BLVD, Suffolk, VA 23435, USA ' Clemson University, Department of Industrial Engineering, 130-A Freeman Hall, Clemson, SC 29634, USA takt time Little's Law throughput one piece flow simulation lean production production capabilities requirements analysis scheduling. 2012-01-31T23:20:50-05:00 10 2 197 216 2012-01-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=45181 The selection and valuation of information technology (IT) investments are challenging as they usually have long durations and require significant amount of capital expenditure. Given the high uncertainty inherent in these investments, traditional tools are proven insufficient to identify the true values. On the other hand, real options analysis (ROA) is a powerful valuation tool that put emphasis on the 'real options' of projects. However, most IT managers do not have the necessary skills to carry ROA. In this paper, we give introduction of ROA and propose an easy-to-use framework for using ROA to value investment opportunities. In addition, we discuss common types of real options and describe a case study of deferral option in a real-world investment opportunity. This paper should serve as a good starting point for managers who want to put ROA into practice. A framework for applying real options analysis to information technology investments
Chris Wang-Ngai Chan; Chun-Hung Cheng; Angappa Gunasekaran; Kam-Fai Wong
International Journal of Industrial and Systems Engineering, Vol. 10, No. 2 (2012) pp. 217 - 237
The selection and valuation of information technology (IT) investments are challenging as they usually have long durations and require significant amount of capital expenditure. Given the high uncertainty inherent in these investments, traditional tools are proven insufficient to identify the true values. On the other hand, real options analysis (ROA) is a powerful valuation tool that put emphasis on the 'real options' of projects. However, most IT managers do not have the necessary skills to carry ROA. In this paper, we give introduction of ROA and propose an easy-to-use framework for using ROA to value investment opportunities. In addition, we discuss common types of real options and describe a case study of deferral option in a real-world investment opportunity. This paper should serve as a good starting point for managers who want to put ROA into practice.

]]> 10.1504/IJISE.2012.045181 International Journal of Industrial and Systems Engineering, Vol. 10, No. 2 (2012) pp. 217 - 237 Chris Wang-Ngai Chan; Chun-Hung Cheng; Angappa Gunasekaran; Kam-Fai Wong Department of Systems Engineering Engineering Management, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong ' Department of Systems Engineering Engineering Management, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong ' Department of Decision and Information Sciences, University of Massachusetts Dartmouth, North Dartmouth, MA 02747, USA ' Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong real options information technology project management project valuation IT investment. 2012-01-31T23:20:50-05:00 10 2 217 237 2012-01-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=45182 A state-of-the-art review, spanning the last two decades, on application of metaheuristic methods in facility layout problems (FLPs) to gauge the current and emerging trends involving new design objectives, algorithms and methodologies to the combinatorial optimisation aspects is presented in this work. Fresh developments in emerging layout research, as analysed in this study, provide a perspective on what the future of the field will be like. A tendency of using metaheuristics, such as genetic algorithm (GA), simulated annealing (SA), ant colony optimisation (ACO) and particle swarm optimisation (PSO) with a trend towards multi-objective approaches to layout and material handling system design is observed. Metaheuristic in facility layout problems: current trend and future direction
Anirban Kundu; Pranab K. Dan
International Journal of Industrial and Systems Engineering, Vol. 10, No. 2 (2012) pp. 238 - 253
A state-of-the-art review, spanning the last two decades, on application of metaheuristic methods in facility layout problems (FLPs) to gauge the current and emerging trends involving new design objectives, algorithms and methodologies to the combinatorial optimisation aspects is presented in this work. Fresh developments in emerging layout research, as analysed in this study, provide a perspective on what the future of the field will be like. A tendency of using metaheuristics, such as genetic algorithm (GA), simulated annealing (SA), ant colony optimisation (ACO) and particle swarm optimisation (PSO) with a trend towards multi-objective approaches to layout and material handling system design is observed.

]]> 10.1504/IJISE.2012.045182 International Journal of Industrial and Systems Engineering, Vol. 10, No. 2 (2012) pp. 238 - 253 Anirban Kundu; Pranab K. Dan Department of Mechanical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110 016, India ' Industrial Engineering and Management, West Bengal University of Technology, BF-142, Salt Lake City, Sector-I, Kolkata 700064, India facility layout layout design metaheuristics methodology grouping soft computing genetic algorithms simulated annealing tabu search ant colony optimisation ACO particle swarm optimisation PSO. 2012-01-31T23:20:50-05:00 10 2 238 253 2012-01-31T23:20:50-05:00