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In 2020, every third fatal accident in Japan’s manufacturing industry was caused by workers getting caught in or between equipment. In order to meet the challenges of increasingly complex factories, Edge AI introduces innovative possibilities for on-site safety management. Making real-time image analysis a reality, Edge AI poses a promising technology for situations where every millisecond counts.
Key Take-Aways
- As severe injuries and fatal accidents are a major concern especially in the manufacturing industry, the complexity of so-called Smart Factories is calling for new safety measures.
- Edge AI is all about real-time processing and analytics to drive greater efficiency and safety. Being called a “revolution in manufacturing”, Edge AI performs inferences right at the data source and at significantly lower running costs than solely cloud-based solutions.
- No matter if it’s the monitoring of humans interacting with robots, the detection of objects located too close to machinery, or the surveillance of shop floors that are frequently rearranged – the Edge AI Camera removes blind spots from supervision.
Common Safety Challenges In Today’s Manufacturing Industry
Accidents in the workplace are especially persistent in the manufacturing sector, and the number of incidents is on the rise. In 2020, stationary machinery (such as conveying and metal manufacturing machines) was the causal agent in 43% of all fatal accidents in Japan’s manufacturing industry. 33% of the total fatal accidents in the industry were caused by parts of the workers’ bodies getting caught in or between heavy equipment. (Source: JISHA)
Understandably, the securing of safety is the number one priority for manufacturing companies. However, as manufacturing plants are becoming increasingly complex (collaborative robots working alongside human workers, frequent rearrangement of machines on the shop floor, etc.), conventional approaches are not feasible or not sufficient any longer. For example:
1. Secluding areas of risk by fencing them off may actually increase the risk of workers getting caught in the equipment as their movements are restricted. In many cases, these designated areas of danger are located at a great distance from the actual machine operator. As the machine area might not be fully visible from a remote control center, hazardous (and usually vastly underestimated) blind spots emerge. If factory machinery starts moving while an undetected worker is still within the restricted area, there is a high risk of their hands or other body parts getting caught in the running machine.
2. As workers might be wearing protective clothing from tip to toe, the use of thermal sensors to detect them near equipment is not a realistic option.
3. If the shop floor layout is rearranged frequently (for example, if a factory rents the shop floor to different external producers), safety tools that are fixed in place and non-adjustable cannot be implemented.
4. Solutions solely based on cloud technology require a stable network connection. Due to its nature, the data transmission to a remote cloud server requires time. However, when it comes to preventing accidents, each millisecond counts. That makes cloud-based solutions a less than ideal choice for safety applications.
With the progression of Industry 4.0 and IoT devices (network-connected devices collecting and transmitting data), new promising solutions are emerging to meet the rising challenges of factories. The recent coronavirus pandemic has been an especially eye-opening event to many companies, once again highlighting the importance of continuous innovation.
What Is a Smart Factory?
In the era of Industry 4.0, companies leverage digital technologies (such as Artificial Intelligence and Big Data) to substantially transform their way of working. Connectivity is key to this process. In a so-called “Smart Factory”, humans, machines (such as collaborative robots), and processes interact seamlessly on a highly digitized shop floor.
In a Smart Factory, sensor-equipped devices are implemented throughout the production area to continuously collect and process data. While smart systems alone might already be improving productivity, analyzing the aggregated data, making it accessible throughout the company, and turning it into meaningful actions seems to be the biggest challenge.
Now, with the help of AI, this data is not only translated, but interpreted by fully automated processes. Being embedded within an end-to-end data management tool, Smart Factories are able to gain deep insights like never before. These insights allow them to make informed, data-driven business decisions and even make predictions regarding future performance and operational health – gaining an invaluable advantage over competitors.
Motives for Becoming a Smart Factory
There are many different and intertwined motives for factories to become “smart”. Most if not all companies will eventually undergo a digital transformation process in order to stay competitive and innovative in the future market (learn why digital transformation is key to survive in our dedicated blog article).
With the help of AI-powered image analysis and Big Data management, a Smart Factory can successfully optimize both its internal and external processes, improve product quality, reduce costly machine downtimes to a minimum, and, foremost, prevent accidents.
Given this new level of complexity within manufacturing companies, automated safety management has become a necessity. Edge AI enables factories to:
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- Observe workers’ movements within a factory
- Secure the interactions between humans and machinery (such as collaborative robots)
- Detect when laborers collapse or are injured/ill
- Monitor suspicious activity and the improper use of equipment
- Report unauthorized access of dangerous or restricted areas
- Take immediate action in case of emergency (such as stopping the machine or send alerts to supervisors)
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Edge AI Brings Image Analysis Right to the Data Source
Working closely with leading companies from various industries, we have learned that there is no “one-size-fits-all” approach to AI and image analysis. As requirements vary significantly from customer to customer, we wanted to develop a modular solution that is highly versatile and fully customizable, while utilizing the latest technology available.
Earlier, we mentioned the challenges associated with cloud-based solutions. Sending all raw data back and forth between a distant cloud server is time-consuming and costly. Now, Edge AI moves the computational power to the actual location. It is able to perform inferences within a nano-computer right at the data source, preventing network delays and large cloud-computing fees.
As data is being processed locally without transmitting it to an external environment, Edge AI also addresses the privacy and security concerns of many manufacturing companies.
Nonetheless, there is still room for cloud technology to be leveraged. For example, once data has been processed at the “edge location”, it may be sent to a cloud environment for storage and further analysis.
Fast, Versatile and Low Cost – How Manufacturing Companies Benefit From Edge AI
In the Avinton Edge AI Camera machine vision plays a central role. Through the fully automated collection of sensor data (primarily visual data), the AI engine gains a deep understanding of a situation. The principle of “making sense from visual data” can be compared to human vision. However, machine vision is able to detect patterns faster and more precisely than any human could.
The Edge AI Camera can be equipped with multiple sensors. This allows us to collect additional types of data specific to the customer’s individual requirements (such as sound, vibration, temperature, humidity, etc.). As the AI within the nano-computer analyzes the data fully automated and in real-time, Edge AI proves especially suitable for situations in which every millisecond matters.
For example, if heavy machinery or a collaborative robot starts moving and the edge device detects a worker standing too close, an immediate action (such as stopping the machine or sending an alert) can be triggered to avoid injuries. At assembly lines, Edge AI technology can play a crucial part in preventing costly downtimes and increasing the overall equipment effectiveness (OEE) score. And even if the manufacturing plant rearranges the shop floor layout frequently, Avinton Edge AI Camera can be adjusted accordingly.
Features of an Edge AI Camera
While there are many hardware manufacturers and software companies out there, many only provide certain parts. At Avinton, we combine digital transformation consultation and software development with AI and IoT device implementation. That way, we are able to deliver holistic and fully customized solutions, while putting a strong emphasis on security.
We will carefully assess our customer’s individual requirements and prepare just the right AI model to implement in the AI camera. Please find an overview of ready-to-use image and audio analysis features beneficial to manufacturing plants below.
Object detection:
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- Detecting body parts (such as hands) in close proximity to heavy machinery or robots
- Detecting if proper safety gear is being worn (helmets, protective glasses, hygienic masks, safety vests, etc.)
- Detecting forgotten maintenance tools, loose bolts, or foreign objects within the machinery
- Detecting surface anomalies, such as corrosion or cracks
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Depth perception:
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- Measuring distances to enable volumetric measuring, gauging of objects, 3D scanning, etc.
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Speed estimation:
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- Estimating the speed of moving objects (e.g. for situations in which careful movements are required)
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Posture recognition:
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- Tracking the posture of workers and recognizing postures that don’t occur usually (e.g. collapsing or getting injured)
- Recognizing misuse of machinery or other suspicious behavior
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Sound classification:
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- Identifying sound patterns (e.g. of machine sounds) and detecting anomalies long before an actual breakdown
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Why Edge AI Is Leading the Way
To sum it up, Edge AI equips factories with unprecedented sensing capabilities for seamless on-site safety management. Avoiding lag-prone and costly cloud transmissions, we bring computing power right to the location. Performing inferences faster and more secure than any other preceding solution, Edge AI is most suited for situations where speed is of the essence.
By leveraging the latest technology, the Avinton Edge AI Camera significantly raises factory safety in the era of Industry 4.0. Its wide range of real-time image analysis features and customizability help remove “blind spots” from shop floor supervision, securing worker safety at production. Our solution is perfectly scalable: as requirements naturally change or increase over time, so does the feature portfolio.
Outside of the manufacturing industry, our Edge AI solutions have proven effective in managing traffic and public transportation, securing construction sites, improving marketing at the point-of-sales, ensuring safety in public spaces and healthcare, and maximizing yield in agriculture.
Basing all strategic consultation and software development on a feasibility analysis and a thorough proof-of-concept phase, we are confident to deliver highly effective and yet economical solutions. It is our goal to solve the specific needs of our diverse customer base on their way to become fully data-driven companies.
Find out more on our Avinton Edge AI Camera page, or get in touch with us for demos and consultation.
We will be happy to provide you with more information.