With the spread of high-speed internet and the evolution of IT, the manufacturing industry is also moving towards smarter manufacturing to improve operational efficiency and predict failures, etc. Edge devices that enable real-time information collection on-site are becoming increasingly important.
This time, we will explain the types and roles of edge devices that are driving smart manufacturing in the manufacturing industry, their relationship with AI and IoT, and examples of their use. Please use this as a reference if you are a manufacturing management person in the manufacturing industry considering using edge devices to make your manufacturing smarter.
What are edge devices in the manufacturing and production management fields?
To understand edge devices in the manufacturing industry, you must first get an overview of edge devices and then understand what types there are. Here, we will provide an overview of edge devices and the types of edge devices used in manufacturing sites in particular.
What is an Edge Device?
In the manufacturing industry, an edge device is a single-function device that collects data at the level closest to the equipment or facility, or a device or apparatus with a certain degree of processing capability.
The advantage of this is that it can be placed near devices and equipment and collect data in real time. In addition, if the device has a certain level of processing capability, data can be processed on the spot without delay, which can reduce the load on networks and data centers.
Incidentally, there is another term similar to edge devices: "IoT devices." IoT stands for "Internet of Things," so the premise is that they are connected to the Internet. On the other hand, "edge" simply means the end, and does not assume a connection to the Internet. Both are assumed to exist at the end, but it can be said that edge devices that are connected to the Internet are called IoT devices.
For more information on edge computing, please see this article:
Why is edge computing attracting attention? What is the difference between cloud and on-premise computing? | Stratus Blog
Main types of edge devices in manufacturing
There are many different types of edge devices. Here we will introduce the main types of edge devices used in the manufacturing industry.
- These include sensors and cameras that collect data
. They are used to check the operation status of machines, inspect the quality and appearance of products, and monitor manufacturing processes. Depending on the purpose of use, many types of devices are used, such as acceleration sensors, vibration sensors, high-resolution cameras, and multi-camera systems. - A typical example of a device that collects data and controls machines
is the PLC (Programmable Logic Controller). A PLC is a device that automatically controls equipment and facilities. By setting the actions you want the equipment or facilities to perform automatically in the PLC, you can remotely control the connected equipment or facilities. - Devices that send collected data to the outside
are not generally included in edge devices, but devices with sensor functions in the gateway may be treated as edge devices. The gateway acts as an intermediary for communication between edge devices and the cloud, enabling data processing that aggregates multiple edge devices. - Devices that process collected data
These are devices that instantly process data collected from devices such as sensors and cameras on-site. These include small, power-saving single-board computers and embedded systems. Of these, devices capable of complex processing are specifically called edge computing.
Mobile devices (smartphones) and tablets are also classified here. In addition to monitoring production lines, issuing work instructions, and managing inventory, these devices use applications to monitor the entire production line in real time.
Examples of edge device usage in manufacturing
Examples of how edge devices are used in manufacturing include the following:
Machine Monitoring
Using sensors and cameras, we monitor the operation status of manufacturing lines and machines. It allows us to monitor the operation status of machines in real time, enabling us to respond quickly when problems occur, improve productivity, and control product quality.
Improving the production process
By analyzing the operation status of machines, it is possible to identify bottlenecks in the production line and make improvements. In addition, by measuring the work time at each process on the production line, it is also possible to propose improvement measures that will lead to increased productivity.
Inventory management
You can efficiently manage your product inventory. You can install sensors in the warehouse to monitor the amount and location of your inventory. You can also use edge devices that can read 2D barcodes to manage the in- and out-of-stock of your inventory.
Affinity between edge devices and AI
According to a market research report published by Global Information Co., Ltd. in January 2022, the IoT market for manufacturing is expected to reach US$399.08 billion by 2026, up from US$175.3 billion worldwide in 2020.
Reference: Internet of Things (IoT) Market in Manufacturing – Growth, Trends, COVID-19 Impact, Forecast (2022-2027) | Global Information Co., Ltd.
IoT in the manufacturing industry continues to grow rapidly, but it also comes with a big challenge. The amount of data acquired by IoT is increasing dramatically, and data processing and analysis on the cloud is reaching its limits. That's why the combination of edge devices and AI, which has a high affinity, is now attracting a lot of attention. One of the reasons for this is that by combining it with AI, it is possible to analyze large amounts of data that human judgment cannot keep up with, and obtain insights.
As mentioned above, edge devices process data collected on-site, reducing the load on central data centers. Combining this with AI not only makes it possible to process data, but also to analyze and make decisions quickly on-site.
For example, if an edge device detects a machine abnormality, AI can identify the cause of the abnormality and determine the need for maintenance. In recent years, edge devices with AI already built into them have also become available. This will make it easier and faster than ever to analyze data and determine optimal production line speeds and factors that affect product quality.
In addition, real-time data analysis using AI on-site requires advanced processing power, but if that processing stops, the impact will be enormous.Specifically, it is possible that downtime will increase due to the inability to detect failures in real time, and the safety of equipment and workers will be reduced.
For this reason, you should consider an edge computing platform that is capable of complex processing and has high availability. Please also refer to this page for information on the platform requirements for using edge computing in the manufacturing industry, such as security functions and low operational burden.
Explaining the advantages and disadvantages of using edge computing in the manufacturing industry and the necessary requirements | Stratus Blog
Utilizing edge devices is important for making manufacturing sites smarter and more efficient
An edge device is a single-function device that collects data at the level closest to equipment or facilities, or a device or apparatus that has a certain level of processing functionality. Some devices are classified as edge computing devices, which not only transmit collected data to a data center via a network for storage, but also process the data on the spot.
In recent years, the use of IoT has been expanding in the manufacturing industry, but the amount of data handled is increasing year by year, and there are now limits to data processing and analysis on the cloud.
In order to make manufacturing sites smarter, there are hopes for the use of edge devices combined with AI, called "edge AI," which enables more efficient and faster data processing on the edge side. For more information on edge AI, please refer to this article:
Edge AI - A key technology for retaining the judgments and experience of experienced engineers | Stratus Blog
