Highlights:
- Artificial Intelligence in manufacturing enables manufacturers to anticipate when or if functioning equipment may fail, allowing them to schedule maintenance and repairs in advance.
- Numerous manufacturing applications, such as machinery inspection, cybersecurity, quality control, and predictive analytics, make substantial use of AI.
Artificial Intelligence (AI) seems to be well on its way to becoming the most overused buzzword for businesses. It’s no longer a futuristic idea and has deftly carved a position for itself in almost every aspect of our lives – customer data analysis, autonomous vehicles, and even art – its applications are everywhere, and its uses are constantly evolving.
To this day, AI is boosting business capacities in several ways. AI and machine learning are, in fact, on track to become the most significant factor driving the power of the manufacturing industry. What once looked like a scene from a science fiction movie is now a reality: Robots have turned up on more factory floors.
Let us quickly glance at AI’s role in the manufacturing industry.
The Role of AI in Manufacturing
According to reports, more than 60% of manufacturing companies have already embraced AI technology to boost operational efficiency, provide high-quality goods, decrease downtime, and automatically process data and make decisions.
According to Fortune Business Insights, the global market for AI in manufacturing was valued at USD 1.82 billion in 2019 and is expected to reach USD 9.89 billion by 2027, growing at a CAGR of 24.2% during the forecast period.
At best, AI analyses ways by which machines can synthesize information and make decisions without human assistance. There’s nothing that can be compared to the efficiency of humans, but they aren’t perfect. One of the important characteristics of AI is its ability to make rational and accurate decisions.
The best example to elucidate this is that humans are not well equipped to process vast amounts of data and the intricate patterns that come with large datasets. It is here that AI in manufacturing plays a key role. AI can efficiently sort sensor data from a manufacturing machine. In addition, it enables manufacturers to anticipate when or if functioning equipment may fail, allowing them to schedule maintenance and repairs in advance. All of this can be achieved by AI in a fraction of the time a human would take.
Significant AI trends in manufacturing
Robotics: The Keystone of Modern Manufacturing
Typically, AI applications involve software rather than hardware. However, robotics primarily focuses on highly specialized hardware. The majority of manufacturing companies employ this technology for several applications. According to some studies, the estimated demand for sophisticated robots in this area will reach USD 3.7 billion by 2021.
Global Industry Insights, Inc. projects that the industrial robotic market will be valued at more than USD 80 billion by 2024. This indicates that a great deal of the work can be automated to minimize product costs, protect human workers, and achieve higher efficiency.
For the robot to perform its tasks correctly, it needs precise hardware and, most importantly, AI software. Robots are specialized but lack decision-making powers. They need to be supervised by human technicians. But when augmented by AI, they boost the overall efficiency of the factory, and their propensity to make errors is less.
Thus, when artificial intelligence is combined with robots, there will be fewer errors and more efficiency, and software activities will be automated.
Artificial intelligence in manufacturing for cybersecurity
According to researchers, the manufacturing sector is the most prone to cyberattacks – if the assembly line is shut down even for a brief period, it can prove costly. And with the use of IoT, the manufacturing sector is set to accelerate and evolve. At the same time, the threats, too, will grow exponentially.
AI-driven cybersecurity systems and risk detection mechanisms can help secure production facilities and mitigate threats. By utilizing self-learning AI, manufacturers can easily spot attacks across cloud services and IoT devices and interrupt them in seconds. Furthermore, the system can send alerts to teams to act and prevent further damage. Security measures such as sandboxing, code signing, and others can help combat threats to IoT technologies.
AI-equipped visual inspection
Quality control is the most crucial use case for AI in the manufacturing sector. It’s evident that industrial robots can make mistakes – though compared to humans, the scope is fewer. But it can be a costly affair to roll out defective products down the assembly line and ship it to customers.
Humans can be at the helm of watching the assembly lines, but some defective products can still make it through. AI in manufacturing can be advantageous as it can inspect the product. AI-enabled cameras and IoT sensors provide better sensitivity to locating objects requiring adjustments and automatically detect flaws. Machine-vision software uses computer vision to detect microparticles and surface flaws, allowing computers to perceive, analyze, and learn from acquired data.
Natural Language Processing: Improving Issue Report Efficiency
Chatbots driven by Natural Language Processing (NLP) have become some sort of an AI trend in manufacturing as they facilitate more efficient reporting of issues and make requests more efficient. This is one aspect of AI that excels in emulating human conversations.
Using web scraping techniques, NLP helps the manufacturing sector make decisive judgments. Web scraping, data extraction, and scanning enable enterprises to collect and retrieve vital business information from the internet.
NLP also attempts to enhance emotional communication via emotional mapping. This will open up a vast array of opportunities for computers to comprehend the emotions of consumers and operators.
Future of AI in the manufacturing industry
The future of AI in the manufacturing industry is enormous. However, the real question arises: What’s the subsequent role of AI in manufacturing with the automation revolution around? Many thoughts may converge around this – from the realm of science fiction and others as extensions of technologies being utilized already. But the most noticeable change will be an increased focus on data collecting. Be ready to witness the impact of AI in manufacturing in ways you have not yet anticipated.
An increase in IoT use facilitates the collection of an ever-increasing amount of real-time data that AI may utilize to simplify manufacturing activities. This will promote an enhanced generative design process where goods are reimagined more akin to evolution.
However, with the development of AI applications over time, there will be a time when factories will be automated and product designs will be made without human intervention. To reach that position, you must, however, sustain the innovation trend and apply it. These technologies can revolutionize the landscape of the manufacturing sector and help organizations stand out from the competition.
Numerous manufacturing applications, such as machinery inspection, cybersecurity, quality control, and predictive analytics, make substantial use of AI. Therefore, it is anticipated that these factors would propel worldwide artificial intelligence in the manufacturing market ahead. AI and machine learning dominate today’s world and will continue to do so.
