Looking ahead: what’s next for AI in manufacturing?

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AI and manufacturing have been on an exciting journey together. It’s a combination that is fast changing the world of manufacturing: 92 percent of senior manufacturing executives believe that the ‘Smart Factory’ will empower their staff to work smarter and increase productivity.

How does AI benefit manufacturers?

Some of the biggest companies are already adopting AI. Why? A big reason is increased uptime and productivity through predictive maintenance. AI enables industrial technology to track its own performance and spot trends and looming problems that humans might miss. This gives the operator a better chance of planning critical downtime and avoiding surprises.

But what’s the next big thing? Let’s look to the immediate future, to what is on the horizon and a very real possibility for manufacturers.

Digital twinning

‘A digital twin is an evolving digital profile of the historical and current behaviour of a physical object or process that helps optimize business performance.’ – According to Deloitte.

Digital twinning will be effective in the manufacturing industry because it could replace computer-aided design (CAD). CAD is highly effective in computer-simulated environments and has shown some success in modelling complex environments, yet its limitations lay in the interactions between the components and the full lifecycle processes.

The power of a digital twin is in its ability to provide a real-time link between the digital and physical world of any given product or system. A digital twin is capable of providing more realistic measurements of unpredictability. The first steps in this direction have been taken by cloud-based building information modelling (BIM), within the AEC industry. It enables a manufacturer to make huge design and process changes ahead of real-life occurrences.

Predictive maintenance

Take a wind farm. You’re manufacturing the turbines that will stand in a wind farm for hundreds of years. With the help of a CAD design you might be able to ‘guesstimate’ the long-term wear, tear and stress that those turbines might encounter in different weather conditions. But a digital twin will use predictive machine learning to show the likely effects of varying environmental events, and what impact that will have on the machinery.

This will then affect future designs and real-time manufacturing changes. The really futuristic aspect will be the incredible increases in accuracy as the AI is ‘trained.’

Smart factories

An example of a digital twin in a smart factory setting would be to create a virtual replica of what is happening on the factory floor in (almost) real-time. Using thousands or even millions of sensors to capture real-time performance and data, artificial intelligence can assess (over a period of time) the performance of a process, machine or even a person. Cloud-based AI, such as those technologies offered by Microsoft Azure, have the flexibility and capacity to process this volume of data.

This would enable the user to uncover unacceptable trends in performance. Decision-making around changes and training will be based on data, not gut feeling. This will enhance productivity and profitability.

The uses of AI in future manufacturing technologies are varied. Contact us to discuss the possibilities and see how we can help you take the next steps towards the future.

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    10 examples of AI in manufacturing to inspire your smart factory

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    AI in manufacturing promises massive leaps forward in productivity, environmental friendliness and quality of life, but research shows that while 58 percent of manufacturers are actively interested, only 12 percent are implementing it.

    We’ve gathered 10 examples of AI at work in smart factories to bridge the gap between research and implementation, and to give you an idea of some of the ways you might use it in your own manufacturing.

    1. Quality checks

    Factories creating intricate products like microchips and circuit boards are making use of ‘machine vision’, which equips AI with incredibly high-resolution cameras. The technology is able to pick out minute details and defects far more reliably than the human eye. When integrated with a cloud-based data processing framework, defects are instantly flagged and a response is automatically coordinated.

    2. Maintenance

    Smart factories like those operated by LG are making use of Azure Machine Learning to detect and predict defects in their machinery before issues arise. This allows for predictive maintenance that can cut down on unexpected delays, which can cost tens of thousands of pounds.

    3. Faster, more reliable design

    AI is being used by companies like Airbus to create thousands of component designs in the time it takes to enter a few numbers into a computer. Using what’s called ‘generative design’, AI giant Autodesk is able to massively reduce the time it takes for manufacturers to test new ideas.

    4. Reduced environmental impact

    Siemens outfits its gas turbines with hundreds of sensors that feed into an AI-operated data processing system, which adjusts fuel valves in order to keep emissions as low as possible.

    5. Harnessing useful data

    Hitachi has been paying close attention to the productivity and output of its factories using AI. Previously unused data is continuously gathered and processed by their AI, unlocking insights that were too time-consuming to analyse in the past.

    6. Supply chain communication

    The aforementioned data can also be used to communicate with the links in the supply chain, keeping delays to a minimum as real-time updates and requests are instantly available. Fero Labs is a frontrunner in predictive communication using machine learning.

    7. Cutting waste

    Steel industry uses Fero Labs’ technology to cut down on ‘mill scaling’, which results in 3 percent of steel being lost. The AI was able to reduce this by 15 percent, saving millions of dollars in the process.

    8. Integration

    Cloud-based machine learning – like Azure’s Cognitive Services – is allowing manufacturers to streamline communication between their many branches. Data collected on one production line can be interpreted and shared with other branches to automate material provision, maintenance and other previously manual undertakings.

    9. Improved customer service

    Nokia is leading the charge in implementing AI in customer service, creating what it calls a ‘holistic, real-time view of the customer experience’. This allows them to prioritise issues and identify key customers and pain points.

    10. Post-production support

    Finnish elevator and escalator manufacturer KONE is using its ‘24/7 Connected Services’ to monitor how its products are used and to provide this information to its clients. This allows them not only to predict defects, but to show clients how their products are being used in practice.

    AI in manufacturing is reaching a wider and wider level of adoption, and for good reason. McKinsey predicts that ‘smart factories’ will drive $37 trillion in new value by 2025, giving rise to research projects like Reboot Finland IoT Factory, which involves organisations as diverse as Nokia and GE Healthcare. The technology is here and the research is ready – how will AI revolutionise your industry?

    Check out our whitepaper: “Industry 4.0: 7 steps to implement smart manufacturing”

    DOWNLOAD THE WHITEPAPER HERE

    The uses of AI in future manufacturing technologies are varied. Contact us to discuss the possibilities and see how we can help you take the next steps towards the future.

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      Nordcloud @ Smart Factory 2018 in Jyväskylä – 20-22.11.2018

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      Nordcloud at Smart Factory 2018 Jyväskylä

      Make sure to visit Nordcloud’s booth (C430) at the ‘Smart Factory 2018’ event, which is held in The Congress and Trade Fair Centre Jyväskylän Paviljonki, Jyväskylä between the 20-22.11.2018.

       

      Smart Factory 2018 is an event focused on how to utilise opportunities offered by digitalisation

      The event gathers together the themes of Industry 4.0 and the related technology, service and expertise offering. Smart Factory 2018 is targeted at all operators who are involved with changes associated with digital transformation in production activities and related new services and concepts. It strongly emphasizes the already known future-building themes, such as automation, machine vision, robotics, industrial internet and cybersecurity.

      You can register for the event here:

      Register to Smart Factory 2018

      See you there!

      Nordcloud at Smart Factory 2018

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