Manufacturers can’t afford to ignore AI any longer
Artificial intelligence (AI) is helping to transform businesses worldwide, and manufacturers that ignore it may find themselves left behind. AI offers manufacturers a range of benefits — including improved automation, better data analysis and advanced forecasting. Adopting an AI platform can make it much easier to get the most out of information many companies already collect.
These benefits can be transformative, and manufacturers that adopt AI soon may secure a crucial competitive advantage over those that don’t.
The manufacturing AI market is growing fast
Experts currently predict that AI in the manufacturing market will be worth nearly US$10bn by 2027. These experts estimate an average annual growth rate of around 24.2% between 2020 and 2027.
Current research on AI adoption by manufacturers backs up these forecasts. According to data and projections from IoT Analytics, the “AI adoption rate in industrial settings has increased from 19%-31% in slightly more than two years.”
In addition to the 31% of businesses that have currently adopted AI, another 39% are already testing or piloting the technology.
Most manufacturers have at least some hands-on experience with artificial intelligence, and adoption of the technology is accelerating fast. Along with other Industry 4.0 technologies, like IoT and big data analytics, AI is likely on track to become more common than not within the manufacturing industry — possibly within the decade.
Early adopters of a new technology often see the biggest returns on investment as it becomes more sophisticated. Experience with AI now may lay the foundation for new systems down the line — possibly putting a business in a better position to adopt future innovations and developments.
The benefits of AI in manufacturing
The biggest advantage of AI for manufacturers will likely be in the technology’s pattern-finding and analytic abilities. Modern businesses have access to more data than ever, especially if they’ve adopted modern collecting technologies like IoT devices.
Processing and leveraging this information can be difficult, however. The more companies have, the more conventional analysis techniques will struggle to extract available insights or make sense of things. At a certain point, it may become impossible or impractical for human data scientists to clean, analyse and remove usable stats with traditional tools.
Artificial intelligence can sift through massive quantities of data, identifying subtle correlations between variables that conventional analytic techniques may not be able to spot.
AI data analysis can support a wide variety of processes. AI-powered systems can streamline maintenance, optimise manufacturing processes and predict global sales numbers. These systems may draw from similar data sets but be used for completely different purposes across an organisation.
Businesses could use AI to streamline management of complex production units distributed across large geographical areas. A centralised AI management system would make it much easier to analyse these production units, integrate them and coordinate them on a day-to-day basis.
Another business may primarily use AI to help workers on the factory floor. Information from data sources like IoT devices can be fed into platforms that may detect subtle relationships between manufacturing parameters, product quality or sources of waste, like wait time.
Existing and emerging use cases for AI in manufacturing
Manufacturers that adopt AI can take advantage of various AI systems and platforms.
One popular example is predictive maintenance. Most manufacturers rely on some form of preventive care — a strategy that uses regular repairs and inspections to keep equipment running for as long as possible.
Some of these manufacturers have begun implementing remote maintenance strategies. They integrate data-collecting devices that can gather information on machines as they run. This enables remote monitoring of important equipment parameters, like current temperature, timing or vibration.
When one of these parameters moves outside a safe operating range, a remote monitoring system can automatically alert site technicians, allowing them to schedule maintenance or perform an emergency inspection.
Predictive maintenance goes one step further, using this real-time data to forecast equipment malfunctions. An AI algorithm, trained on historical operating information, can use subtle patterns in a machine’s performance to determine when to schedule upkeep.
For example, a pattern of vibrations and temperature fluctuations may signal the impending failure of a specific component. The AI maintenance algorithm can detect this pattern and alert technicians, allowing them to take corrective action.
Specific benefits of the technology can vary depending on the effectiveness of the underlying preventive maintenance program. Research has shown that adoptees of predictive maintenance can reduce overall maintenance costs by 5%-10%, increase equipment uptime by 10%-20% and reduce the time needed to plan upkeep by 20%-50%.
Predictive maintenance is an increasingly common use case for real-time data and shows how AI can be used to deliver significant cost savings and performance improvements.
Autonomous robots use AI to navigate
AI can also directly enable several automated factory technologies. Autonomous robots may use machine vision to help them navigate complex, changing environments — like warehouses or factories.
These robots take advantage of machine vision, a form of applied artificial intelligence that allows machines to “see.” The machine vision AI algorithm can continuously analyse information from video cameras mounted on the robot, breaking down visual information into objects like navigable floor space, obstacles and co-workers.
The machine can then use this information to navigate the floor on its own, steering around obstacles without human intervention.
Autonomous robots are already being used experimentally by major companies like Amazon. They support human warehouse workers by performing tasks like picking and packing orders. The company may soon adopt autonomous drones that use similar, AI-powered technology to move goods around warehouses faster or even complete deliveries by air.
How AI could continue to transform manufacturing
Artificial intelligence can be an extraordinarily valuable tool for manufacturers. The technology is used within the industry to extract insights from large datasets, improve predictive algorithms and enable new robotics innovations. AI will likely provide even more benefits in the future for the manufacturers that adopt it.
Businesses that adopt AI now can secure a competitive advantage, but waiting may have consequences. AI adoption in manufacturing has risen consistently over the past few years, and most manufacturers already have some level of experience with the technology.
Investing in AI sooner rather than later will help businesses stay ahead of their competitors and prepare for the future.