International Journal of Productivity and Quality Management http://www.inderscience.com/browse/index.php?journalID=177&year=2012&vol=9&issue=2 Inderscience Publishers Ltd en-uk International Journal of Productivity and Quality Management 1746-6474 1746-6482 © 2012 Inderscience Publishers Ltd editor@inderscience.com https://www.inderscience.com/images/files/coverImgs/ijpqm_scoverijpqm.jpg http://www.inderscience.com/browse/index.php?journalID=177&year=2012&vol=9&issue=2 http://www.inderscience.com/link.php?id=45189 Engineering quality software depends much on the control of the defects which in turn involves inhibiting the natural injection of defects and preventing the propagation of defects from its origination. Inspection is an effective process to realise the aforementioned objectives. Hence, inspection has been a focal point of studies and several innovative approaches have been brought out to enhance the quality of software through better inspection. The introduction of two quality metrics namely depth of inspection (DI), which is a process metric, and inspection performance metric (IPM), which is a people metric, enable the quality professional to have quantitative estimation of inspection process and people process. This paper aims to present the modes of practical implementation of the two metrics in software houses to facilitate the production of quality software product. Implementation of the pair metrics reflects continual process improvement and endurance of the company in the competitive environment. Quality enhancement by implementation of depth of inspection metric and inspection performance metric in software industry
T.R. Gopalakrishnan Nair; V. Suma
International Journal of Productivity and Quality Management, Vol. 9, No. 2 (2012) pp. 137 - 157
Engineering quality software depends much on the control of the defects which in turn involves inhibiting the natural injection of defects and preventing the propagation of defects from its origination. Inspection is an effective process to realise the aforementioned objectives. Hence, inspection has been a focal point of studies and several innovative approaches have been brought out to enhance the quality of software through better inspection. The introduction of two quality metrics namely depth of inspection (DI), which is a process metric, and inspection performance metric (IPM), which is a people metric, enable the quality professional to have quantitative estimation of inspection process and people process. This paper aims to present the modes of practical implementation of the two metrics in software houses to facilitate the production of quality software product. Implementation of the pair metrics reflects continual process improvement and endurance of the company in the competitive environment.

]]> 10.1504/IJPQM.2012.045189 International Journal of Productivity and Quality Management, Vol. 9, No. 2 (2012) pp. 137 - 157 T.R. Gopalakrishnan Nair; V. Suma Research and Industry Incubation Centre (RIIC), (Recognised by Ministry of Science and Technology), Dayananda Sagar Institutions, Kumaraswamy Layout, Bangalore 560078, Karnataka, India ' Advanced Software Engineering Research Group, Research and Industry Incubation Centre (RIIC), (Recognised by Ministry of Science and Technology), Dayananda Sagar Institutions, Kumaraswamy Layout, Bangalore 560078, Karnataka, India software engineering software quality metrics inspection defect management software process continuous improvement process improvement. 2012-01-31T23:20:50-05:00 9 2 137 157 2012-01-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=45190 This study aims to identify suitable productivity indicators derived from a firm's operational and supplier-selection strategies. The correlation and multiple regression techniques are applied for the analysis of surveys' responses. There are many useful results such as when focusing on flexibility as its primary operational strategy and delivery and management as key strategies for supplier selection in maintenance services, mean time to repair should be an important productivity indicator. Finally, the research's limitations are recognised with some recommendations for future studies in the areas of productivity measurement. This study is sponsored by Thailand's Department of Industrial Work to help promote productivity measurement and the cluster concept. Identifying productivity indicators from business strategies' surveys
Kongkiti Phusavat; Sansanee Nilmaneenava; Rapee Kanchana; Christian Wernz; Petri Helo
International Journal of Productivity and Quality Management, Vol. 9, No. 2 (2012) pp. 158 - 176
This study aims to identify suitable productivity indicators derived from a firm's operational and supplier-selection strategies. The correlation and multiple regression techniques are applied for the analysis of surveys' responses. There are many useful results such as when focusing on flexibility as its primary operational strategy and delivery and management as key strategies for supplier selection in maintenance services, mean time to repair should be an important productivity indicator. Finally, the research's limitations are recognised with some recommendations for future studies in the areas of productivity measurement. This study is sponsored by Thailand's Department of Industrial Work to help promote productivity measurement and the cluster concept.

]]> 10.1504/IJPQM.2012.045190 International Journal of Productivity and Quality Management, Vol. 9, No. 2 (2012) pp. 158 - 176 Kongkiti Phusavat; Sansanee Nilmaneenava; Rapee Kanchana; Christian Wernz; Petri Helo Center of Advanced Studies in Industrial Technology, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand ' Center of Advanced Studies in Industrial Technology, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand ' Department of Industrial Engineering, Rajamangala University of Technology Thanyaburi, Pathumthanee 12110, Thailand ' Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA ' Department of Production, University of Vaasa, FIN-65101 Vaasa, Finland productivity measurement manufacturing strategy cluster concept productivity indicators supplier selection flexibility maintenance services mean time to repair Thailand clusters. 2012-01-31T23:20:50-05:00 9 2 158 176 2012-01-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=45191 The outputs from the manufacturing processes are often assumed to be independent but actually the observations are correlated and when this correlation builds-up automatically in the entire process, it is called autocorrelation. The performance of a chart is measured in terms of average run length (ARL). The performance of the traditional exponentially-weighted moving average (EWMA) chart is studied under the effect of the positive correlation. ARL at various levels of correlation (Φ), weightage factor (λ) and at various width of control limits (K), are studied using simulation with MATLAB software. Optimal schemes of EWMA chart are proposed for each level of correlation and showed better performance compared to EWMA chart, suggested by Zhang (2000). Moreover, optimal schemes of EWMA chart at given weighting factor, λ = 0.2, are very much comparable with the EWMA stationary chart, proposed by Winkel and Zhang (2004) at the various levels of the correlation. Effect of autocorrelation on the performance of EWMA chart
Sukhraj Singh; D.R. Prajapati
International Journal of Productivity and Quality Management, Vol. 9, No. 2 (2012) pp. 177 - 193
The outputs from the manufacturing processes are often assumed to be independent but actually the observations are correlated and when this correlation builds-up automatically in the entire process, it is called autocorrelation. The performance of a chart is measured in terms of average run length (ARL). The performance of the traditional exponentially-weighted moving average (EWMA) chart is studied under the effect of the positive correlation. ARL at various levels of correlation (Φ), weightage factor (λ) and at various width of control limits (K), are studied using simulation with MATLAB software. Optimal schemes of EWMA chart are proposed for each level of correlation and showed better performance compared to EWMA chart, suggested by Zhang (2000). Moreover, optimal schemes of EWMA chart at given weighting factor, λ = 0.2, are very much comparable with the EWMA stationary chart, proposed by Winkel and Zhang (2004) at the various levels of the correlation.

]]> 10.1504/IJPQM.2012.045191 International Journal of Productivity and Quality Management, Vol. 9, No. 2 (2012) pp. 177 - 193 Sukhraj Singh; D.R. Prajapati Department of Mechanical Engineering, PEC University of Technology, Chandigarh 160 012, Punjab, India ' Department of Mechanical Engineering, PEC University of Technology, Chandigarh 160 012, Punjab, India EWMA control charts exponentially-weighted moving average ARL average run length coefficient of correlation weightage factor width of control limits MATLAB SPC statistical process control autocorrelation. 2012-01-31T23:20:50-05:00 9 2 177 193 2012-01-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=45192 Environmental issues constitute continuous concern for governments, societies and business organisations. Green quality (GQ) emerged as a new approach that extends environmental responsibility of organisations in maintaining their quality performance. This paper investigates the existence of GQ practices in Malaysia, its antecedents that motivate firms to adopt these practices, and the outcome of adoption. To attain these objectives, this study utilises quantitative approach by distributing survey questionnaires to ISO 14001 certified companies in Malaysia. A total of 108 usable responses were received. This study examines the relationships between GQ practices which is the product lifecycle management with five variables of antecedents (management commitment, employee awareness, worker health and safety, available resources, internal efficiency and customer requirements), and GQ practices with sustainable quality management (SQM). The results of the survey indicate that only customer requirements have positive effect on the adoption of GQ practices. However, the study finds no convincing evidence to support the correlation between GQ practices and SQM. Determinants of the green quality practices towards sustainable quality management
Leow Kheng Yee; Suhaiza Zailani
International Journal of Productivity and Quality Management, Vol. 9, No. 2 (2012) pp. 194 - 216
Environmental issues constitute continuous concern for governments, societies and business organisations. Green quality (GQ) emerged as a new approach that extends environmental responsibility of organisations in maintaining their quality performance. This paper investigates the existence of GQ practices in Malaysia, its antecedents that motivate firms to adopt these practices, and the outcome of adoption. To attain these objectives, this study utilises quantitative approach by distributing survey questionnaires to ISO 14001 certified companies in Malaysia. A total of 108 usable responses were received. This study examines the relationships between GQ practices which is the product lifecycle management with five variables of antecedents (management commitment, employee awareness, worker health and safety, available resources, internal efficiency and customer requirements), and GQ practices with sustainable quality management (SQM). The results of the survey indicate that only customer requirements have positive effect on the adoption of GQ practices. However, the study finds no convincing evidence to support the correlation between GQ practices and SQM.

]]> 10.1504/IJPQM.2012.045192 International Journal of Productivity and Quality Management, Vol. 9, No. 2 (2012) pp. 194 - 216 Leow Kheng Yee; Suhaiza Zailani Graduate School of Business, Universiti Sains Malaysia, Penang 11800, Malaysia ' Graduate School of Business, Universiti Sains Malaysia, Penang 11800, Malaysia green quality practices green quality adoption determinants outcomes SQM sustainable quality management Malaysia sustainability environmental responsibility quality performance ISO 14001 environmental management product lifecycle management PLM management commitment employee awareness health and safety available resources internal efficiency customer requirements. 2012-01-31T23:20:50-05:00 9 2 194 216 2012-01-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=45193 This study proposes a new analysis and practice of Six Sigma methodology to define, measure, analyse, innovate and control (DMAIC). Six Sigma is a well-known concept who means the perfection: a process of production to three sigma makes 3.4 defaults/million unit, whereas Six Sigma means for us the perfection. We used it now to mean the type of specialised training aiming at the attack of very high objectives for processes improvement. The method Six Sigma is a method of continuous improvement and elimination of non-quality, passing by six stages or cycle DMAIC carried out by a team of project. In this paper, we propose a new practice of Six Sigma for reduction and optimisation of non-conformity for aluminium company. Six Sigma methodology applications within aluminium company
Tarek Sadraoui; Chafik Kammoun
International Journal of Productivity and Quality Management, Vol. 9, No. 2 (2012) pp. 217 - 244
This study proposes a new analysis and practice of Six Sigma methodology to define, measure, analyse, innovate and control (DMAIC). Six Sigma is a well-known concept who means the perfection: a process of production to three sigma makes 3.4 defaults/million unit, whereas Six Sigma means for us the perfection. We used it now to mean the type of specialised training aiming at the attack of very high objectives for processes improvement. The method Six Sigma is a method of continuous improvement and elimination of non-quality, passing by six stages or cycle DMAIC carried out by a team of project. In this paper, we propose a new practice of Six Sigma for reduction and optimisation of non-conformity for aluminium company.

]]> 10.1504/IJPQM.2012.045193 International Journal of Productivity and Quality Management, Vol. 9, No. 2 (2012) pp. 217 - 244 Tarek Sadraoui; Chafik Kammoun Dynamic Economic Unit and Environmental Research, Higher Institute of Industrial Management of Sfax, University of Economics and Management Sfax, ISGI Sfax Route Mharza Km 1.5 BP No. 1164, Sfax 3018, Tunisia ' Unit of Applied Economics Research (UREA), Higher Institute of Industrial Management of Sfax, University of Economics and Management Sfax, ISGI Sfax Route Mharza Km 1.5 BP No. 1164, Sfax 3018, Tunisia DMAIC define measure analyse innovate control control charts Pareto diagrams six sigma aluminium firms training processes improvement continuous improvement. 2012-01-31T23:20:50-05:00 9 2 217 244 2012-01-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=45194 Due to an increasing amount of public resources dedicated to healthcare systems, it is important to measure the efficiency of hospitals. Systematically analysing hospital systems is one important way to discover and improve inefficiencies. The purpose of this study is to propose a data envelopment analysis (DEA)-artificial neural network (ANN)-based model to measure and evaluate the efficiency scores of hospitals. DEA is straightforward but requires time, knowledge and more process time than ANN. By combining these two methods, it is possible to lessen the shortcomings of DEA. In the proposed model, DEA classifies each hospital as either efficient or inefficient. Input and output variables of DEA are used for the inputs, and the efficiency scores of the hospitals are defined as the outputs of the ANN system. After the system is trained, the ANN model is applied to the test data to classify each hospital into efficient or inefficient. The results are then compared with each other, and discriminant analysis (DA) is compared with ANN. Results show that a well-trained ANN performs good classification and even gives better solutions than DA. Also, ANN shows the advantage of using less CPU time and computer resources than the DEA, especially in large data sets. Using data envelopment analysis-neural network model to evaluate hospital efficiency
Omur Tosun
International Journal of Productivity and Quality Management, Vol. 9, No. 2 (2012) pp. 245 - 257
Due to an increasing amount of public resources dedicated to healthcare systems, it is important to measure the efficiency of hospitals. Systematically analysing hospital systems is one important way to discover and improve inefficiencies. The purpose of this study is to propose a data envelopment analysis (DEA)-artificial neural network (ANN)-based model to measure and evaluate the efficiency scores of hospitals. DEA is straightforward but requires time, knowledge and more process time than ANN. By combining these two methods, it is possible to lessen the shortcomings of DEA. In the proposed model, DEA classifies each hospital as either efficient or inefficient. Input and output variables of DEA are used for the inputs, and the efficiency scores of the hospitals are defined as the outputs of the ANN system. After the system is trained, the ANN model is applied to the test data to classify each hospital into efficient or inefficient. The results are then compared with each other, and discriminant analysis (DA) is compared with ANN. Results show that a well-trained ANN performs good classification and even gives better solutions than DA. Also, ANN shows the advantage of using less CPU time and computer resources than the DEA, especially in large data sets.

]]> 10.1504/IJPQM.2012.045194 International Journal of Productivity and Quality Management, Vol. 9, No. 2 (2012) pp. 245 - 257 Omur Tosun Faculty of Economics and Administrative Sciences, Department of Business Management, I.I.B.F. Isletme Bolumu, Akdeniz University, Antalya, Turkey hospital efficiency health services ANNs artificial neural networks DEA data envelopment analysis healthcare management modelling. 2012-01-31T23:20:50-05:00 9 2 245 257 2012-01-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=45195 Indian industries need overall operational excellence in today's era of global competitiveness. Especially, the basic manufacturing sectors such as foundries and other metal working/forming industries need breakthrough improvements in quality as well as in productivity. Six Sigma is one of the most effective breakthrough improvement strategies having direct impact on operational excellence of an organisation. It addresses efficiency and effectiveness of the industry thus improving quality and productivity, both simultaneously. From the researches and surveys published so far, it appears that Six Sigma is not being explored by the Indian foundry industries to its full potential. Very few literatures are reported regarding step-by-step implementation of Six Sigma in foundry industries. This paper illustrates a real-life case study of practicing Six Sigma at a small-scale foundry industry. This paper explains phase with application of define-measure-analyse-improve-control methodology and ultimately shows how breakthrough improvement can be brought in quality and productivity in a foundry industry. Quality and productivity improvement through Six Sigma in foundry industry
Darshak A. Desai
International Journal of Productivity and Quality Management, Vol. 9, No. 2 (2012) pp. 258 - 280
Indian industries need overall operational excellence in today's era of global competitiveness. Especially, the basic manufacturing sectors such as foundries and other metal working/forming industries need breakthrough improvements in quality as well as in productivity. Six Sigma is one of the most effective breakthrough improvement strategies having direct impact on operational excellence of an organisation. It addresses efficiency and effectiveness of the industry thus improving quality and productivity, both simultaneously. From the researches and surveys published so far, it appears that Six Sigma is not being explored by the Indian foundry industries to its full potential. Very few literatures are reported regarding step-by-step implementation of Six Sigma in foundry industries. This paper illustrates a real-life case study of practicing Six Sigma at a small-scale foundry industry. This paper explains phase with application of define-measure-analyse-improve-control methodology and ultimately shows how breakthrough improvement can be brought in quality and productivity in a foundry industry.

]]> 10.1504/IJPQM.2012.045195 International Journal of Productivity and Quality Management, Vol. 9, No. 2 (2012) pp. 258 - 280 Darshak A. Desai Department of Mechanical Engineering, G.H. Patel College of Engineering & Technology (GCET), Vallabh Vidyanagar, Anand 388 120, Gujarat, India quality improvement productivity improvement six sigma implementation DMAIC define measure analyse improve control SSI small-scale industries foundry industry India foundries case study breakthrough improvement. 2012-01-31T23:20:50-05:00 9 2 258 280 2012-01-31T23:20:50-05:00