Start with smart sensing
smart maintenance

For factory equipment maintenance
Are you spending more time and money than necessary?
With SENSSPIDER
Smart maintenance system (CBM system)
Simple and easy to build
Broadband vibration sensor data acquisition, data preprocessing,
Until the implementation of the user's original AI inference model,
Develop quickly and efficiently

WHY SENSPIDER?

Downtime reduction

Before
Prolonged downtime due to machine stoppage, loss of production plan

After
SENSPIDER monitors abnormal signs and realizes predictive maintenance

Maintenance cost optimization

Before
Retain parts with regular parts replacement

After
Minimize parts replacement by grasping equipment status with SENSPIDER

Waste reduction

Before
Unintentionally defective products occur during manufacturing due to sudden abnormalities

After
Eliminate defective products by detecting abnormalities in advance with SENSPIDER

automation/autonomy

Before
The problem with automation is that it is not possible to detect anomalies that humans have been able to detect up until now.

After
Solved by constantly monitoring conditions with SENSPIDER

FEATURE

A tremendous presence,
Compact enough to forget its existence.

150mm wide, 85mm deep and 100mm high. It is compact enough to forget its existence once it is installed. The sensor amplifier, data logger, computing terminal (PC, etc.), sensor power supply, and external communication interface necessary for monitoring are integrated into a single unit. A compact all-in-one is a pronoun.

Compact enough to forget its existence with a tremendous presence.

Making it easier than ever to acquire data for use in AI.

Acquisition of data used in AI,
Above all, it's easy.

Instead of blindly collecting data, we can easily extract only the data necessary for AI to utilize it. Compared to arranging randomly collected data, post-processing is overwhelmingly easier. This is the shortcut to efficient use of data. Another strength of SENSPIDER is that the conditions for acquiring data can be set in detail and flexibly.

Speedy data analysis.
Edge computing is here.

I want to analyze the acquired data in real time. Now is the time for edge computing to analyze the data obtained with SENSPIDER on the spot. It is useful for predictive maintenance and anomaly detection of equipment. So use the data. Being able to incorporate these functions as needed is another reason to choose SENSPIDER.

Compatible with all analog sensors.
We are proud of our extensive coverage.

SENSPIDER has 4 expansion slots. By installing a "high-speed vibration sensor interface card", "temperature sensor interface card", and "general-purpose sensor interface card", it is possible to support most analog sensors in the world. Despite its compact size, it boasts a wide range of coverage.

high-speed sampling,
surprisingly affordable.

It supports wideband vibration sensors and can perform high-speed sampling at a maximum of 48ksps. It is also a point that it is affordable while supporting high-speed sampling. A high-speed vibration sensor interface card is installed by default. This is a bit of a price break.

High-speed sampling at surprisingly reasonable prices.

PROCESSING

What's Processing Function?

By utilizing the processing function, it is possible to build a smart maintenance system without a PC.
It can be used for various processing purposes, from user original AI model implementation to feature value implementation without programming.
It is a friendly function for specialized engineers in various fields.

Resources

Processing function explanation material
*Registration is required for viewing and downloading.

SENSPIDER Developers Package reference design tutorial video

Demonstration video of anomaly detection using SENSPIDER

One shot solution! Sigma De Py ~ Development without programming, realization of smart maintenance without PC ~ [Part 1]

One shot solution! Sigma De Py ~ Development without programming, realization of smart maintenance without PC ~ [Part 2]
*Application is required for viewing.

Body specifications

Interface list

USECASE

For machine tool and industrial machine manufacturers

Utilizing IoT and AI
Ability to develop functions such as anomaly detection and predictive maintenance

In addition to data acquisition, it is possible to implement custom algorithms that are optimal for the products handled by each machine tool and industrial machinery manufacturer, contributing to shortening product development times and reducing development costs. Macnica provides total support for product development, including ``developing algorithms to be implemented in SENSPIDER,'' ``proposing sensors to connect,'' and ``providing an AI learning environment.''

[For PC] For machine tool and industrial machine manufacturers

Case study: Okamoto Machine Tool Co., Ltd.

For machine tool and industrial machine manufacturers

By using IoT×AI Ready Platform,
Improve detection accuracy of anomaly detection and predictive maintenance

By using the "IoT x AI Ready Platform", you can enhance the convenience of SENSPIDER. For example, data from the NC can be used to control the trigger timing of the SENSPIDER, and the results of multivariate analysis using the data from the NC and SENSPIDER can be used for machine anomaly detection and predictive maintenance. This improves the detection accuracy of anomaly detection and predictive maintenance.

[For PC] Improve detection accuracy of anomaly detection and predictive maintenance by using IoT x AI Ready Platform

[For smartphones] Improve detection accuracy of anomaly detection and predictive maintenance by using IoT x AI Ready Platform

For manufacturers

Digitization of equipment accompanying the shift to smart factories,
For anomaly detection and predictive maintenance using IoT and AI

Since it can handle various sensor inputs, it is possible to acquire sensing data from important equipment with a single unit. This will greatly contribute to the creation of smart factories. Macnica not only proposes sensors that connect with SENSPIDER, but also supports data analysis and visualization using linked software.

Digitization of equipment accompanying smart factories, anomaly detection and predictive maintenance using IoT and AI

For manufacturers

A data management platform for the manufacturing industry
PLC and NC data can also be collected

In addition to installing a sensor and SENSPIDER for each production facility, you can also collect PLC and NC data of the facility by connecting with "Data management platform for manufacturing industry (Orizuru)". In addition, if AI is implemented, it will be possible to determine equipment abnormalities in combination with sensor data. Equipment information and judgment results can also be sent to the host system using OPC UA.