AI in production
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This document discusses how artificial intelligence (AI) is revolutionizing industry and manufacturing through cognitive technologies. It provides a brief history of AI development and outlines several current industrial applications of AI, including predictive maintenance and quality inspection using computer vision, acoustic analytics, and edge processing. Both the opportunities and challenges of adopting AI in industry are considered. The document advocates an approach of first gathering and visualizing manufacturing data, then infusing digitization efforts with cognitive analytics to gain insights and continuously advance systems.
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AI in production
- 1. AI in Production Revolution or Evolution? Peter Schleinitz, jens-peter.schleinitz@de.ibm.com #industrie4.0 #ibmaot
- 2. Why AI?
- 3. >1890 Tabulating 1960 Programmable >2010 AI/Cognitive
- 4. 80% of all data is not searchable 2018 20222013
- 5. 1x1 Millimeter 0,1 € x86 chip 90‘s PV powered > 100.000 transistors 124 Minicomputer www.research.ibm.com/5-in-5/
- 6. 1950 Turing test: measures machine intelligence 1957-1965 First attempts to simulate human problem solving (General Problem Solver) Ende 1960er First chatbot 1988 German Research Center for Artificial Intelligence (DFKI) is established Ab 1997 Annual Robocup 1956 The term artificial intelligence is introduced by John McCarthy First functioning AI program 1965-1975 Little progress is made, cutbacks are made to AI financing 1975-1985 Public awareness of AI research is created through expert system technologies (e.g., MYCIN) 1997 AI chess computer becomes world chess champion 2011 IBM develops Watson 2016 Google develops AlphaGo 1936 Turing machine: first machine to simulate any computer algorithm Further Internet 4.0 and Internet of Things innovations
- 7. 7
- 8. We’re entering the fourth revolution of industry and it is fully differentiated from any that came before it Line Production Electrification & Automation Miniaturization & Global Scale Cognitive Manufacturing Complexity Era 1783 1870 1960 2020 Water, steam, and conveyors; modern materials handling Assembly systems: Lighting, electricity and assembly lines Embedded systems: Semiconductors, computers, information technologies and increase in trade Cyber-physical systems: sensors, big data, predictive analytics, cognitive computing, robotics, 3D printing
- 9. Artificial Intelligence • Logical thinking • Making decisions in case of uncertainty • Learning • Planing • Communication in natural language • Understanding images • All these abilities to achieve a goal • Goal:“Machines that behave as if they have intelligence.“ John McCarthey (1955)
- 10. AI current status 10 • The systems implemented today are a form of narrow AI. • They can only do just one thing really good or better than humans. • … like recognizing objects, natural language understanding.
- 11. Learns from experience Uses what is learned to draw conclusions Identifies images Solves difficult problems Understands different languages Creates new perspectives AI SYSTEMS
- 12. Watson IoT / Interactive hospital rooms Consumer AI vs Enterprise AI
- 15. A human instructor can guide the robot as it learns the corresponding movements. Trained robots can collaborate with the human worker and hand him/her objects. They constantly improve their algorithm. As soon as the robot has finished learning, it can repeat the new movements independently and can automatically handle slight changes in its environment. Various sensors and cameras can provide information to computer-vision algorithms that ensure safe collaboration between worker and robot.
- 17. Edge Processing so the production doesn't stop when the internet doesn't work
- 18. Acoustic & Noise Analytics
- 19. Collecting parametric and event data from machines, SCADA, PLC, MES Production- or industry-specific analytical models, prediction of disturbances, energy consumption optimization Suggested solutions, optimal time for preventive measures, optimal settings Monitor Predict Optimize Improve production processes and equipment
- 20. Increased Production AI-powered root cause analysis can speed up the decision-making process on improvement measures. AnAI-based analysis of process information can predict locations of production disturbances. Production tool data can be linked and supplied to theAI machine so that optimized process conditions can be automatically determined.
- 22. 22 Industrie 4.0 made with The world's first manufacturer- independent Industrie 4.0 production plant http://smartfactory.de
- 24. Opportunities faster decision making better forecasting increased efficiency eliminate human error help humans perform better reduce costs/labor force
- 25. Challenges resistance and cultural change poses threat to labor intensive and management positions lacks empathy lacks moral compass increased competition rapid technological development training efforts data quality
- 26. Infuse with cognitiveAdvance to analytics & digitization Visualize the patterns • Use the platform to visualize your data in meaningful dashboards • Start to see current status and patterns • Instrument your equipment/assets to collect data • Gather already existing data • Gain insights from the data • produce analytical models to predict equipment failures and provide recommendations • Streamline business processes • Refine models with cognitive machine learning • Use speech, video, image to diagnose complex problems • Utilize other cognitive functions to improve engagements Gather the data Approach
Notas do Editor
- ---- Tabulating Systems...1880...Counting polulations in US...Hollerith Programmable: Here System 360..first large scale c0mputing power....around 1960...2nd most expensive project in the 60s....after Apollo... 5 system 360 needed for Apollo mission....Storage equals 2 mp3 music files..... Cognitive Era – Understand/Reason & Learn...future of IoT is cognitve Why cognitive: Explosion of data..strucutre (ERPO and unstrutured social, image – meanwhile Brontobyte...Billion times every grain of sand on earth..data volume in 10 years....you cannot deal with that in a programmable manner...no enough code and manpower to do so Cogitare – lat. denken Understand, reason and learn Everybody currently works on become digitail and industry 4.0. Fast ones will be winners...but what is if all is digital...we belive cognitive makes the difference It took 1000 years to get 500 million people to Christianty....internet 5 years ..it took 35 days to get angry birds to 500 million people... Why cognitive
- ---- Noice, pictures, video, Brontobyte = 1 billion times every corn of sand on the planet...in 10 years amount of data we produce per year Why cognitive: Explosion of data..strucutre (ERPO and unstrutured social, image – meanwhile Brontobyte...Billion times every grain of sand on earth..data volume in 10 years....you cannot deal with that in a programmable manner...no enough code and manpower to do so Cognitive systems are fundamentally different from what we have today Everybody currently works on become digitail and insustry 4.0. Fast ones will be winners...but what is if all is digital...we belive cognitive makes the difference Unstructured data — “dark data” — accounts for 80% of all data generated today.
- Es gibt immer leistungsstärkere Systeme, um die Informationen sinnvoll zu verarbeiten
- Auch mit der künstlichen Intelligenz haben wir uns schon seit sehr vielen Jahrten beschäftigt
- Den Begriff künstliche Intelligenz und entsprechende Lösungen gibt es schon sehr lange. Aber erst in der jüngsten Vergangenheit wurde der Einsatz immer verbreiteter. Das hat u.a. mit den fallenden Kosten für die benötigten Komponenten zu tun. Früher gab es bereits Extertensystem, regelbasiert, sehr aufwändig zu programmieren. Um die Programmierung zu vermeiden, werden heute Systeme eingesetzt, die die Erkenntnisse aus den Daten selbstständig gewinnen. Dazu sind natürlich viele Daten nötig.
- We’re entering the fourth revolution of industry, the Cognitive Manufacturing era, and it is fully differentiated from any that came before it Digital transformation of production processes create new opportunities to achieve levels of productivity and specialization not previously possible Benefits include: Higher automation and productivity of manufacturing process Increased quality and competitiveness across the value chain Ability to create new markets by establishing new services and business models
- Logisches Denken Treffen von Entscheidungen bei Unsicherheit Lernen Pl…
- Und damit kann künstliche Intelligenz in der Praxis erst sinnvoll eingesetzt warden Das sind einige Tätigkeiten, die KI-Systeme durchführen können
- Zu beachten sind dabei Unterschiede zwischen KI für Consumer und Unternehmen --- Ownership of Data Industry process skills Security & Trust
- Ein Anwendungsfall ist zB Industrieroboter. In diesem Fall lernen die Greifer im laufenden Betrieb und werden dabei – mit Unterstützung von Menschen – schlauer. Generelll kann man sagen, dass die Systeme durch Verwendung der vielen Daten schlauer und die Programmierungsaufwände reduziert werden.
- Mitsubishi Robot MELFA RV-7FLM 1. IBM Visual Insights We are using our Visual Insights product to perform automated quality inspection on the BMW spare parts. The inspection is done based on the pictures that the camera at the tip of the robot is taking. 2. IBM Predictive Maintenance Using our Predictive Maintenance solution, we are detecting subtle anomalies in the robot's operating behavior which may be early indicators for future breakdowns. For that purpose, we built up a model using high resolution servo current data representing normal behavior. Using our custom MQTT Gateway we are now forwarding actual operational data to the model for scoring. Subtle changes in the servo current patterns are then picked up and raised as alerts by Predictive Maintenance. 3. IBM Acoustic Insights We are using the Acoustic Insights solution to detect anomalies in the robot's operating noise. For that purpose, we are attaching a contact microphone to the robot base that's picking up its sound patterns. Using Acoustic Insights we already trained a model based on "normal" noise during operation. We are then applying the model to pick up abnormal sound patterns that we provoke on stage. 4. IBM Equipment Advisor Equipment Advisor is bringing the different pieces together. It provides a single entry point to access operational, historical and supporting information about the robot and even interact directly with it. In our case, the single entry point is a chatbot that allows access to these data points and functionality. In the background, Equipment Advisor is correlating real-time operational data with unstructured data from operating manuals and presents it in a curated and targeted way.
- Erkennen von Qualitätsproblemen in der Produktion oder im Betrieb über unstrukturierte Daten (Bilder, Töne, Vibrationen) und analytische Verfahren (Frühwarnsysteme)
- Goal Automated diagnosis of dishwasher spray arms in final test via acoustic analytics in the factory environment Challenges Unobservable in normal working state with door closed Need abnormal operation to test with door open in working state Time-consuming and complicated Value to client Enable new test function for normal working status with (door closed) that is unobservable in current status Ensure the high quality product with high accuracy of final test by overcoming the limitation of experience and physical status of test engineers Explore the new tecnologies that could be widely appied to other such as microwave oven, washing machine, range hoods, etc. and spanning the whole product lifecycle from production to after-sale service Schaffler winfmill bearing SMCF bearing at train
- Verbessern von Produktionsprozessen anhand wesentlicher Kennzahlen (OEE) mit Hilfe von Industriespezifischen Modellen für diskrete Fertigung und Prozessindustrie.
- Ein Beispiel für eine modulare Fabrik ist die SmartfactoryKL. Dort werden von den Modulen der beteiligten Unternehmen Visitenkartenhalter hergestellt. Ist bei der Hannover-Messe zu sehen und kann auch besucht werden. Roboter transportiert Werkstücke.
- Users of the Cognitive Factory get the status of the production process either by using the GUI or by chatting in English or German. Again, the PSB is used to integrate productiomn systems the cloud-based solution. Instructions and more Information can be found here (i).
- Bei Ihrem Einsatz ergeben sich eine Reihe von Vorteilen
- Allerdings gobt es auch eine ganze Reihe von Herausforderungen
- Wir empfehlen eine stufenweise Vorgehensweise