Manufacturing has always been a great frontier for human civilization. Since the dawn of time, we have been creating tools to make work easier. From rudimentary axes to windmills and the steam engine, our inventions have allowed us to produce more while doing less. With every industrial revolution, we are shown infinite possibilities for the future.
We are now in the midst of the fourth industrial revolution, otherwise known as Industry 4.0. This era of smart manufacturing is characterized by the use of data and automation to improve manufacturing processes and produce goods more efficiently across the value chain.
Industry 4.0 is rapidly changing the way that manufacturers create and distribute their products. Instead of mass production, the focus is now on mass customization, where companies can meet the varying demands of their customers with more flexibility and agility than before.
New technologies such as cloud computing, artificial intelligence (AI), Internet of Things (IoT), and big data analytics are integrated into manufacturing operations across the entire production chain to allow for better information transparency and timely decision making.
The increased optimization and automation of Industry 4.0 has allowed manufacturers to achieve a new level of efficiency and responsiveness that was not possible in the past. From discrete manufacturing to the mining sector, Industry 4.0 technologies are making a world of difference.
AI is a large factor of Industry 4.0. Computer vision is a type of AI where computer systems scan digital data—like images or videos—to gather meaningful information. The computer system then analyzes this information and performs or recommends certain actions.
Computer vision utilizes a massive pool of data to train machines to discern between the expected and unexpected qualities of any given item. Instead of being programmed to recognize images, AI uses algorithmic models to enable the machine to learn through the process of examining data.
However, funding a computer vision lab takes an immense amount of resources. Aside from the extraordinary computing power required to run the huge visual data sets, organizations need to create deep learning models and neural networks that will enable computers to learn.
Nonetheless, backed by the biggest names in technology and R&D, machine vision is now used in a myriad of industries from manufacturing inspections to self-driving cars and Google Lens. As research continues into the applications of this technology, it is expected to reach a market size of $48.6 billion in 2022.
There are numerous benefits to integrating computer vision into a manufacturing system. Not only can a fully-automated system operate much faster than a human and analyze thousands of items per minute, but it can also work every hour of the day, every day of the year.
Computers are not prone to contagious diseases. Hence, companies can maintain safe distancing and protect their existing employees in the post-pandemic era. Computers do not get bored either. So, they can perform repetitive monotonous tasks that would otherwise drive a human mad.
Operational health and safety standards are a concern for all businesses. It is estimated that a worker gets injured on the job every seven seconds. Computer vision systems take workers off the dangerous manufacturing floor and avoid unnecessary accidents.
Other than reducing labor costs and staffing headaches, computer vision solutions improve manufacturing outcomes exponentially. Products created are better in quality, defects are identified quickly, and there is less waste involved in the manufacturing process. Customers are satisfied with their products, and businesses enjoy higher profits.
The main advantage of computer vision is the superior level of accuracy that cannot be matched by manual processes. Advanced computer vision algorithms and equipment can be combined to achieve near-perfect accuracy in manufacturing and quality control.
On assembly lines, computer vision solutions can use 3D imaging capabilities to inspect products. Defects on small, assembled items or tiny components such as microchips or electronic connectors can be easily and precisely identified by multiple-camera 3D computer vision.
Certain products need to be packaged with specific quantities while others to exact measurements. In addition, imperfect packaging can result in a product recall. Computer vision can maintain packaging standards to ensure the uniform appearance and safety of finished products.
In addition to monitoring products, computer vision can be used to observe the manufacturing equipment itself. By identifying corrosion, degradation, decreased range of motion, and more, computer vision systems can recommend signal the need for maintenance before manufacturing lines fail.
Our fourth industrial revolution is all about using intelligent machines to observe and communicate. Artificial intelligence is developing every minute and AI-driven systems will soon be front and center of our production lines and supply chains.
Computer vision is just one facet of the power of smart manufacturing. As industries learn to leverage technology, our factories and products will become safer for production workers and consumers respectively. Companies can look forward to a manufacturing process that is more refined, more efficient, and more accurate.