Enablers in Industrial Autonomy

Enablers and Drivers

From AI, digital twins and robots, new technologies are revolutionizing the way that plants operate. They are facilitating a shift whereby physical tasks and decision-making processes are being made more autonomous with the aim of improving productivity and worker safety. In today’s business environment, operational resilience has never been more important.

The transition to industrial autonomy requires a variety of technologies across information technology (IT) and operational technology (OT) areas. Yokogawa's strength comes from its combination of both IT and OT expertise.

All the advanced digital technologies built on the reliable and sustainable architectures are already available. How these technologies are integrated and applied to the industrial autonomy is essential to the journey.

Yokogawa & KBC have years of experience and expertise to implement transformation programs starting from a very early consulting phase. Yokogawa & KBC understand what key issues must be solved and what types of technology are available to solve the issues.

 

AI and Robotics Are at the Heart of Industrial Autonomy

It was clear from speaking with industry experts that autonomy levels can vary widely, not only across industries but also within individual organizations. And while there are applications that have already achieved the level of Autonomous Orchestration, with autonomous systems responsible for decision making, even most new projects are just moving to Automated or Semi-Autonomous levels.

This is because movement to greater levels of autonomy is influenced by the type of application. In more complex multi-system applications, or in applications possessing greater levels of uncertainty and unpredictability, human operators will be present.

Moreover, while it is an exciting time for new technologies, various challenges exist and must be overcome for industrial autonomy implementations to be successful.

Overall, the most common technologies being labeled as “game-changers” by industry leaders are artificial intelligence (AI) and robotics. AI is an important enabler of data analysis, decision-making, and providing autonomous functionality. For instance, AI comes into play in the handling of large volumes of data, and in supporting predictive analytics that can be applied to applications such as asset health monitoring, process optimization, and quality-management. However, the benefits of analyzing data without domain knowledge is limited. The value comes when these technologies are combined with expertise that can identify both the business pain points alongside understanding the context of the data feeding the algorithms.

AI and Robotic


On the other hand, robots and drones are another important enabler of industrial autonomy. They are being used for monitoring, surveillance, and supporting people to perform tasks in hazardous environments; and are doing tasks such as leak detection, corrosion monitoring, chimney inspection, and so on. As more intelligence is embedded, they will become more versatile and perform more operational and maintenance tasks autonomously. Oil and gas professionals discussed how robotic solutions are increasingly being utilized in both different formats and environments, from mobile robots such as drones being used to support aerial inspection, for example in the monitoring for methane emissions, to remote operated vehicles with robotic arms that can be utilized in subsea maintenance of pipelines.
In addition, “fixed” land-based robots have been introduced in applications on the drill floor to automate pipe-handling and tool operations.

The what, where, when, and how to introduce industrial autonomy solutions is also greatly influenced by the facility and its readiness level. Those with brownfield sites commented that introducing advanced technologies presents big hurdles, as many of these sites were not designed with autonomy in mind, nor to limit involvement of human operators. But these sites were also highlighted as where maximum benefits can be achieved since they use more energy, deal with greater inefficiencies, and require more maintenance. In contrast, greenfield sites are increasingly being designed to include autonomous operations and elements, such as robotics.
 

robotics

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Preparing for an Autonomous Future

Digital transformation encompasses the entire enterprise. DX applied to manufacturing is called Smart Manufacturing. Yokogawa believes for many end users, autonomous operations is the destination of smart manufacturing. 

The transition from industrial automation to industrial autonomy requires sensing and a digital infrastructure that spans the entire operation and integrates data, smart devices at the edge, bulletproof hardware and software to deliver the required level of flexibility, adaptability, resilience, and eventually, autonomy. 

Yokogawa is preparing the way for a future in which industries will make the transition from industrial automation to industrial autonomy (IA2IA). We offer a wide range of smart manufacturing solutions and digital consultancy services that will help customers on their digital transformation journey towards autonomous operations. For more information about Yokogawa’s Smart Manufacturing solutions, please click here.

 

Related Links

 

Related Links - AI    Decoding Artificial Intelligence: The brain, the myth, and the legend

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