Acquisition and use of life-cycle knowledge for product innovation

Theme	Industry 4.0, Artificial Intelligence
Project title	Acquisition and use of life-cycle knowledge for product innovation (LeWiPro)
Project duration	01.01.2013 – 30.06.2015
Download	Article in IPH's annual report 2013 (in German)
Press release	Data mining helps to create innovations

The analysis of lifecycle data has the potential to identify weaknesses of current products or production processes and to support the development of innovative products. The knowledge of the weaknesses of an existing product can be used to increase the quality of a product and to facilitate product manufacturing. But currently lifecycle date is often not systematically analysed. Therefore valuable knowledge that is hidden in the data stays undetected and cannot be used. In this research project an automated data analysis using predefined analysis models was developed. The use of predefined analysis models allows analysing lifecycle data systematically with low effort. In this way, lifecycle data is not only gathered but systematically used for a continuous improvement.

Publications about the project

Industry 4.0 Bentlage, A.; Gehler, F.; Kastenhuber, W.; Kind, C.; Langenberg, D.; Meng, L.: Wissenschatz Lebenszyklusdaten. In: Productivity Management, GITO Verlag, o. Jg. (2014), H.5/2014, S.39-43.

An analysis of lifecycle data offers the potential to identify product weaknesses and starting points for product innovations. The paper describes a concept to analyze lifecycle data using predefined analyses and interactive searches. Moreover, a concept to integrate the results of the data analysis into an existing software environment is presented.

data-mining, life-cycle-data, data analysis, knowledge akquisition

Industry 4.0, Artificial Intelligence Bentlage, A.; Zenker, M.: Data-Mining of lifecycle information. In: AST Symposium on Automated Systems and Technologies (15-16 October 2014), Konferenzband, Hrsg: Prof. Dr.-Ing. Ludger Overmeyer. PZH-Verlag, Garbsen 2014, S.15-20. ISBN: 978-3-944586-84-7

The systematic analysis of life cycle data provides the potential to identify weaknesses of current products and starting points for product innovations. This paper presents a tool for an automated analysis of life-cycle data and describes the necessary steps of a data analysis. In particular, the merging of data from different systems, the pre-processing of raw data, the data analysis and interpretation are explained. In this context, the pre-processing of free text is described. Moreover, two models for an automated analysis of life cycle data are introduced. Finally, the implementation of this concept into a software tool is described.

software tool, lifecycle, data analysis, data mining, knowledge deployment

www.lituro.de

Industry 4.0, Artificial Intelligence Bentlage, A.; Zenker, M.; Kind, C: Analyse von Lebenszyklusdaten. In: ERP Management, GITO Verlag, o. Jg. (2014), H.3, S.50-53.

An analysis of lifecycle data offers the potential to identify product weaknesses and starting points for product innovations. The paper describes a concept to analyze lifecycle data and declares which partial steps are necessary to collect, preprocess and analyze the data.

software tool, lifecycle, data analysis, data mining, knowledge deployment

Industry 4.0, Artificial Intelligence Schirrmacher, S.; Zenker, M.: Wissen, was gefragt ist: Wissensmanagement im Produktlebenszyklus. In: phi – Produktionstechnik Hannover informiert, PZH-Verlag, 14. Jg. (2013), H. 2, S. 8-9.

Innovative developments often result from the knowledge generated in the lifecycle of existing products. Following this approach in a current research project engineers of IPH develop methods and tools for the acquisition and utilization of knowledge from the entire product lifecycle.

product lifecycle, knowledge management

Acquisition and use of life-cycle knowledge for product innovation

Publications about the project

Industry 4.0 Bentlage, A.; Gehler, F.; Kastenhuber, W.; Kind, C.; Langenberg, D.; Meng, L.: Wissenschatz Lebenszyklusdaten. In: Productivity Management, GITO Verlag, o. Jg. (2014), H.5/2014, S.39-43.

Industry 4.0, Artificial Intelligence Bentlage, A.; Zenker, M.: Data-Mining of lifecycle information. In: AST Symposium on Automated Systems and Technologies (15-16 October 2014), Konferenzband, Hrsg: Prof. Dr.-Ing. Ludger Overmeyer. PZH-Verlag, Garbsen 2014, S.15-20. ISBN: 978-3-944586-84-7

Industry 4.0, Artificial Intelligence Bentlage, A.; Zenker, M.; Kind, C: Analyse von Lebenszyklusdaten. In: ERP Management, GITO Verlag, o. Jg. (2014), H.3, S.50-53.

Industry 4.0, Artificial Intelligence Schirrmacher, S.; Zenker, M.: Wissen, was gefragt ist: Wissensmanagement im Produktlebenszyklus. In: phi – Produktionstechnik Hannover informiert, PZH-Verlag, 14. Jg. (2013), H. 2, S. 8-9.

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