Paul Calver, Chairman and CFO of The Data Analysis Bureau, examines how Artificial intelligence (AI) and machine learning (ML) are enhancing manufacturing operations across the board.
Manufacturers are resetting priorities around resilience, sustainability and operational excellence, and meeting the immediate challenges of securing supplies and recruiting workers.
AI and machine learning ML powered technologies are playing a vital part in accelerating manufacturers’ capabilities in these areas and achieving their goals to capture market share and remain globally competitive.
What is AI and ML? Artificial intelligence is the science and engineering of making intelligent machines, especially intelligent computer programs, and machine learning is a branch of AI which enables a machine to automatically learn, using data and algorithms, without explicitly programming, and can gradually improve its accuracy over time.
Manufacturers have been adopting physical technologies, such as robotics and automated machine tools, for many decades and have recently started to focus on additive manufacturing.
But as manufacturers become more aware of the power of data, many are turning to advanced data analytics, AI and ML, supported by IoT platforms, to leverage their key data assets. The adoption rate of these technologies is increasing rapidly.
A recent survey from The Manufacturer and IBM reported that 65 percent of manufacturing decision makers were working towards adoption, implementation or use of AI and ML.
This trend is set to accelerate with AI and ML in the manufacturing market expecting to grow at 57.2 percent CAGR over the next five years as manufacturers realise the low hanging opportunities enabled through data.
From our experience working closely with leading manufacturers across industry and as a successful recipient of an Innovate UK award to build a global predictive analytics service, we want to share with you a vision of AI and ML applications inside and outside the factory.
AI outside the factory
A typical supply chain involves many sub players, logistical interfaces and geographical locations. The supply chain is depicted (next page) as a linear flow but generally they are three dimensional complex networks. If at any time, especially if the supply chain is lean, there is a failure in any one node in the supply network, many other parts can fail.
Synchronising demand and supply are key to avoiding the supply chain whiplash we are currently experiencing. Also, as manufacturing becomes more sustainable and business models such as products as a service and reuse/remodel become more common, knowing the condition of your product in the field will become essential.
AI and ML has a key role to play in the supply chain where the technology can be used to predict future risks and behaviours so that risks can be mitigated, and asset and product utilisation maximised.
AI Inside the factory
Digital technologies now allow you to create flexible and intelligent manufacturing processes, not reliant on humans, that can rapidly adapt to changes and allow bespoke products to be made at scale. These are the principles of Industry 4.0.
The Internet of Things (IoT) is at the heart of this and provides the information platform for AI and ML to be applied as it connects the physical world, both inside and outside the factory, to the digital world through sensors and edge and cloud computing.
AI and ML can then, through analytics, deliver insight, predict the future and instigate real-time change often actuated through the IOT platform and factory enterprise systems.
However, with advances in APIs, natural language processing and the advent of federated learning, the data for AI and ML to learn does not just have to come from your factory or supply chain.
Information from your factory can be combined with open source and marketplace data, such as commodity prices, weather conditions, market behaviour, competitor actions and also from all your factories across the globe.
This ability multiplies the power of AI and ML at scale and brings a new level of machine intelligence across your whole organisation. This is known as strong AI. Manufacturers need to access to their insights quickly and overcome any barriers of time, cost resource and management to enable the use of this technology. Click here to download our free guide on AI inside and outside of the factory and find out how to build and scale AI.
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