Towards a Reference Model for Knowledge Driven Data Provision Processes

[1]  Frank Neumann Analyzing and Modeling Interdisciplinary Product Development , 2015 .

[2]  Manuel Filipe Santos,et al.  KDD, SEMMA and CRISP-DM: a parallel overview , 2008, IADIS European Conf. Data Mining.

[3]  Liu Lu,et al.  Quality Analytics in a Big Data supply chain: Commodity data analytics for quality engineering , 2016, 2016 IEEE Region 10 Conference (TENCON).

[4]  Sarabjot Singh Anand,et al.  Decision support using data mining , 1998 .

[5]  Mingguang Zheng,et al.  Mechanism design of data management system for nuclear power , 2019 .

[6]  Rainer Stark,et al.  Data-driven business model a methodology to develop smart services , 2017, 2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC).

[7]  Lukasz A. Kurgan,et al.  A survey of Knowledge Discovery and Data Mining process models , 2006, The Knowledge Engineering Review.

[8]  Ralph Kimball,et al.  The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling , 2013 .

[9]  Hajo Wiemer,et al.  Data Mining Methodology for Engineering Applications (DMME)—A Holistic Extension to the CRISP-DM Model , 2019, Applied Sciences.

[10]  Sándor Vajna,et al.  Integrated Design Engineering , 2014 .

[11]  El-Sayed M. El-Alfy,et al.  Intrusion detection taxonomy and data preprocessing mechanisms , 2018, J. Intell. Fuzzy Syst..

[12]  N. Madenas,et al.  Improving root cause analysis through the integration of PLM systems with cross supply chain maintenance data , 2015 .

[13]  M. Lynne Markus,et al.  Toward A Theory of Knowledge Reuse : Types of Knowledge Reuse Situations and Factors in Reuse Success , 2022 .

[14]  Steffen Ihlenfeldt,et al.  DMME: Data mining methodology for engineering applications – a holistic extension to the CRISP-DM model , 2019, Procedia CIRP.

[15]  Daniela Fogli,et al.  A Survey on Digital Twin: Definitions, Characteristics, Applications, and Design Implications , 2019, IEEE Access.

[16]  Dimitris Kiritsis,et al.  Closed-loop PLM , 2007 .

[17]  Wilhelm Frederik van der Vegte,et al.  Towards an Approach Integrating Various Levels of Data Analytics to Exploit Product-Usage Information in Product Development , 2019, Proceedings of the Design Society: International Conference on Engineering Design.

[18]  Klaus-Dieter Thoben,et al.  Information and Data Provision of Operational Data for the Improvement of Product Development , 2015, PLM.

[19]  Shang-Hsien Hsieh,et al.  A concept-based information retrieval approach for engineering domain-specific technical documents , 2012, Adv. Eng. Informatics.

[20]  Andreas Holzinger,et al.  Importance of medical data preprocessing in predictive modeling and risk factor discovery for the frailty syndrome , 2019, BMC Medical Informatics and Decision Making.

[21]  Rafael Batres,et al.  Ontology-based similarity for product information retrieval , 2014, Comput. Ind..

[22]  Milton Borsato,et al.  Bridging the gap between product lifecycle management and sustainability in manufacturing through ontology building , 2014, Comput. Ind..

[23]  Francisco Herrera,et al.  A survey on data preprocessing for data stream mining: Current status and future directions , 2017, Neurocomputing.

[24]  Robert Schmitt,et al.  A Framework for the Capture and Analysis of Product Usage Data for Continuous Product Improvement , 2019, Journal of Manufacturing Science and Engineering.

[25]  Rainer Stark,et al.  Engineering activities — considering value creation from a holistic perspective , 2017, 2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC).

[26]  M. Porter,et al.  How Smart, Connected Products Are Transforming Competition , 2014 .

[27]  R. Ramadan,et al.  IoT Data Provenance Implementation Challenges , 2017, ANT/SEIT.