Journal of Korean Society for Quality Management (품질경영학회지)

Korean Society for Quality Management (한국품질경영학회)
권호 표지
DOI QR코드

DOI QR Code

Understanding and Reducing Performance Variation in New Product Development Using Paper Helicopter Experiment

종이 헬리콥터 실험을 통한 개발단계 성능변동의 이해와 개선

  • Shin, Byung-Cheol (Department of Industrial and Systems Engineering and Engineering Research Institute, Gyeongsang National University) ;
  • Kim, Si-Ung (Department of Industrial and Systems Engineering and Engineering Research Institute, Gyeongsang National University) ;
  • Jeong, Sun Min (Department of Industrial and Systems Engineering and Engineering Research Institute, Gyeongsang National University) ;
  • Byun, Jai-Hyun (Department of Industrial and Systems Engineering and Engineering Research Institute, Gyeongsang National University) ;
  • Nam, Yong-Seog (Quality Management Bureau, Defense Agency for Technology and Quality)
  • 신병철 (경상대학교 산업시스템공학부, 공학연구원) ;
  • 김시웅 (경상대학교 산업시스템공학부, 공학연구원) ;
  • 정순민 (경상대학교 산업시스템공학부, 공학연구원) ;
  • 변재현 (경상대학교 산업시스템공학부, 공학연구원) ;
  • 남용석 (국방기술품질원 품질경영본부)
  • Received : 2015.10.05
  • Accepted : 2015.11.11
  • Published : 2015.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Purpose: In developing new products, reducing performance variation is important for competitiveness factors such as quality, cost, and delivery. This paper aims at evaluating three performance variations; measurement, performance evaluation, and manufacturing variations, and then improving product and process design, focused on paper helicopter making case study. Methods: For measurement system analysis, gage R&R (repeatability and reproducibility), linearity, stability are evaluated. Since gage R&R are not satisfactory, the measurement system is improved by adopting voice memos application of iPhone and providing standard measurement procedure. To evaluate performance variation, product deterioration and environment factor (wind speed) is considered. Since the existing design is sensitive to these noise factors, a new product design is developed, which is proven to be robust to the noise factors. Finally, manufacturing variations are evaluated with five factors which can cause variation in flight time. To reduce the impact of three significant factors, three improvement methods are applied. Results: Three performance variations are evaluated and robust paper helicopter design is presented. Conclusion: To reduce measurement and process variations, improved measurement method and paper helicopter making procedure are proposed. A new product design is also presented which is robust to deterioration and environmental variation. This paper is expected to benefit students and practitioners who want to have hands-on knowledge on new product quality improvement.

Keywords

References

  1. AIAG(Automotive Industry Action Group). 2010. Measurement Systems Analysis Reference Manual, 4th ed. USA.
  2. Agrawal, R., Lawless, J. F., and MacKay, R. J. 1999. "Analysis of Variation Transmission in Manufacturing Processes - Part II." Journal of Quality Technology 31(2):143-154. https://doi.org/10.1080/00224065.1999.11979911
  3. Anand, K. N. 1998. "Dispersion Control: A Company Philosophy to Meet Competitive Challenges." Quality Engineering 10(4):605-615. https://doi.org/10.1080/08982119808919178
  4. Bai, D. S., Ryu, M. C., Kwon, Y. I., Yun, W. Y., Kim, S. B., Hong, S. H., and Choi, I. S. 1999. Statistical Quality Control, 2nd ed. Seoul: Youngjimunhwasa.
  5. Escalante, E. J. 1999. "Quality and Productivity Improvement: A Study of Variation and Defects in Manufacturing." Quality Engineering 11(3):427-442. https://doi.org/10.1080/08982119908919259
  6. Heredia1, J. A., and Gras, M. 2010. "Empirical Procedure for Modelling the Variation Transmission in a Manufacturing Process" Quality Engineering 22(3):150-156. https://doi.org/10.1080/08982111003724929
  7. Lawless, J. F., MacKay, R. J., and Robinson, A. J. 1999. "Analysis of Variation Transmission in Manufacturing Processes - Part I." Journal of Quality Technology 31(2):131-142. https://doi.org/10.1080/00224065.1999.11979910
  8. Lee, S. H. 2006. MINITAB Measurement System Analysis. Gunpo, Seoul: Eretec Inc.
  9. Liu, J. 2010. "Variation Reduction for Multistage Manufacturing Processes: A Comparison Survey of Statistical-Process-Control vs Stream-of-Variation Methodologies." Quality and Reliability Engineering International 26(7):645-661. https://doi.org/10.1002/qre.1148
  10. MacKay, R. J., and Steiner, S. H. 1997. "Strategies for Variability Reduction." Quality Engineering 10(1):125-136. https://doi.org/10.1080/08982119708919115
  11. Mader, D. P., Prins, J., and Lampe, R. E. 1999. "The Economic Impact of Measurement Error." Quality Engineering 11(4):563-574. https://doi.org/10.1080/08982119908919276
  12. Minitab Inc. 2010. MINITAB Software, Release 16. PA: State College.
  13. Montgomery, D. C. 2012. Design and Analysis of Experiments, 8th ed. USA: Wiley.
  14. Montgomery, D. C. 2013. Statistical Quality Control, 7th ed. USA: Wiley.
  15. Palumbo, B., De Chiara, G., Sansonea, F., and Marroneb, R. 2011. "Technological Scenarios of Variation Transmission in Multistage Machining Processes." Quality and Reliability Engineering International 27(5):651-658. https://doi.org/10.1002/qre.1223
  16. Taguchi, G., and Wu, Y. 1981. Off-Line Quality Control. Central Japan Quality Control Association, Tokyo.
  17. Taylor, W. A. 1991. Optimization and Variation Reduction in Quality. USA: McGraw-Hill.