Beyond the Hype- Artificial Intelligence in Manufacturing. Erik Johnson, chief architect, Epicor Software.


Artificial intelligence (Al) seems to have travelled from sci-fi fantasy to board room hyperbole at warp speed, in no time at all.

Whilst it's not surprising that a future working environment with fully autonomous thinking and acting robots is a topic that captures imaginations, trying to work out the relevance of Al to today's manufacturing environment is somewhat less clear.

Here, we ask Erik Johnson, chief architect, Epicor Software, to help debunk some common myths around Al and put the hyperbole into some context for manufacturers trying to work out its relevance today.

Debunking the myths

Al is already an over-hyped technology within business. Its important manufacturers understand what it isn't before coming to a decision about what it is and how it should be used in a manufacturing context. Predictive analytics and machine learning are often confused with Al and whilst they have similar capabilities, they don't work in the same way.

Where predictive analytics uses historical data to predict the future, Al goes further, analysing more variables to provide more detailed conclusions.

Similarly, in relation to machine learning, Al is the broader term for something that constitutes 'smart' systems and machine learning is a subset of approaches where machines use data to learn and reason and get better over time.

Quantifying the benefits

When it comes to understanding the practical applications of Al, one quantifiable way Al is being used in manufacturing is via robotics. The same technology being used to help self-driving vehicles navigate, or keeping a Roomba[TM] vacuum from running over your cat, is making its way to the shop floor. Robots aren't new to manufacturing, but they have traditionally been very expensive to deploy. Some models required magnets embedded in the floor to serve as tracks for guiding the machines, whose routes and tasks all had to be pre-programmed. This means any changes to the plant layout, an expected pallet of material in a corridor, or new manufacturing processes required reprogramming the robotic staff.

But companies like Adept changed the game with robots that sense the plant layout automatically. These robots can walk the plant to discover all of the areas. Once a map has been created, the human staff can provide the names of important areas, which then makes it easy to instruct a robot to fetch material from one place and deliver it to another. If a new obstacle is discovered--like an unexpected pallet...

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