The pace of product development is ever accelerating, fueled by factors such as the rapid development of Artificial Intelligence (AI).
The accumulation of high-quality data will be a key source of future business value. While machines and equipment are one part of a wider production system that creates value, software will play an increasing role in transforming data into digital services and solutions – enabling us to get more out of the equipment and production in a controlled way.
A massive amount of data is already available – waiting to be harnessed for value creation.
So far, manufacturing industries have been unable to fully benefit from this shift, because a huge amount of accumulating data needs to be processed, and the tools for this haven’t been available. But as these tools now exist, manufacturing companies will be able to take a quantum leap here and benefit from rapid AI development.
The new AI-based systems will automatically classify and synthetize data from databanks. Well, not fully automatically… Of course, you have to train them with your industry- and process-specific knowledge. But they won’t need a huge amount of information to be able to learn, because they can draw conclusions from one or two examples and then recognize the same patterns exactly.
I recently visited a paper mill which aims to be fully AI-controlled within two and a half years’ time.
Although the mill doesn’t have any well-developed automation solutions yet, this step change is a fully realistic and achievable target. It involves the development of advisory solutions based on dataflows and the increased autonomy of machines. As they’re starting from scratch, they can avoid common mistakes and benefit from current tools and technical development.
In future, technology providers may play an even greater role as “performance partners” for their customers.
AI applications are evolving rapidly, and the evaluation of dataflows will enable the creation of new kinds of ecosystem.
In turn, this will open the door for even greater value creation. Sharing is the key.
Partners in the value chain can exploit this data in developing their products and boosting their existing business by creating innovative new services. Success requires not only new technologies, but a customer-centric mindset for value to be created and captured in a new way. In future, we will see an ever-increasing number of data stream partnerships – from raw materials to the end consumed products – to further optimize the production and supply chain and ensure a fit-for-purpose end product.
The advantages of mill-wide optimization
Jun 4, 2020
The development of the Industrial Internet in the direction of Artificial Intelligence (AI) and autonomous mills will enable mill-wide optimization of processes. Good examples of this and good results can already be seen in the energy industry, which has been taking concrete steps toward this target with centralized remote control rooms and daily heat network optimization.
Predicting the future using data
Dec 12, 2019
Instead of typical production planning and control, data-driven applications incorporating artificial intelligence (AI) help us take a more holistic view of the entire chain of production by utilizing data from several sources. While Industrial Internet applications can be used to instantly optimize processes, they also allow us to predict what’s around the corner.
Towards new AI-based business models
Jun 19, 2019
High-quality data will be a key source of business value in the future. While machines and equipment are one part of a wider production system that creates value, software will have an increasing role in transforming data into digital services and solutions.