The Compounding Impact of Robotics and Robotic Processes in Manufacturing

Manufacturers are experiencing a significant transformation driven by the adoption of everything from fixed to mobile robots.

Kyle Crum, director of advanced technology at Rockwell Automation

November 8, 2024

4 Min Read
robots in manufacturing
SweetBunFactory for iStock / Getty Images Plus via Getty Images

At a Glance

  • Impactful changes in robotics come from a convergence of technologies rather than a single innovation.
  • A full 94% of manufacturers say they will expand hiring while implementing robotics.
  • Displaced workers are getting reallocated to cognitive tasks requiring creativity and insight.

The manufacturing sector is experiencing significant transformations driven by the further application of robotics and introduction of effective Robotic Process Automation (RPA). When applied thoughtfully, these technologies are enhancing conventional manufacturing, resulting in improved productivity, and increased quality, for manufacturers worldwide. This article explores the synergy that should be expected with the continued implementation of autonomous robotics combined with an acceleration of RPA capabilities driven by recent advancements in Artificial Intelligence (AI).  These two technologies together will be much more than the sum of their parts.

An incomplete transition

Manufacturers have been implementing various forms of robotics—six-axis arms, delta robots, gantry systems, autonomous mobile robots (AMRs), automated guided vehicles (AGVs), etc.— for the last several decades resulting in dramatic increases in productivity.  Processes that were once only achievable through labor intensive, manual operations can be mechanized with relatively common commercial offerings.  Workers that would have spent long hours doing monotonous and repetitive tasks have been reallocated to cognitive tasks requiring creativity and insight.  This revolution is still active, but has seemingly reached a natural crescendo, seemingly awaiting the next movement.

Related:Robots on the Rise in Manufacturing

While all this played out, worker-executed tasks still rely on processes that have been relatively static since Frederick Taylor introduced what we now call industrial engineering.  Sure, some progressive institutions have transitioned to pdf or html-based documents, some even use digital forms, but these have limitations based on a human’s ability to search, read, and digest content. Fundamentally, we are still using paper-based processes, just transitioned to a digital medium. Industry has effectively accelerated the process side, but not really the human facing side of operations. 

The convergence of digital tools

The most impactful changes are often brought about due to a convergence of technologies rather than a single innovation.  Kodak arguably didn’t fail because of the digital camera.  Kodak failed due to the convergence of the digital camera and wireless communications in the form of the cell phone.

The application of Generative Pre-trained Transformers (GPT) to Natural Language Processing (NLP) has begun to supercharge various forms of knowledge work.   This has seen the introduction of a series of innovations that are almost certain to increase worker productivity dramatically.  We’re seeing the development and implementation of GPT-based NLP and code development systems that are completing our digital transition. When they mature, these systems will offer workers access to the knowledge inside manuals, guides, and examples without the limitations associated with human-based search, review, and memory.

Related:Robots Are Advancing Quickly

Ramifications of the digital convergence

Taken in combination with the digitation of existing manufacturing systems, manufacturers will have complete access to what is happening with their systems and the why.  Humans (and machines) with access to the combination of real-time data and the associated knowledge bases will be able to make inferences hereto impossible.  These, collectively called Generative AI (GenAI), systems will allow insights and optimizations that aren’t considered today because it would be ridiculous to even consider them.

For instance, GenAI-assisted maintenance workers might work with data realizing that their condenser failed whenever the temperature outside transitioned through the freezing point (a real issue that took a team years to put together).  Automation technicians will use GenAI tools to help trouble shoot logic in a system, and because the GenAI has access to manuals they determine a root cause with almost no effort.

Investment is increasing, along with security

This convergence is real, and organizations are taking note. According to a recent report, 83% of manufacturing enterprises anticipate utilizing GenAI in their operations by 2024.  Approximately 42% of them also intend to increase automation, while another 34% aim to incorporate other AI technologies.  Contrary to some commentary, 94% of manufacturers in the same study suggest that they will also expand hiring during the same period.

Obviously, all this digitization comes with new challenges.  Reporting suggests that 71% of all cyber-attacks against industrial organizations focused on the factory floor. The need to secure converged Information Technology / Operational Technology (IT/OT) systems will continue to increase importance.

Outlook for the future

Over the next several years, the industrial environment will transform for organizations that choose to invest. This is not hyperbole. We’re quickly coming to the day when we’ll have a digital worker online with us, helping troubleshoot code and alarms. Digitation came for our processes and has come for our cognitive work.  The future is bright for those willing to embrace change and design their systems to further expand human capabilities.

About the Author

Kyle Crum

director of advanced technology at Rockwell Automation, Rockwell Automation

Kyle Crum is the director of advanced technology at Rockwell Automation. Crum is a US Navy veteran with over 10 years of experience in leading and managing R&D projects that shape the future of industrial automation. 

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