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AI leaves an impact on Agile Production

By CIOReview | Wednesday, April 17, 2019

In lean production, the focus is on minimizing waste and maximizing value. This has enabled manufacturing operations to get rid of excess inventory, create a continuous production flow, simplify the manufacturing process, and minimize defects. As this process is integrated into more operations, the next step is to apply an agile production methodology. In Agile manufacturing, artificial intelligence can help manufacturing operations by focusing on customer-specific products. It is crucial to evaluate the principles of agile manufacturing before applying agile methodology to the operation. AI enables businesses to create and maintain their own in-house algorithms and intellectual property cost-effectively, which is cheaper and more adaptive to ever-changing equipment and market conditions.

Conventional solutions for enhancing classical line production attain their limits, as all techniques assume that the different production scenarios are known beforehand. This is not enough to cope with rising volatility. It won't be possible to think about everything in advance in the future. Agile production system integrates all subsystems, learning autonomously, responding dynamically to unknown requirements and identifying the best solution possible.  At the same time, multi-modal sensors measure additional environmental data such as movement and contact. They are enacted in plant technology, industrial robots, and vehicles, among others, and collect data relevant to production. On the basis of these data, driverless transport systems supply the necessary goods to the modular production stations. In addition, the data is used by collaborative, mobile, and autonomous robots to adapt their strategies of action.

Check out: Top Artificial Intelligence Companies ​

The manufacturing system holds unique learning algorithms using artificial intelligence (AI) and existing technical knowledge. They also promote learning from human workers ' activities and views with whom industrial robots work. The motors must be disassembled and prepared for reuse in an agile and automated process. Remanufacturing is of high economic relevance that illustrates the holistic, domain-overlapping, and smart production systems of the future.

Machines are becoming more intelligent and interconnected in this AI-powered industrial revolution. To generate meaningful insights, manufacturers use embedded machine intelligence to collect and analyze data. These are then used, among other things, to efficiently run equipment, optimize operation workflows, and supply chains. Thus, throughout the agile production cycle, AI leaves an indelible impact.    

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