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Dark Factory / Lights Out Manufacturing
Industrial processes are in a constant state of change and in the 21st century, this transformation is primarily shaped by topics in the context of Industry 4.0 (machine learning, artificial intelligence, cloud/edge computing, and automation). In this context, the term "dark factory" has emerged, which is mainly used in German-speaking countries. In English-speaking countries, the term "lights out manufacturing" is more common instead.
Both terms refer to a factory or production without light. Conversely, this means that there are no people working in this factory/production who normally need lighting for their work. The basic idea here is that a fully automated production process works according to fixed programs and routines, which work without direct human intervention. However, the terms "dark factory" and "lights out manufacturing" are symbolic. For many automations or activities that are carried out by robots, lighting is still required for the optical sensors to function.
In many production facilities, individual sections are designed in the sense of a "dark factory", complete or near-complete "dark factories" are not widely used.
A better-known example of a near-complete "dark factory" is FANUC in Japan, where robots build more robots without light, air conditioning, or heating, 7 days a week, 24 hours a day. Without light, the factory can operate 600 hours at a time, with humans on site only for maintenance or emergencies.
Another example, of an almost complete "dark factory" from Europe is the factory of Philips in the Netherlands, where electric razors are produced and only the quality control at the end of the production is carried out by humans.
Several technology trends promote the development towards a production/factory without light. In particular, the steady and fast development ("law of accelerating return") in areas of robotics, machine learning and artificial intelligence coupled with the decreasing costs of robots and the global increase in personnel costs mean that and increasing number of factories operate without light in a figurative sense. The advantages of stabilized production, with constant costs and usually significantly fewer errors are obvious. However, people are still needed: for maintenance, for control or in the event of an incident. Even in the long run, specific activities will only be automated to a certain extent, respectively the personnel costs will be lower than the costs of a robot for the time being. Until a constant implementation of 100% profitable “dark factories” is achieved, further technological advances are necessary. But the trend to automate large parts of production will continue to grow.
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Resources:
Data Science Grundlagen - Grundlagen im Bereich Data Science (datenbanken-verstehen.de)
Data Science in Manufacturing: An Overview | R-bloggers [1]
Was ist Data Science? (bigdata-insider.de)
https://iiot-world.com/connected-industry/what-data-science-actually-means-to-manufacturing/.
Was ist das ARIMA-Modell? (bigdata-insider.de) [2]
Long short-term memory - Wikipedia [3]
Data Science Usage in Manufacturing Industry | Datatrained [4]
Thomas Barton, Christian Müller (2021). Data Science anwenden: Einführung, Anwendungen und Projekte. 1. Auflage. Springer Vieweg
Sandro Scheid, Stefanie Vogel (2021). Data Science: Grundlagen, Methoden und Modelle der Statistik. 1. Auflage. Carl Hanser Verlag
Uwe H. Kaufmann, Amy B.C. Tan (2021). Data Science für Einsteiger: Daten analysieren, interpretieren und richtige Entscheidungen treffen. Carl Hanser Verlag
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