Resuscitating Manufacturing Industry with Machine Vision in the Age of COVID-19

Machine Vision in Manufacturing

Over the last few years, machine vision has garnered immense esteem, especially in manufacturing. Already, the technology has made a significant contribution to the manufacturing sector as it provides automated inspection capabilities as part of quality control processes. Since the COVID-19 pandemic continues to wreak havoc manufacturing worldwide, manufacturers are scrambling to restart production and supply chains, hoping to get back to the normality resembling that of the pre-pandemic world.

To do so, some manufacturers around the world started rapidly transforming their businesses by leveraging Industry 4.0 technologies to be able to resume and produce critical and high-demand products. As COVID-19 has stimulated the adoption of these technologies, GlobalData, a leading data and analytics company noted that machine vision will see strong growth in the APAC region over the next five years. According to the company, in pursuit to adopt Industry 4.0 initiatives, a large number of companies in Asia are now striving to perk up their various industrial processes, by leveraging various technologies like machine vision coupled with computer vision.

With enhanced developments of imaging techniques, sensors, embedded vision, machine learning and deep learning, robotics, and data transmission standards, vision technology has the potential to benefit manufacturers at different levels. Machine vision refers to all applications and combines both hardware and software and provides operational guidance to devices in the implementation of their functions based on the capture and processing of images.

The growing demand of better quality products from end-users has facilitated a major role for machine vision software in the quality control section across all kinds of industries. As several manufacturing companies have adapted their operations prior to the COVID-19 outbreak, they are now adding new digital technologies and digitally driven solutions to explore opportunities. Machine vision in this way could be an effective approach, as manufacturers need to provide high-quality products to meet their customers’ satisfaction levels. 

According to a report, the market of machine vision is predicted to reach US$4.42 billion, at a growing CAGR of almost 8 percent during the period of 2020-2024. 

Conventionally, in machine vision technology, developers need to manually define and validate individual features for the machine in the software. However, owing to the cognitive nature of deep learning algorithms, the machines have the ability to automatically find and pull out patterns in order to distinguish meticulously detailed and larger components being produced. Today, machine vision has evolved and continues to evolve.

As the role of barcode scanners in manufacturing is vital, by powering this technology with advanced capabilities like Optical Character Recognition (OCR), Optical Barcode Recognition (OBR), and other image processing techniques, manufacturers can use the system to automate the overall scanning process.

Machine vision software typically uses supervised deep learning algorithms to train machines as deep learning processes can learn new things autonomously, without manual classification. With machine vision systems, manufacturers can spot flaws or any imperfections in a physical product. Also, these systems can easily check for accurate measurements of components or parts that are used while the product is being assembled.