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Survey: More Expect M4.0 Tech Adoption to Increase

A new MLC survey reveals that rapid technology adoption continues as manufacturers deploy transformative technologies to reshape how work gets done.  

Famed computer scientist Alan Turing’s seminal 1950 paper, “Computing Machinery and Intelligence,” ends with the line, “We can only see a short distance ahead, but we can see plenty there that needs to be done.”

While Turing’s paper dealt specifically with artificial intelligence – something manufacturers have become quite familiar with in recent years – his closing sentiment could be applied to nearly any Manufacturing 4.0 technology. Futurists may have an idea of what may come 50 years from now, but our clearest views are of technology’s transformative nature for the remainder of this decade.

The MLC’s new Transformative Technologies in Manufacturing research survey provides such a view, revealing details and data that reflect current realities and the expectations for manufacturing two years out and in 2030.

While some see technology as a disruptor, the survey results point to consistent and sustained innovation that will transform how manufacturers operate, how people do their jobs, and how money will be invested to evolve the processes used to create things in the years ahead.

In fact, last year’s Transformative Technologies in Manufacturing survey revealed that the pandemic had accelerated information and operational technologies. Some 51% of respondents in 2021 said they expected to accelerate spending on IT and OT.

“A whopping 89% said they expect their company’s rate of adoption of M4.0 technologies to increase over the course of the next two years.”

 

If COVID-19 was the accelerant, the post-pandemic world is now fully ablaze. This year, a whopping 89% of respondents said they expect their company’s rate of adoption of M4.0 technologies to increase over the course of the next two years. In fact, not a single respondent expects that adoption will decelerate (Chart 1).

Answering the Why with Measured Concern

Technology for technologies sake may create some change, but to be truly transformative, a strategy must be created, and a desired future state must be identified. MLC members were asked to identify the three most important reasons to invest in transformative M4.0 technologies. Reducing costs and improving operational efficiency led the pack, with 83% of respondents identifying it among their most important reasons for pursing M4.0. This was followed in distant second by improving operational visibility and responsiveness with 61%. Other leading reasons for investing in M4.0 technologies include a strategic initiative to increase digitization (40%), creating a true, sustained competitive advantage (36%), and improving quality (30%) (Chart 2).

But new technologies also bring about some uncertainty. Respondents were asked if they agreed or disagreed with the statement “The accelerating pace at which new M4.0 technologies are emerging is causing us to fall behind in our efforts to evaluate and understand their business potential.” The results indicate a near even split among respondents’ sentiments. In fact, 48% disagree or strongly disagree with the statement, while 47% agree or strongly agree (Chart 3).

The Unstoppable Tide of Transformative Tech

The Transformative Technologies survey indicates that – among IT-related technologies – general data analytics and ERP software, cloud computing, manufacturing execution systems, and supply chain management (SCM) software are already in use at more than half of the respondents’ organizations.

Expected future investments in artificial intelligence are down from last year’s survey. In 2021, 22% of respondents expected to invest in artificial intelligence during 2022 or 2023. That number now sits at 14%. The decline in future investments tells that many who previously indicated they would invest in AI have now done so. Indeed, the percent of those who are investing in 2022 has risen to 45%, a 10-percentage point increase over the 2021 figure.

Leading the next wave of investments during the subsequent 12-24 months will be digital twin modeling and simulation software, augmented and virtual reality, high performance computing, and further investments in SCM software. What’s more, should the expected investments indicated in the survey come to fruition, within the next two years nearly all of the IT-related technologies mentioned in the survey will be in use at 50% or more of the companies.

Like in the 2021 survey, quantum computing and blockchain technology bring up the rear with 61% and 40% of respondents, respectively, reporting no plans to invest in the technology. This isn’t completely unexpected for these emerging technologies which have seen some incremental adoption – 11% say they have already invested in quantum computing and 17% say they have already invested in blockchain, up from 4% and 8% compared to last year (Chart 4).

“More than half of manufacturers think artificial intelligence and machine learning will be game-changers by 2030.”

 

Meanwhile, a quarter of respondents indicated that their company will invest in Industrial IoT within the next two years, bringing the total percentage of companies with an IIoT investment to 77% in 2024. 5G network investments are expected over the next two years at 17% of respondents’ companies, bringing total penetration to 58%. At present, 87% of companies indicate that enterprise communication platforms like Teams or Slack help their team members collaborate internally (Chart 5).

In a change from the 2021 survey, this year’s respondents indicate that current factory floor industrial robot investments have surpassed 3D printing and sensor usage on the production technology front. In 2022, 66% of respondents noted their company has invested in factory floor industrial robot investments, up from 52% in 2021. While 3D printing and sensor investments have increased since the 2021 survey, they now lag just behind industrial robots with 62% of respondents indicating that they have invested in the technology. On the horizon for production technologies investments, the survey indicates that OE/predictive maintenance technologies, machine learning, and plant floor simulation/modeling will see the biggest boost in the next 12-24 months. It is important to note that PLCs have reached a near ubiquitous level of usage. In fact, 86% of respondents note that their company has made an investment in PLCs/process control systems (Chart 6).

AI/ML Interest Rules the Day

It will come as no surprise that artificial intelligence and machine learning usage continues to grow. For AI, nearly 50% of respondents indicate that their company has implemented AI in their manufacturing operations either on a single-project basis (40%) or in all factories (9%). Meanwhile, only 9% of respondents indicate that they have made no progress adopting AI in their manufacturing operations (Chart 7).

Respondents cite diverse application areas for AI and ML technologies. About 75% indicate that they’re applying AI and ML to reduce costs and improve productivity and processes. Meanwhile, 60% indicate AI and ML use cases including preventative/predictive maintenance or quality improvement (Chart 8).

Beyond manufacturing operations, a significant number of respondents anticipate a rise in AI and ML system usage in non-manufacturing areas of the business. Nearly half indicate they plan to use the technology in their procurement process. Other non-manufacturing areas of anticipated growth include supply chain (44%), back-office functions (43%), and sustainability programs (42%). Should these deployments occur, it is anticipated that AI and ML systems will be used in 73% of respondents’ supply chain operations, 66% of customer facing systems, and 63% of back-office functions in the next two years (Chart 9).

Once implemented, AI and ML are expected to have a considerable impact on the jobs people currently do. Respondents expect it will enable better decision making, provide new insights that will drive greater efficiency, bring more value to existing/remaining jobs, and provide better/easier access to key production data (Chart 10). Other expected effects of implementing AI and ML are better forecasts, the elimination of some routine and repetitive jobs, and new insights that will drive innovation.

“83% of respondents say reducing costs and improving operational efficiency are their most important reasons for pursing M4.0 technologies”

 

While the positive outcomes of AI are clear, the effect its implementation will have on headcount is unclear according to respondents. The top response to this question is “Don’t Know,” with nearly 30% of respondents choosing this option. Meanwhile, a quarter of respondents indicate they will need more people or there will be no impact to headcount. Still, 45% of respondents expect at least a 1% reduction in their workforce headcount as a result of AI adoption (Chart 11).

The positive outlook for AI and ML continues to grow as well. While only 10% of respondents see AI and ML as a game-changer today, 53% expect it to be a game-changer by 2030. That 2030 figure tracks closely with the results of the 2021 survey in which 54% of respondents expected AI and ML to be a game-changer by 2030 (Chart 12).

The Emerging Manufacturing Metaverse

A new topic covered this year, the Manufacturing Metaverse, is perhaps the least understood. According to survey respondents, 38% are still trying to understand the technology and concept, 20% have no plans to adopt a Manufacturing Metaverse approach, and 15% don’t know how to respond to the question. Those three answer choices represent nearly three-quarters of our survey-takers’ responses. Of those sharing other insights, 8% have an exploratory pilot already in place and 18% are actively assessing the potential, but do not yet have deployment plans (Chart 13).

Over time, of course, it will be interesting to see how investments in the metaverse change and what trajectory it takes. Will the metaverse become ubiquitous like PLCs, or will it remain an elusive concept? Based on the adoption of other recent emerging technologies and the speed of innovation, a step forward in next year’s survey would not be unexpected.  M

Part 1: M4.0 Technology Adoption

1. Overwhelming Sentiment Supports Adoption Acceleration

Q: Do you expect you company’s rate of adoption of M4.0 technologies to increase or decrease over the next two years?

 

2. Tech Investments Lead to Operational Payoffs

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

 

3. New Technologies Cause Concern for Some, Not for Others

Q: Please indicate the extent to which you agree with the following statement: “The accelerating pace at which new M4.0 technologies are emerging is causing us to fall behind in our efforts to evaluate and understand their business potential.”

 

Part 2: Technology Investments

4. Supply Chain and Simulation Software Top IT Plans

Q: Please indicate your company’s investment posture for the following IT-related technologies (Check all that apply)

 

5. 5G, IIoT Implementations Continue

Q: Please indicate your company’s investment posture for the following communications and networking technologies (Check all that apply)

 

6. Factory Floor Robot Use Surpasses 3D Printing and Sensors; PLCs ubiquitous

Q: Please indicate your company’s investment posture for the following production technologies (Check all that apply)

 

Part 3: AI Coming into Its Own

7. AI Implementation Reaches Nearly 50%

Q: Where does your company stand today in adopting AI in manufacturing operations?

 

8. Various Ways to Apply AI and ML

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

 

9. Future AI/ML Plans Outweigh Current Implementations for Non-manufacturing Areas of the Organizations

Q: In what other areas of the organization are you already deploying AI and Machine Learning systems, or plan to deploy over the next two years? (Check one option for each area)

 

10. AI and ML Enhance Decision Making and Efficiency

Q: What impact do you expect the widespread use of AI and Machine Learning will have on the jobs people do and the way they work? (Check all that apply)

 

11. AI’s Impact on Headcount Unclear

Q: What percentage of your current workforce headcount do you expect may be replaced or removed by 2030 as a result of AI adoption? (Check one)

 

12. AI & ML’s Full Impact on the Horizon

Q: Overall, what is your current assessment of the potential of AI and Machine Learning, both today and by 2030? (Check one for each row)

Part 3:Virtual & Remote Work Technology

13. Manufacturing Metaverse Offers Room for Understanding, Adoption

Q: How would you describe your current posture to the concept of a Manufacturing Metaverse and the creation of a cohesive, virtual operational environment in the future? (Check one)

About the authors:

 

Jeff Puma is Content Director for the Manufacturing Leadership Council.

 

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

 

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