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Domestic AGVs, high stopping accuracy, enter domestic large-scale factories

Google 우선 소스 기사입력2020.01.15 16:34

AGVs are replacing forklifts and conveyors
Autolat receives support for technology to improve stopping accuracy
We supply our own AGVs to large companies and are technologically independent.



Autolat, a manufacturer of unmanned transport vehicles, announced on the 15th that it received support from the Korea Institute of Industrial Technology (KITECH) for technology that can improve the stopping accuracy of unmanned transport vehicles and succeeded in supplying them to a large company.
Domestic AGVs enter large-scale factories (Photo = Saenggiwon)

As smart factories increase, automated guided vehicles (AGVs) are replacing forklifts and conveyor systems. AGVs are autonomous vehicles that repeatedly transport various types of cargo along designated routes, minimizing the intervention of workers and reducing the risk of accidents, and can move weights ranging from a minimum of 50 kg to a maximum of 10 tons at a time.

AGVs are largely divided into wired and wireless types depending on the principle of guiding vehicle movement. In the past, wired methods were used that induced movement by laying electric wires on the ground, but recently, wireless methods based on laser sensors have been mainly used. However, the wireless method has a slower response speed than the wired method and the location recognition is not precise, so if the stopping accuracy is not sufficiently secured, there is a high possibility of a collision accident or the device not being properly connected to the charging device.

Autorat has focused on developing its own wireless-guided AGV, but its stopping accuracy is at the level of ±25mm, which is a wide margin of error, and its reliability is also low compared to overseas products, so it has had difficulty entering the market. There is no objective standard or systematic measurement method to evaluate stopping accuracy, so even if it is delivered, it is expected to be difficult to after-sales service and quality control.

Dr. Cho Han-cheol's research team at the Saenggiwon Precision Machining Control Group began developing the technology at the request of its partner company, Autolat, and secured technological competitiveness by achieving a stopping accuracy of within ±15mm.

The research team first focused on improving the electrical characteristics of the vehicle motor, adjusting about 20 variables such as speed and load ratio through a real-time estimation experiment of the motor inertia, and then applied an appropriate driving algorithm to improve the stopping accuracy. Then, they set the average value of the position where the vehicle stops after receiving a stop signal as the reference position and developed an objective evaluation system that combines the laser error measurement method with the existing manual measurement method to verify the reliability of the stopping accuracy.

In addition, the wheel structure was designed with a wider surface area to ensure sufficient grip even on oily or tarpaulin-covered floor environments, and the braking performance was also improved by adopting anti-slip tires.

In January 2019, Autorat successfully delivered five AGVs of three types (for conveyors, lifts, and roll transport) to Company S’s workplace. This is the first case of technological independence in which a domestic small and medium-sized enterprise delivered to a large corporation in the AGV market.

After one year of actual operation since delivery, the stopping accuracy and reliability have been verified, and Company S is currently requesting an additional order. Compared to overseas products, it is evaluated as having low installation costs, being able to receive customized vehicles of a size appropriate for the manufacturing situation through custom manufacturing, and quick after-sales service response.

Meanwhile, according to data released by Market and Market in 2019, the global AGV market is expected to grow at an annual average of approximately 7.8%, reaching a size of USD 2 billion in 2019 and USD 2.9 billion in 2024.
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