Study: Two thirds of process industry fully autonomous by 2030

Last week, Yokogawa released a study finding that two-thirds of process industry companies anticipate fully autonomous operations by 2030. That’s huge shift. That’s a small timeframe for the change. 

We wanted to learn more, so we connected with Duncan Micklem, Yokogawa Corporation of America EVP of strategy and marketing, to dive deeper into the findings. Take a look… 

Smart Industry: What most surprised you about the findings?

Duncan: Most surprising was how the appetite for Remote Operations Centers (ROCs) has accelerated. For example, in 2018, when KBC (a Yokogawa company) performed a global OpX/digital survey, ROCs seemed a lot less of a priority for businesses. However, in just two years, they have grown astronomically. COVID-19 has contributed to the interest in ROCs, for sure, as a safety measure for workers. Another contributing factor seems to have been intensifying global competition and the need for companies to improve their cost positions and, therefore, explore new business models. In addition, there is a keen interest in autonomy, not only for safety, but to improve productivity and reduce human error in order to make operations more resilient against disruptions.

More recently, our customer engagements highlighted the industry’s desire to accelerate their digital transformation efforts, particularly shifting from industrial automation to industrial autonomy, or what we call “IA2IA.” A big surprise to us was that about two-thirds of the respondents indicated they expect to leverage technology to automate most plant decision-making processes in the next few years. 

Smart Industry: What industries/verticals are leading this movement? What can others learn from them in this regard?

Duncan: I would say all of them, but for different reasons. The types of ROCs that are desired differ by industry. In addition, there are big differences between greenfield and brownfield installations. Industries such as chemical, petrochemical and renewables that are building new facilities are designing in digitalization, autonomous components, processes and business models. However, this is significantly more challenging for brownfield situations, which call for retrofits to existing assets. In both cases, there are efforts to improve asset reliability, worker productivity and situational awareness.

Smart Industry: What are some of the most widely used "technologies that aid decision-making" referenced in this report?

Duncan: Robotics, AI/ML, digital twins, cloud, cyber, IIoT smart sensors, knowledge graphs, edge devices, and AR/VR are now widely used. Bear in mind that there are some less glamorous technologies that have been around for some time and are fundamental building blocks along the path to autonomy, e.g. process simulators (operationalized with real-time data), APC, modular-procedure automation, etc.

Plants and assets generate a lot of data. Much of it is isolated in silos and not leveraged or used properly for collaboration or decision-making. The data can be processed at the edge or collected and analyzed in the cloud using big-data analytics, AI and digital twins. The information can be disseminated to workers through KPI dashboards, advanced graphical displays, and mobile devices. To do this properly requires a strong automation foundation within a secure environment utilizing smart sensors and devices, IIoT, etc. This is where the less glamorous building blocks are vital. Leveraging the latest AI algorithms that learn and adapt allows some of the decisions to be made autonomously or with minimal human intervention.

Smart Industry: What does this projected shift to fully autonomous operations mean for the human workforce?

Duncan: To start, it means there are fewer people in harm’s way in the plant. Also, roles are changing, for instance, through upskilling of blue-collar workers. More autonomy means that the more mundane, repetitive, number-crunching tasks are accommodated by RPA, AI/ML and machine-based decision-making, freeing up the human for high level thinking on things like strategy. Initially, benefits to the workforce include keeping people safe, improving productivity, and reducing human error. For the near to mid-term, it will mean some people will need to re-focus and re-skill for more value-added activities and different roles. The shift to industrial autonomy is also, in some respects, being driven by the energy transition. So we should expect a corresponding shift in workforce market dynamics. For example, if peak oil is a certainty over the next decade, but global energy demand continues to grow, then there has to be a corresponding shift in the workforce that corresponds to the energy source.   

Smart Industry: How can manufacturers respond to this projected trend?

Duncan: This depends on the level of maturity of operators and companies. ROCs aren’t all made the same. For some, the starting point is the Central Optimization Center. For others, it might be minimally manning a facility. Highly advanced assets might be pursuing fully autonomous operations. There is a maturity model for what the different companies are striving for, and their as-is starting position. 

Initially, companies should audit existing technology applications, build an application register and understand how effective they are in relation to current and future goals. The path to autonomy cannot or should not be in isolation from digital roadmaps. Companies must establish the right KPIs then build an integrated asset model of molecule-transformation processes and reliability. Operationalizing it with real-time data is key. This is where money is made and lost. Business must manage the transfer of knowledge; the net loss of tacit knowledge from the crew change through adoption of knowledge graphs is important.

Smart Industry: What do you find most encouraging in this report?

Duncan: Primarily, people are removed from harm’s way. Our industry is about safety first. But there are other benefits. For example, the need to accommodate fewer people on an offshore platform reduces cost, weight and capital expense. Those cascade to even further benefits such as reduced emissions.