AI The New Differentiator In Industry 4.0

AI The New Differentiator In Industry 4.0

AI is different from other technologies because it is capable of accumulating knowledge — of learning — by doing and adjusting its response based on past performance.

by Stuart Michie As companies move towards Industry 4.0, artificial intelligence (AI) has become a key differentiator in digital transformation str

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by Stuart Michie

As companies move towards Industry 4.0, artificial intelligence (AI) has become a key differentiator in digital transformation strategies.

Businesses are using AI to help make sense of this new data-laden world. The amount of data that is being generated is overwhelming and almost impossible to process manually. AI helps organisations process this information in order to derive value and insights from the data that is being generated.

According to Accenture, the emerging technology has an even greater capacity to increase productivity with the potential to boost profitability by 38% by 2035.

A significant percentage of the population is unaware that AI plays a central role in the everyday functions of most tech giants and many utilities. For example, AI algorithms drive the search capabilities of Google Assistant and Amazon’s intelligent voice assistant, Alexa which uses neural networks and powerful natural language processing to analyze the human voice and respond logically.

Microsoft uses AI to power chatbots in Skype and analyzes data in Office 365. The list goes on with Apple, IBM, Facebook, Uber and many others using AI to run their businesses and offer services to customers.

AI helps scale our expertise

The successful deployment of AI is likely to lead to better customer experiences while, at the same time, cutting the cost of doing business — in short, building a considerable competitive advantage for the companies successfully deploying it.

We believe the biggest opportunity for AI is to move from “automation” (rule-based systems) toward “autonomy” where sophisticated machines (robots, smart cars, smart grids) increasingly perform tasks by taking decisions with less human supervision required.

Rather than blindly following rules, these increasingly autonomous systems will learn from prior experience and human intervention to boost uptime, speed, yield, energy efficiency, and safety. We see this new, more autonomous AI helping our business in three main areas: scalability of expertise, improving product development and identify trends and new opportunities.

ABB is not only a technology provider, but increasingly we also possess extensive domain expertise in many of our customer segments (i.e. utilities, chemicals, mining, oil and gas, transportation, buildings, and so on). Today, this domain expertise is concentrated in our “human capital”, the accumulated experience of our global workforce.

We are continually looking to scale this expertise by codifying it in intelligent systems that are enabled by AI. This will take the form of smarter robots, smarter electrical systems, adaptive cybersecurity defences, and other ABB Ability™ solutions that incorporate AI technologies.

AI improves product development

Any value proposition that is put forward, at ABB, the outcome must be “what are the results”.

It needs to address whether my operations and processes are more efficient if it makes my factory run better, has my downtime been reduced. The emphasis needs to be based on the outcomes and AI might be a component of that particular solution, but we are looking for results that make sense for our customers and in this instance, AI  is key.

Digital connectivity provides us with information about how customers use our products specifically in terms of which features are used versus those that are not, which components may be more prone to failure under particular conditions, and the operating conditions in which our products are used. This data can be distilled into insights with machine learning to make these products better and more reliable.

Asset Performance Management (APM) is a key AI application for ABB because it has now enabled us to create models that previously didn’t exist and enabled us to predict, for example, the remaining expected lifetime of an asset. This allows scarce maintenance resources to be applied more effectively.

Another use case is in manufacturing as robotics are becoming increasingly intelligent and adaptable, essentially AI will drive what the robot does. We see that AI has been able to help the business to react in a much more proactive way to the issues that they may encounter or things they may need to change as part of their business operations resulting in a more agile and adaptable business to the fast-changing environment.

Spotting new trends and opportunities

AI is still a fairly new concept in the industrial sector, its future promises a new era of disruption and productivity, where human ingenuity is enhanced by speed and precision leading to better business decision making.

We see that AI has been able to help the business to react in a much more proactive way to the issues that they may encounter or things they may need to change as part of their business operations.

For us, with any value proposition that is put forward, the outcome must be “what are the results”. It needs to address whether my operations and processes are more efficient if it makes my factory run better, has my downtime been reduced. The emphasis needs to be based on the outcomes and AI might be a component of that particular solution, but we are looking for results that make sense for our customers.

AI is different from other technologies because it is capable of accumulating knowledge — of learning — by doing and adjusting its response based on past performance. ABB is active in the Asset Performance Management (APM) area, where we are building systems that enable a customer to predict how their assets are performing.

It is a prediction of important things like product or machine failures, to deterioration to allow the customer to able to prioritise maintenance work to be done. This process was previously done manually. We now use AI to create new performance models in less time.

Lastly, as we continue to  employ ecommerce tools to transact a growing proportion of our business online, we can start using AI to look for insights into the sales side of our business in order to look for new opportunities to create bundles, adapt prices, or measure the effectiveness of various incentives and investments in driving up sales.

  • Stuart Michie is ABB Ability Southern Africa Digital Leader

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