{"id":72,"date":"2025-01-08T11:18:14","date_gmt":"2025-01-08T11:18:14","guid":{"rendered":"https:\/\/projects.itcurated.com\/innotech\/?p=72"},"modified":"2025-01-17T07:34:48","modified_gmt":"2025-01-17T07:34:48","slug":"an-eye-on-quality-and-occupational-safety","status":"publish","type":"post","link":"https:\/\/projects.itcurated.com\/innotech\/an-eye-on-quality-and-occupational-safety\/","title":{"rendered":"An Eye on Quality and Occupational Safety"},"content":{"rendered":"\n
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Highly automated factories deliver enormous benefits for manufacturers. Yet machines, equipment, and automation represent genuine risks. Add humans to the mix, and the stakes get higher.<\/p>\n\n\n\n

Humans are prone to errors. They get tired, become distracted, and occasionally make mistakes and miscalculations. An inability to adhere to occupational safety guidelines can lead to employee injuries\u2014and worse.<\/p>\n\n\n\n

For manufacturers, these errors and inefficiencies add up. They boost costs, undermine productivity, pose regulatory and reputational risks, and put workers at further risk. The result? Falls, slips, burns, cuts, bruises, blunt force injuries, and numerous other problems.<\/p>\n\n\n\n

Many factories use manual safety systems that rely on a human-centric and reactive approach. These systems are costly to operate, slow to detect violations and problems, and human error is a constant concern. Unfortunately, safety violations frequently slip through the cracks.<\/p>\n\n\n\n

As a result, a major beverage bottler in Asia turned to Innotech and Aotu<\/a> to build a framework that could transform various manufacturing and safety inspection processes at ten regional factories. The company recognized that there was a more effective way to manage occupational safety through machine vision and artificial Innotechligence (AI).<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Manual Processes = Errors and Problems
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Manufacturers understand that occupational safety is critical for business. However, manually monitoring conditions, events, activities, and human behavior within facilities is typically difficult and human-intensive. Machinery, equipment, vehicles, tanks, and other tools represent a significant risk if they are not used correctly and if employees fail to follow safety guidelines, such as using protective gear and following specific protocols and procedures.<\/p>\n\n\n\n

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On average, a typical factory with a 10,000 square meter footprint requires approximately ten or more safety personnel who require extensive and ongoing training on safety standards. In many cases, the need for 24-hour safety supervision results in long working hours that in turn, cause miscalculations and errors, safety violations, and injuries.<\/p>\n<\/div><\/div>\n\n\n\n

In addition, manufacturers often encounter regulatory issues that can put them at risk. In many cases, fines can range from tens of thousands to hundreds of thousands of dollars per violation. Longstanding and repeated problems can lead to government actions, including lawsuits, that can top $1 million.<\/p>\n\n\n\n

Many manufacturers rely on video feeds to analyze processes and events along production lines. Staff reviews these videos, looking for errors, infractions, or larger problems. For this bottling manufacturer, the manual video review workload was significant and only offered a reactive approach to safety.<\/p>\n\n\n\n

To safeguard workers, specialists checked for several important things, including whether workers on the line were wearing equipment and goggles correctly, handling machinery and equipment correctly, staying in authorized areas, avoiding vehicle and robotic paths, and following guidelines about how products and materials should be stored or transported.<\/p>\n\n\n\n

The existing monitoring and inspection process was costly and time intensive. The task required dozens of safety personnel working long hours. Workers had to stay focused at every moment. If an inspector\u2019s attention waned, an error or violation could go undetected. As hours passed, the odds of missing a violation piled up.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Unleashing the Power of Machine Vision and AI<\/h2>\n<\/div>\n\n\n\n
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There\u2019s a better way. Machine vision and AI can automate monitoring and inspection\u2014and deliver instant notifications and alerts when something goes awry. Moreover, with real-time visibility, an organization can build the safety framework with a best-in-class solution that\u2019s quickly and easily deployed\u2014using prebuilt algorithms, existing cameras and Industrial PCs (IPCs), and a browser-based dashboard.<\/p>\n\n\n\n

The bottling company recognized the need to establish a more automated and proactive monitoring framework. Ease of use and speed of implementation were critical success factors. It required a technology framework that could be installed easily and, ideally, a system that could automatically flag problems in real time, greatly reduce, or even eliminate human errors and dramatically cut costs. And a system that would also allow the bottler to improve training processes to help further reduce injuries and associated problems.<\/p>\n\n\n\n

The company hoped to take the safety monitoring process into the digital age through machine vision and AI\u2014but without revamping its core IT systems. The bottler already had a great deal of infrastructure in place. For example, one 37-acre site with 1,500 employees had 65 cameras. Another 11-acre site with 1,000 employees had 54 cameras. IoT-connected safety cords and smart locks were also used for protection in high places and underground wells. All of these devices and systems had to be integrated with the new system.<\/p>\n\n\n\n

Recognizing that it could adopt a more advanced and evolved way to automate occupational safety, in March of 2022, the bottler began exploring options and vendors\u2014eventually deciding to move forward with a sophisticated and \u201csmart\u201d factory production safety solution from Aotu and Innotech. Aotu\u2019s automated video management solution, built on Innotech\u00ae architecture, offered an efficient way to evolve to smart manufacturing and an advanced level of automated safety.<\/p>\n\n\n\n

With Innotech and Aotu on board, the company embarked on a safety transformation project to revamp security processes at the ten factories covering half of China.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Transforming a Vision into a View
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Aotu\u2019s BrainFrame platform was the foundation for the new safety automation framework. The platform optimized on Innotech offers plug-and-play Vision Capsules, which are pre-designed and pre-tested algorithms designed explicitly for factories optimized on Innotech hardware. As a result, the company could skip AI training and transition straight to a fully functional safety automation system. From the moment the video stream from the existing cameras was connected to the Aotu solution, it was possible to spot violations in real time.<\/p>\n\n\n\n

The technology framework enabled achieving results within three months of initiating the project. The bottler switched on the new machine vision systems at the first two sites in June 2022.<\/p>\n\n\n\n

Yet the goal to improve safety and operations didn\u2019t stop there: the existing camera infrastructure\u2014including settings and configurations\u2014was redesigned and updated to address specific business scenarios. Together, these represented a complete set of safety procedures that addressed behavioral issues, transport practices in the factory, the misuse of safety equipment, and other general workplace issues.<\/p>\n\n\n\n

Altogether, the bottler incorporated more than 1,000 existing cameras into the system. The smart cameras oversaw manufacturing line practices and a variety of other areas and activities, including:<\/p>\n\n\n\n