Manufacturing is Getting Smarter With AI
October 15, 2024
|
Manufacturing
October 15, 2024
|
Manufacturing
Artificial intelligence (AI) is proving a game-changer for manufacturing — offering better quality and increased efficiency while reducing costs and downtime. AI is transforming the industry by crunching massive amounts of data and driving value.
Here are just a few examples:
-
AI improves quality control. At global giant Siemens, AI helps predict — much earlier in the process than before — if a part will meet quality standards. This early fault assessment means the company performs 30 percent fewer X-ray tests, achieves a 100 percent quality rate, and reduces capital investment by $555,000.1
-
AI provides workflow insights. Auto technology supplier Faurecia uses an AI platform with cameras to help analyze workflow and workstations to improve and better balance the factory line.2
-
AI helps optimize operations. Johnson & Johnson deploys AI to sort massive amounts of data that help inform the process of developing medicine, restocking hospitals, and creating targeted treatments.3
-
At Hitachi, AI is used to improve maintenance and repair, manage safety and supply chain, and boost quality assurance.
With its data crunching expertise and speed, AI is already delivering big benefits to these early adopters, inspiring them to further invest in the technology and incorporate it into their long-term planning.
AI shows its Return on Investment (ROI)
Respondents to a survey of manufacturers said in 2024, they planned to invest an average of 44 percent of their technology budgets in AI, the National Association of Manufacturing (NAM) found.4
After deploying AI technology, manufacturers reported significant ROI, including:
-
72 percent reduced costs and improved operational efficiency;
-
51 percent improved operational visibility and responsiveness; and
-
41 percent improved process optimization and control.
What's more, manufacturers reporting “high” or “very high” levels of Generative AI expertise are scaling Gen AI more rapidly and reaching their goals to a greater degree.5
Data plays big role in AI
Over the past decade, most enterprises have collected a lot of data — from sensors, Industrial Internet of Things (IIoT) devices, and machine learning algorithms. In those early days, simply having the data could generate excitement. Now, manufacturers realize that data is of little use without insights.
AI can quickly deliver board-level insights — on production, quality, supply chain, maintenance, weather predictions, world events, customer insight and more — rather than waiting weeks for an analytics report.
Using publicly available and supplier data, generative AI could help identify and simulate potential disruptions or risks in the supply chain. Generative design can enable product development teams to produce multiple versions of a new 3D product design based on input constraints such as weight, strength, performance requirements, and material costs.6
Reap benefits with a strategic approach
To fully realize these benefits, manufacturing leaders should take a strategic approach by integrating the technology into their factories. Successful early adopters focus first on use cases with the best ROI and/or in areas where they’re experiencing challenges.
The top uses for AI in manufacturing are:7
-
Predictive maintenance
-
Predictive quality
-
Reducing scrap
-
Increasing yield and throughput
-
Demand and inventory forecasting
Similarly, manufacturers told the National Association of Manufactures (NAM) their top uses for AI are:
-
Manufacturing/production: 39 percent
-
Inventory management: 33 percent
-
Quality operations: 24 percent
-
R&D: 24 percent
Where to begin? Start small by identifying the factory, production line, and/or process where the people involved are the most open to technological change. When you’ve achieved early results, continue with a step-by-step approach with other plants, lines, processes, and people.
Training frontline workers is essential
Buy-in from fellow decision-makers is one of the keys to AI's success. But don’t forget about frontline workers. Eighty percent of leaders say they regularly use generative AI, and 44 percent say they have received training in AI to sharpen their skills and remain relevant. However, only one in five frontline workers regularly use generative AI; 86 percent say they need additional training, and only 14 percent have received such training.8
Three keys to implementing AI are:
-
Invest in regular AI training. Since AI is evolving so rapidly, this is not a one-and-done upskilling.
-
Prioritize building a responsible AI program. Employees want reassurance their leaders are taking an ethical approach to AI.
-
Create spaces for responsible experimentation. The more regularly employees use AI, the more clearly they’ll see the benefits, limitations, and risks.
Address security
More than one in three IT leaders feel ill-prepared to respond to an AI-powered cyber-attack. But there are reasons for optimism. Although 70 percent of CISOs fear generative AI will help open the door to a cyber-attack, they also point to the potential to use AI to bolster cyber defense.9
More than one in three CISOs already use AI for security applications; some six in 10 will likely use it in the next 12 months; and more than eight in 10 believe generative AI will alleviate security skills gaps and talent shortages.10
Understanding AI's potential
As AI develops its capabilities, its importance to manufacturing will likely grow. However, humans will remain key decision-makers in determining what problems AI should solve, what data AI should analyze, and how to optimize this data and reap the benefits of its insights.
1. AI’s revolutionary impact on industrial manufacturing, March 2023.
2. Utilizing Digital Tools for Lean Optimization, 2024.
3. Working Smarter: How Manufacturers Are Using Artificial Intelligence, 2024.
4. Survey: Manufacturers Leading the Charge in AI Adoption, June 2024.
5. Now Decides Next: Getting Real About Generative AI, April 2024.
6. The Generative AI Dossier, 2023.
7. Artificial Intelligence in Manufacturing: Real World Success Stories and Lessons Learned. January 2022.
8. AI at Work: What People Are Saying. June 2023.
9. Keeper Security states that cyber attacks are more sophisticated than ever. March 2024.
10. The CISO Report. 2023.
Read more
Artificial intelligence (AI) is proving a game-changer for manufacturing — offering better quality and increased efficiency while reducing costs and downtime. AI is transforming the industry by crunching massive amounts of data and driving value.
Here are just a few examples:
-
AI improves quality control. At global giant Siemens, AI helps predict — much earlier in the process than before — if a part will meet quality standards. This early fault assessment means the company performs 30 percent fewer X-ray tests, achieves a 100 percent quality rate, and reduces capital investment by $555,000.1
-
AI provides workflow insights. Auto technology supplier Faurecia uses an AI platform with cameras to help analyze workflow and workstations to improve and better balance the factory line.2
-
AI helps optimize operations. Johnson & Johnson deploys AI to sort massive amounts of data that help inform the process of developing medicine, restocking hospitals, and creating targeted treatments.3
-
At Hitachi, AI is used to improve maintenance and repair, manage safety and supply chain, and boost quality assurance.
With its data crunching expertise and speed, AI is already delivering big benefits to these early adopters, inspiring them to further invest in the technology and incorporate it into their long-term planning.
AI shows its Return on Investment (ROI)
Respondents to a survey of manufacturers said in 2024, they planned to invest an average of 44 percent of their technology budgets in AI, the National Association of Manufacturing (NAM) found.4
After deploying AI technology, manufacturers reported significant ROI, including:
-
72 percent reduced costs and improved operational efficiency;
-
51 percent improved operational visibility and responsiveness; and
-
41 percent improved process optimization and control.
What's more, manufacturers reporting “high” or “very high” levels of Generative AI expertise are scaling Gen AI more rapidly and reaching their goals to a greater degree.5
Data plays big role in AI
Over the past decade, most enterprises have collected a lot of data — from sensors, Industrial Internet of Things (IIoT) devices, and machine learning algorithms. In those early days, simply having the data could generate excitement. Now, manufacturers realize that data is of little use without insights.
AI can quickly deliver board-level insights — on production, quality, supply chain, maintenance, weather predictions, world events, customer insight and more — rather than waiting weeks for an analytics report.
Using publicly available and supplier data, generative AI could help identify and simulate potential disruptions or risks in the supply chain. Generative design can enable product development teams to produce multiple versions of a new 3D product design based on input constraints such as weight, strength, performance requirements, and material costs.6
Reap benefits with a strategic approach
To fully realize these benefits, manufacturing leaders should take a strategic approach by integrating the technology into their factories. Successful early adopters focus first on use cases with the best ROI and/or in areas where they’re experiencing challenges.
The top uses for AI in manufacturing are:7
-
Predictive maintenance
-
Predictive quality
-
Reducing scrap
-
Increasing yield and throughput
-
Demand and inventory forecasting
Similarly, manufacturers told the National Association of Manufactures (NAM) their top uses for AI are:
-
Manufacturing/production: 39 percent
-
Inventory management: 33 percent
-
Quality operations: 24 percent
-
R&D: 24 percent
Where to begin? Start small by identifying the factory, production line, and/or process where the people involved are the most open to technological change. When you’ve achieved early results, continue with a step-by-step approach with other plants, lines, processes, and people.
Training frontline workers is essential
Buy-in from fellow decision-makers is one of the keys to AI's success. But don’t forget about frontline workers. Eighty percent of leaders say they regularly use generative AI, and 44 percent say they have received training in AI to sharpen their skills and remain relevant. However, only one in five frontline workers regularly use generative AI; 86 percent say they need additional training, and only 14 percent have received such training.8
Three keys to implementing AI are:
-
Invest in regular AI training. Since AI is evolving so rapidly, this is not a one-and-done upskilling.
-
Prioritize building a responsible AI program. Employees want reassurance their leaders are taking an ethical approach to AI.
-
Create spaces for responsible experimentation. The more regularly employees use AI, the more clearly they’ll see the benefits, limitations, and risks.
Address security
More than one in three IT leaders feel ill-prepared to respond to an AI-powered cyber-attack. But there are reasons for optimism. Although 70 percent of CISOs fear generative AI will help open the door to a cyber-attack, they also point to the potential to use AI to bolster cyber defense.9
More than one in three CISOs already use AI for security applications; some six in 10 will likely use it in the next 12 months; and more than eight in 10 believe generative AI will alleviate security skills gaps and talent shortages.10
Understanding AI's potential
As AI develops its capabilities, its importance to manufacturing will likely grow. However, humans will remain key decision-makers in determining what problems AI should solve, what data AI should analyze, and how to optimize this data and reap the benefits of its insights.
1. AI’s revolutionary impact on industrial manufacturing, March 2023.
2. Utilizing Digital Tools for Lean Optimization, 2024.
3. Working Smarter: How Manufacturers Are Using Artificial Intelligence, 2024.
4. Survey: Manufacturers Leading the Charge in AI Adoption, June 2024.
5. Now Decides Next: Getting Real About Generative AI, April 2024.
6. The Generative AI Dossier, 2023.
7. Artificial Intelligence in Manufacturing: Real World Success Stories and Lessons Learned. January 2022.
8. AI at Work: What People Are Saying. June 2023.
9. Keeper Security states that cyber attacks are more sophisticated than ever. March 2024.
10. The CISO Report. 2023.
This is part 1
of a
3-part series on
Manufacturing Trends
PART 2
Collaboration Is Key to Manufacturers' Decarbonization Goals
September 06, 2024 Manufacturing
As businesses transition to a net-zero world, it's become increasingly clear that partnerships within and across all industries are key to addres…
PART 3
Diversity and Inclusion Emerge as a Manufacturing Labor Shortage Solution
September 24, 2024 Business Strategy, Manufacturing
There are about 500,000 unfilled manufacturing jobs in the United States, and the total is expected to reach 2.1 million by 2030, according to a rece…
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