Longard, Lukas ; Schiborr, Lara ; Metternich, Joachim (2022)
Potentials and obstacles of the use of data mining in problem-solving processes.
In: Procedia CIRP, 107
doi: 10.1016/j.procir.2022.04.041
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Systematic problem-solving is an important component of sustainable and continuous improvement in production. Recent developments such as decreasing product lifecycles on the one hand and increasing product individualization and globalization on the other hand, impose new challenges to production systems. Due to the rising complexity, the analysis of a problem with conventional methods is becoming more and more difficult. One way to overcome these obstacles is to use the vast amount of data that is being gathered in manufacturing processes. Through data-based methods, product quality as well as the quality of decisions can be improved by revealing correlations and potentially underlying causalities that would have otherwise remained hidden to the observer. Previous research has revealed the need to investigate use cases of data-based support in systematic problem-solving processes. The goal of this publication is to review such use cases and to analyze the potentials and obstacles for their application. For this purpose, a systematic literature review was conducted. The relevant publications were analyzed in regards of the data-based methods used as well as the objectives pursued. Moreover, an overview of their application in each individual step of the problem-solving process is given in this paper.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Longard, Lukas ; Schiborr, Lara ; Metternich, Joachim |
| Art des Eintrags: | Bibliographie |
| Titel: | Potentials and obstacles of the use of data mining in problem-solving processes |
| Sprache: | Englisch |
| Publikationsjahr: | 26 Mai 2022 |
| Verlag: | Elsevier B.V. |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Procedia CIRP |
| Jahrgang/Volume einer Zeitschrift: | 107 |
| DOI: | 10.1016/j.procir.2022.04.041 |
| Kurzbeschreibung (Abstract): | Systematic problem-solving is an important component of sustainable and continuous improvement in production. Recent developments such as decreasing product lifecycles on the one hand and increasing product individualization and globalization on the other hand, impose new challenges to production systems. Due to the rising complexity, the analysis of a problem with conventional methods is becoming more and more difficult. One way to overcome these obstacles is to use the vast amount of data that is being gathered in manufacturing processes. Through data-based methods, product quality as well as the quality of decisions can be improved by revealing correlations and potentially underlying causalities that would have otherwise remained hidden to the observer. Previous research has revealed the need to investigate use cases of data-based support in systematic problem-solving processes. The goal of this publication is to review such use cases and to analyze the potentials and obstacles for their application. For this purpose, a systematic literature review was conducted. The relevant publications were analyzed in regards of the data-based methods used as well as the objectives pursued. Moreover, an overview of their application in each individual step of the problem-solving process is given in this paper. |
| Freie Schlagworte: | Data based production, data mining, systematic problem-solving process |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) |
| Hinterlegungsdatum: | 29 Jul 2022 06:52 |
| Letzte Änderung: | 06 Okt 2022 08:36 |
| PPN: | 497711745 |
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