AI Technology Developed for Rapid FA Equipment Setup in Factories
Mitsubishi Electric and National Institute of Advanced Industrial Science and Technology collaboration
TOKYO, February 5, 2019 – Mitsubishi Electric Corporation (TOKYO: 6503) and the National Institute ofAdvanced Industrial Science and Technology (AIST) announced today that they have developed an artificialintelligence (AI) technology that can reduce time for setting up factory-automation (FA) equipment. The newtechnology, which combines AIST’s AI technologies and Mitsubishi Electric’s FA technologies for highly
effective application in the FA field, will be implemented in Mitsubishi Electric's Maisart®1 products for greatly
increased factory productivity.
1 Mitsubishi Electric's AI creates the State-of-the-ART in technology

AI technology for rapid FA equipment setup in factories

The time for setting up FA equipment and systems prior to production, such as tuning or programming, isincreasing in line with the growing demand for small-lot production. In addition, the supply of experts capableof performing such procedures is becoming insufficient. In response, Mitsubishi Electric collaborated todevelop an AI technology that reduces the time for setting-up FA equipment and systems.

1/4Key Features
1) Servo system 2 positioning parameters tuned automatically in one day- Mitsubishi Electric's drive-control expertise is combined with AIST's Bayesian optimization3
application technology to enable positioning parameters to be tuned automatically in one day compared
to one week for manual tuning by experts.
- High-speed positioning control cuts positioning time up by to 20 percent using as many as 720
parameters in eight categories, which even experts would have difficulty adjusting.
2

Drives and controls various industrial machines at high speed and with high accuracy

3

Method for searchingly estimating maximum or minimum values of unknown functions or non-differentiable functions

High-speed positioning within allowable positioning error ranges is required when using servo systems
for positioning control. Vibration and other characteristics usually differ depending on the target position
and travel distance, so it is necessary to establish optimal parameters to determine the desired speed andacceleration for each position and distance. However, it can be difficult to adjust large numbers ofparameters. Mitsubishi Electric previously developed products with 18 parameters in two categories.
Mitsubishi Electric has now developed a new system with 720 parameters in eight categories for highly
precise control, where even experts would have difficulty adjusting such an extensive number ofparameters. Since the time required to automatically determine optimal settings for so many parameters
would be a problem, the process has now been reduced by limiting the search range with Mitsubishi
Electric's drive-control expertise and by increasing search efficiency with AIST's Bayesian optimization
application technology. As a result, it has become possible to complete servo-system parameter
adjustments in just one day, rather than at least one week as conventionally required by experts. In
addition, positioning time is reduced by up to 20 percent.
2)

Laser processing quality determined automatically without the participation of experts- The combination of Mitsubishi Electric's laser processing knowhow and AIST's machine-learningtechnology for image recognition enables automatic evaluations of processing quality comparable tomanual evaluations performed by experts.
A standardized procedure using the above evaluations allows operators to change settings for enhanced
processing quality.
In sheet metal-cutting using laser processing machines, various factors can lower processing quality, suchas debris on the lens used to focus the laser beam, changes in the temperature of the machine, and thecondition of the workpiece surface, any of which can lead to scratches or discoloration on the cut surface,which lower quality. Conventionally, experts must check the cut surface to evaluate the resulting quality
and then make adjustments as required to improve the quality.
By combining Mitsubishi Electric's laser-processing knowhow and AIST's machine-learning technology
for image recognition, the automatic quality-evaluation technology using cut-surface images achieves thelevel of manual evaluations performed by experts. In addition, a newly standardized procedure allows
laser-processing machine operators to change settings based on the automatic evaluations and thereby
improve processing quality without the experts' skills.
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3)

Programming time reduced to one-third of precedent to cope with anomaly of industrial robots- Mitsubishi Electric's force-feedback control4 technology and AIST's machine learning technology fordata analysis are combined in a machine-learning system that classifies anomalies in the assembly
operations of industrial robots.
- The time to create programs to cope with anomalies, a serious burden in setting up industrial robot
systems, is reduced by some 66 percent.
4Technology for modifying position commands according to force-sensor outputs

In setting up industrial robot systems, a high volume of programs is required to cope with anomalies, which
differ from system to system. Conventionally, experts predict possible anomalies in advance, such as errors
in grasping or alignment, and then develop the many programs required to address the anomalies andrecover normal operations. Developing such programs, however, takes far more time than the actual
programming of normal robotic motions.
Accordingly, the new technology learns to classify anomalies using force-sensor outputs obtained during
robotic operations. This is achieved by combining Mitsubishi Electric's force-feedback control technology
for industrial robots and AIST's machine-learning technology. As a result, the new technology eliminates
the need to develop anomaly classification algorithms, which conventionally must be created separately
for each system, and thereby reduces the time required to create such programs by some 66 percent.
Collaboration in using AI for FA
Name
Mitsubishi Electric
National Institute ofAdvanced Industrial
Science and Technology

Contributions
Expertise in servo systems, laser processing and industrial robot systems.
Implementation, improvement and evaluation of AI algorithms.
Optimization, image-recognition and data-analysis technology using AI

About Maisart
Maisart encompasses Mitsubishi Electric’s proprietary artificial intelligence (AI) technology, including
compact AI, automated-design deep-learning algorithm and extra-efficient smart-learning AI. Maisart is anabbreviation for "Mitsubishi Electric's AI creates the State-of-the-ART in technology." Under the corporate
axiom "Original AI technology makes everything smart," the company is leveraging original AI technology
and edge computing to make devices smarter and life more secure, intuitive and convenient.

Maisart is a registered trademark of Mitsubishi Electric Corporation.

3/4Inquiries
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Mitsubishi Electric Corporation
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Customer Inquiries
Advanced Technology R&D Center
Mitsubishi Electric Corporation
www.MitsubishiElectric.com/ssl/contact/company/rd/form.html
www.MitsubishiElectric.com/company/rd/AISTMedia Relations Office, Planning Headquarters
press-ml@aist.go.jp
www.aist.go.jp/index_en.html###About Mitsubishi Electric Corporation
With nearly 100 years of experience in providing reliable, high-quality products, Mitsubishi Electric
Corporation (TOKYO: 6503) is a recognized world leader in the manufacture, marketing and sales of electricaland electronic equipment used in information processing and communications, space development and satellite
communications, consumer electronics, industrial technology, energy, transportation and building equipment.
Embracing the spirit of its corporate statement, Changes for the Better, and its environmental statement, EcoChanges, Mitsubishi Electric endeavors to be a global, leading green company, enriching society withtechnology. The company recorded consolidated group sales of 4,444.4 billion yen (in accordance with IFRS;
US$ 41.9 billion*) in the fiscal year ended March 31, 2018. For more information visit:
www.MitsubishiElectric.com*At an exchange rate of 106 yen to the US dollar, the rate given by the Tokyo Foreign Exchange Market on
March 31, 2018
About AISTThe National Institute of Advanced Industrial Science and Technology (AIST), one of the largest publicresearch organizations in Japan, focuses on the creation and practical realization of technologies useful toJapanese industry and society, and on “bridging” the gap between innovative technological seeds andcommercialization. For this, AIST is organized into 5 departments and 2 centers that bring together coretechnologies to exert its comprehensive strength. AIST, as a core and pioneering existence of the nationalinnovation system, has about 2000 researchers doing research and development at 10 research bases acrossthe country, based on the national strategies formulated with the changing environment involving innovationin mind. AIST is also actively building a global network by, for example, signing memorandums ofunderstanding for comprehensive research cooperation (MOUs) with 30 major research institutes around theworld.
AIST endeavors to achieve a rich and eco-friendly society through “Green Technology,” healthy and safe
living through “Life Technology,” and a super smart society through "Information Technology," with the hopeof building a sustainable society.

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