Hidden behind a dense forest in the shadow of Mount Fuji lies FANUC headquarters. The sprawling campus contains 22 windowless factories, where the company’s iconic yellow robots make other robots that have a hand in making many recognizable products, including Apple’s iPhone. FANUC robots are an integral part of global manufacturing, making the company’s recent foray into artificial intelligence (AI) even more exciting. Using an internet of things (IoT) platform, FANUC can funnel global manufacturing data to its self-teaching robots. What was once taught through programming is now being learned through “experience.”
FANUC’s interest in AI offers a glimpse into the future of manufacturing, but the true challenge may lie in convincing companies to embrace this new technology. Over three-quarters of manufacturers are exploring AI, but only 21% have AI initiatives in production. Don’t expect that to be the case for long, however. AI and other Industry 4.0 technologies, although resource intensive, will only become more appealing as the sector struggles. Let’s step inside the smart factories of the future to learn how AI is changing the face of manufacturing.
Why Artificial Intelligence? Why Now?
Considered one of the founding fathers of AI, computer scientist John McCarthy defines AI as “the science and engineering of making intelligent machines, especially intelligent computer programs.” AI technologies are capable of mimicking the mechanisms of human intelligence, or the natural phenomena enabling us to learn and problem solve. However, AI isn’t bound by physical limitations, and its potential lies in its ability to learn at speeds and in ways the mind is incapable of.
Advances in computing power and Big Data (the application of AI tools to vast amounts of data) have made AI a source of disruptive innovation across numerous industries. Manufacturers have always embraced new technologies to meet demand in the face of supply chain issues, production costs and labor shortages. Now, with these issues exacerbated by the COVID-19 pandemic, manufacturing companies are turning to AI for the solution, if they haven’t done so already. Most manufacturers—66%—who are assisted by AI report an increasing reliance on this disruptive technology.
The Smart Factory
Deloitte defines the smart factory as a self-optimizing, self-adapting system that can run entire processes autonomously. Characterized by its connected, optimized, transparent, proactive and agile nature, the smart factory represents the ideal manufacturing environment, one that evolves from insights gleaned from the application of AI.
Finding Any Flaw
We may learn through experience, but AI systems use machine learning: the training of algorithms to make predictions and, in the case of deep learning, improve based on patterns found in data. When coupled with machine-learning algorithms, automated systems can conduct visual inspections with incredible speed, accuracy and efficiency. Manufacturers now have a consistent and reliable way to inspect every single product rather than a random sample. According to Andrew Ng, founder of Landing AI, the company’s deep-learning algorithm is capable of inspecting a part within a half-second.
Predicting the Future
The sound you hear on the factory floor is more than a cacophony of screeches, hisses and crashes. It’s a source of acoustic data. AI applications can home in on these sounds and determine when one indicates a problem in much the same way you get goosebumps after hearing an unfamiliar sound from your car. “By analyzing the data,” said Siemens AG President and CEO Roland Busch, “our artificial intelligence systems can draw conclusions regarding a machine’s condition and detect irregularities in order to make predictive maintenance possible.” Paired with visual inspections, sound inspections will help ensure that only products of the highest quality leave the factory floor.
Controlling Supply Chains
Supply chains are traditionally linear—design, develop, deliver—but are evolving into dynamic, interconnected systems through the use of AI. By collecting data along the supply chain, AI can predict demand and manage inventory with increasing efficiency. For example, Amazon’s machine learning algorithms enable anticipatory shopping: the online retailer’s patented approach to getting products as close to customers as possible before they click to buy. (How else would Amazon be able to deliver on its promise of two-day shipping?) Amazon’s algorithms have also picked up on more nuanced patterns, such as the tendency for customers to abandon online shopping carts when bananas are out of stock. Algorithms like these can’t tell whether a pattern is reliable, but they don’t have to, since their predictions become more accurate with time.
What Does the Future Hold?
Industry 4.0 technologies like AI are blurring the line between the physical and digital world and, in the process, revolutionizing manufacturing. Although they’ve been slow to adapt to the new paradigm, manufacturers will have little choice but to adopt AI if they hope to remain competitive. Think of it as a leap of faith. AI is advancing at such a rapid pace that there’s no telling where the industry will land. One thing is certain, however: Manufacturing will never be the same.
To help mechanical engineers remain at the forefront of an ever-changing landscape, The University of Texas at Austin offers two 100% online mechanical engineering programs:
Executive Master of Science in Mechanical Engineering
Graduate students in our 30-credit-hour, non-thesis program utilize emerging technology while learning to design, analyze and produce products and design processes. Ranked the No. 11 best mechanical engineering program in the country, our program imparts the skills, knowledge and experience students need to advance their careers.
Mechanical Engineering Controls Graduate Certificate
Our 9-credit-hour certificate program takes an in-depth look at critical competencies engineers need to compete in the industry. Designed for working professionals and petroleum engineers, our program deepens students’ knowledge of the control and optimization of processes and systems.
Both of our programs are entirely online and updated regularly in response to industry trends. Want to get ahead of the many changes coming to manufacturing? Apply to one of UT Austin’s 100% online mechanical engineering programs.
Sources:
https://www.bloomberg.com/news/features/2017-10-18/this-company-s-robots-are-making-everything-and-reshaping-the-world
https://www.pwc.com/gx/en/industrial-manufacturing/pdf/intro-implementing-ai-manufacturing.pdf
https://www.pwc.com/m1/en/media-centre/articles/5-minutes-pwc-ai-and-big-data-manufacturing.html
https://policyinstitute.iu.edu/doc/mpi/smart-factories.pdf#page=12
https://www.ibm.com/blogs/services/2021/05/03/sound-as-a-new-data-source-for-industry-4-0/
