Production IoT for DX in Manufacturing Industry – Latest Tools and Case Studies
The environment is becoming more and more conducive for companies of all sizes to adopt IoT for their manufacturing and production processes. Each company will need to develop a plan for implementing IoT that is appropriate to its own needs. In doing so, it is important to consider not only the short-term effects of IoT as a mere “kaizen” on the shop floor, but also the medium- to long-term vision of IoT as a key component of a company-wide system, which will lead to improved competitiveness.
In order to achieve digital transformation (DX) in the manufacturing industry, it is important to achieve “digital transformation of the engineering chain, centered on 3D models,” “digital transformation of the supply chain, including production processes,” and “optimization of overall corporate activities by linking the above two, as stated in the 2020 White Paper on Manufacturing.
In this context, the IoT of production processes is one of the key components in terms of
- Transforming “tacit knowledge” into ” explicit knowledge” and utilizing digital technology will greatly improve operational efficiency and utilization rates.
- Visualizing the skills of aging skilled technicians will enable them to pass on their skills.
- Optimization of the entire supply chain process, including order receipt, production management, production, distribution, sales, and after-sales service.
- For example, it will be possible to provide accurate and quick responses to quotations and delivery dates.
- Furthermore, by linking with the engineering chain, the entire product development and production supply process can be optimized.
- For example, by being able to simulate the production process at the design stage, it is possible to study production periods and costs, and thus optimize the process in a short period of time through flexible responses.
- This will lead to improved dynamic capability, such as overseas expansion and flexible production planning.
- The production process can be made into a service, enabling the creation of new business models such as providing technology to other companies.
New environments, tools, and services for the IoT of production processes are beginning to spread. While the efficient use of these tools and services will make it possible to realize the above benefits, companies that are unable to utilize them may lose their competitive edge.
Case of Kyoto Semiconductor
They have started to convert some of their equipment to IoT using a combination of Raspberry Pi and various sensors, and monitor the operation status over the network.
By automating the sending e-mails to detect abnormalities, this system allows workers to check the operating status of equipment and identify abnormalities at an early stage, even if they are not there.
The sensor data is automatically recorded to a server on the network. Therefore, when an abnormality occurs or the condition of the equipment changes before or after maintenance, the data on the operating status of the equipment in question can be reviewed, and the “awareness” that has been based on the experience and knowledge of skilled workers to identify and deal with problems can be shared with even less experienced workers.
Early detection of failures and analysis of operational status data will reduce downtime by 70%, analyze the causes of previously unknown failures, improve the speed of improvements, and enable the accumulation of data for failure prediction. In addition, by reducing costs and automating the failure prediction function and analysis through the use of AI, etc., they expect that the effect will be equivalent to an increase in sales of 500 million yen in five years.
“Amazon Monitron” by Amazon Web Services (AWS)
Amazon Monitron includes
- Sensors to capture vibration and temperature data from devices (Amazon Monitron Sensors)
- A gateway device for securely transferring data to AWS (Amazon Monitron Gateway)
- Monitron service that uses machine learning to analyze data and detect abnormal machine patterns (Amazon Monitron ML-based service)
- A companion mobile app for configuring the device to receive reports on its behavior and alerts about possible machine failures (Monitron mobile app)
Users can start monitoring the health of their equipment in minutes without any development work or ML experience, enabling predictive maintenance using the same technology used to monitor equipment in Amazon Fulfillment Centers.
As an example of the price,
5 sensors, 1 gateway, and Amazon Monitron service (1 year)
for a total of 965 USD (about 105,000 yen for the first year).
Amazon Monitron
Detect abnormal machine behavior and enable predictive maintenance
“JIGlet” by Murata Manufacturing and ACCESS
Murata Manufacturing Co., Ltd. and ACCESS have launched “JIGlet,” a smart manufacturing support tool, on February 19, 2021.
It includes
- “Illuminance device” to detect when a work lamp is turned on or off
- “Button device” to count the number of buttons pressed.
- “Dice device” to operate and record time during any work.
In addition to the three types of sensor devices with built-in data communication SIM
- Chat Application for screens for data collection, visualization and notifications
is also included.
For Price, for example, if you start with three sensor devices, the cost is 366,000 yen for the first year and 126,000 yen per year after the second year.
THK OMNIedge
In 2019, THK also began offering OMNIedge, a system that enables condition diagnosis and predictive detection by attaching sensors to machine components and using proprietary algorithms to quantify and analyze the collected data via a secure communications network.
About 1,000 units of the system have already been installed at customers and their plants, according to the company.
The price ranges from 8,000 yen per device per month.
An IoT Service for Manufacturing OMNIedge
What is IoT using Raspberry Pi?
The Kyoto Semiconductor example above is “combining Raspberry Pi and various sensors to create IoT”, but how exactly does one go about developing such a system?
An example for beginners is available as a video from AMUY Inc.
Summary
As mentioned above, an environment is being created in which companies of all sizes can adopt IoT for their manufacturing production processes. Each company will need to develop a plan for introducing IoT that is appropriate to its own needs, but in doing so, it is important to consider not only the short-term effects of IoT as a mere “kaizen” on the shop floor, but also the medium- to long-term vision of IoT as a key component of a company-wide system, which will lead to improved competitiveness.