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Published on March 3, 2014

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International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 91-100, © IAEME AND TECHNOLOGY (IJMET) ISSN 0976 – 6340 (Print) ISSN 0976 – 6359 (Online) Volume 5, Issue 2, February (2014), pp. 91-100 © IAEME: www.iaeme.com/ijmet.asp Journal Impact Factor (2014): 3.8231 (Calculated by GISI) www.jifactor.com IJMET ©IAEME QUALITY MANAGEMENT SYSTEM IN R&D: A CRITICAL LITERATURE REVIEW Parvesh Kumar1, 1 Jimmy Kansal2, Dr. Sandeep Singhal3 M.Tech Scholar, Department of Mechanical Engineering, National Institute of Technology, Kurukshetra, India 2 Phd Scholar, Department of Mechanical Engineering, National Institute of Technology, Kurukshetra, India Scientist, Snow & Avalanche Study Establishment, Chandigarh, India 3 Professor, Department of Mechanical Engineering, National Institute of Technology, Kurukshetra, India ABSTRACT The purpose of this study is to explore the nature of research topics and methodologies employed in existing studies of quality management (QM) in Research and Development (R&D). Using a systematic review methodology, this paper analyse the literature to identify the performance of R&D organizations. The literature review reveals that researchers have mainly explored only how to implement quality principles and practices in the R&D environment and made little effort to analyse the effectiveness of QM in an R&D set-up. QM practices discussed in the literature consist of top management commitment, R&D workforce involvement, training, a process-based approach, teamwork and cross-functional teams, fact-based measurement and feedback mechanisms, R&D client focus, and good communication with suppliers. The paper provides researchers with valuable information about how this research area has evolved, what main themes have been discussed in the literature, and what management practices are effective in pursuing quality efforts in R&D. This study also makes a contribution to the development of quality theory in R&D by pointing out the necessity of performance measurement and suggesting important areas for future study. KEYWORDS: Quality Management System, R&D, Performance Measurement. 91

International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 91-100, © IAEME 1.0 INTRODUCTION A Quality Management System can be seen as a complex system consisting of all the parts and components of an organisation dealing with the quality of processes and products. A QMS can be defined as the managing structure, responsibilities, procedures, processes, and management resources to implement the principles and action lines needed to achieve the quality objectives of an organisation. Research and Development has been recognized as most important for future competitiveness to survive in this competitive and highly turbulent environment. A huge amount of money and other resources are being deployed in R&D by government as well as private organization. A major consideration is required on performance improvement that needs to continuously evaluate the performance of R&D in line with vision and strategy of the organization. In the last three to five years, quality principles and quality management have been a top priority for R&D managers. This has been the cumulative result of: • external pressures – corporate commitment to total quality requires all functions in an organization to be active in quality improvement and quality management; • internal deficiencies – realization of the need to improve effectiveness of R&D. A key reason for the relatively late adoption of quality management in R&D is that many of the established quality programmes are seen as quantitatively oriented, and are not easily transferable to R&D activities. Measures to quantify R&D quality are difficult to design and accept. Another reason is that the central tenets of the established programmes, such as “fitness for use”, “conformance to requirements”, “right first time”, cause much argument when used to evaluate the effects of implementation of QMS in an R&D set-up. In particular the definition of “defect” in R&D is controversial. R&D managers in sympathy with the difficulties of evaluation of R&D tasks have shrugged to find suitable measures to use. This has led to many suggestions on how to track various components of quality in R&D. Methods have been reported, e.g. for quantifying R&D productivity, R&D innovativeness, R&D team effectiveness. However, a general feeling from the literature is that the measures are artificially derived to satisfy the need for measurement, rather than being critical parameters or reliable indicators of quality in R&D. This leaves the stage set for the development of: • Reliable indicators of quality in R&D; • A quality management system for the R&D environment. The ideal arenas for this development are in the R&D laboratories themselves, each of which are at their own particular stage of implementation. Empirical studies are of paramount importance in developing total quality management for R&D. However this empirical work must take account of all the organizational and cultural differences between the laboratories, in interpreting the apparent successes and failures of implementing quality management. Throughout this paper, we will explore how traditional quality management systems can be adapted and developed into research & development organizations. 92

International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 91-100, © IAEME 2.0 THE NECESSITY ORGANIZATIONS OF QUALITY MANAGEMENT SYSTEMS IN R&D Quality in Research and Development (R&D) work has become increasingly important as companies commit themselves to quality improvement programmes in all areas of their activity. Quality improvement forms an important part of their competitive strategy. Quality management systems have been successfully designed and implemented for manufacturing and service functions; but so far the quality principles and systems are finding it difficult to translate to the R&D arena. The importance of quality management (QM) systems to improve the quality of services has been long recognised due to the growing interest in the globalisation of industrial activities and the market economy and also due to great concern for risk and safety factors. Today, QM systems are established in nearly all kinds of industrial activities, in measurement and testing laboratories and also in areas such as “operating theatres” or sales departments. During the last few years there has been ever increasing interest in the development of a more general strategy for applying QM systems in Research and Development activities in research laboratories or institutions. The driving force behind these activities has been the need for conformity with international quality standards given by ISO and others and also by the accreditation and certification bodies. Parts of the scientific community, especially the chemical industry with its research and development (R&D) laboratories, were also forced to adopt these mandatory standards for international trading. However, in most academic and public research centres for basic or applied research there seems to be deep concern as well as scepticism regarding the introduction of too rigid a QM system. Furthermore, the question of quality control and quality evaluation has expanded from R&D in analytical chemistry to R&D in general and to associated services. This means, for example, research in the fields of medicine, the social sciences etc. and also the quality of university education, which is regarded as a high-quality service to society. 3.0 PERFORMANCE MEASUREMENT SYSTEMS IN R&D Performance measurement (PM) in R&D is difficult and complex as the effort levels may not be observable, high uncertainty in success, influenced by uncontrollable factors, and long gestation period. R&D has a larger extent of problems with PM than manufacturing and services. Performance of an R&D organization is measured in line with its vision, strategy and goals, which needs to be clearly defined and communicated at all levels of the organization and all efforts and actions be focused on achieving them. R&D Performance Management has four main functions as alignment and prioritization viz. Cascading measures from strategy, Evaluation and incentives, Operational control and Learning & improvement. The measures must be matched to different research profiles viz. basic versus applied, short verses long term, developed versus undeveloped area of research, routine support services versus breakthrough ideas and knowledge development. Generally, manufacturing and service organizations use financial indicators for Performance Management. These indicators only emphasize operational results and not the processes, lack forecasting function and do not explain the cause-effect of operational results. Using only financial performance indicators may be easy, simple and cost-effective, but management may focus too much on the short-term financial effects and turn down the projects that bring long-term strategic gain to the company. A performance assessment system should integrate both financial and non-financial indicators assess both operational results and processes, and measure organizational performance from top to bottom. A strategy-oriented performance assessment can help management to evaluate business managerial system, operation process, operation system, management processes, and the complexity of the processes. Performance assessment system can provide management with timely information about whether the business operation is on the right track or not. A proper performance 93

International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 91-100, © IAEME assessment system should possess long term and short term focus, operational and strategic aspects in terms of the construct, and local and macro integration in terms of assessment span. Performance must be measured from the four perspectives as Customer, Financial, Organizational learning and growth and Internal business processes perspective. There are certain other difficulties in defining the output of R&D as R&D organization output measures can be subjective or objective, discrete or scalar, and quantitative and non-quantitative and there can also be qualitative aspects associated with them; Relationship of output measures to organizational goals must be included; Different organizations (governmental, commercial, and educational) will weigh the different criteria differently; Getting the clarification and deciding the specific criteria to determine the attainment by the individual or the organization takes time and is too complex; Different criteria should be measured and weighted fairly and objectively; R&D PM tends to vary with the character of work; Different R&D projects have different objectives to accomplish and take varying time, skills and other resources; Different R&D projects have different risk associated with them and different technological complexities and uncertainties; Some R&D organizations might include local operations but some might include international operations also; Some R&D organizations might be working on radical innovations but some might be doing incremental innovations; Sometimes number of patents or number of new products formed cannot be the sole criteria for judging the performance but also skills formation or technical capability formation can be the criteria; Sometimes the market conditions, government regulations and political factors might not be favourable towards a particular technology at a particular time but might be in demand later on in future and it is difficult to describe the quality of scientific manpower. A good performance assessment system should provide forecasting function. Neely et al. have given the issues to be considered while designing PM system. In this paper, balanced scorecard has been used to design the performance evaluation of R&D organizations. 3.1 Balanced Scorecard (BS) Balanced scorecard is a strategic measurement system including both non-financial and financial measures adopted by academic scholars and practitioners to measure the performance of a business organization. It is distinct from other strategic measurement systems in that it is more than collection of financial and non-financial measures. It contains outcome measures and the performance drivers of outcomes, linked together in cause-and- effect relationships and thus aims to be a feed-forward control system. Furthermore, BS is intended not only as a strategic measurement system but also as a strategic control system, which can align departmental and personal goals to overall strategy. BS translates the vision and strategy of a business unit into objectives and measures in the financial, customer, internal-business-process and learning and growth perspectives. The crux of BS is the linking together of the measures of four areas in a causal chain, which passes through all four perspectives. Measures of organizational learning and growth are drivers of the measures of internal business processes. Measures of these processes are in turn the drivers of measures of customer perspective, while these measures are the drivers of measures of the customer perspective, while these measures are the drivers of the financial measures. A good BS should have a mix of outcome measures (lag indicators) and performance drivers (lead indicators). BS integrates both financial and non-financial indicators, assess both operational results and processes, and measures organizational performance from top to bottom. It not only records operational results but also explains the cause-effect of operational results, and forecasts possible future. Scorecard translates vision and strategy of a business unit into objectives and measures of four areas and lastly it is simple to use. 94

International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 91-100, © IAEME 3.2 Balanced Scorecard applied to R&D 3.2.1 User Perspective The output of an R&D organization is generally in the form of new knowledge, product, process or technology or in the form of a solution to a particular problem. For these outputs, organizations may have either internal or external users or both. Internal users are their parent business units and the external users can be end users, industrial customers or the society. It depends upon the scope and target of the R&D organization, which they are targeting. But there is no meaning of investing in R&D unless it is useful for the society whether in terms of new knowledge, product or technology. It must give some value to the society who acts as the customers of the output of R&D. Performance must be measured from the customer’s perspectives with following objectives: i) Match the needs of the customers; ii) Create the demand for a new product/process/technology; iii) Provide value to the customer; iv) Improve customer satisfaction; and v) Improve product quality and features. 3.2.2 Internal Business Perspective Internal-business-process perspective describes the business processes at which the company has to be particularly adept in order to satisfy its shareholders and customers. The objectives from internal business perspective may be i) Persist in project’s schedule and shorten lead times; ii) Improve cost effectiveness in a product supply chain; iii) Identify different requirements of the supply chain, e.g. produceability of a product; iv) Efficient in resource utilization; and v) Extend and intensify co-work done in R&D. 3.2.3 Innovation and Learning Perspective Organizational learning and growth perspective involves changes and improvements, which the company needs to realize if it is to make its vision come true. Continuous innovation and learning is the key to success of R&D. Objectives from innovation and learning perspective are: i) Innovate; ii) Improve company’s or product’s competitiveness; iii) Extend and intensify co-work done in R&D; iv) Increase knowledge and learning; and v) Improve manufacturing process. 3.2.4 Financial Perspective Financial perspective identifies how company wishes to be viewed by its shareholders. R&D organizations cannot continue to survive without generating profits and funds for R&D. Objectives of an R&D organization from financial perspective are: i) Improve cost effectiveness of R&D; ii) Influence company’s or product’s sales; iii) Maximize shareholders wealth; iv) Source funds for R&D; v) Avail funds in time; vi) Minimize cost of capital; vii) Generate internal funds for R&D; viii) Run supporting business for R&D; ix) Arrange funds from external sources from government or customers; x) Improve returns; and xi) Continuous flow of funds. Different R&D organizations have different objectives and strategies. Appropriate PM parameters depend upon objectives of the specific organization. Therefore, BS can be designed for an individual R&D organization depending upon its vision and strategy. 95

International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 91-100, © IAEME Balanced Scorecard framework for R&D Organizations PM system of R&D organization should be aligned with its vision, strategy and goals to D know exactly it wants to be, where it is and what it should be and the performance should be measured from different perspectives. BS helps to measure performance of an organization in line with its vision, strategy and goals. BS technique can be used to measure the performance of R&D 96

International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 91-100, © IAEME organizations from the four perspectives as customer, innovative and learning, internal business processes and financial perspective, which focus on achieving the R&D vision and strategy. This technique also provides feedback and initiatives to be taken to achieve the desired performance level. A BS can be designed for an individual R&D organization, private or government, to capture its performance from four perspectives in line with one’s vision, strategy and goals. 4. THE ROLE OF ISO 9001 BASED QUALITY MANAGEMENT SYSTEM IN R&D ORGANIZATION Studies on quality management system (QMS) reveal that all the quality elements within an integrated system are closely associated with the basic framework set by the ISO 9000 series of standard. However, the idea of reducing the variability through standardization and at the same time looking for continual improvement in the system often seems paradoxical and is misunderstood for a R & D activity. But organizations, which are not even ISO certified and engaged in R & D functions, place greater emphasis on bridging the gap between requirements of quality assurance and the principles of quality management system. Increase in the complexity and globalization of competitive business environment has made R & D as one of the sources of competition. So, it is necessary to have systematic processes for an R & D activity for managing quality. Perhaps an activity constitutes a process or a set of processes / sub-processes, and ISO 9001: 2000 standard, which is a process driven quality management system, has a great potential to control and manage the R & D quality very effectively. Thus R & D managers have the advantage to achieve total quality management (TQM) by implementing ISO QMS in their organizations. The effective implementation of ISO QMS has been widely recognized as a means of building sustainable competitive advantage and thereby enhancing organization’s performance. ISO 9000 are internationally recognized and designed to demonstrate that an organization has achieved basic level of quality by the formalization and documentation of its effective QMS. Presently, an organization is certified ISO 9001: 2000 only, irrespective of the type of activity engaged in and services rendered by it. In ISO 9001: 2000 standard, in addition to system compliance, the main attention is focused on the issues of Customer Satisfaction (CS) and Continual Process Improvement (CPI), which can be achieved by suitably identifying the Key Performance Indicator (KPI) and measuring them periodically. Finally, the analysis of data may be carried out to verify the extent of CS achieved through CPI. However, in the standard what should be the approach of an organization to comply with the customer requirements is not specifically defined. It is the responsibility of the organization to decide what information it will monitor and measure to determine CS. The level of satisfaction achieved is the measure of Customer Satisfaction Index (CSI). An organization needs to have its own methodology for measurements of CSI keeping in mind the customers’ needs and expectations. ISO 9001: 2004 make it clear that CPI must be planned and implemented. Key elements for CPI may be quality policy and objectives, analysis of customer feedback data, corrective and preventive actions, audit results and management review meeting outputs etc. Some of the sources of CS may be: i) Customer complaints; ii) Customer feedback reports; iii) Results of focused group meeting; iv) Reports from customers’ organization; v) Questionnaires and surveys; iv) Media, sector and industry studies; and vii) Bench marking data etc. Information about CS and dissatisfaction is often poorly organized or seldom used by an organization to improve its overall performance. In this respect, an organization is required to develop knowledge and expertise on what information may be gathered, the methodology to be followed for gathering information, and who is responsible to collect and analyse data / information etc. 97

International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 91-100, © IAEME 5. LITERATURE REVIEW A. Blanton Godfrey For most organizations, applying quality management in research and development would be a journey into unexplored territory. Although they may have reduced defects by 90 percent and cycle times by 50 percent in production processes, reduced delivery times by 75 percent, cut inventories by 80 percent and improved the accuracy and timeliness of the order-entry processes significantly, they haven't dared to venture into the sacrosanct halls of R&D. In the past few years, quality management activities have become common place in a few R&D organizations. In a remarkable new book published by John Wiley & Sons, Improving R&D Performance the Juran Way, Al C. Endres, head of the management department at the University of Tampa, documents many of the breakthroughs in R&D quality management reported by leading companies during the past five years reported on at Juran Institute's R&D Quality Symposia. Rosalind Taylor and Alan Pearson (1994) There are three central figures in the literature and history of quality and quality improvement: Juran, Crosby and Deming. Juran and Crosby advocate a team-based approach to improving business operating levels, by permanently curing non-conformances to customer requirements. They stress that the basis for quality improvement is identification of chronic waste and quantification of the cost of non-conformance. Deming focuses on statistical techniques for quality improvement and asserts that “bottom-up” is as important as “top-down”. Juran’s methodology stresses a project by- project implementation and a “universal breakthrough sequence” for significantly reducing the level of chronic waste. The strength of Crosby’s programme is the attention it gives to transforming attitudes towards quality. Crosby involves everyone in the organization in the process by stressing individual conformance to requirements. David Flores In the past companies would have to conduct expensive external supplier audits to verify a supplier’s product conformed to product specifications using a total quality management (TQM) approach. In 1987 ISO 9000 was created by a committee in Europe to help set quality measurement standards. The word ISO is Greek, which means the same. ISO in this paper refers to the International Organization for Standardization. ISO is a network of the national standards institutes of 157 countries, based on one member per country, with a Central Secretariat in Geneva, Switzerland, that coordinates the system. The standards establish by the organization are also referred to as ISO standards. The ISO 9000 standard allows a registrar company to conduct outside audits of a company’s quality management system (QMS), which certifies the implementation and compliance of the QMS to the ISO 9000 standard (Anderson, Daly, and Johnson 1999). The ISO 9000 certified company can achieve a competitive advantage over its rivals by closely following the ISO requirements listed in the ISO 9000 requirements manual and tailoring it to fit internal processes. D K Banwet and S G Deshmukh (2006) Research and Development has been recognized as most important for future competitiveness to survive in this competitive and highly turbulent environment. A huge amount of money and other resources are being deployed in R&D by government as well as private organizations. A major consideration is required on performance improvement that needs to continuously evaluate the performance of R&D in line with vision and strategy of the organization. In spite of high costs and an increasing importance of R&D for future competitiveness, many companies and government institutions struggle to shape well their R&D function and find it difficult to assess its contribution to 98

International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 91-100, © IAEME the organization1. Every R&D organization needs to focus on continuous improvement in its performance that requires evaluating the performance for tracking the exact position and getting the feedback to know the gaps to improve. In competitive market, success of R&D does not only depend upon how much resources one has employed but also depends highly on the sharp vision, mission and strategy of an organization. 6. SCOPE & CONCLUSIONS The scope of QMS in R&D is presented and is followed by an overview of the TQM philosophy and its associated tools and techniques. Special attention is given to defining performance measures for R&D as a back-drop to measuring the success of TQM actions in an R&D organization. Implementation models for QM in R&D which are derived from an extensive review of the open literature, are also examined. The paper concludes with a brief discussion of future work that will be necessary to develop a complete model for the application of Quality Management System to R&D. The measurement aspect of QM in the service sector is a difficult process, requiring a clear understanding of Quality and Measurement concepts. This paper provides a systematic approach to applying measurement principles to management of the service sector. Measurement is an inherent part of the quality management process for the provider of services, both internal and external to the organization. Measurements of service sector work appear to be practical and should be developed on a case basis. Having examined the principles of both good TQM and good R&D it is clear that far from being in conflict the requirements are consistent and compatible. In a TQM company the departments will find support for their ideas, guidance on how to utilise them, but above all freedom to express them. REFERENCES 1. Rosalind Taylor and Alan Pearson. “Total Quality Management in Research and Development” Juran J.M “A Universal approach to Managing for Quality – The Quality Trilogy” Quality Progress, Aug. 1986,. 2. A.I.C Endres “Quality in Research and Development” 3. Joseph M. Juran and A. Blanton Godfrey “Juran Quality Handbook” Fifth Edition. 4. Dolors Barrot and Laure Dassonville “CERCO Working group of quality”, Handbook for Implementing a Quality Management System in a national mapping agency. [www.eurogeographics.org/sites/default/files/handbook_VI.pdf] 5. Scott A. Dellana and Henry A Wiebe “Engineering Management Department” 6. Starr, L., “Celanizing the Quality Program”, Research Management, November/December 1987. 7. Murray, T.J., “Meeting the New Quality Challenge”, Research Management, November/December 1987. 8. Krogh, L.C., “Measuring and Improving Laboratory Productivity/Quality”, Research Management, November/December 1987. 9. R. K. Jain and H.C. Triandis, Management of Research and Development Organization Managing the Unmanageable, John Wiley h Sons, Inc., 1990. 10. R.A. Pappas and D.S. Remer, "Measuring R&D Productivity", Research Management, May-June 1985. 11. M.G. Brown and R.A. Svenson, "Measuring R&D Productivity", Research Management, July-Aug. 1988. 12. National Science Foundation, "Enhancing Research and Development and Expanding the Human Frontier, The Budget for Fiscal Year 1993", Feb. 1992. 99

International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 91-100, © IAEME 13. A. Blanton Godfrey “TQM in R&D”. 14. Anderson, S.W., Daly, J.D., and M.F. Johnson (1999). “Why Firms Seek ISO 9000 Certification: duction and Oper Regulatory Compliance or Competitive Advantage?” Production and operation Management. 15. Barney, J. (1991). Firm Resources and Sustained Competitive Advantage, Journal of Management. 16. Gupta, A. (2000). “Quality Management Practices of ISO vs. Non-ISO Companies: a Case of Indian Industry” Industrial Management & Data Systems. 17. Loch C H & Tapper U A S, Implementing a strategy-driven performance measurement system for an applied research group, J Product Innovation Manage, 19 (2001) 185-198. 18. Hsu K H, Using balanced scorecard and fuzzy data envelopment analysis for multinational R&D project performance assessment, J Am Academy Business, 7 (2005) 189-196. Maisel C S, Performance measurement: The balanced 19. scorecard approach, J Cost Manage, Fall (1992) 47-52. 20. Hoffecker J & Goldenberg C, Using the balanced scorecard to develop company wide performance measures, J Cost Manage, Fall (1994) 5-17. 21. Brown M G & Svenson R A, Measuring R&D productivity, Res Technol Manage, 41 (1998) 30-35. Jain R K & Triandis H C, Management of Research and Development Organizations: Managingthe. 22. Performance measurement system design: should process based approaches be adopted, Int J Prod Econ, 46-47 (1996) 423-431. 23. Cooper R B, Dermuth K W, Garg I D, Sherman G R, Truss K J & Willborn W, Applying quality assurance to R & D projects, Quality Progr, July 1990. 24. Auer A, Karjalainen J & Seppanen V, Improving R & D processes by an ISO: 9001 based quality management system, J Syst Architecture, 42 (1996). 25. ISO 9001: 2000, Explained, 2nd edn (ASQ Quality Press, Milwaukee, Wisconsin) 2000, Chapter 12,188-192. 26. ISO 9001: 2000, Quality management systems requirements, 3rd edn (ISO Central Secretariat, Switzerland) 2000, 12-15. 27. Arbale A A, Working paper for guidelines to CSIR Labs, CSEU, Pune, July 2004. 28. Anil Khurana, Jamal A Farooquie, Manjit Singh and Jimmy Kansal, “Study of Differences Among the Management Systems of the ISO 9001 Certified and Non-ISO 9001 Certified Units of Indian Defence R&D Organisation”, International Journal of Advanced Research in Management (IJARM), Volume 5, Issue 1, 2013, pp. 1 - 22”. ISSN Print: 0976 – 6324, ISSN Online: 0976 – 6332. 29. Neeti Jain, Jimmy Kansal, Ashwagoshaganju, Anil Khurana and Pramodsatyawali, “The Effect of Implementation of ISO 9001:2008 Qms on the Organizational Performance in an R&D Establishment”, International Journal of Management (IJM), Volume 4, Issue 1, 2013, pp. 47 - 55, ISSN Print: 0976-6502, ISSN Online: 0976-6510. 30. Anil Khurana, Prof. Jamal A Farooquie, Dr. Manjit Singh and Jimmy Kansal, “Effect of ISO 9001 Quality Management Systems Certification on the Performance in Indian Defence R&D Organisation”, International Journal of Management (IJM), Volume 4, Issue 6, 2013, pp. 61 - 76, ISSN Print: 0976-6502, ISSN Online: 0976-6510. 100

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