Analysis and Application of Selected Control Charts Suitable for Smart Manufacturing Processes
Nonparametric control charts (NPCC) have shown great potential for monitoring processes in conditions of smart manufacturing with complex structures, various monitored characteristics and the need to process big data. Practical applications of NPCCs are very rare. The main reasons for this situation...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/11/5410 |
| _version_ | 1827665664200933376 |
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| author | Tereza Smajdorová Darja Noskievičová |
| author_facet | Tereza Smajdorová Darja Noskievičová |
| author_sort | Tereza Smajdorová |
| collection | DOAJ |
| description | Nonparametric control charts (NPCC) have shown great potential for monitoring processes in conditions of smart manufacturing with complex structures, various monitored characteristics and the need to process big data. Practical applications of NPCCs are very rare. The main reasons for this situation are a deficiency in software support and a lack of simple but complete instructions for their application. The introduction of such manual, which is based on the authors’ own simulations of performance of wide spectrum of NPCCs in conditions of different violations of data prerequisites, leading to recommendations for the selection of the most effective NPCC in various practical situations, is the main goal of this paper. Compared to other similar studies, this approach covers a wider range of control charts, and it was applied to a wider spectrum of data assumption violations. As an integral part of these analyses, an examination of various control chart performance indicators such as ARL, MRL, <i>x</i><sub>5</sub> and <i>x</i><sub>95</sub> was performed using simulations to select the best of them. The designed methodology was verified using real data. |
| first_indexed | 2024-03-10T01:31:18Z |
| format | Article |
| id | doaj.art-0df068ac3821424b8362f4b3d0e49863 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T01:31:18Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-0df068ac3821424b8362f4b3d0e498632023-11-23T13:41:14ZengMDPI AGApplied Sciences2076-34172022-05-011211541010.3390/app12115410Analysis and Application of Selected Control Charts Suitable for Smart Manufacturing ProcessesTereza Smajdorová0Darja Noskievičová1Department of Quality Management, Faculty of Materials Science and Technology, VŠB-Technical University of Ostrava, 17. listopadu 2172/15, 708 00 Ostrava, Czech RepublicDepartment of Quality Management, Faculty of Materials Science and Technology, VŠB-Technical University of Ostrava, 17. listopadu 2172/15, 708 00 Ostrava, Czech RepublicNonparametric control charts (NPCC) have shown great potential for monitoring processes in conditions of smart manufacturing with complex structures, various monitored characteristics and the need to process big data. Practical applications of NPCCs are very rare. The main reasons for this situation are a deficiency in software support and a lack of simple but complete instructions for their application. The introduction of such manual, which is based on the authors’ own simulations of performance of wide spectrum of NPCCs in conditions of different violations of data prerequisites, leading to recommendations for the selection of the most effective NPCC in various practical situations, is the main goal of this paper. Compared to other similar studies, this approach covers a wider range of control charts, and it was applied to a wider spectrum of data assumption violations. As an integral part of these analyses, an examination of various control chart performance indicators such as ARL, MRL, <i>x</i><sub>5</sub> and <i>x</i><sub>95</sub> was performed using simulations to select the best of them. The designed methodology was verified using real data.https://www.mdpi.com/2076-3417/12/11/5410nonparametric control chartscontrol chart performance simulationscontrol chart performance indicatorsdata assumption violationssmart manufacturing |
| spellingShingle | Tereza Smajdorová Darja Noskievičová Analysis and Application of Selected Control Charts Suitable for Smart Manufacturing Processes Applied Sciences nonparametric control charts control chart performance simulations control chart performance indicators data assumption violations smart manufacturing |
| title | Analysis and Application of Selected Control Charts Suitable for Smart Manufacturing Processes |
| title_full | Analysis and Application of Selected Control Charts Suitable for Smart Manufacturing Processes |
| title_fullStr | Analysis and Application of Selected Control Charts Suitable for Smart Manufacturing Processes |
| title_full_unstemmed | Analysis and Application of Selected Control Charts Suitable for Smart Manufacturing Processes |
| title_short | Analysis and Application of Selected Control Charts Suitable for Smart Manufacturing Processes |
| title_sort | analysis and application of selected control charts suitable for smart manufacturing processes |
| topic | nonparametric control charts control chart performance simulations control chart performance indicators data assumption violations smart manufacturing |
| url | https://www.mdpi.com/2076-3417/12/11/5410 |
| work_keys_str_mv | AT terezasmajdorova analysisandapplicationofselectedcontrolchartssuitableforsmartmanufacturingprocesses AT darjanoskievicova analysisandapplicationofselectedcontrolchartssuitableforsmartmanufacturingprocesses |