KR-102961617-B1 - System for Prognostics and Health Managemnet

Abstract

The present invention relates to a predictive maintenance management system for a driving unit constituting a manufacturing facility, comprising: a driving unit life DB storing statistical data related to usage and failure occurrences of said driving unit; a sensor unit disposed in said driving unit to collect the usage and usage environment of said driving unit; an effective usage calculation unit converting the usage of said driving unit into a standardized value based on the usage and usage environment collected by the sensor unit; and a life prediction unit calculating the remaining life of said driving unit by referring to the standard usage value of said driving unit calculated by the effective usage calculation unit and the data stored in the driving unit life DB.

Inventors

• 김성수
• 이유진
• 김소희

Assignees

• 케이씨미래기술 주식회사

Dates

Publication Date

20260507

Application Date

20250917

Claims (9)

1. As a system for managing predictive maintenance of drive units constituting manufacturing equipment, A drive unit life DB that stores statistical data related to usage and failure occurrence for the above drive unit; and A sensor unit disposed in the above-mentioned drive unit to collect the usage amount and usage environment of the above-mentioned drive unit; An effective usage calculation unit that converts the usage of the driving unit into a standardized value based on the usage amount and usage environment collected from the sensor unit; and A lifespan prediction unit that calculates the remaining lifespan of the drive unit by referring to the standard usage value of the drive unit calculated by the effective usage calculation unit and the data stored in the drive unit lifespan DB; A standard load is applied to the above drive unit, and It further includes a verification unit that determines whether the sensor unit is operating normally by comparing the measurement value of the sensor unit with the authorized standard load. The above verification unit is, A driving command part that operates the above driving unit with the above standard load; A simulation part that provides virtual measurement values corresponding to the above standard load; and It includes a verification part that compares the virtual measurement value performed in the simulation part above with the actual measurement value measured by the sensor part above, and The sensor unit above is, A power measuring sensor for measuring the usage of the above-mentioned drive unit; An acceleration measuring sensor that measures the usage environment of the above-mentioned drive unit; A load cell for measuring the weight of a heavy object connected to the above drive unit; and It includes a distance measuring sensor that measures the movement of a heavy object connected to the above-mentioned drive unit; The above effective usage calculation unit is, Calculate the correlation between each measurement value measured by the power measurement sensor, the acceleration measurement sensor, the load cell, and the distance measurement sensor to derive the fatigue strength applied to each component forming the drive unit, and The above effective usage calculation unit is, A predictive maintenance management system for manufacturing equipment characterized by comparing the derived fatigue strength with the SN curve of the corresponding part to calculate the usage amount driven at a fatigue strength exceeding the fatigue limit (endurance limit) of the corresponding part as a standard usage value.
2. delete
3. delete
4. delete
5. delete
6. delete
7. In claim 1, The sensor unit above is, It further includes a vibration sensor that measures the natural frequency applied to the above-mentioned driving unit, and The above effective usage calculation unit is, If the above drive unit is a crane, A predictive maintenance management system for manufacturing equipment characterized by applying a weight for the natural vibration to the derived fatigue strength when the frequency of the natural vibration occurring while a heavy object is mounted deviates from the measurement cycle of the power measuring sensor, the acceleration measuring sensor, the load cell, and the distance measuring sensor.
8. In claim 7, The above vibration sensor is, As a laser measurement method, A laser irradiation unit positioned on an external fixture structurally separated from the above crane; A reflector provided on the trolley of the above crane; and A predictive maintenance management system for manufacturing facilities characterized by including a laser receiver positioned on an external fixture structurally separated from the crane.
9. In claim 1, The above effective usage calculation unit is, A predictive maintenance management system for manufacturing equipment characterized by deriving the fatigue strength by calculating the correlation in a simulation manner by inputting each measurement value measured by the power measurement sensor, the acceleration measurement sensor, the load cell, and the distance measurement sensor into a virtual drive unit implemented as a digital twin.

Description

System for Prognostics and Health Management for Manufacturing Facilities The present invention relates to a predictive maintenance management system for manufacturing equipment, and more specifically, to a system that measures the actual usage of machine parts of manufacturing equipment and predicts the lifespan of said parts to perform predictive maintenance of the equipment. An electric motor is an electromechanical device that converts electrical energy into mechanical energy, specifically rotational energy, to perform mechanical work, and is also known as a motor. In industrial settings, electric motors are used in a wide variety of applications, ranging from small home appliances to large industrial uses. In particular, for industrial applications, they play the role of providing rotational force and power transmission in rotating machinery and equipment that requires rotation. As these motors are continuously operated, wear and tear increases, and eventually, a time comes when replacement or repair is required. If a breakdown occurs during motor operation and the motor suddenly stops, it can have an adverse effect on the entire facility, including the motor. Therefore, in facilities using electric motors, it is crucial to predict the remaining lifespan of the motor in advance. Operators must establish inspection and maintenance plans prior to failure to not only prevent damage caused by breakdowns but also reduce post-failure maintenance costs and ensure the equipment is operated until its lifespan limit. Conventional technology for predicting the remaining lifespan of an electric motor has been disclosed. For example, Korean Registered Patent No. 10-2315492 (Prior Art 1) discloses a motor life prediction system and a method for implementing the same, which can predict the remaining life of a current motor by measuring an electrical signal of a motor, converting it into digital data, and analyzing it. As another example, Korean Registered Patent No. 10-0608235 (Prior Art 2) discloses an apparatus and method for predicting the lifespan and failure rate of an induction motor by measuring the stator current, winding temperature, and ambient temperature of the induction motor. However, in the prior art including the aforementioned prior art documents 1 and 2, the lifespan of the motor is predicted using the electric signal or temperature of the motor, so the lifespan prediction is indirect and there are limitations in accurately predicting the lifespan. FIG. 1 is a block diagram of a predictive maintenance management system for a manufacturing facility according to one embodiment of the present invention. Figure 2 is a detailed block diagram of the verification unit. FIG. 3 illustrates a general configuration of an overhead crane as an example of a manufacturing facility to which the present invention is applied. Figure 4 illustrates the operation of a typical crane. Figure 5 is an example of an SN curve of a standard rotational fatigue test. FIG. 6 is a block diagram of an effective usage calculation unit according to one embodiment. Figure 7 is a schematic diagram illustrating a vibration sensor. FIG. 8 is a schematic diagram illustrating a reflector and a laser receiver according to one embodiment. FIG. 9 is a schematic diagram illustrating a reflector and a laser receiver according to another embodiment. Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Note that in the accompanying drawings, identical components are indicated by the same reference numerals whenever possible. Furthermore, detailed descriptions of known functions and configurations that may obscure the essence of the invention will be omitted. For the same reason, some components in the accompanying drawings may be exaggerated, omitted, or schematically depicted. FIG. 1 is a block diagram of a predictive maintenance management system for manufacturing equipment according to one embodiment of the present invention, FIG. 2 is a detailed block diagram of a verification unit, FIG. 3 is a diagram explaining the general configuration of an overhead crane as an example of manufacturing equipment to which the present invention is applied, FIG. 4 is a diagram explaining the operation of a general crane, FIG. 5 is an example of an S-N curve of a standard rotational fatigue test, FIG. 6 is a block diagram of an effective usage calculation unit according to one embodiment, FIG. 7 is a schematic diagram explaining a vibration sensor, FIG. 8 is a schematic diagram explaining a reflector and a laser receiver according to one embodiment, and FIG. 9 is a schematic diagram explaining a reflector and a laser receiver according to another embodiment. Referring to FIGS. 1 to 9, the predictive maintenance management system (1000) for manufacturing equipment according to the present invention includes a sensor unit (100), an effective usage calculation unit (200), a lifespan predict