Autors: Georgiev, K. K.
Title: Statistical analysis of the quality of a technological process for the production of shafts for electric motors by roughness study
Keywords: accuracy, adjustability, analysis, quality, quality control, stability, surface roughness, technological process

Abstract: This paper presents a statistical analysis of the quality of a technological process by investigating the surface roughness of shafts for electric motors obtained during machining. Repeated measurements have been carried out using a portable roughness tester INSIZE ISR - C002 and the results are summarized. Statistical analysis is applied to analyse the accuracy, adjustability, and stability of technological process. The stability of the process is presented by investigating the correlation between the experimental and theoretical curve of the quality index. Accuracy evaluation is performed by calculating the accuracy coefficient. The adjustability analysis is evaluated by the relative position of the distribution curve of the obtained quality index with respect to the tolerance field.

References

  1. Mitra, A. (2016). Fundamentals of quality control and improvement. John Wiley & Sons.
  2. Hristov, M. H. (2023, September). SPC as an Instrument for Implementation and MSA as an Instrument for Evaluation of NonLinear Object Based Temperature Compensation into Shop Floor CMM. In 2023 15th Electrical Engineering Faculty Conference (BulEF) (pp. 1-9). IEEE.
  3. Gejdoš, P. (2015). Continuous quality improvement by statistical process control. Procedia Economics and Finance, 34, 565-572.
  4. Montgomery D. C., Introduction to Statistical Quality Control, Sixth Edition, Copyright 2009 by John Wiley & Sons, Inc., ISBN 978-0-470-16992-6
  5. Oakland, J., & Oakland, J. S. (2007). Statistical process control. Routledge.
  6. H.R. Radev, “Metrologiya i izmervatelna tehnika”, vol. II, S., Softtreyd, 2010, ISBN: 978-954-334-093-4
  7. Дюкенджиев Г., Р.Йорданов, Контрол и управление на качеството, София., Софттрейд, 2002.
  8. Statistical process control (SPC), Reference manual, Copyright 1992, Chrysler Corporation, Ford Motor Company, and General Motors Corporation
  9. Allen T., Introduction to Engineering Statistics and Lean Six Sigma, Statistical Quality Control and Design of Experiments and Systems, Third Edition Springer-Verlag London Limited 2006, ISBN 978-1-4471-7420-2 (eBook), https://doi.org/10.1007/978-1-4471-7420-2
  10. Qiu P., Introduction to Statistical Process Control, 2014 by Taylor & Francis Group, LLC, ISBN-13: 978-1-4822-2041-4 (eBook - PDF)

Issue

Vide. Tehnologija. Resursi - Environment, Technology, Resources, vol. 3, pp. 70-74, 2024, , https://doi.org/10.17770/etr2024vol3.8137

Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus