Schreiber, Markus ; Metternich, Joachim (2022)
Data Value Chains in Manufacturing: Data-based Process Transparency through Traceability and Process Mining.
In: Procedia CIRP, 107
doi: 10.1016/j.procir.2022.05.037
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Traceability systems are widely used in manufacturing processes, mainly for legal reasons. Based on their ability to generate and gather data along processes, they are an excellent base for creating performance indicators. Changing market demands lead to a rising amount of product variants and decreasing batch sizes causing higher complexity in production processes. In this context the growing availability of data along the value chain offers new opportunities. Based on a manufacturing data set, this paper presents a concept for building a data value chain consisting of a traceability system for data generation and acquisition, as well as a process mining application for the analysis of the generated process data. Firstly, to determine the traceability systems ability to generate relevant process data for manufacturing, secondly to demonstrate how this data contributes to data-based transparency through process mining analysis. Transparency is essential to enable data-based decisions as well as improvement measures in production. The results of the process mining analysis are then connected to the specific configurations of the traceability system in order to show the correlations and dependencies along the entire data value chain. The understanding of the data value chain from traceability system to process mining can empower companies to further benefit from their traceability system, by configuring it to deliver the needed data-based transparency and improvements in their production management.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Schreiber, Markus ; Metternich, Joachim |
| Art des Eintrags: | Bibliographie |
| Titel: | Data Value Chains in Manufacturing: Data-based Process Transparency through Traceability and Process Mining |
| Sprache: | Englisch |
| Publikationsjahr: | 2022 |
| Verlag: | Elsevier B.V. |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Procedia CIRP |
| Jahrgang/Volume einer Zeitschrift: | 107 |
| DOI: | 10.1016/j.procir.2022.05.037 |
| Kurzbeschreibung (Abstract): | Traceability systems are widely used in manufacturing processes, mainly for legal reasons. Based on their ability to generate and gather data along processes, they are an excellent base for creating performance indicators. Changing market demands lead to a rising amount of product variants and decreasing batch sizes causing higher complexity in production processes. In this context the growing availability of data along the value chain offers new opportunities. Based on a manufacturing data set, this paper presents a concept for building a data value chain consisting of a traceability system for data generation and acquisition, as well as a process mining application for the analysis of the generated process data. Firstly, to determine the traceability systems ability to generate relevant process data for manufacturing, secondly to demonstrate how this data contributes to data-based transparency through process mining analysis. Transparency is essential to enable data-based decisions as well as improvement measures in production. The results of the process mining analysis are then connected to the specific configurations of the traceability system in order to show the correlations and dependencies along the entire data value chain. The understanding of the data value chain from traceability system to process mining can empower companies to further benefit from their traceability system, by configuring it to deliver the needed data-based transparency and improvements in their production management. |
| Freie Schlagworte: | Data Value Chain, Data-based Process Transparency, Manufacturing Processes, Process Mining, Traceability System |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) > Management industrieller Produktion |
| Hinterlegungsdatum: | 07 Jun 2022 05:32 |
| Letzte Änderung: | 07 Jun 2022 05:32 |
| PPN: | |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
 |
Frage zum Eintrag |
Optionen (nur für Redakteure)
 |
Redaktionelle Details anzeigen |
Drucken
Impressum