22 Tem 2022
4 dk okuma süresi
Manufacturing companies can alter their operations with real-time insights thanks to the convergence of edge computing, IoT, computer vision, and data analytics.
Manufacturers require real-time insights into their operations from data created across the manufacturing environment to compete successfully. One of the keys to lowering downtime, enhancing product quality, raising factory output, and accomplishing other business-driven objectives is to achieve this.
Smart manufacturers are reshaping their business processes to meet these objectives by implementing advanced edge technologies that automate data collection and bring processing and analytics near the data source. These intelligent manufacturing solutions enable systems to act immediately to optimize everything from supply chains, logistics, and plant security to machine performance and equipment maintenance.
Instead of sending everything to the cloud and data centers for processing, there are strong arguments for bringing analytics to the edge. This is the case, for instance, when a machine begins to malfunction, when faulty materials enter the production process, or when computer vision systems see symptoms of security breaches. Events like these necessitate quick responses, which is a major justification for bringing analytics close to the data rather than transferring it to a faraway data center. Another justification is the expense of delivering and retaining so much data when decisions can be taken at the edge.
Thanks to a sharp decline in sensor costs that made data gathering possible at every stage of production, today's manufacturers are collecting large volumes of data. They now need an edge and IoT solutions to make the most of it all. On this front, there is encouraging news. Manufacturing edge and IoT solutions are becoming more advanced, intelligent, and deployable.
How can edge computing and IoT be used in manufacturing?
A Microsoft-commissioned "IoT Signals" study report emphasizes the application cases for edge and IoT technologies in manufacturing contexts. According to that analysis, based on an international survey, the supply chain and logistics, production planning and scheduling, quality assurance, and plant safety and security are the top use cases for IoT in manufacturing.
Let's take a broad look at some intriguing use cases that show how edge and IoT methods open the way for more intelligent manufacturing tactics.
Industrial automation
There are too many sensors, devices, and data in today's digitally-driven manufacturing environments to rely on manual operations. Manufacturers must automate their responses to unusual situations and problems, such as machinery showing signs of stress and monitoring systems throughout the factory floor. Intelligent systems can automatically fix some difficulties in advance with quick input from monitoring apps, and they can then notify plant operators of problems on the manufacturing floor.
Quality and compliance
Using real-time quality control procedures, edge solutions are essential for upholding the highest product quality standards. For instance, producers can automate the thorough inspection of products and materials, discover flaws, and immediately eject defective products from a production line using data from IoT sensors, computer vision, and machine learning skills. They can accomplish this more quickly and precisely using edge computing than human inspection.
These kinds of capabilities can result in considerable savings. According to a McKinsey & Company study, compared to processes relying on human inspection, AI-driven quality testing can enhance productivity by up to 50% and defect detection rates by up to 90%. Edge solutions are extensively reliant on these procedures.
Manufacturing companies can benefit from edge computing by automating the gathering and management of regulatory and compliance data. Automating promotes more accurate reporting by assisting producers in avoiding mistakes and other hazards associated with manual data gathering techniques and individuals strolling the plant floor with clipboards in hand.
Production planning and scheduling
Using better production planning and scheduling tools and real-time production line monitoring, edge and IoT technologies are assisting firms in increasing product quality and factory yields.
One company discovered that more than 200 manual inspections were necessary for their production process and took up to 30% of the production time. To enhance throughput, the factory operators had to automate these tests. To get this information, they added sensors to monitor the temperature, humidity, and dust levels during manufacturing. Then, a solution for edge analytics absorbed sensor data and provided real-time insights into changes that could affect the quality of the manufactured components. The new infrastructure system completely covered the factory after six months of its deployment, saving 5,000 hours of manual data entry annually.
Plant safety and security
To improve safety and security in production environments, IoT-enabled devices and computer vision skills are now among the most important factors. The development of edge and IoT security solutions has had a significant impact.
Examples include deploying rugged solutions in the most hostile locations to protect workers from repeated inspections in unstable regions and employing computer vision to supervise 360-degree safety operations both within and outside a facility. Another application for computer vision in manufacturing is monitoring business vehicles, property, on-site injuries, and facility loss or damage. Safety and security solutions can determine the best ways to protect personnel and assets once established KPIs.
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