The Reality of AI & Industrial Robotics: Present & Future

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| October 16, 2024

Understanding the Emergence of AI in Industrial Robotics

Industrial robots are nothing new; they’ve been utilized in manufacturing since the 1960s. That’s not to say that their abilities have proliferated exponentially over that time, or that they haven’t been a huge factor in the growth of manufacturing. The emergence of AI technology that can be applied to industrial robotics is proving the next step in robots gaining even additional abilities, but it won’t be as simple as switching out a few sensors and waiting for a facility to become sentient.

The promise of AI in automation is exciting and potentially revolutionary, but the truth is it’s in its early stages, and the logistics of it are poorly understood. So, what’s a revelation vs the reality of AI-powered industrial robots? Let’s discuss how AI robots vs traditional robotic automation, sector applications, benefits in manufacturing, obstacles to integrating AI into robotic systems, and thoughts on what the new landscape of industry will look like in the future.

AI Technology Will Enhance, Not Eradicate Industrial Robots

There is a common misconception that AI is an evolution that will cover every piece of equipment in a facility and make it into something new – quite like how human evolution is often misunderstood as a step-by-step process. But just like our human ancestors, pre-AI industrial robots do many complex things! Pick and place, welding, bottling, batching – there are hundreds of different precise, repetitive tasks that don’t necessarily require AI in order to be performed at the highest possible level, especially since automation software and coding has become so complex.

So, what is the difference, then, that makes an AI-powered robot more advanced than a very intricately-programmed one? The answer is that code has its limitations; without AI, it cannot learn. Traditional industrial robots reach a ceiling of abilities, and they also lack adaptability and flexibility. These crucial capabilities are unlocked with AI integration. Learning begets flexibility begets adaptability. The major technology affecting this “cognitive” behavior in robots are:

AI (Artificial Intelligence)

What is AI in the context of robotic automation? It’s a system with the ability to perceive, react to and learn from environmental stimuli. An industrial robot is defined by the ISO as an “automatically controlled, reprogrammable, multipurpose manipulator, programmable in three or more axes, which can be either fixed in place or fixed to a mobile platform for use in industrial automation applications”. An AI robot would be autonomously controlled and self-reprogrammable because it has the ability to learn, adapt and improve without human intervention.

ML (Machine Learning)

Machine learning is a branch of AI. As opposed to traditional programming, it uses experience – huge sets of data – in order to program and reprogram itself.

DL (Deep Learning)

Deep learning is a subset of machine learning. Where machine learning utilizes recognizable industrial data analytics like statistical regressions, decision trees, etc., to learn, deep learning AI occurs in artificial neural networks that attempt mimic the human brain’s learning processes.

4D Vision

This technology provides industrial robots and AI robots the ability to perceive the world around them in the same dimensions humans do.

Industrial Sectors that Will Be Transformed by AI Robotics

Considering an automation system and control hub that operates an entire facility with the ability to adapt, pivot, learn, and improve, the sector applications for AI robotics automation are myriad, and the implications promising:

Agriculture

There aren’t many other industrial sectors where human experience, perception and expertise is so critical as agriculture. But that’s also why AI has such huge potential to improve crop yields, livestock quality of life, environmental impacts, and much more. Applications for AI in agricultural robotic automation include:

• Disease detection: AI vision systems have the ability to inspect crops and detect visual signs of blight. A DL AI program recently affected a 95% success rate with detecting a common apple tree disease.
• Weed control: AI vision and associated robotics have been developed the ability to see the difference between crops and weeds, then apply herbicides only in the relevant area, reducing the toxicity let into the soil, water, fauna, etc.
• Water management: AI can affect precision irrigation systems that control water and soil saturation levels to a high degree, reducing water usage and waste while improving crop husbandry.

Healthcare

Robert Wood Johnson University Hospital in 2019 invested in Tru-D, an autonomous AI robot that uses UV to continuously disinfect target areas across the facility. AI robots are being introduced in other applications as well, and we are starting to see the potential of AI robots in operating rooms. This includes not only microsurgery, but non-patient facing tasks, too, like fetching supplies, handing over instruments, monitoring vitals, etc.

Automotive

If you have a newer car, you may already have some AI in your vehicle. The promise of self-driving vehicles has myriad implications – better driver experience, increased safety, reduced fuel use, improved traffic patterns. And this potential applies to everything from a single driver to an entire supply and distribution chain of freight vehicles. Consider things like:

• Public Safety: autonomous emergency braking, lane departure warnings, adaptive cruise control
• Predictive Maintenance: tracking real-time conditions of the vehicle and comparing it against masses of vehicle data to determine the imminence of maintenance/repairs
• Manufacturing: replace human labor in unsafe, physically difficult, repetitive and error-prone tasks to improve all stages of design, manufacture and testing of vehicles

Benefits & Applications of AI in Manufacturing & Distribution

The benefits of AI-powered robotic automation in the automotive industry applies to manufacturing at-large. From data center automation to pharmaceutical control systems, AI robotics adds value at every step of the production line:

• A fully-automated line that can identify and remedy problems without the need for shut down and human intervention improves throughput as well as quality and consistency.
• Improved consistency and the ability to inspect, identify and immediately intervene in problems improves regulatory compliance.
• AI-automated processes can accomplish continuous production, unlocking the ability to scale.
• Collaborative AI robots can be used alongside human labor to improve worker conditions while optimizing production by augmenting human skill.
• When you couple in the logistical consequences of these AI abilities, you realize it’s not just on the floor that benefits – it’s all other stages as well. Predictive maintenance allows for better budgeting and planning. Continuous monitoring improves inventory practices. Operational analytics improve role organization.

And in manufacturing, of course, there is always the constant shortage and high cost of labor to contend with, especially as you try to grow and scale your company. Industrial robots in automation have taken off some of that stress; AI robotics will alleviate it much more, even as the labor challenge continues to grow. A Main Automation Partner with expertise in AI applications in manufacturing can help you harness the power of AI to make your facility more effective and efficient, on and off the production line.

Present Pitfalls to the Adoption of AI in Automation

While the buzz around AI evokes this apocalyptic tipping point where AI eclipses all and replaces everyone and everything with super-intelligent algorithms, the automation sector can tell you unequivocally – that’s not what’s happening. In fact, there are 3 significant factors that will make this new step in the digital transformation a gradual transformation across industry and manufacturing before you even think about your smart home waking up and turning the tables on you.

1. You need smart people to make smart machines.

We rely on coders to create the AI necessary for industrial robotics, and there aren’t exactly thousands of coders with the unbelievable skill set needed to generate software that has the intelligence to learn and adapt (yet!). This sets the ability to develop and deploy industrial AI as dependent on the supply of “super” coders we have. And gaining that type of knowledge, skill and talent takes time and experience. (Another good reason to put your kids in STEM programs!)

2. The upfront cost is currently prohibitive.

A big issue with the stage of AI robotics we’re at is the time it takes to become a cost-effective approach to automating your processes. Presently, the upfront cost can be astronomical, making it an investment only few large entities have the deep pockets to carry for the years and years it will take to see the ROI. Meanwhile, there are perfectly good automation products on the market that can still affect a fully-automated facility that reduces labor needs and improve operational logistics.

For most companies, AI robots just aren’t in the cards yet. That being said, there are many new and emerging automation products on the market that have begun to incorporate AI. As additions and upgrades to control systems, AI-laced automation technology can improve every stage of the industrial value chain. The key is to partner with the right automation system integrators, who can help you implement current AI tech and also prepare for future AI adoptions.

The Future of AI-Powered Robots: A Slow Transition into a Big Transformation

On the surface, the mystery and magic of AI offer a promise of a new world of automation – a magic portal that transports you directly into a new age of industry. But the real deep learning to be done is that there is no magic portal, no decisive moment, no singularity. Human intelligence required evolution, and so will AI – it’s created in our image, after all.

This concept of gradual development will hold especially true when we consider the accessibility of AI. When we have achieved a level where AI robotic automation is not only autonomous but easy to access, afford, implement, and maintain for everyone – that will be the new paradigm.

It’s already happening. But it will be over a series of important developments we have yet to face, which is why partnering with an automation services company is key. Future-proofing your facility isn’t just about upgrading your automation system to the latest technology now, it’s about upgrading in a way that your system has the flexibility to incorporate new AI and robotic capabilities as they become accessible.