Quantitative assessment of quality management systems’ processes
Bibliographic Data
| ID | 15068205 |
|---|---|
| Authors | Romualdas Ginevicius (0000-0003-2067-4398, Vilnius Gediminas Technical University, corresponding author), Halyna Trishch (Ukrainian Engineering Pedagogics Academy), Vladislavas Petraskevicius (0000-0002-6131-1318, Vilnius Gediminas Technical University) |
| Year | 2015 |
| Volume | 28 |
| Issue | 1 |
| Pages | 1096-1110 |
| Publication date | 2015-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Economic Research-Ekonomska Istraživanja (JOURNAL) |
| Journal identifiers | ISSN: 1331-677X • E-ISSN: 1848-9664 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/1331677x.2015.1087676 |
| OpenAlex | W2181167108 |
| Language | EN |
| Citations received | 2 |
| References cited | 15 |
Based on the particularities of assessment of quality management systems, we have developed an aggregate of dependencies between the singular indicators of process quality and their values, on a dimensionless scale. The application of the aggregate allows a quantitative quality assessment of processes to be obtained and takes into account a diversity of indicators and the significance of processes in the enterprise. The application of the said dependencies allows to assessment of quality indicators and interval assessment of quality indicators. Taking into account changes of process quality over time, coefficients are developed. We have proved the use of the tests of non-parametric characteristics for the analysis of the dynamic characteristics of process quality. The results of the application of the developed methods of qualitative quality assessment in the mechanical engineering enterprises are presented
Business · Evaluation methods · Management system · Operations management · Quality assessment · Quality management · Reliability engineering · Computer Science · Economic and Technological Systems Analysis · Engineering · Engineering and Environmental Studies · Engineering Diagnostics and Reliability · Materials Science
| Citations per year | 0.29 |
|---|---|
| Citation span | 2019 - 2020 (2) |
| Highly cited | No |