Quality assessment and risk forecast in enterprise management system processes using qualimetric methods
Abstract
DOI: https://doi.org/10.32820/2079-1747-2024-33-92-101
To assess the quality and predict the risks in the processes of the Quality Management
System (QMS) of enterprises based on ISO 9000 series standards, it is recommended to use
qualimetric methods based on the criteria of nonparametric statistics. The article considers two
practical tasks. One of them concerns determining the randomness of the time series of assessments
of the QMS process quality. It is proposed to use the series criterion to determine the period when
random or natural factors influence the distribution of the process quality indicators. This approach
allows to predict the behaviour of quality assessment time series and development of corrective
measures. The second task focuses on establishing confidence intervals for the variance of the
generalized quality indicator of the QMS process over time, using the Wilcoxon criterion. An
algorithm has been developed to identify the systematic component of QMS process performance
over time and to define its confidence intervals. Monitoring and analyzing the movement of the
median value of the quality indicator facilitate forecasting and decision-making to enhance process
quality. Understanding confidence intervals assists in determining the stability of variations in the
generalized quality indicator of the QMS process during its operation.
Downloads
References
DP «UkrNDNTs» (2019), DSTU ISO 45001:2019 (ISO 45001:2018, IDT) Systemy upravlinnya okhoronoyu zdorovya ta bezpekoyu pratsi. Vymohy ta nastanovy shchodo zastosuvannya, [DSTU ISO 45001:2019 (ISO 45001:2018, IDT) Occupational health and safety management systems. Requirements and instructions for use], Kyiv.
Cherniak, O, Sorocolat, N, Bahaiev, I & Fatieieva, L 2022, ‘Zastosuvannia funktsionalnoi zalezhnosti dlia bahatokretyrialnoho otsiniuvannia bezpeky pratsi, yak obiekta kvalimetrii’ [Application of functional dependence for multi-cretirialassessment of labor safety asan object of qualimetry], Suchasnyi stan naukovykh doslidzhen ta tekhnolohii v promyslovosti, no 1, Pp. 76–84. DOI: https://doi.org/10.30837/ITSSI.2022.19.076 .
Ginevičius, R, Trišč R, Remeikienė, R, Zielińska, A & Strikaitė-Latušinskaja, G 2022, “Evaluation of the condition of social processes based on qualimetric methods: The COVID-19 case”, Journal of International Studies, vol. 15, no. 1, pp. 230–249, doi: 10.14254/2071-8330.2022/151/15.
Cherniak О, Sorocolat N & Kanytska I 2020, ‘Zastosuvannia metodu intehruvannia dlia otsiniuvannia yakosti obiektiv kvalimetrii’ [Application of the integration method for assessing the quality of qualimetry objects], Visnyk Natsionalnoho tekhnichnoho universytetu «KhPI». Seriia: Novi rishennia v suchasnykh tekhnolohiiakh, no. 4 (6), pp. 93-98, doi: 10.20998/2413-4295.2020.04.14.
Kupriyanov, O, Trishch, R, Dichev, D & Bondarenko, T 2022, ‘Mathematic Model of the General Approach to Tolerance Control in Quality Assessment’, InterPartner 2021. Lecture Notes in Mechanical Engineering, pp. 415–423, doi: https://doi.org/10.1007/978-3-030-91327-4_41
Budanov, P, Grinchenko, H, Nechuyviter, O & Tsykhanovska, I 2022, ‘Zastosuvannia metodiv kvalimetrii dlia otsinky kompleksnykh pokaznykiv yakosti bahatoparametrychnykh obiektiv’ [Application of qualimetry methods to evaluate complex quality indicators of multi-parameter objects], Mashynobuduvannia, Iss 30, pp. 73–84, doi: https://doi.org/10.32820/2079-1747-2022-30-73-84.
Cherniak, O, Sorocolat, N & Kanytska, I 2020, ‘Hrafoanalitychnyi metod vyznachennia kompleksnoho pokaznyka yakosti obiektiv kvalimetrii’ [Graph analytical method for determining the complex quality indicator ofqualimetry objects], Suchasnyi stan naukovykh doslidzhen ta tekhnolohii v promyslovosti, no. 4 (14), pp. 169–175, doi: 10.30837/ITSSI.2020.14.169.
Trishch, R, Nechuiviter, O, Dyadyura, K, Vasilevskyi, O, Tsykhanovska, I & Yakovlev, M 2021, “Qualimetric method of assessing risks of low quality products”, MM Science Journal, no. 4, pp. 4769–4774, doi: 10.17973/MMSJ.2021_10_2021030.
Trishch, GМ & Denisenko, MV 2014, ‘Analiz stanu systemy upravlinnia yakistiu v dynamitsi’ [Analysis of the state of the quality management system in dynamics], Tekhnolohycheskyi audyt y rezervy proyzvodstva, vol. 15 no. 1, pp. 14–16. doi: 10.15587/2312-8372.2014.21717.
Trishch, R, Maletska, O, Cherniak, O, Semionova, Ju & Jancis, V 2020, ‘Analysis of the requirements of international and national standards for measure-ment methods and metrological equipment’, Innovative Technologies and Scientific Solutions for Industries, no. 1 (11), pp. 156-162. doi: 10.30837/2522-9818.2020.12.075
Bubela, T, Mykyychuk, M, Hunkalo, A, Boyko, O & Basalkevych, O 2016, ‘Exploration of uncertainty in results of expert measurements in the system of quality management’,
Eastern-European Journal of Enterprise Technologies. no. 3, pp. 4–11. doi: https://doi.org/10.15587/1729-4061.2016.71607
Ginevičius, R, Trishch, R, Bilan, Y, Lis, M & Pencik, J 2022, “Assessment of the Economic Efficiency of Energy Development in the Industrial Sector of the European Union Area Countries“, Energies, Vol. 15, no. 9, рр. 3322. doi: https://doi.org/10.3390/en15093322.
Cherniak, О, Trishch, R & Denysenko, A 2019, ‘Metodyka otsiniuvannia shkidlyvykh chynnykiv, yaki vplyvaiut na zdorovia robitnykiv mashynobudivnoho pidpryiemstva’ [Methods of assessing the harmful factors affecting the health of workers of a machine-building enterprise], Visnyk NTU «KhPI», Seriia: Novi rishennia v suchasnykh tekhnolohiiakh, no 5 (1330), pp. 70-76, doi:10.20998/2413-4295.2019.05.09.
Julius, B & Piersol, A 1971, Random Data: Analysis and Measurement Procedures, John Wiley and Sons, Incorporated, Hoboken, New Jersey.
Pikh, SS, Popel, OM, Rovenchak, AA & Talianskyi, II 2011, Metody matematychnoyi fizyky, [Methods of mathematical physics], LNU named after Franka, Lviv.
