Bibliography
[1] Roosevelt Institute: Six Reasons Manufacturing is Central to the Economy. URL: rooseveltinstitute.org/six-reasons-manufacturing-central-economy/, Abrufdatum 02.04.2019.[2] McKinsey: Manufacturing the future. The next era of global growth and innovation. URL: www.mckinsey.com/~/media/McKinsey/Business%20Functions/Operations/Our%20Insights/The%20future%20of%20manufacturing/MGI_%20 Manufacturing_Full%20report_Nov%202012.ashx, Abrufdatum 02.04.2019.
[3] Ademujimi, T. T.; Brundage, M. P.; Prabhu, V. V.: A Review of Current Machine Learning Techniques Used in Manufacturing Diagnosis. In: Lödding, H.; Riedel, R.; Thoben, K.-D. u. a. (Hrsg): Advances in Production Management Systems. The Path to Intelligent, Collaborative and Sustainable Manufacturing. Cham 2017.
[4] Geissbauer, R.; Schrauf, S.; Berttram, P. u. a.: Digital Factories 2020: Shaping the future of manufacturing. URL: www.pwc.de/de/digitale-transformation/digital-factories-2020-shaping-the-future-of-manufacturing.pdf, Abrufdatum 02.04.2019.
[5] Gursch, H.; Wuttei, A.; Gangloff Theresa: Learning Systems for Manufacturing Management Support. SamI40 workshop at i-KNOW ’16. Graz 2016.
[6] Harding, J. A.; Shahbaz, M.; Srinivas u. a.: Data Mining in Manufacturing: A Review. Journal of Manufacturing Science and Engineering 128 (2006) 4, S. 969.
[7] Lödding, H.; Riedel, R.; Thoben, K.-D. u. a. (Hrsg): Advances in Production Management Systems. The Path to Intelligent, Collaborative and Sustainable Manufacturing. Cham 2017.
[8] McKinsey & Company: Smartening up with Artificial Intelligence (AI). What’s in it for Germany and its Industrial Sector?. Düsseldorf, Berlin, München 2017.
[9] McKinsey Global Institute: The Age of Analytics: Competing in a Data-Driven World. In collaboration with McKinsey Analytics. Düsseldorf, Berlin, München 2016.
[10] Tata Consultancy Services Ltd. (TCS): The Emerging Big Returns on Big Data. A TCS 2013 Global Trend Study. URL: https://ch.semweb.ch/_/wordpress/wp-con- tent/uploads/2013/08/TCS-Big-Data-Global-Trend-Study-2013.pdf, Abrufdatum 02.04.2019.
[11] Tata Consultancy Services Ltd. (TCS): Using Big Data for Machine Learning Analytics in Manufacturing 2014. URL: pdfs.semanticscholar.org/2f6a/0e8a8ce601b-d435aeaa140c7168177dc4820.pdf, Abrufdatum 02.04.2019.
[12] Wang, J.; Ma, Y.; Zhang, L. u. a.: Deep learning for smart manufacturing: Methods and applications. Journal of Manufacturing Systems 48 (2018), S. 144-156.
[13] World Economic Forum with A.T. Kearney: Technology and Innovation for the Future of Production: Accelerating Value Creation. Geneva 2017.
[14] Wuest, T.; Weimer, D.; Irgens, C. u. a.: Machine learning in manufacturing: advantages, challenges, and applications. Production & Manufacturing Research 4 (2016) 1, S. 23-45.
[15] Priya Singh: 10 Reasons why big data and analytics projects fail. URL: www.analyticsindiamag.com/10-reasons-big- data-analytics-projects-fail/, Abrufdatum 16.02.2019.
[16] Driscoll, M: Building data startups: Fast, big, and focused. URL: http://radar.oreilly.com/2011/08/building-data-startups.html, Abrufdatum 16.02.2019.
[17] von Enzberg, S; Waschbusch, L. M.: Datenanalyse. Big Data in der Produktion: große Daten = großes Potential. URL: www.industry-of-things.de/big-data-in-der-produktion-grosse-daten-grosses-potential-a-776716/, Abrufdatum 16.02.2019.
[18] Helden, J. von; Dorißen, J.: OPENMIND – On-demand production of entirely customised minimally invasive medical devices – H2020. Impact 2018 (2018) 10, S. 60-62.
[19] Deloitte: Predictive Maintenance. Taking pro-active measures based on advanced data analytics to predict and avoid machine failure 2017.URL: www2.deloitte.com/ content/dam/Deloitte/de/Documents/deloitte-analytics/Deloitte_Predictive-Maintenance_PositionPaper.pdf, Abrufdatum 02.04.2019.
[20] Deloitte: Predictive maintenance and the smart factory. URL: www2. deloitte.com/content/dam/Deloitte/us/Documents/process-and-operations/us-cons-predictive-maintenance.pdf Abrufdatum 02.04.2019.
[21] DIN: Arbeitsausschuss Künstliche Intelligenz gegründet. URL: www.din.de/de/din-und-seine-partner/presse/mitteilungen/arbeitsausschuss-kuenstliche-intelligenz-gegruendet-259904, Abrufdatum 27.02.2019.
[22] IEEE Standards Association: IEEE Launches Ethics Certification Program for Autonomous and Intelligent Systems. URL: standards.ieee.org/news/2018/ieee-launches-ecpais.html, Abrufdatum 27.02.2019.
[23] TÜV SÜD: TÜV SÜD und DFKI entwickeln „TÜV für Künstliche Intelligenz“. URL: www.tuev-sued.de/tuev-sued-konzern/presse/pressearchiv/tuv-sud-und-dfki-entwickeln-tuv-fur-kunstliche-intelligenz, Abrufdatum 27.02.2019.
[24] VDE Presse: KI: VDE|DKE und IEEE wollen Ethik in der Technik implementieren. URL: www.vde.com/de/presse/pressemitteilungen/vde-und-ieee-wollen-ethik-in-ki-implementieren, Abrufdatum 27.02.2019.
[25] Bundesministerium für Bildung und Forschung: Forschung und Innovation für die Menschen. Die Hightech-Strategie 2025. Berlin 2018.
