The machine vision revolution has arrived and with it, the chance to capitalize on the promises of Industry 4.0: automation, advanced analytics, and real-time decision-making. Machine vision (MV) enhances this by bringing the power of sight to computers and equipment.
The goal? To leverage advanced image processing techniques so that computing systems can mimic how humans see and perceive objects. This powerful technology is closely linked to artificial intelligence (AI), with deep learning models making it possible to accurately classify objects detected via machine vision.
Valuable across many industries, this integration of MV and AI has proven especially impressive in manufacturing, logistics, and for optimizing the supply chain. Implementation matters, however, and organizations need to be aware of best practices and limitations to ensure a strong return on investment.
Machine Vision vs Computer Vision
Machine vision and computer vision are frequently confused, and, while both mimic human vision and leverage advanced algorithms, these terms are not truly interchangeable. Computer vision is a far broader field that, although also linked to AI, offers many other use cases.
In general, computer vision systems involve tech-driven image detection, with visual data interpreted by advanced computing systems. For example, computer vision influences medical imaging, classroom instruction, and even data acquisition. Furthermore, computer vision integrates visuals beyond specific images captured by dedicated cameras, with the goal of extracting as much information as possible.
With machine vision systems, the focus is narrower: leveraging computer vision to automate key processes within industrial settings. In these environments, MV technologies make it possible to read barcodes, measure components, or automatically inspect products for quality control purposes. This focused setup can prompt fast decision-making and improved productivity in highly structured and controlled settings.
Machine Vision Applications by Industry
Despite their focused nature, machine vision technologies can be leveraged across numerous industries. Below, we have highlighted a few of the many sectors in which these solutions are especially valuable, along with specific applications that — alongside AI integration — allow these technologies to improve accuracy, productivity, safety, and customer satisfaction.
Manufacturing & Warehousing
As clear leaders in implementing machine vision, the manufacturing and warehousing sectors are well-suited to this technology because so many visually identifiable products and components pass through facilities. MV is relevant in all corners of the manufacturing industry, ranging from the automotive assembly plants to the production of in-demand electronic devices.
No matter where or how it is used, MV technology integrates exceptionally well with cutting-edge AI solutions and warehouse management systems. The following use cases are especially compelling:
- Quality control and inspection systems. From visual inspections (which reveal scratches and other defects) to label verification and even dimension checks, machine vision adds a reliable layer to the quality control process. This may also extend to MV-oriented misplacement systems, which reveal when items have been stored in the wrong location.
- Assembly line optimization. Promoting robotic guidance, machine vision systems help ensure that robotic arms and other components are properly positioned for assembly tasks. MV also supports component verification, which confirms that the correct components are used in every phase of manufacturing. Furthermore, it influences manufacturing equipment, as predictive maintenance solutions can reveal when this equipment needs extra attention.
- Inventory management. Through every stage of inventory management, MV can contribute to data-driven strategies, which promise real-time insights and opportunities to make key workflows more efficient and cost-effective. Real-time inventory tracking keeps inventory records up to date, while automated scanning further speeds up the process to increase throughput. These MV systems integrate not only with inventory management solutions, but also, with enterprise resource planning (ERP) systems for streamlined replenishment.
Logistics & Transportation
It takes exceptional coordination and oversight to procure and distribute products to the right clients or consumers and at the right time. As demands for swift service continue to increase, and with labor shortages and supply chain challenges continuing to cause problems, machine vision-enabled systems promise to bridge the gap in logistics and transportation. Exciting opportunities include:
- Traffic monitoring and management. Offering real-time traffic analysis opportunities, MV systems place cameras in strategic locations to verify traffic conditions. Often used alongside advanced sensors, these cameras can help determine vehicle speeds and density at different times and in many different scenarios. This wealth of data is then analyzed to reveal meaningful traffic patterns and to demonstrate why certain areas are prone to congestion. Based on this information, strategic decisions can be made to alleviate congestion and other detected issues.
- Package sorting and tracking. Advanced imaging capabilities allow machine vision systems to optimize numerous package sorting processes. Often, this involves scanning barcodes and QR codes, although MV solutions may also involve optical character recognition (OCR) when barcodes are not present. These solutions can be integrated with conveyor belt systems to support real-time sorting, ensuring that identified packages are sent to the correct bins.
- Autonomous vehicles. Machine vision allows autonomous vehicles to accurately perceive their surroundings. This includes recognizing lane markings and detecting obstacles such as pedestrians or other vehicles. While autonomous vehicles are often associated with big tech companies, automated guided vehicles are coming to play a greater role in logistics and in warehousing. Automatic guided forklifts, for example, are ideal for repetitive material handling tasks. MV can also optimize routes to improve productivity and even to reduce fuel consumption.
Retail & eCommerce
It is easy to see how MV influences retail and eCommerce through driving warehouse optimization. When warehouses achieve real-time information and efficient workflows, it is possible to avoid stockouts and to live up to demands for quick order fulfillment.
Other applications, however, relate directly to the in-store or online shopping experience, determining whether shelves are stocked and the extent to which service is personalized. Applications worth noting include:
- Customer analytics. The data-driven world of eCommerce calls for advanced techniques that provide extra insight into consumer behavior and preferences. This may play into return analysis, with MV technology revealing defects or other issues that prompt returns. In retail, machine vision can support foot traffic analysis to determine the flow of customers within brick-and-mortar settings. MV-enabled systems may also prove useful for loss prevention.
- Inventory management and shelf monitoring. Product availability is crucial in retail settings, and MV promotes this by monitoring stock levels to determine when items are beginning to run low. If integrated with advanced inventory management systems, this technology can promote automated reordering, in which purchase orders are immediately generated when stock reaches a specific threshold.
- Visual search and augmented reality (AR). While machine vision identifies objects, AR can incorporate interactive elements. For example, if an MV system identifies a package, AR systems may display handling instructions or other relevant information. Visual search represents an especially exciting opportunity from the modern customer’s perspective; this goes beyond the text-based searches (or even voice searches) to allow customers to search for products using images alone. This can be valuable when consumers aren’t quite sure how to describe desired items via conventional keywords, and this intuitive approach to product searches could have huge implications for customer satisfaction.
Leveraging Machine Vision Technology for Your Business
The exciting opportunities highlighted above are only the beginning. As the technology that underscores machine vision and AI continues to advance, new use cases will continue to emerge. Moving forward, it will become ubiquitous in sectors such as manufacturing and warehousing — and enterprises that fail to keep up may lose their competitive advantage.
This is a great time to leverage machine vision solutions, but not just any approach will produce a strong return on investment. Before committing to machine vision technology, it is important to determine core objectives, examine available options, and select the right system for your organization. No single approach will be ideal for every enterprise; the best setups should seamlessly integrate into key workflows to enhance accuracy and productivity.
Our team at Peak Technologies can help. We offer many machine vision system services, ranging from system design to onsite setup, a powerful suite of machine vision smart cameras and even fixed industrial scanners. Get in touch to learn more about our cutting-edge supply chain solutions.
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