From the perspective of global manufacturing transformation trends, intelligentization has become a core direction for countries to seize the commanding heights of industrial competition, and China is accelerating breakthroughs in this field under the guidance of its "manufacturing power" strategy. Entering the critical period of the "15th Five-Year Plan," China manufacturing industry has officially entered a crucial stage of transitioning from a "manufacturing giant" to a "manufacturing power." The deep integration of "artificial intelligence + manufacturing" is continuously reshaping production models, management methods, and the industrial ecosystem, promoting the large-scale implementation of intelligent technologies from pilot projects.

As a benchmark practice in the field of intelligent manufacturing, the Lighthouse Factory is a concentrated embodiment of the achievements of the integration of "artificial intelligence + manufacturing". In the AI applications of the Lighthouse Factory, 77% of the top five core use cases utilize analytical AI. This data fully demonstrates the core value and priority of analytical AI in intelligent manufacturing scenarios, with industrial equipment health monitoring being a typical area of deep penetration. Industrial equipment health monitoring technology is deeply integrating with analytical AI and edge computing, accelerating its evolution towards "rapid localization of known faults" and "early warning of unknown/progressive faults," becoming a crucial breakthrough in addressing pain points in the manufacturing industry such as "difficult equipment maintenance, high transformation costs, and insufficient release of data value".

However, regardless of how industrial equipment health monitoring technology iterates and upgrades, technology providers always face three common challenges during the implementation phase: How to enhance the reliability of analytical AI, improve the accuracy of fault early warning, reduce false alarms and missed alarms, and effectively reduce unplanned downtime? How to achieve unified coverage of health monitoring for a mix of new and old equipment with minimal production disruption? How to achieve seamless integration of the monitoring system with the existing management system while ensuring data security?

Against this backdrop, TDK SensEI was born. Leveraging 90 years of technological expertise from the TDK Group, and refined through internal incubation, full-scenario application development, and continuous iteration and optimization, this platform integrates advanced sensor systems and complex software design into edgeAI customized hardware-software solution. It precisely matches the technological development needs of industrial equipment health monitoring, empowering intelligent manufacturing. More notably, TDK SensEI deeply integrates an intelligent decision support expert system for equipment operation and maintenance based on a "mechanism + AI" model . This system aims to improve the efficiency of equipment fault diagnosis, the accuracy of prediction, and the intelligence level of operation and maintenance decisions, injecting stronger technological momentum into industrial equipment health monitoring and management. TDK SensEI, originating from edge perception and excelling in intelligent analysis, uses analysis as a shield to protect the pulse of industrial equipment.
Since its inception, TDK SensEI has helped electronics manufacturing companies mitigate downtime losses significantly through on-site immersive R&D , improved production changeover efficiency in the beverage and daily chemical industries, and enhanced Overall Equipment Effectiveness in precision manufacturing and reduced unplanned downtime of port quay cranes by leveraging the ability of "self-developed sensors + edge computing + artificial intelligence" technology triangle . It provides "localized response + global technology " support, becoming a significant force in promoting the large-scale implementation of equipment health monitoring technology. Intriguingly, how does TDK SensEI address these three common problems? And how does its integrated intelligent equipment operation and maintenance agent function?

I. From reactive response to proactive prediction: Redefine the era of "passive emergency repair" in equipment management.

 "SensEI" precisely embodies the core positioning of "Sensor + Edge + Intelligence," and since its inception, it has carried the mission of "Low touch, No touch: enabling intelligent technology to penetrate the production line and ending redefine the era of 'passive emergency repair' in equipment management." This brand aspiration not only continues TDK Group's core philosophy of "giving back to culture and industry with abundant creativity," but also directly addresses pain points such as inaccurate equipment health monitoring and early warning, cumbersome adaptation, and difficulties in integration.

Mechanism and AI model work together to improve early warning accuracy.

TDK SensEI , centered on "equipment mechanism + AI model collaboration ," combines expert systems to enhance the reliability of analytical AI,establishing accurate fault mapping relationships for complex systems with nonlinear and strongly coupled characteristics. Simultaneously, the industrial models built by TDK SensEI integrate the experience of equipment operation and maintenance experts, coupled with multi-dimensional sensing data from TDK's self-developed sensors, enabling the generation of analytical reports that can interpret diagnostic paths. This significantly improves the accuracy of data interpretation and the timeliness of analytical decision-making in industrial scenarios . The SensEI edgeRX equipment monitoring and maintenance platform achieves fault early warning up to 48 hours in advance with an accuracy rate of 97.9%, reducing unplanned downtime by 72%, providing solid technical support for enterprises to build proactive operation and maintenance systems and reduce costs and increase efficiency.
 

Lightweight deployment and full-scenario compatibility enable unified monitoring of both new and old devices with low power consumption.

TDK SensEl, through a combination of lightweight multi-sensors and intelligent systems, and based on the "Low touch, No touch" product design philosophy, truly makes worry-free, low-intervention operation and maintenance management a reality. On the hardware side, its independently developed edgeRX edge intelligent sensors and edge intelligent gateways eliminate the need for complex wiring and can be quickly deployed in industrial environments with low temperatures. Installation disruptions to production are minimized, providing a solid hardware foundation for the stable operation of the system's data acquisition module and ensuring real-time, uninterrupted acquisition of operational data from both new and old equipment. On the software side, the SensEI AI algorithm incorporates multiple types of industrial adaptation algorithms for rapid adaptation to various devices, while also providing low-latency, lightweight algorithms for instant response. It supports the rapid construction of monitoring models for different process equipment, reducing modification costs by more than 40%, and supporting the monitoring of more than 20 industrial parameters, further expanding the system's application scope and enabling intelligent decision support capabilities based on " mechanism + AI" models to cover more new and old equipment.
 

Secure foundation + open ecosystem, achieving seamless system integration

TDK SensEI prioritizes security while balancing data security with system integration requirements. In terms of data security, sensor data is encrypted during both transmission and storage to prevent unauthorized access and data leakage, ensuring the security of device operation data. This provides a reliable data foundation for AI model inference and analysis, preventing data leaks or tampering from affecting the accuracy of analysis results.

It supports multiple communication protocols and industrial interfaces, including 4G LTE, WiFi 802.11b/g/n and BLE 5.0.It can directly connect to existing monitoring systems, ensuring smooth interaction between the " mechanism + AI" model -based intelligent decision support system and the enterprise's existing monitoring system. This allows for the acquisition of more multi-dimensional data, while simultaneously synchronizing analysis results and early warning information to existing systems. The SensEI AI platform offers flexible deployment on a local/cloud-based basis, easily achieving on-prem and cloud-based collaborative management. It also supports seamless integration with existing management systems such as MES and ERP, without requiring the reconstruction of existing business processes. Personalized maintenance suggestions generated by the system can be directly integrated into the enterprise's production management processes, guiding maintenance personnel to work efficiently and truly achieving a closed loop of "data-analysis-decision-execution."

After extensive practical application and refinement, TDK SensEI, with its edgeRX equipment monitoring and maintenance platform, SensEI AI algorithm components, and high-precision scenario-based sensors at its core, relies on an intelligent decision support system for equipment operation and maintenance based on a " mechanism + AI" model . This system achieves seamless collaboration across the entire chain, from sensor data acquisition and edge preprocessing to low-latency communication and algorithm analysis. TDK SensEI has further improved its three-tiered architecture of "sensor layer - platform layer - application layer," forming a replicable and easily implementable industrial equipment health monitoring implementation path. This helps enterprises upgrade their existing equipment operation and maintenance systems into an intelligent closed loop of proactive prevention, automatic optimization, and self-evolution, easily achieving a transformation from "passive emergency repair" to "proactive prediction" in operation and maintenance.

II. Rejecting "generic solutions," TDK SensEI directly addresses industry pain points.

TDK SensEI's innovation in operation and maintenance models does not rely on so-called "universal solutions." "Universal solutions" are difficult to adapt to the characteristics and operating scenarios of equipment in different industries, easily leading to incompatibility and failing to support core enterprise production goals. Its integrated intelligent decision support system for equipment operation and maintenance, based on a " mechanism + AI" model, consistently adheres to an "industry-customized" logic, rather than a "one-size-fits-all" universal application.

To this end, TDK SensEI takes "deep industry cultivation + modular design" as its core logic, decomposes the full-stack technical capabilities of "sensor hardware + edge computing + industry algorithms" into standardized modules that can be flexibly combined. Through a modular combination strategy of hardware adaptation, algorithm customization and network optimization, it accurately matches the special scenarios and core needs of different industries, and truly realizes "allowing intelligent technology to penetrate the production line".

Electronics Manufacturing: A "48-Hour Early Warning Revolution" for Motors and Pumps

The electronics manufacturing industry is characterized by precision, high automation, and 24-hour continuous production. According to industry data, the average annual unplanned downtime losses of leading companies account for 3%-5% of their revenue. The compatibility rate of general monitoring solutions with precision equipment is less than 40%, and the identification rate of low-frequency and early-stage faults by manual inspection is generally less than 30%. The disconnect between equipment monitoring and quality traceability is a prominent issue.
 
TDK SensEI team conducted three months of in-depth R&D at a leading domestic electronics manufacturer.By monitoring equipment operation, recording vibration and temperature data under multi-load conditions, and leveraging proprietary sensors to precisely capture vibration signatures,we enabled real-time local data processing through the edgeRX edge computing architecture, with algorithm latency reduced to milliseconds level.

Meanwhile, considering the precision and continuous operation characteristics of equipment in the electronics manufacturing industry, the intelligent decision support system for equipment operation and maintenance based on the "AI + mechanism" model was customized and optimized. On the one hand, the data acquisition module was optimized to more accurately capture subtle changes in the operating parameters of precision equipment such as motors and pumps, such as small fluctuations in bearing vibration frequency and subtle differences in pump pressure. On the other hand, the artificial intelligence and machine learning models in the system were adjusted to incorporate the fault characteristics and process parameters of equipment in the electronics manufacturing industry, improving the accuracy of predicting typical faults such as bearing wear and pump leakage. At the same time, in combination with the needs of enterprises for 24-hour continuous production, when generating maintenance suggestions, production gaps and spare parts inventory are given priority to avoid maintenance work from interfering with production.

The final solution was a "dedicated monitoring and maintenance solution for motors and pumps," which yielded significant results. The fault prediction accuracy rate reaches 98.6%, with motor bearing failures predicted 72 hours in advance and pump leakage 48 hours in advance. Unplanned downtime is significantly reduced annually, maintenance costs are reduced by 25%, and manual inspection workload is reduced by 60%. This solution has been simultaneously deployed to overseas factories. To address the differences in industrial environments in different regions, the environmental adaptability of the system's data acquisition module and the parameter configuration of the decision-making model have been further optimized, successfully adapting to the varying industrial environments of different regions.

Port quay cranes: "Intelligent alternative" to high-risk manual inspections

Port quay cranes are characterized by high-load continuous operation and high salinity and humidity along the coast. Industry data shows that among domestic terminals with a capacity of over 10,000 tons, only 28.7% have infrastructure with intelligent sensing functions, and more than 70% of the facilities rely on traditional operation and maintenance.

A sudden shutdown of a single quay crane at a port in China caused a daily loss of over 1.2 million yuan. Manual high-altitude inspection carries high risks, with an early fault detection rate of less than 20% and collaboration efficiency with automated equipment below 50%, severely restricting the upgrading of smart ports.
 
Addressing the operational characteristics and maintenance pain points of port quay cranes, TDK SensEI has developed a customized intelligent monitoring solution. In terms of hardware deployment, considering the corrosive effects of the high-salt and high-humidity coastal environment on equipment, corrosion-resistant sensors and edgeRX smart gateways are selected to ensure stable and reliable data acquisition. At the software and algorithm level, it deeply integrates with an intelligent decision support system for equipment operation and maintenance: through multi-dimensional data acquisition modules, it comprehensively covers core indicators such as vibration of key rotating components of the quay crane and temperature at overheating risk points, and can even capture subtle data such as stress changes in components under high-load operations. This data is input into a deep learning model trained on port industry fault characteristics, combined with a quay crane-specific fault feature library and adaptive threshold algorithms, to accurately identify problems such as gearbox pitting and bearing wear, completely avoiding the limitations of traditional manual inspections.

Meanwhile, when generating operation and maintenance decision suggestions, the system fully considers the characteristics of port operation scheduling, such as planning maintenance work during the idle window of the quay crane to avoid affecting the efficiency of cargo loading and unloading; for high-risk high-altitude inspection scenarios, the system reduces the frequency of manual high-altitude inspections through accurate fault location and early warning, and even completely replaces them in some scenarios, ensuring the safety of operation and maintenance personnel.

Ultimately, it enables early warning of critical component failures up to 72 hours in advance, significantly reducing unplanned downtime; reducing manual high-altitude inspection workload by 80%, completely replacing high-risk operation modes and reducing maintenance costs by 40%; optimizing the capital tied up in spare parts inventory; and shifting maintenance decisions from "experience-based" to "data-driven".

Beverage, Daily Chemical, and Pharmaceutical Industries: Flexible Intelligent Management Solutions for High-Speed Production Lines

Take the beverage and daily chemical industry as an example. It features high-speed continuous operation, multi-category flexible production, and strict hygiene compliance.Industry data shows that the CNC rate of key processes in major industrial enterprises in my country's beverage and daily chemical industry has reached only 63.3%, and nearly 40% of production lines still rely on traditional operation and maintenance models; Small and medium-sized enterprises face a triple bottleneck of "low automation, poor changeover efficiency, and frequent hygiene failures," with unplanned equipment downtime accounting for an average of 8.2% of output value loss.
 
To address the three core needs of high-speed operation, frequent production changeovers, and hygiene compliance, TDK SensEI, relying on its edgeRX equipment health monitoring solution, has developed an integrated "Flexible Production + Predictive Maintenance" solution tailored for a well-known beverage enterprise. In terms of hardware deployment, it precisely covers key equipment such as air blowers, mold making machines, heat sealing machines, and belt drive systems. Each piece of equipment is equipped with a dedicated sensor monitoring point, utilizing IP67-rated edgeRX intelligent wireless sensors and smart gateways, adaptable to harsh environments such as washing and disinfection. The sensors feature a compact design, adjustable direction, and can be deployed in confined spaces, comprehensively capturing vibration characteristics during the start-stop intervals of mold making machines, temperature changes in air blower bearings, and subtle anomalies such as gear failure, imbalance, misalignment, and looseness. After data is uploaded via the gateway, it is input into a model trained on fault characteristics from the beverage and daily chemical industry, dynamically identifying equipment anomaly patterns. Combined with a dedicated fault feature library and customizable adjustable anomaly sensitivity parameters, it accurately identifies early-stage faults, completely avoiding the drawbacks of traditional manual inspections: low efficiency, high missed detection rate, and susceptibility to contamination.

The solution has yielded significant results, precisely meeting the production and maintenance needs of the beverage and daily chemical industries: critical component failures can be predicted in advance, the frequency of unplanned downtime has been significantly reduced, and losses from single downtimes have been kept to a lower level; the efficiency of production changeover and commissioning has been greatly improved, and the delivery delay rate has been reduced to 4%, and the response capability for small-batch orders has been greatly enhanced; the workload of manual inspections has been significantly reduced, remote diagnostic coverage has reached 70%, and customized equipment health reports are generated monthly, providing precise support for maintenance decisions . Simultaneously, the edgeRX dashboard enables real-time visualization of equipment status, providing a replicable intelligent path for equipment management upgrades in industries such as beverage, daily chemical, and pharmaceutical.

Breaking free from the constraints of "general solutions" and focusing on industry-specific customization, TDK SensEI leverages its full-stack technical capabilities to continuously drive operational innovation across various industries, enabling proactive prediction to permeate the entire production chain and building a robust intelligent defense for efficient enterprise production.

III. TDK SensEI 2025-2026: From Deep Cultivation to Empowerment

Looking back at 2025, TDK SensEI has consistently worked closely with manufacturing companies. Its engineering team has ventured into high-temperature, noisy production lines, high-salt, high-humidity port terminals, and precision-controlled cleanrooms, continuously debugging and optimizing solutions to transform technical solutions into tangible value for enterprises. This hands-on approach to production allows TDK to accurately grasp the pain points and needs of enterprises' intelligent equipment management transformation, providing rich practical evidence for its technology iteration and solution optimization.

Looking ahead to 2026, TDK SensEI will continue to anchor its presence in the Chinese market with its core positioning of "originating from industry practice," and leverage its core advantages of "edge computing + artificial intelligence + self-developed sensors" throughout its development. Building on this foundation, TDK SensEI will continue to focus on the needs of Chinese enterprises, deepening its "localized service + global technology" concept: on-site dedicated teams will deeply integrate into the front lines of various industries, accurately identifying actual pain points under specific working conditions. Through a path of "sensor data acquisition + industry knowledge base + mechanism + AI model decision system optimization," they will refine customized solutions more suited to local scenarios. Meanwhile, global R&D resources will focus on upgrading core technologies, integrating cutting-edge sensing technologies and AI algorithms into industrial model construction, transforming them into practical capabilities that can be directly implemented by local enterprises.

From an industry development perspective, TDK SensEI's "originating from and serving industry" DNA, along with its full-stack technological capabilities, makes its "In Everything, Better" motto more than just an empty slogan; it represents a pursuit of the practicality and adaptability of intelligent manufacturing equipment management technologies. This unique advantage will also drive TDK SensEI to achieve broader industry penetration by 2026, becoming a key force empowering the high-quality transformation of China's manufacturing industry.

Equipment health is the cornerstone of intelligent manufacturing. TDK SensEI's technological approach and industry-focused strategy provide a viable model for the transformation of equipment management in the manufacturing sector from "reactive emergency repairs" to "proactive prediction." For companies seeking to upgrade their equipment management, it's crucial to focus on the compatibility of the intelligent decision support capabilities based on " mechanism + AI" models within the TDK SensEI solution with their specific industry needs, as well as the effectiveness of relevant case studies. Currently, the TDK SensEI China technical team offers customized equipment health management solution consultations. Companies can also apply for free equipment health assessments to obtain targeted maintenance and upgrade recommendations, further understanding how to address their equipment maintenance pain points through a combination of "sensors + edge computing + mechanism + AI models ."

TDK SensEI China Technical Team Contact Email : SenDG.Sales@tdk.com
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