The word mechatronics was first coined by an engineer at Yaskawa Electric in 1969. This word consists of the term “mechanism”, which is short for mechanical engineering, and “electronics”, which encompasses the idea of electrical engineering. Our passion for automation is built in to this word. Yaskawa added three “i” (integrated, intelligent, and innovative) to the word, “mechatronics” to help identify solutions to business challenges right at the customers’ production sites by incorporating the use of data in mechatronics products.
Yaskawa has provided solutions, such as automation, using mechatronics technologies and products, including servos, AC drives, and robots, to respond to customers’ demands for higher quality manufacturing and improvements in productivity at production sites.
i3-Mechatronics helps support business challenges together with customers from production sites with the addition of “digital data management” to solutions for automating systems.
The term “IoT” or “industrie 4.0” has come to be used in a broad meaning in recent years because of advances in telecommunications technologies, and many things such as automobiles, factories, and home appliances are connected digitally. Yaskawa promotes i3-Mechatronics as a solution concept in response to such trends in IoT and industrie 4.0.
At i3-Mechatronics, we propose that in addition to automating “cells,” digital data should be used to manage these tasks. This enables us to manage the operation status of equipment with process data and the production status with status data as “numerical values” rather than “expert knowledge”. We want to provide our customers with data management that eliminates red lights that are out of service and keeps the green lights on at their factories.
The i3-Mechatronics will proceed in three “i” steps: (1) integrated, (2) intelligent, and (3) innovative. Specifically, we will connect the factory cells and systems such as equipment and devices to the IT layer by (1) integrating data. Next, the collected data is analyzed and fully utilized (2) intelligently. By doing so, we will be able to achieve (3) innovative, such as the improvement of operating facilities and the stability of production quality, and consequently resolve business challenges that customers are seeking to build smart factories.
Let’s look at what you can do with i3-Mechatronics with each solution.
First of all, in order to promote smart factories, it is important to visualize the situation in which the equipment/devices of factories such as industrial robots, machine tools, and sensors are integrated and operating in integrated, which is the first I of i3-Mechatronics.
The features of Yaskawa Cockpit (YCP), is a software tool for this purpose, are the “collection, accumulation and analysis” of data through visualization. In the area of data collection and accumulation, it is possible to link various equipment and devices at production sites, including those of other companies, to YCP, to collect data in units of one-millionth of a second by combining the time series of each equipment, and to match the time stamp.
For data analysis, YCP enables you to execute analysis models such as inferences, created by AI, on upper-tier. Additional add-ons such as health monitoring and production count monitoring are also added, and IT vendors provide centralized control of the transfer of data to upper-tier systems such as ERP, MES and Big Data.
By introducing YCP, it is possible to perform predictive failure diagnosis, operation status monitoring/diagnosis, equipment abnormality diagnosis, quality defect detection, etc.
By utilizing the AI technology “Alliom” developed by Yaskawa Group, the installation time to actual operation is drastically shortened, and the accuracy to actual machine can also be improved.
High Variety and Variable Quantity Production
By using digital data to manage automated production lines, setup can be prepared automatically without manual intervention, enabling high variety and variable quantity production from a minimum of one unit.
Autonomous Distributed Manufacturing
Digital data such as the torque value, vibration value, and temperature of the servomotor is absorbed into the controller, and the robot can think for itself how to move.
Accuracy Improvement of Defect Cause Analysis
By “visualizing” the operation status of equipment/devices with Yaskawa Cockpit, it is possible to identify the root cause by comparing the normal value of the data in the factor analysis for defects in production.
Automated Product Quality Assesment with AI
When the quality inspection process is labor-saving, the use of an image judgement service that utilizes AI technology such as deep learning makes it possible to automatically determine complex No Good paterns with the same level of accuracy as humans.
Predictive Failure Diagnosis of Equipment
To reduce downtime to zero by performing planned maintenance in anticipation of equipment failure due to wear, etc., in response to concerns that production may become impossible due to the sudden shutdown or something else.
Investigating The Cause of Equipment Failure
By acquiring quality data on when, with which equipment, and how it was processed, it is possible to accurately identify the cause of the problem between which equipment and equipment at the time of failure.
Faster Recovery Simulation
The planning technology that Yaskawa developed automatically generates optimal paths, enabling simulation in a few minutes and dramatically reducing engineering time for recovery from sudden stop.