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IoT solution for production site

What is Olive@Factory?

Solve the problem of analog data analysis with edge computing

Olive@Factory is a solution for Factory IoT that realizes predictive maintenance of production sites.

At the production site, it becomes difficult to maintain systems by the traditional method of spotting deteriorated function by an engineer experienced in the area.

By utilizing machine learning, Olive@Factory grasps the function deterioration of production equipment and signs of abnormality and predicts breakdown. By detecting abnormality at an early stage, costly downtime can be avoided, maintenance cost can be reduced, and equipment availability can be improved.


Analog data analysis task and Olive@Factory's solution

Analog data analysis has various challenges in acquired data and real-time characteristics. Olive@Factory can solve each problem and efficiently analyze necessary data.

Acquired data

Issues of analog data analysis

At the production site, the waveform of the measurement data that is obtained from the sensor will contain various patterns depending on the installation location and surrounding environment. Therefore, in order to judge the breakdown of facilities and its possibility, knowledgeable and experienced technicians are necessary, and it is one of direct causes of down time and increase in cost of quality control.

Olive@Factory's solution

Olive@Factory can analyze acquired data on its own machine learning and carry out judgment according to the environment in a much shorter time than human operation. You can also easily identify the cause by using multiple sensors.


Real time property

Issues of analog data analysis

Sensor data of physical phenomena occurring consecutively such as temperature and vibration is large, and even if it is sent to another place every time when analyzing it, it will not be enough for the communication bandwidth. Also, through the network, a time lag occurs from generation to feedback.

Olive@Factory's solution

Since Olive@Factory analyzes by machine learning on the spot, delay due to the network does not occur, and feedback with real-time nature can be performed. You can operate efficiently by sending only the necessary information to the cloud.


Main function


Record and display sensor data in real time


Predict failure by grasping signs of equipment abnormality by machine learning


Detect outliers in real time and notify by SMS, e-mail, phone etc.


Recorded data can be linked with PI System


AE sensor measurement, analysis


Usage record of working group at production site (welding, cutting)


Cooperation with Gyro, temperature, acceleration sensor (TI tag), and camera module


Simultaneous management of multiple units using network


Achieve high efficiency and accuracy in analysis by synchronizing all sensors


When it takes time to analyze with just AE sensor, analysis efficiency can be improved by combining with other sensor input such as trigger input, image analysis

How to use

PoC, first of all.

To determine whether Olive@Factory can be used at your production site, we propose PoC (Proof Of Concept) first. We also conduct operation consultation in the operation environment for the selection of sensors, acquisition and analysis and visualization of data, and collaboration with the cloud.
Please contact us.


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