ML Journal

A growing number of manufacturing organizations have brought AI to the shop floor, and as usage grows, so do aspirations for its future impact, a new MLC survey reveals.   

There were two open-ended questions at the close of the Manufacturing Leadership Council’s 2023 Transformative Technologies survey. The first: Which single technology is currently having the most impact on your manufacturing operations?

Of the 171 respondents to this year’s survey, 19 cited AI or machine learning, the most commonly mentioned response, with four of those mentioning generative AI specifically. Not far behind were manufacturing execution systems, with 13 responses. Rounding out the pack were automation and data analytics with about 10 responses each. Honorable mentions went to cobots, vision systems and ERPs. Some respondents elaborated on the power of system consolidation and broader data access.

Far more consensus was seen, however, on the second open-ended question: What technology do you believe will have the most future impact on your manufacturing operations? For this question, 79 respondents mentioned AI or machine learning (or their cousin, predictive analytics), with robotics and digital twins also receiving multiple, if far fewer, mentions.

This tracks with the 40% of respondents who said they have adopted AI widely or at least on a pilot basis, with another 53% saying they were either researching use cases of developing a plan for implementation.

The MLC has been closely following the AI groundswell in manufacturing, with more use cases continuing to emerge. Most are currently using it for process improvement or predictive maintenance, and many plan to broaden its use in their supply chain, distribution, and sustainability efforts.

Read more below on the results of this survey:

Part 1: Strategy and Organization

While almost 90% of respondents to last year’s Transformative Technologies survey said they expected M4.0 technology adoption to increase, this year’s response shows a more measured approach to investment – possibly due to economic headwinds faced by many manufacturers.

1. Do you expect your company’s rate of M4.0 technology adoption to increase or decrease over the next two years? (Check one)

Many companies continue to take a fragmented approach to M4.0 – just 16% say they have an organization-wide technology roadmap. Far more either only have partial strategies or an informal approach to M4.0 deployment.

2. Which statement best describes the current status of your company’s M4.0 technology roadmap or strategy? (Check one)

The person in charge of M4.0 strategy is most frequently an operational VP, followed by the CIO/IT department or a collaborative effort between teams.

3. Who is responsible for leading and implementing your M4.0 strategy? (Check one)

At the end of the day, the bottom line rules – most respondents said that reducing costs and improving efficiency were the top reason for investing in M4.0.

4. What are the most important reasons your company invests in transformative M4.0 technologies? (Check top 3 reasons)

Part 2: Technology Investment Plans

Presently, the most common OT/IT investments are data analytics software, cloud computing, ERP planning software, and MES. Strongest near-term plans (12-24 months) are in AI and supply chain management software followed by edge computing and product lifecycle management. Additionally, about a third are considering digital twins and quantum computing for longer-range plans.

5. What are your company’s investment plans for the following OT/IT-related technologies? (Check one in each column)

For production technologies, process control systems are in the lead for current investments while nearly half say they have industrial robotics and/or vision systems in place. Other popular technologies are additive manufacturing and AGVs or mobile robots. In the near-term manufacturers indicate plans to implement machine learning and condition monitoring technologies.

6. What are your company’s investment plans for the following production technologies? (select one)

Part 3: Adoption of AI and Machine Learning

Drilling specifically into AI, over a third of respondents said they had implemented AI in pilots or on a single project (34%), with almost as many saying they were developing a plan for implementation (27%), a slight uptick compared to last year’s responses on AI usage. Very few say they have implemented it widely (6%), while even fewer said they had made no progress toward adopting AI (5%).

7. Where does your company stand today in adopting AI in manufacturing operations? (Check one)

The current key applications for AI usage are process improvement, preventive/predictive maintenance, productivity/cost reduction, and quality improvement.

8. What are the key application areas for AI and Machine Learning technologies in your manufacturing operations? (Check all that apply)

Outside of manufacturing operations, respondents say the greatest number of current AI use cases are in sales and customer intelligence followed by product design and development. Within the near term, manufacturers expect to broaden its use within distribution and logistics, supply chain, sustainability, and procurement.

9. In what other areas of the organization are you deploying AI and Machine Learning, or planning to deploy over the next two years? (Check one option for each area)

Asked specifically about generative AI technologies like ChatGPT or Bard, 44% indicated they are using it on a limited basis and 17% said they are using it regularly. 10% say they have no plans to use it at all.

10. What is your organization’s position on using generative AI like ChatGPT or Bard? (Check one)

Views on the impact of AI in manufacturing show that while many already see it as significant (36%), nearly half of respondents felt it will be a game-changer by the year 2030 (47%).

11. Overall, what is your current assessment of the potential of AI and Machine Learning, both today and by 2030? (Check one in each column)

Part 4: Impacts and Challenges of Transformative Technologies

When it comes to sharing data across functions of the enterprise, the digital thread is coming –only 23% of manufacturers have one currently, but 50% say they have plans to implement it in the future.

12. Has your company implemented a digital thread to share data generated by one or more of the M4.0 technologies you have adopted across multiple functions? (Check one)

The trend toward workplace flexibility, likely emerging out of necessity during the pandemic, hasn’t fully abated – 63% say they have invested in technology meant to allow for remote operations.

13. Has your company made technology investments with an eye toward allowing greater workforce flexibility (i.e. remote operations)?

When asked what their most pressing challenges were related to M4.0 adoption, the top responses were developing a cohesive strategy (42%), assessing the cost and benefit of deployments (37%), understanding and evaluating new technologies (31%), and migrating from or integrating with legacy systems (31%).   M

14. What are your top three challenges related to adopting and using M4.0 technologies? (Select top three)

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About the author:

Penelope Brown is Senior Content Director for the Manufacturing Leadership Council.

Survey development was led by the MLC editorial team with input from the MLC’s Board of Governors.