Predict anomalies before they happen: Ultra-compact sensor modules redefine the status quo of equipment maintenance

Factories and production sites need to prevent abnormal conditions of machinery and equipment to minimize downtime. Productivity can be improved by anticipating problems and preempting maintenance, rather than reacting to failures. To facilitate such predictive maintenance, TDK has developed the i3 Micro Module – the world’s first ultra-compact sensor module with embedded edge artificial intelligence.

Factories and production sites need to prevent abnormal conditions of machinery and equipment to minimize downtime. Productivity can be improved by anticipating problems and preempting maintenance, rather than reacting to failures. To facilitate such predictive maintenance, TDK has developed the i3 Micro Module – the world’s first ultra-compact sensor module with embedded edge artificial intelligence.

The technical challenges of implementing predictive maintenance on the production floor

Generally, production sites should operate their machinery and equipment at full capacity. Because operating at full capacity can maintain high productivity – in fact, many factories operate 24/7 year-round. Today, there is great interest in the concept of predictive maintenance as a means of reducing machine and equipment downtime. Predictive maintenance is the use of sensors to monitor plant machinery in real time, predicting abnormalities and failures before they occur, and taking action first.

Predictive maintenance reduces the risk of failure, minimizes production downtime, and extends equipment life compared to traditional reactive maintenance that takes action after a failure or abnormal condition. This is an important theme*1 in the ongoing global smart factory movement and is expected to be adopted in various production environments.

In predictive maintenance, the use of sensors to monitor the condition of equipment and machinery in real time is called condition monitoring, and it is seen as a particularly critical technology. However, trying to achieve this will face two main challenges. First, in a factory, the various sensors and analytics tools are often provided in disparate systems, which complicates the collection and processing of data, making it difficult to leverage the analytics results. Second, due to cabling and other physical constraints, sensing is often not possible where the user wants it, making it difficult to achieve optimal condition monitoring.

Predictive Maintenance of Plants

Predict anomalies before they happen: Ultra-compact sensor modules redefine the status quo of equipment maintenance

Abnormalities and failures of machinery and equipment can be predicted mainly by monitoring motor movements inside factories and industrial robots using various sensors.

Ultra-compact sensor module solution integrating sensors, edge AI and networking

The i3 micromodule developed by TDK, the world’s first sensor module*2 with built-in edge AI, overcomes both of the above challenges.

The i3 Micro Module integrates the capabilities of various sensors (vibration, temperature, sound, pressure, etc.), edge AI and mesh networking*3 into a single unit, facilitating data aggregation, integration and processing, which was difficult to achieve in the past . Since the i3 Micro Module is an ultra-compact, battery-powered wireless sensor module, users can sense anywhere they want without physical constraints such as wiring. This greatly facilitates the prediction of machinery and equipment anomalies, enabling ideal condition monitoring.

Brings many benefits to the production floor, such as monitoring by visualizing equipment information rather than relying on human labor, understanding the health of machinery and equipment to help extend its life, and minimizing production downtime by preventing unexpected failures – This helps to build an ideal predictive maintenance system.

The i3 Micro Module is a multi-sensor

Predict anomalies before they happen: Ultra-compact sensor modules redefine the status quo of equipment maintenance

By attaching this compact module to the device, various sensors can monitor conditions such as vibration, temperature and sound in real time. Various abnormalities and faults can be detected in time.

Edge AI-based predictive maintenance (concept map)

Predict anomalies before they happen: Ultra-compact sensor modules redefine the status quo of equipment maintenance

The data detected by the sensors is processed by the embedded edge artificial intelligence of the i3 micromodule. There is no need to aggregate and analyze data in the cloud, minimizing network traffic. Modules are connected to each other via a wireless mesh network, and connections are automatically formed between modules simply by installing them.

Artificial intelligence at the edge gives great potential to sensor modules

Predict anomalies before they happen: Ultra-compact sensor modules redefine the status quo of equipment maintenance
Endo Kazuyuki
CbM Development Department
Condition Monitoring Business Department
Next Generation Products and Solutions Grp.

Battery-powered modular products such as i3 micromodules require advanced technology to miniaturize and integrate sensors and wireless communications, and to optimize everything within the control module in an energy-efficient manner. By applying technology cultivated by TDK’s extensive experience in the two core product fields of Electronic components and batteries, TDK has been able to achieve miniaturization, integration, and energy-saving control of these components. TDK has also long been committed to the research and development of edge AI as an application technology based on its sensor products, and has successfully developed the world’s first sensor module with embedded edge AI capabilities.

Kazuyuki Endo of TDK’s Next Generation Products and Solutions Grp. talks about the future of the i3 micromodule. “We will continue to incorporate new sensing technologies and power technologies such as solid-state batteries, while expanding the range of applications and integrating them into smaller packages for embedding in various devices. We also plan to further refine embedded edge AI , enabling it to continuously learn what is happening at the point of installation and make autonomous decisions, enabling the module to support the type of advanced decision-making required for integration frontiers.”

TDK also envisions offering customers i3 micromodules as a solution for integrating cloud integration.

TDK will continue to help realize the next generation of smart factories through advanced software and hardware development and integration.

The Future of i3 Micromodules: Modules Supporting Advanced Decision Making

Predict anomalies before they happen: Ultra-compact sensor modules redefine the status quo of equipment maintenance

TDK will continue to incorporate new sensing and power technologies, such as energy harvesting and solid-state batteries, into smaller packages, while expanding the range of applications, so that modules can be embedded in various devices.

the term

1. Smart Factory: An initiative targeting the frontiers of manufacturing that facilitates the collection and utilization of real-time big data, as well as the automation and autonomous operation of production lines, by leveraging digital technologies such as the Internet of Things, artificial intelligence and robotics.
2. Edge AI: Technology that builds artificial intelligence into edge devices such as IoT devices and sensors, allowing edge devices to learn and infer. Inference and decisions are performed within edge devices based on data collected through the edge.
3. Mesh Network: A communication network in which multiple relay devices, equal to each other, form a mesh transmission path and pass data back and forth through them.

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