AI Apps for Manufacturing Strategy Council
Oracle Modern Business Experience (MBX) is an Oracle conference that was held March 19-21 in Las Vegas. Unlike Oracle Open World in San Francisco which covers database, technology, and applications, MBX is solely focused on financial, supply chain, and human resource software applications that is needed to run global and local enterprises. At MBX, the AI Apps for Manufacturing Strategy Council was held at 9AM on Tuesday. Despite the early start, the room was packed by 9:30AM, and was standing room soon afterwards for nearly the entire session. A scan of attendees reveal that over 25 companies from diverse industries including:
Manufacturing Latching on to Industry 4.0
Industry 4.0, aka Smart Manufacturing, Advanced Manufacturing, or Intelligent Manufacturing, is defined in this 2013 document from Germany's National Academy of Science and Engineering. Fast forward to 2019, and that document might look quite different. Today’s version of Industry 4.0 might include these technologies that were either nascent or not even invented back in 2013: 1) A/R, V/R 2) Big Data 3) Mobile 4) Artificial Intelligence 5) Cloud 6) Computer Vision 7) 3D/4D Additive Printing 8) Digital Thread 9) Block Chain. At the AI Apps for Manufacturing Strategy Council, we surveyed the current level of Industry 4.0 technology adoption, and the results were mixed. Some already had implemented Industrial Internet of Things (IIoT) sensors, storage systems (Historian), some form of analytics (embedded or external), and some even implementing a mild form of “remote” or “lights out” manufacturing. But most are looking to build their next factory with Industry 4.0 as a key requirement.
AI and Machine Learning: The Next Focus for Industry 4.0
Whilst the adoption of components of Industry 4.0 is already underway, the adoption of AI and Machine Learning has not kept up with the adoption of PLC, MES, and IoT. Operational Technology (OT) data, the generic category name for IoT data, has been “easy” to collect. But much of that data is stuck in data siloes such as Historian or MES systems, where the data sits and rots. The path to extracting this data has not be a high priority, unmotivated by what these data can reveal. But AI and ML now is coming to the rescue. With these technologies, previous siloed OT data can be mined to reveal deep insights about manufacturing that were previously difficult.
Core Features in Oracle AI Apps for Manufacturing
Oracle AI Apps for Manufacturing is a machine learning powered analytics application tuned specifically for manufacturing. The application sits on top of a built-in datalake. This datalake was designed to connect to heterogeneous systems: both live Operational Technology (OT) and business centric Information Technology (IT). What makes Oracle’s application unique is that it is specifically tailored for manufacturing. So typical manufacturing data schema is already mapped into templates, making adopting AI for manufacturing much easier. Oracle AI Apps for Manufacturing has four major features that uniquely enables manufacturing organizations to monitor, control, and impact manufacturing.
Strawberry Jam Factory Live Demonstration
At the Strategy Council, a live demo of AI Apps for Manufacturing on a strawberry jam manufacturing was shown. Jam consistency is one of the main qualities consumers expect in a jam. But multiple factors impact the consistency of jam. In the demo, we showed that:
In a standing room only session, the presence of diverse types of companies and the varied depth of adoption of Industry 4.0 has shown that AI and Machine Learning is the next big thing for manufacturing. For more information on Oracle AI Apps for Manufacturing, please visit https://cloud.oracle.com/ai-apps-for-manufacturing