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Ensuring the reliability and reduction of quality control costs by minimizing process variability

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper presents a method for planning the range of quality control while ensuring its reliability and minimizing costs. The method is dedicated to destructive inspection, in which the cost of performing the measurement is significant in relation to the cost of manufacturing a part or product. The methodology was divided into four main stages: (1) selection of the measurement system and definition of the inspection scope and sample size, (2) process control, (3) redefining the scope of control and (4) verification of control cost and reliability after sample size change. The article presents the results of applying the author's procedure to the process of evaluating seat belts in automotive industry. Belts are used in the process of controlling the final product, which is a seat belt anchor plate. This approach allowed to reduce the number of destroyed parts during control while maintaining the credibility of the decision based on the assessment. As a result of double-decreasing the sample size, the costs of seat belt quality control were reduced. Assuming an average of 40 seat belt deliveries per year, the material cost was reduced by 50%. Limiting the sample size to 15 pieces per delivery would reduce the cost of testing from by 45%. It was achieved maintaining the appropriate level of credibility of decisions made greater than 0.8.
Rocznik
Strony
art. no. 162626
Opis fizyczny
Bibliogr. 41 poz., rys., tab., wykr.
Twórcy
  • Poznan University of Technology, Faculty of Mechanical Engineering, Poland
  • Poznan University of Technology, Faculty of Mechanical Engineering, Poland
  • Poznan University of Technology, Faculty of Mechanical Engineering, Poland
Bibliografia
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  • 12. Fernández A J. Economic lot sampling inspection from defect counts with minimum conditional value-at-risk. European Journal of Operational Research 2017; 258(2): 573–580, https://doi.org/10.1016/j.ejor.2016.10.042.
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  • 14. Gruszka S, Gašpar Š. Effect of Human Factor on Product Quality in Manufacturing Activities. Multidisciplinary Aspects of Production Engineering 2018. doi:1.851-856.10.2478/mape-2018-0107, https://doi.org/1.851-856.10.2478/mape-2018-0107.
  • 15. Hamrol A, Kujawińska A, Bożek M. Quality inspection planning within a multistage manufacturing process based on the added value criterion. International Journal of Advanced Manufacturing Technology 2020; 108(5–6): 1399–1412, https://doi.org/10.1007/s00170-020-05453-0.
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  • 31. Shin B C, Byun J H, Chang W L et al. Small-sample inspection plans for the new product quality level evaluation of finite population: Focused on guided weapons in development stage. Journal of Korean Institute of Industrial Engineers 2015; 41(5): 481–488, https://doi.org/10.7232/JKIIE.2015.41.5.481.
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  • 33. Tambe P, Kulkarni M. A reliability based integrated model of maintenance planning with quality control and production decision for improving operational performance. Reliability Engineering and System Safety 2022. doi:10.1016/j.ress.2022.108681, https://doi.org/10.1016/j.ress.2022.108681.
  • 34. Timischl W. Qualitatssicherung: Statistische Methoden. 4th edition. Munchen, Hanser: 2012.
  • 35. Toteva P, Vasileva D. Tasks in planning of quality inspection. Proceedings in Manufacturing Systems, 2013; (Volume 8, Issue 3): 183–188.
  • 36. Vaghefi A, Sarhangian V. Contribution of simulation to the optimization of inspection plans for multi-stage manufacturing systems. Computers and Industrial Engineering 2009; 57(4): 1226–1234, https://doi.org/10.1016/j.cie.2009.06.001.
  • 37. Verna E, Genta G, Galetto M, Franceschini F. Economic impact of quality inspection in manufacturing: A proposal for a novel cost modeling. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 2022. doi:10.1177/09544054221078090, https://doi.org/10.1177/09544054221078090.
  • 38. Wang C H, Meng F C. Optimal lot size and offline inspection policy. Computers and Mathematics with Applications 2009; 58(10): 1921–1929, https://doi.org/10.1016/j.camwa.2009.07.089.
  • 39. Wei D, Li D, Zheng Y et al. Online quality inspection of resistance spot welding for automotive production lines. Journal of Manufacturing Systems 2022; 63: 354–369, https://doi.org/10.1016/j.jmsy.2022.04.008.
  • 40. Yun W Y, Han Y J, Kim H W. Simulation-based inspection policies for a one-shot system in storage over a finite time span. Communications in Statistics: Simulation and Computation 2014; 43(8): 1979–2003, https://doi.org/10.1080/03610918.2013.815772.
  • 41. Yun W Y, Liu L, Han Y J. Metaheuristic-based inspection policy for a one-shot system with two types of units. Journal of Mechanical Science and Technology 2014; 28(10): 3947–3955, https://doi.org/10.1007/s12206-014-0905-9.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-baa50249-048f-407b-bfe4-f90b0966e42f
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