How Omron’s adaptive algorithms create new ways to optimise production

Artificial Intelligence presents an opportunity to increase Overall Equipment Effectiveness (OEE) which results in combined reduced costs with increased productivityArtificial Intelligence (AI) in the engineering sector is gaining momentum. This is owing to increased processing power and the availability of increasing volumes of data. Omron offers innovative solutions to automate factories.

In the case of the advancements required for Industry 4.0, such as predictive maintenance and networked efficient production, the use of adaptive algorithms offers enormous potential.

Many manufacturing companies realise AI presents an opportunity to increase Overall Equipment Effectiveness (OEE). This results in combined reduced costs with increased productivity.

Many of the AI solutions advertised on the market, which are often cloud-based, have significant requirements in terms of infrastructure and IT. These solutions also work with an overwhelming amount of data that is laborious and time-consuming to prepare and process. The question of added value often remains somewhat murky for providers, who cannot determine whether and how the investment in AI will provide a return. 

System designs for the engineering sector are generally both complex and unique. As a result, it is not a matter of simply transferring learnt experiences from other machinery as may be the case for mass-produced products in the consumer goods industry. The majority of systems are generally so complex that it is not possible to map out the entire system mathematically and maintain costs at an acceptable level. It is Omron's view that a ‘black-box approach’ is more common. The available data in these systems for typical AI algorithms is underdetermined. A reliable operation can only be confirmed through testing, optimisation and over-dimensioning. 

How to design and integrate AI

According to Omron, algorithms integrated in the machine’s control system create the framework for real-time optimisation, at the machine, for the machine. In contrast to edge computing, where individual manufacturing lines or sites are analysed using limited processing power, the AI controller used by Omron, features adaptive intelligence. It is closer to the action and learns to distinguish normal patterns from abnormal ones for the individual machine.

The AI controller integrated in the Sysmac platform, which is a complete solution for factory automation, features modules for control, motion and robotics, image processing and machine safety. These are primarily used in the manufacturing process at the points where the customer is experiencing the greatest efficiency problems such as bottlenecks. The processes gain intelligence based on previous findings and improvements that have been made and subsequently drive holistic optimisation of the entire manufacturing process. 


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