In IIoT-based smart factory setups, AI-enabled digital assistants are linked into all assets and all data. It is this intelligence that takes the IIoT beyond data collection to predictions and decisions
The smart factory vision is gaining momentum, with advanced manufacturing companies increasingly turning to end-to-end digitization, ensuring viability and sustainability in the “new now.” Moreover, the pandemic introduced a range of new challenges, including full and partial lockdowns, social distancing on the production floor, employee absences, remote working, supply chain disruptions and demand instability.
McKinsey’s 2020 Cloud in Discrete Manufacturing Industries survey showed that the total potential value of cloud solutions for the industry until 2025 is $700 billion, of which 30 percent ($210 billion) is within manufacturing and an additional 10 percent ($70 billion) in supply chain. Furthermore, a McKinsey Global Institute analysis also shows the importance of early adoption, concluding that AI “front-runners”—those who adopt new AI tech within its first seven years—can “anticipate a cumulative 122 percent cash flow change.”
This compares to 10 percent for slow adopters.
Manufacturers who adopted Industrial Internet of Things (IIoT) technology prior to the pandemic have already reaped rewards through their ability to manage the unprecedented global disruption.
While digitization in and of itself is positive, data workflows, which include collecting and storing the data, are only part of the solution because information on its own is of limited use.
It is what you do with information that counts, and therefore AI can complement data workflows with automatic decision workflows to create significant business value.
In IIoT-based smart factory set-ups, AI-enabled digital assistants are constantly linked into all assets and all data. It is this intelligence that takes the IIoT beyond data collection to predictions and decisions because AI software can react to what is going on, either taking action autonomously or giving prompts to employees to let them know something needs to be done.
For example, production-scheduling software can take into account all factory variables and KPIs to automatically create the best possible production plans.
Once the production plan is in action, AI-based technology can be fully integrated with shop-floor systems to keep a constant eye on every element of production in real time, allowing both the AI software and human managers to ensure that production is happening in line with the plan.
The schedule can also be adjusted as needed in response to or in anticipation of unexpected events, such as misplaced tools or broken-down machines.
Benefits are not confined to planning and tracking operations. For example, by using sensor-driven data of available raw material, AI can predict material failure or shortage and minimize material waste by ensuring that workers always select the best material for the job at hand, given the multitude of variables and constraints inherent to dynamic production and inventory environments.
Plataine, an AI-based solutions provider for advanced manufacturers, is based in Israel, which is rapidly becoming an international hub for Industry 4.0 innovations.
The deep historical focus on AI of the Israeli tech ecosystem, and the agile response of its companies to the COVID-19 crisis, has seen the country attract record levels of investment recently across firms dedicated to a wide range of industrial use cases, including manufacturing process optimization, machine uptime, inventory reductions and supply-chain management.
The immense potential projected by McKinsey is now a reality for many manufacturers.
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