Quality is an important attribute of performance which reflects the excellence of performance of a product or a service. It is generally regarded as a concern of manufactures. All manufacturing processes involve materials, men and machines and they all have inherent variability in addition to an attributable variability, which can be controlled to an irreducible minimum. Reducing the variability is synonymous to improving quality of a product or a service. The most widely used definition of quality states that it is a degree of conformance of a product to design specifications and workmanship standards. This leaves enough scope of improvement in design specifications to satisfy the intended user or customer and by raising workmanship standard.

All enterprises of the world compete on the basis of quality, cost and time and quality is an important characteristic or attribute to compete with. ISO 8402 defines quality as a” summary of characteristics or features of a product or a service determining their ability to satisfy established or anticipated needs or requirements.” Customer satisfaction thus becomes an important parameter of quality improvement program or planning. Long ago, inspectors were assigned the task of controlling the quality and to accept, reject or rework a product. This involved 100 percent inspection. It was in 1930s, Shewhard first developed his statistical approach to control quality and laid down the foundation of charts to control the variability. This was followed by a period of extensive development of

statistical quality control procedures and many other concepts like statistical process control etc. The details of which shall be discussed in a review paper by the Guest Editor and other papers presented in this issue..

With the introduction of the dimension of consumer satisfaction, improving quality has become an engineering as well as a management function. This led to several new definitions of quality and its scope widened considerably. Eventually, the subject of quality engineering and management is about reducing the variability in products and processes, quality costs and to provide maximum satisfaction to the customers through improved performance. This cannot be done without the involvement of every one in an enterprise and to develop organizational structure, resources, procedure, programs and processes for documentation and standardization during production, their stabilization and improvement in the form of corrective and preventive measures and based on standardization directives. In other words, it is about introducing a quality management system in an enterprise.

On the other hand, the concept of total quality management (TQM) is about exploiting the knowledge and skills and ability of all personnel of an enterprise, including suppliers in resolving problems and improving processes with an ultimate goal of providing customer satisfaction and the satisfaction of employees, management and owners of an enterprise. The important element of TQM philosophy is to prevent defects and to place emphasis on quality in design, elimination of losses and reduction of variability. At the same time, it also stresses development of relationship between employees, suppliers and customers. Everyone is required to participate in making the mission of an enterprise successful.

There are several other programs that complement or supplement the quality improvement strategy. The details of which can be found in the Handbook [1].

I am thankful to all those authors who enthusiastically contributed to make this special issue a success. I like to thank Professor V.N.A. Naikan, Reliability Engineering Centre of IIT Kharagpur, who accepted the invitation of organizing this special issue and spare his valuable time. I sincerely hope that this issue will be received well by the readers of the International Journal of Peformability Engineering for whom we have been bringing out special issues on topical and important themes from time to time.

[1] Misra, Krishna B. Handbook of Performability Engineering, Springer, London, 2008.

An Update on IJPE

The International of Journal of Performability Engineering is a refereed interdisciplinary journal which presents all engineering aspects of performance of products, systems or services. This journal was started in July 2005, and has completed eight years of its publication. We like to present here how this journal has progressed during these eight years. Undoubtedly, we have come a long way and will continue making special efforts to ensure that we have participation and representation of all major countries of the world and the journal has a wide coverage of the topics that are within the scope of this journal. It is a matter of great satisfaction that the journal, in general, has been appreciated and has been received very well by the scientific community of the world. This is reflected through the demand /orders received for the copies of the papers published in this journal. We will of course continue to keep the standard of this journal very high and strive to provide high quality papers to our readers. It may be mentioned that we take utmost care to subject the submitted papers to a rigorous refereeing process involving competent reviewers so that the published papers are brief, precise and compact.

We have been bringing out special issues in the important and new emerging areas of research and invite acclaimed researchers and practitioners to serve as Guest Editors in order to provide interaction with leading researchers in the area. A special issue on Best Practices in RAM and Assets Management has been planned for early 2013.

IJPE also provides a unique facility to authors/researchers to present their new ideas to the scientific community through the medium of Short Communication, which otherwise might take quite some time to develop the idea into a full-fledged research paper.

Book reviews of latest books are often published in the journal to apprise our readership of new arrivals in the literature to keep them up-to-date in their respective area.

The details of IJPE issues published during these eight years (July 2005-Nov. 2012) are as follows:

List of 46 Countries which have contributed papers to IJPE: The following countries (in alphabetic order) contributed papers to the IJPE during this period:

Abu Dhabi, Algeria, Australia, Brazil, Canada, China, Czech Republic, Denmark, Egypt, Finland, France, Germany, Greece, Holland, Hong Kong, Hungary, India, Iran, Israel, Italy, Japan, Jordan, Korea (South), Kuwait, Latvia, Malaysia, Morocco, New Zealand, Norway, Oman, Pakistan, Poland, Portugal, Romania, Russia, Singapore, Slovenia, South Africa, Spain, Sweden, Switzerland, Taiwan, Turkey, United Kingdom, United States of America, Venezuela.

Major contributing countries happen to be: Australia, China, Canada, France, Germany, India, Israel, Italy, Japan, Norway, Sweden, South Korea, Taiwan, U.K., U.S.A. (The highest number of papers published have been from U.S.A.).

Areas represented: Our effort has been to emphasize and to ensure a balanced representation of all constituent areas of Performability Engineering (viz., Quality, Reliability, Maintainability, Survivability, Safety, Risk and Sustainability).

We like to thank a large number of anonymous reviewers of papers, who over this period have given us their precious time and advice to keep the standard of this journal very high. We like to thank them here collectively and would like to record our gratitude to them.

International Journal of Performability Engineering has been regularly publishing special issues highlighting important current research topics within the scope of the journal. This special issue on New Trends in Quality Engineering and Management is the fourteenth such special issues of the journal in 8 years. This issue focuses on the latest theoretical as well as applied research worldwide in the broad areas of quality. After an initial screening, 20 papers were short listed for review by the experts in the field. Based on the referee comments and theme of the special issue, finally 11 papers have been selected for publishing in this special issue.

The first paper, Research Trends in Quality Engineering and Management by V.N.A. Naikan, Joydeep Majumdar, and B.K. Vijaykumar outlines the levels of knowledge currently held in the areas of quality engineering and management, and identifies the trend of exploratory improvements which have caught the imagination of academics and industries alike in this area. The paper also explores the frontiers of quality and its state of the art applications in both production and service sectors and identifies future potential research areas.

The second paper, Process Monitoring and Feedforward Control for Proactive Quality Improvement, by Lihui Shi and Kailash C. Kapur focuses on engineering process control (EPC). This article discusses the rationales for feedforward control and proposes a new philosophy on its application for process improvement. The paper also addresses important issues on process monitoring, feedback control, feedforward control and feasibility conditions for application.

The third paper, A Product Quality and Process Feasibility Modeling System, by David Kazmer and Liang Zhu presents methods to derive the feasible universe of process settings satisfying the specification limits. The authors consider three different types of feasibilities viz., global set that establishes the extreme limits of feasibility by allowing all the process variables to vary simultaneously within their allowable range, local set that shows the immediate feasibility for each process setting holding other process variables at their current setting, and controllability that indicates the range that may be obtained for each quality attribute while holding other quality attributes at their current value.

The fourth paper, System Dynamics Approach for Modeling Cost of Quality, by Biswajit Mahanty, V.N.A. Naikan, and Thuleswar Nath presents the dynamics of quality costs in an Indian manufacturing company using a system dynamics model. The paper presents simulation models to study the time dependent quality deterioration process, quality perception, market reaction and the effects of investments on quality activities.

The fifth paper, Quality Surveillance Methodology for Pipe Welding: An Industrial Case Study, by R.M. Chandima Ratnayake and K.T. Vik presents a practical methodology to recognize the most vulnerable welding procedure specifications (WPSs) that contribute to the majority of defective welds. Based on the identified WPSs, it also suggests a methodology to recognize the most critical imperfection groups and the related imperfection sub-groups.

The sixth paper, Fuzzy Control Charts for Correlated Multi-Attribute Quality Characteristics, by Sai Anjani Kumar K. V. N. and Pratap K. J. Mohapatra, considers the subjective estimate of the quality experts’ correlated multiple-attribute quality characteristics to find the aggregate fuzzy values of the samples, using interactive fuzzy addition and presents two fuzzy control charts, one based on possibility measure and the other on the necessity measure. The paper proposes a novel approach that uses the concept of the α-level and β-level set to identify the specific quality characteristic(s) that are responsible for an out-of-control condition of the process.

The seventh paper, Challenges and Barriers to Total Quality Management: An Overview, Connie Rokke and Om Prakash Yadav, provides a historical journey of TQM from its beginnings through its evolutionary transformation into today’s business climate. The paper discusses fundamental principles of TQM and the challenges and barriers that prohibit many companies from achieving successes by sustaining this management technique founded on sound quality principles.

The eighth paper, Relationships among Total Quality Management Practices -An Empirical Study in Turkish Industry, by Cemal Zehir, and Esin Sadikoglu investigates the relationships between TQM practices and multiple performance measures using a cross-sectional survey among the 750 randomly selected ISO 9001:2000 certified companies in Turkey. Using structural equation modeling, the study shows interdependency and interaction between TQM practices and performance.

The ninth paper, Identification of Quality Improvement Strategies using COPQ in Software Industry, by Yeong-SeokSeo, Donghwan Shin, Gookhyun Kim, Jongmoon Baik, and Doo-Hwan Bae, investigates the methods, COnstructiveQUALity Model (COQUALMO) and Defect Amplification Model (DAM) that are commonly used as the quality estimation model, to estimate software COPQ in a software development organization that starts establishing software quality improvement strategies. The paper also derives a relationship for software COPQ from the software defect data that collected from the organization and make an analysis of the additional experimental results by using the data.

The tenth paper, A Fuzzy Model for Early Software Quality Prediction and Module Ranking, by Ajeet Kumar Pandey, and N. K. Goyal, presents a new approach for early software quality prediction and ranking by classifying software modules as fault-prone and not fault-prone. The authors propose ranking of modules using software metrics and fuzzy ordering algorithm on the basis of their degree of fault proneness.

The eleventh paper, Utilizing Quality Tools: A Predictive Maintenance Perspective, by Aamer Hanif and Mujtaba Hassan Agha presents the application of SPC and quality tools to a maintenance process in a local oil refinery and shows that the results have great value especially when the facts and findings are linked with the cost of quality. The study shows that quality tools help to identify factors causing maintenance problems, high cost and downtime.

The last paper, entitled, Optimal Distribution of Software Testing Time considering Multiple Releases, by Qingpei Hu, Rui Peng and Gregory Levitin, is actually a Short Communication, which is a regular feature of this journal and discusses a software development scenario where a software development team develops, tests and releases software, version by version. The paper proposes a modeling framework to study the expected number of remaining faults, the optimal development time and testing time for each version.

Lastly, I like to thank all the authors, who have contributed to this special issue, for their cooperation and patience. I am highly grateful to all the referees who gave their valuable time to review the papers timely.

I am thankful to Professor Krishna B. Misra, Editor-in-Chief of IJPE, for inviting me and in providing all the help in organizing this special issue.

I sincerely believe that the papers in this issue present the glimpses of current research being carried out in the vast area of quality engineering and management and I do hope - this special issue will highlight some salient features of the current research in this area and motivate academicians, researchers and engineers as well for further research leading to the achievement of sustainable quality of products and services.

V. N. A. Naikan, is currently a Professor of Reliability Engineering and Industrial Engineering & Management at the Indian Institute of Technology Kharagpur, India. He had been Head of the Reliability Engineering Centre, IIT Kharagpur, which is a unique centre of its kind in India, founded in 1983 by Krishna B. Misra (Editor-in-Chief of IJPE) to offer formal educational, research and consultany facilities in reliability, quality, safety and allied areas in India. Naikan graduated in mechanical engineering with second rank from the University of Kerala and earned his M.Tech. and Ph.D. degrees from Reliability Engineering Centre of IIT Kharagpur, India. Before joining the Reliability Engineering Centre as faculty, he also worked with Indian Space Research Organization, Chinese University of Hong Kong, Indian Institute of Management, Ahmedabad and Union Carbide India Limited in various capacities. He has published more than 90 research papers in international journals and conferences, and a book on Reliability Engineering and Life Testing and a chapter on SPC in the Handbook on Performability Engineering edited by Krishna B. Misra. He is the regional editor of the International Journal of Performability Engineering, advisory and editorial board member of several other journals. He had been the technical chair of several international conferences. He has guided about 100 students for their B.Tech., M.Tech., and Ph.D. theses. He is a member of professional societies including, IEEE, IEI, SREI, System Society of India, etc. He has been doing consultancy and research projects for organizations like ISRO, Bhabha Atomic Research Centre, Bharat Heavy Electricals Ltd., Defence Forces, and Ministry of Textiles.

This expository cum review paper outlines the levels of knowledge currently held in the areas of quality engineering and management, and identifies the trend of exploratory improvements which have caught the imagination of academics and industries alike in this area. The paper also explores the frontiers of quality and its state of the art applications in both production and service sectors and identifies future potential research areas.

Process adjustment strategy is an important part of the process improvement methods, which is also called engineering process control (EPC), and it is often integrated with statistical process control (SPC) to improve the process control performance. While feedback control is used to compensate for the output deviation, feedforward control is a proactive control strategy based on a direct measurement of the disturbance, and it acts before the disturbance affects the system. Feedforward control is usually combined with feedback control for variation reduction. In this article, rationales for feedforward control are explained, and a new philosophy on its application is given. The feasibility condition for feedforward control application illustrated from a new disturbance decomposition viewpoint, and the validity of some disturbance models which work well for feedforward control is investigated. Some relevant issues on process monitoring, feedback control and feedforward control are discussed and addressed.

A quality modeling system is described to support manufacturing process development and quality control. The system relies on the main effects relating the process variables to the quality attributes. The extensive simplex method is used to derive the feasible universe of process settings satisfying all specification limits. Three different types of feasibility are analytically derived including 1) the global feasible set that establishes the extreme limits of feasibility by allowing all the process variables to vary simultaneously within their allowable range, 2) the local feasibility, which shows the immediate feasibility for each process setting holding other process variables at their current setting, and 3) the controllability that is indicative of the range that may be obtained for each quality attribute while holding other quality attributes at their current value. The described system explicitly considers both modeling uncertainty and uncontrolled variation; the specification limits may be automatically tightened by the magnitude of the confidence intervals and process standard deviations to ensure a desired level of confidence and robustness. An example is provided for an injection molding process with four process variables and three quality attributes.

This paper presents the dynamics of quality costs in an Indian manufacturing company. A system dynamics model is developed for this purpose. The new features of the model are: a) time dependent deterioration process, b) formation of quality perception, and c) market reaction. The effects of investments on quality activities are experimented by simulation runs. A number of policy runs presented in this paper quantifies the extents of such investments in order to achieve the best possible results.

This manuscript suggests a methodology to recognize the most vulnerable welding procedure specifications (WPSs) that contribute to the majority of defective welds annually. Based on the identified WPSs, it also suggests a methodology to recognize the most critical imperfection groups and the related imperfection sub-groups as specified in NS-EN ISO 6520-1.

In many industrial situations, process stability has to be determined with the help of two or more quality characteristics simultaneously. Many researchers in the past used fuzzy set theory to model linguistic data and construct control charts. In many such charts, the assumption of fuzziness is not retained through all the steps. The current paper considers the case when quality experts subjectively estimate correlated multiple-attribute quality characteristics. These estimates are used to find the aggregate fuzzy values of the samples, using interactive fuzzy addition. Two fuzzy control charts are developed, one based on possibility measure and the other on the necessity measure. The paper proposes a novel approach that uses the concept of the a-level and ?-level set to identify the specific quality characteristic(s) that are responsible for an out-of-control condition of the process.

Total Quality Management (TQM) has been touted as the second industrial revolution dating back to the 1940’s where it began its journey to bring Japan into the forefront of competitive quality. This paper provides a historical journey of TQM from its beginnings through its evolutionary transformation into today’s business climate. The fundamental principles of TQM are explored and the resounding benefits identified with detailed measures of success. A review of the challenges and barriers that prohibit most companies from achieving these successes is conducted to better understand why even the most well intentioned companies are not always able to sustain this management technique founded on sound quality principles. Finally, this paper outlines future research direction to develop sound understanding and reasoning related to the identified challenges and barriers and to propose a conceptual implementation model based on them.

This study investigated the relationships between Total Quality Management (TQM) practices and multiple performance measures using a cross-sectional survey methodology. We sent questionnaires to 750 randomly selected ISO 9001:2000 certified companies in different industries in the Marmara region of Turkey in 2005 and 2010, obtaining 486 usable questionnaires for a response rate of 64.8%. After confirming the validity and reliability of the latent variables, we tested the model and the hypotheses using structural equation modeling. The measurement and structural models fit the data satisfactorily. The study shows interdependency and interaction between TQM practices and performance.

Software COPQ is one of the most important performance measures in Six Sigma or any key improvement effort. However, in practice, many software development organizations are having difficulty in estimating their valid software COPQ. Thus, in this paper, we investigate the methods, COnstructive QUALity MOdel (COQUALMO) and Defect Amplification Model (DAM) that are commonly used as the quality estimation model, to estimate software COPQ in a software development organization that starts establishing software quality improvement strategies. In addition, we derive software COPQ from the software defect data that collected from the organization and make an analysis of the additional experimental results by using the data. This study is currently being used for making decisions to set software quality improvement strategies in the organization.

Testing is one of the most expensive but essential software development activity that helps the software professionals to deliver quality software. The quality of software is judged on the basis of number of faults lying dormant inside the software. Software systems are developed by integrating various independent modules. These modules are neither equally important nor do they contain an equal amount of faults and may be categorized as fault-prone (FP) or not fault-prone (NFP) depending on the number of fault present in the module. FP modules may require more testing than NFP modules because of its likelihood of containing more faults. Also, modules either NFP or FP may not have the equal fault-prone degree and therefore testing resources should be allocated on the basis of its fault-prone degree. Therefore, it is desirable to rank these FP modules on the basis of its fault prone degree. Ranking helps software professionals to prioritize their testing action.
This paper presents a new approach of early software quality prediction and ranking. Quality prediction is done by classifying software modules as FP or NFP. Furthermore, modules are ranked using software metrics and fuzzy ordering algorithm on the basis of their degree of fault proneness. Ranking of fault-prone module along with classification found to be a new approach to help in prioritizing and allocating test resources to the respective software modules. The model accuracy is validated through KC2 dataset. The results observed are found promising, when compared with some of the earlier models.

The application of SPC and quality tools to a maintenance process in a local oil refinery is presented and shown that the results have great value especially when the facts and findings are linked to the cost of quality. It is found that utilization of SPC and quality tools is essential to answer questions like identifying factors causing maintenance problems, identifying most critical conditions that result in machine failures in future and relating problems with causes etc. These questions relate to establishing and implementing a predictive maintenance plan where the overall effect gained is improved maintenance quality at reduced cost and downtime.

This paper considers a software development scenario where a software development team develops, tests and releases software version by version. A modeling framework is proposed to study the expected number of remaining faults in each version. The optimal development time and testing time for each version are also studied.