- By Dr. Tsuyoshi “Ted” Abe
- February 23, 2022
- Yokogawa
- Feature
Summary
Survey results indicate that manufacturers around the world understand the value of digital transformation, seeing it as a critical tool for sustainability, process optimization and more.
The worlds of manufacturing, and especially process manufacturing, are evolving. In some areas this results in rapid change and in others it is more measured, but the direction is deliberate and toward specific goals. For all the variety of companies and industries, the goals are surprisingly similar: there is a determined march toward industrial autonomy. This is not an end in itself, but instead provides tools to support a variety of goals, including environmental sustainability, improved deployments of robotics, and optimization of processes and supply chains.
This complex but exciting message is drawn from Yokogawa’s Surveys on Industrial Autonomy, conducted in 2020 and again in 2021. The results indicate that companies are moving in this direction, and their efforts are accelerating. To see how this is happening, we can look at highlights from the most recent results and consider the previous data.
What is industrial autonomy?
But before we dig into the results, we should answer the question, what is industrial autonomy? How is it used in process manufacturing, and what benefits can it deliver?
Autonomy suggests that an individual, group, or thing has self-determination. So how does this apply to a chemical processing plant or other type of manufacturer? Should a process be able to run itself without human intervention?
Industrial automation, as we have seen it used in the last five to ten years, may already appear highly autonomous in the sense that a well-automated process can indeed run itself in a very stable manner. Countless plants around the world do this every day, but there are differences between automation and autonomy, and the benefits achievable with increased autonomy are why so many industries are advancing towards it.
As a hypothetical example, a chemical manufacturing process calls for a reaction where feedstocks are mixed, and heat is then applied. The amount of heat is specified per volume of feedstocks, and this value is programmed into the automation system based on the ratio specified by the process engineer. This can be a very stable and well controlled process, but it might also be wasteful if the process engineer decided to push the heat rate slightly higher than necessary to “be on the safe side.” An engineer examining process data may figure this out if there is opportunity to perform the necessary analysis, but the process might run at less than peak efficiency for years before anyone recognizes the waste.
An autonomous plant uses artificial intelligence (AI) to perform this kind of analysis continuously across every aspect of the process. As it compiles data, its algorithms evaluate energy consumption and will recognize that this reaction can work just as well with less heat applied. It will turn down the input until it determines the lowest practical level based on product quality analysis. It optimizes energy consumption in this case and repeats this kind of analysis throughout the plant. It can do this in dozens of places within the process to optimize energy consumption, feedstock utilization, and product quality. The same concepts can be applied to asset management, reliability, maintenance, and even supply chain interaction.
An autonomous system can suggest changes to operators or management, but often it can simply take independent action on a continuous basis since it is able to watch how a change in one area interacts with others from one end to the other. Carried to its greatest extent, autonomy can optimize everything from supply chain to logistics. Such system-wide optimization is a critical driving force for this evolution. How and why companies are applying the concept is outlined in the survey results.
Understanding the survey
The 2021 survey represents a truly global undertaking:
- 534 respondents from 390 companies located throughout China, Germany, India, Japan, Saudi Arabia, southeast Asia, and the United States.
- About 62% of the respondents are end-user manufacturers, with the balance divided between equipment OEMs and system integrators.
- Industry sectors include chemical/petrochemical, life sciences, upstream and midstream oil & gas, refining, electrical utilities, and renewable power.
- Job functions include management in various areas, including IT, operations, projects, plants and corporate offices.
Areas of deployment
When respondents consider areas where they see the most potential for positive impacts going forward, environmental sustainability holds the first position (Figure 1) with 45% of plant operators expecting industrial autonomy to have significant impact on environmental sustainability improvements. More specifically, respondents expect large gains related to sustainability will be realized in areas of energy management (50%), worker safety (50%), greenhouse gas reduction (47%), and waste reduction (45%). This likely reflects the challenges many companies have realized when trying to tackle these types of issues using conventional approaches, but autonomy provides new techniques and solutions.
As the graph in Figure 1 points out, sustainability does not have a huge lead as a number of other critical areas are close behind, and the belief that industrial autonomy will have either a significant or moderate impact across these areas is very consistent at 79% to 83% across the board. So, if respondents believe all these disparate areas have roughly the same potential for success, where have they already begun making investments in industrial autonomy projects, or where do they expect to make their first actual investments?
Again, there is a high degree of consistency across the functional areas, and an encouragingly high number of companies that already have working implementations (Figure 2). In many respects, seeing maintenance and asset health implementations high on the list is not a surprise since concepts of predictive maintenance and reliability driven by device diagnostics and data analysis has been a working practice at many companies for years.
For many manufacturers, these efforts represent early manifestations of industrial autonomy, providing positive lessons for how such techniques can deliver reduced costs and efficiency. Similarly, supply chain optimization has also been in the works for many companies since it is a data-centric process, and more in the realm of corporate networks and analysis than production.
Environmental sustainability is also high on the list, perhaps for the opposite reason of maintenance. For most companies, efforts to improve sustainability are more recent, so they have decided to proceed directly to newer technologies, rather than implementing traditional approaches first. Others may have found traditional methods inadequate and moved to industrial autonomy methods as a solution. Whatever the case, 68% of companies have implemented environmental sustainability efforts using some aspect of industrial autonomy at one or more sites.
Another interesting aspect of the implementation plans is that process control technologies did not rank as high as some of the non-process control functions. Adaptive advanced process control (APC) is the first automation area to appear and it is in the fourth position. Some of this could stem from the fact that plants using the latest generation of distributed control system (DCS) platforms, such as Yokogawa’s CENTUM VP (Figure 3), already have many of the capabilities of autonomous technologies available, such as AI, predictive maintenance, and machine learning.
But many plants operate with older systems, so these are likely slated for upgrades. Remote operations capability has also been built into current systems since this has been so important for companies in recent years, particularly most recently due to COVID restrictions.
Return on investment
As might be expected, respondents anticipate that the greatest return on investment (ROI) will come from undertaking digital transformation in production and manufacturing applications (Figure 4).
The second highest rank relates to health, safety, and environmental (HSE) uses. The benefits of HSE may be just as important, but from an accounting standpoint, these are harder to quantify since they generally reflect costs avoided, rather than increased production.
Are technologies available today?
We asked respondents if they see the technologies necessary to support industrial autonomy as practical today, or if the hardware/software has some catching-up to do (Figure 5). Process industries are generally very conservative about adopting new ideas due to the high risks involved in refining, chemical processing, and similar areas, so users like to be sure before they commit.
Cloud technology (Figure 6) and cybersecurity lead the list, characterized as mature or mature for certain use cases at 70% and 59% respectively. These two technologies are basic building blocks of industrial autonomy and will be used in many deployments. Other items on the list—such as distributed ledger technology/block chain, AR/VR/MR, and digital twins—will be applied more selectively depending on the application, but where needed, these will also be critical.
The adoption and availability of smart sensors (Figure 7) is perceived as one of the most important technologies for providing the data necessary for industrial autonomy, leading to the third-place ranking of this technology.
Data from smart wired and wireless sensors provides the information needed to guide industrial autonomy actions, and to monitor performance.
New opportunities for the workforce
In any discussion of new technologies, the changing roles of people enter into the discussion, particularly as considerations of COVID-19 continue to weigh on the world.
Questions related to remote operations are reflected in every business and industry, and process manufacturing is no exception. The majority of respondents, at 64%, say their company has already implemented remote operations at single or multiple sites, with an additional 19% saying they are currently piloting projects. The question remains, is this related to the pandemic, or a direction that will continue permanently? Among respondents, 80% say industrial autonomy will have a significant or moderate impact on remote operations capability over the next three years, so the change looks permanent.
Technology changes can cause apprehension among workers, believing their roles and jobs will be made obsolete. There is no doubt that industrial autonomy will change some roles, calling for retraining, but for many companies, finding people is the greater challenge, so few workers remain that could be considered surplus. If anything, industrial autonomy adds value and opportunities for employees at all levels.
Looking ahead
The survey results make it clear that industrial autonomy, in its many forms and functions, is here to stay, although there will be much variability in the ways different companies adopt it. Each location will have to determine where its weaknesses lie, and how these new approaches can strengthen an entire operation. Fortunately, industrial autonomy can be adopted incrementally and deployed where it is needed most. Like other new technologies, it can prove its worth one step at a time, demonstrating and building value, so each expansion is easier as positive history builds.
Some companies will surely struggle, trying to determine where and how to advance. If there is no clear roadmap for adoption, a well-intentioned manufacturer can choose a path leading to poor performance. Survey respondents recognize this, and they cited “Creating a company roadmap for digital transformation/IA,” and, “Creating an initial business case/ROI justification for measuring success,” as the most significant challenges. They also cited “A clear technology vision and strategy,” and “Technology integration capability,” as the most important points for evaluating a technology partner.
To address these and other issues, Yokogawa can conduct an organizational readiness assessment to determine where your company is now, develop a roadmap to depict plans, and work with your company to help reach goals and achieve objectives.
Many companies are already realizing the benefits of programs built with Yokogawa’s direction and cooperation, especially for their industrial autonomy projects.
All figures courtesy of Yokogawa
About The Author
Dr. Tsuyoshi Abe is the senior vice president at Marketing Headquarters for Yokogawa Electric Corporation. Dr. Abe spent 31 years at Intel Japan in a variety of technology, manufacturing, and marketing roles before joining Yokogawa in 2016 as senior vice president of Yokogawa’s global Marketing Headquarters. His broad mandate includes not only market intelligence and communications, but also business planning, R&D, intellectual property, industrial design, new business development, M&A and alliance management, public affairs and standards management.
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