Adopting AI
Graphic: MakerVerse
A recent European report offers insights into manufacturing priorities for artificial intelligence as well as exploring the main implementation challenges and future impact
Artificial intelligence in manufacturing is not new, but it has now reached critical mass in awareness. Al has developed to the point where it helps with everything from predictive maintenance, to providing instant quotes within manufacturing platforms. With such a big opportunity, investment in AI is flourishing; according to data from Research & Markets, the Al in manufacturing market is expected to grow globally from US$3.2 billion in 2023 to $20.8 billion in 2028.
Germany-based MakerVerse, an online platform for sourcing industrial parts, recently conducted a European-wide survey on respondents working across a variety of manufacturing sectors, to assess the reality of how AI is being infused into their manufacturing operations.
A strategic priority
According to the survey, 34% of respondents said adopting Al into their manufacturing operations is important but not central. However, 24% answered that it is central, with 34% stating it has been considered but not a priority, and only 8% having not considered it.
The gap between hype and adoption
European manufacturers show a gap between what they wish to achieve and what they currently do with Al.
Most European manufacturers (43%) state they aren’t using AI at all yet, with only 5% stating they use it extensively.
Things are different in other parts of the world, however. In North America, 21% of manufacturing companies say they already use an AI solution. An additional 18.5% say they’ve established AI use cases that generate business value.
Popular Al applications
While there are plenty of applications for Al in manufacturing, some key outcomes are sought. Some of these, as reported by the MakerVerse survey, include:
- Quality control and inspection: Potential faults and imperfections can be automatically identified, saving time and effort. In one use case, machinery OEM reduced assembly process failures by 70%.
- Optimising production planning: Manufacturers strive for efficient production planning. AI-enabled production planning helps improve decision-making and adapt to rapidly changing situations in real-time.
- Maintenance: Machines can undergo predictive maintenance with dynamic scheduling to ensure maximum performance with minimum downtime.
- Supply chain management: Al can mitigate or prevent supply chain disruptions to help find alternative suppliers, onboard new suppliers, and more.
AI challenges
While the opportunities for AI in manufacturing are plentiful, so are the challenges. There is the difficulty of having the correct data, and cost is always a concern. In 2020, only 10% of companies said they received “significant financial benefits” from artificial intelligence. However, cost is no longer the major obstacle. Instead, the biggest challenge cited in the MakerVerse survey was lack of expertise (60%).
The high demand for Al is outpacing the available skills, showing a significant difference between the demand for the technology and the means to implement it.
High hopes for the future
European manufacturers may face challenges in implementing AI as freely as they’d like, but they’re optimistic about the future. They have high expectations: 79% of survey respondents said they see AI greatly helping efficiency in their manufacturing operations in the future.
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