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Informative Value of Measurements for Quality Management of Auto Parts

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Proceedings of the 4th International Conference on Industrial Engineering (ICIE 2018)

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Abstract

The end result of applying many modern methods of quality management is the development of corrective measures to intervene in the process in the form of general recommendations, without specific measures. Only for the sake of assessing the stability of the process according to one measure, the standard recommends conducting more than thousand measurements, which in no way can be recommended for the current production. As a result of the research, it was established that the methods of statistical management of quality indicators, correlation analysis, and other frequently used methods are extremely ineffective, in which corrective measures are developed after additional engineering procedures. We also proposed criteria for measuring the effectiveness and efficiency of analyzing measuring information. Measurement effectiveness indicator—the complexity of planning corrective actions based on measurement data. Efficiency is the laboriousness of carrying out the measurements themselves and analyzing the data. The increase of these indicators is ensured by: the preliminary assignment of the coordinates of the measurement points; measurement of the workpiece at these points; and identification of the position coordinates of the workpiece during processing. Measurement of the part at the same points after treatment, it is experimentally proved that the time for planning improvements is reduced by 3–6 times. The technique was tested in the factory by a number of enterprises—suppliers of auto components of KAMAZ Corp.

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References

  1. IATF 16949:2016. Quality management systems. Particular requirements for the application of ISO 9001:2015 for automotive production and relevant service part organizations

    Google Scholar 

  2. Statistical Process Control, SPC (2005) Reference manual, 2nd ed. Automotive Industry Action Group, p 221

    Google Scholar 

  3. Measurement Systems Analysis, MSA (2010) Reference manual, 4th ed. Automotive Industry Action Group, p 241

    Google Scholar 

  4. Anikeeva O, Ivakhnenko A, Zhirkov A (2016) Parametric reliability assurance for machine-tools. In: Procedia Eng 150:712–716; 2nd international conference on industrial engineering, ICIE 2016, 19–20 May 2016

    Article  Google Scholar 

  5. Balabanov IP, Balabanova ON, Groshev AV (2015) Formation of initial data of the workpiece batch in simulation modelling precision forming. In: IOP Conf Ser Mater Sci Eng 86(1); International scientific and technical conference on innovative mechanical engineering technologies, equipment and materials-2014, ISC IMETEM 2014, Kazan Federal University, Kazan, Russian Federation, 3–5 Dec 2014

    Google Scholar 

  6. Khusainov RM, Belov SF, Chukhontseva OV (2014) Diagnosis of CNC machine tools in terms of circular interpolation’s accuracy figure. In: IOP Conf Ser Mater Sci Eng 69(1); International scientific conference on innovative mechanical engineering technologies, equipment and materials—2013, IMETEM 2013, Kazanskaya Yarmarka, Kazan, Russian Federation, 25–27 Sept 2014

    Google Scholar 

  7. Kas’yanov SV, Safarov DT (2004) Diagnosis of technical state of equipment and tools according to indices of technological accuracy. Avtom Prom 5:24–28

    Google Scholar 

  8. Safarov DT, Fedorova KA and Ilyasova AI (2015) Algorithms development of making special techniques in APQP manufacturing process of automotive components. In: IOP Conf Ser Mater Sci Eng 134(1); International scientific-technical conference on innovative engineering technologies, equipment and materials 2015, ISTC-IETEM 2015, Kazan FairKazan, Russian Federation, 2–3 Dec 2015

    Google Scholar 

  9. Kasyanov SV, Biktimirova GF (2014) Tekhnologicheskii perekhod kak klyuchevoi protsess upravleniya kachestvom produktsii v sootvetstvii s ISO/TS 16949-09 (Machining step as a key quality management process according to ISO/TS 16949-09). Avtom Prom 3:27–29

    Google Scholar 

  10. Kasjanov SV, Kondrashov AG, Safarov DT (2017) Regulation of geometrical parameters deviations of automotive components parts through diagnostic measurements organization. In: Procedia Eng 206:1508–1514; International conference on industrial engineering, ICIE 2017, 16–19 May 2017

    Google Scholar 

  11. Safarov DT, Kondrashov AG, Glinina GF and Safarova LR (2017) Algorithm of calculation of energy consumption on the basis of differential model of the production task performed on machines with computer numeric control (CNC). In: IOP Conf Ser Mater Sci Eng 240(1); International scientific-technical conference on innovative engineering technologies, equipment and materials 2016, ISTC-IETEM 2016, Kazan, Russian Federation, 7–9 Dec 2016. https://doi.org/10.1088/1757-899x/240/1/012060

    Article  Google Scholar 

  12. Safarov DT, Kondrashov AG, Safarova LR, Glinina GF (2017) Energy planning in production shops with numerically controlled machine tools. Russ Eng Res 37(9):827–834

    Article  Google Scholar 

  13. Kas’janov SV, Kondrashov AG, Safarov DT (2013) RU patent 2496611, 27 Oct 2013

    Google Scholar 

  14. Kondrashov AG, Kas’janov SV, Safarov DT et al (2016) RU patent 2581384, 24 Mar 2016

    Google Scholar 

  15. Kas’janov SV, Kondrashov AG, Safarov DT (2013) RU patent 133039, 10 Oct 2013

    Google Scholar 

  16. Kas’janov SV, Kondrashov AG, Safarov DT (2013) RU patent 133040, 10 Oct 2013

    Google Scholar 

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Correspondence to D. T. Safarov .

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Safarov, D.T., Kasyanov, S.V., Kondrashov, A.G. (2019). Informative Value of Measurements for Quality Management of Auto Parts. In: Radionov, A., Kravchenko, O., Guzeev, V., Rozhdestvenskiy, Y. (eds) Proceedings of the 4th International Conference on Industrial Engineering. ICIE 2018. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-95630-5_177

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  • DOI: https://doi.org/10.1007/978-3-319-95630-5_177

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95629-9

  • Online ISBN: 978-3-319-95630-5

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