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The top three ways computer vision can make a major impact for manufacturing

Let’s meet Mike, who oversees worker safety for a large manufacturing firm. He ensures employees on the job floor adhere to the standard guidelines issued by the company. Mike spends most of his time in the factory’s command center, watching live feeds from cameras positioned throughout the shop floor. If he notices an employee without a helmet or a safety jacket, he immediately calls the manager to ensure the safety protocols are followed. There are times when Mike must visit the shop floor to talk to the employee.

The pandemic had a major impact on Mike’s department. Since most of them work in-person, in close proximity to each other, Mike and his team of four contracted COVID-19. Several team members were hospitalized and spent time at home recovering. During that period, the company hired an external firm to oversee employee safety. The investment was huge because it was a short-duration contract — but unavoidable, because worker safety is of prime importance.

Do you think Mike’s employer could have handled things differently?

Let’s take another example: Say a large Europe-based manufacturer is struggling with its quality control processes. The plant operates 24/7 with staff working in shifts. Its customers have been complaining about product quality and uniformity. Since the plant is dependent on humans to handle the end-to-end processes, slippages are bound to happen. Despite their best efforts, they have been able to reduce human errors — but can’t eliminate them. Or can they?

A visionary technology

Thanks to the rise of advanced digital technologies, companies today have tools like computer vision to address worker safety and quality process issues.

Computer vision is a breakthrough technology that uses deep learning AI algorithms to recognize events and trigger automatic alerts. This innovative technology vision relies on high compute capacities enabled by graphics processing units (GPUs) to process massive amounts of complex data in real-time. A typical computer vision setup comprises motion cameras that capture videos and share them with edge servers that use AI and deep learning algorithms to identify deviations from the norm. This information is shared with the worker safety department or quality assurance team, who can then take the necessary action.

Here are three important ways that manufacturers can employ computer vision within the enterprise to generate tangible benefits.

1. Creating safer shop floors
These advanced technologies make computer vision very effective. Due to the pre-configured algorithms, it can quickly detect and identify objects and can be used to improve worker safety and enhance productivity in the manufacturing sector. For example, computer vision can be used to detect if security equipment on manufacturing floors has been regularly serviced, ensure employees are using safety equipment like helmets or safety glasses, or wearing masks and practicing social distancing.Computer vision can be deployed 24/7 and augments human capabilities by enabling employees on the shop floor or other departments to carry out their duties efficiently. If the system senses any deviation from the norm, it sends real-time alerts to the worker safety or security officials.

2. Making the quality process error-free
Computer vision algorithms can be improved and altered depending on your unique requirements, making it a great tool for quality control. Some flaws are too subtle and small to detect by the human eye, resulting in production errors and quality problems. Manufacturers must adhere to strict regulatory requirements, failing which they could face lawsuits. Computer vision can detect subtle issues in the quality of products and remove defective products, making the entire process efficient. It enhances human efficiency by, making the whole process error-free and helping maintain product consistency.

3. Securing the plant perimeter
Computer vision can also help in securing plant operations and reducing instances of theft. Using facial recognition and contactless access control, computer vision ensures that only authorized personnel have access to the facility premises. It can also help detect whether sensitive areas like emergency exits are free of obstructions to ensure easy movement during a crisis. By using computer vision, companies can also remotely secure areas where it is hazardous for human beings to be present.

Computer vision uses automated algorithms to ensure both employee safety and quality control are not compromised. It helps manufacturing companies increase employee productivity, maintain stringent quality control, and even optimize security. As manufacturers digitalize their plant operations, implementing computer vision will bring them one step closer to becoming true digital enterprises.

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About Emmanuel le Roux
SVP, Global Head of Big Data, Atos
Responsible for the overall Big Data infrastructure portfolio, Emmanuel leads the development of innovative Big Data Analytics, Machine Learning and AI solutions for the Enterprise market. The global portfolio includes Atos Enterprise Servers (x86, Mainframe), the SAP Hana, Oracle, Hadoop, AI and Analytics appliances as well as the Big Data Software and Services teams. Emmanuel has many years of experience in the IT and telecoms industry having worked in product management, business development, marketing & sales as well as R&D, architecture & strategy and program management. He is an expert in Big Data solutions (Hadoop, Analytics, ML and AI), IT infrastructure (servers, storage, networking), server virtualisation, cloud computing, OS, Database, Middleware, OSS/BSS and Voice over IP technologies.

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