CN-121995861-A - Method, system and medium for vehicle production automation control

CN121995861ACN 121995861 ACN121995861 ACN 121995861ACN-121995861-A

Abstract

The present disclosure relates to methods, systems, and media for automated control of vehicle production. A method for automated control of vehicle production is provided, including receiving, by a real-time Internet of things, a first request from a programmable logic controller, the first request including location information, determining, by the real-time Internet of things, a geofence associated with the location information based on the location information, the geofence being a physical space defined in three-dimensional coordinates, determining, by the real-time Internet of things, a vehicle identifier of a vehicle within the determined geofence, wherein the vehicle identifier is associated with a real-time location tag coupled to the vehicle, transmitting, by the real-time Internet of things, the determined vehicle identifier to the programmable logic controller, comparing, by the programmable logic controller, the received vehicle identifier to a predetermined vehicle identifier, and determining, by the programmable logic controller, whether to trigger an operational event based on a result of the comparison.

Inventors

LI YINMING
MENG YAO
ZHANG JINLIANG
LIU LICHENG

Assignees

华晨宝马汽车有限公司

Dates

Publication Date: 20260508
Application Date: 20241101

Claims (10)

1. A method for vehicle production automation control, comprising: receiving, by the real-time internet of things, a first request from the programmable logic controller, the first request including location information; Determining, by the real-time internet of things, a geofence associated with the location information based on the location information, the geofence being a physical space defined in three-dimensional coordinates; Determining, by the real-time internet of things, a vehicle identifier of a vehicle within the determined geofence, wherein the vehicle identifier of the vehicle is associated with a real-time location tag coupled with the vehicle; the real-time internet of things sends the determined vehicle identifier to the programmable logic controller; Comparing, by the programmable logic controller, the received vehicle identifier with a predetermined vehicle identifier, and Determining, by the programmable logic controller, whether to trigger an operational event based on the result of the comparison.
2. The method for vehicle production automation control of claim 1, further comprising: And the first request is sent to the real-time Internet of things by the programmable logic controller in response to failure of an RFID reader associated with a certain station to read an RFID tag of a vehicle.
3. The method for vehicle production automation control of claim 1, further comprising: triggering, by the programmable logic controller, a subsequent production operation associated with the vehicle in response to the comparison being affirmative; Sequentially transmitting, by the programmable logic controller and in response to the comparison being negative, up to N subsequent requests including the location information to the real-time Internet of things until a vehicle identifier is received from the real-time Internet of things and the comparison being positive, wherein N is a predetermined integer greater than or equal to 1, and And stopping, by the programmable logic controller, a subsequent production operation associated with the vehicle in response to either no vehicle identifier having been received from the real-time internet of things after the N subsequent requests have been sent or the comparison result has been negative.
4. The method for vehicle production automation control of claim 1, wherein determining, by the real-time internet of things, a vehicle identifier for a vehicle within the determined geofence further comprises: determining that the tag type within the determined geofence is a real-time locating tag of the vehicle; A vehicle identifier of a vehicle coupled to a real-time locating tag of the tag type of the vehicle within the determined geofence is determined.
5. The method for vehicle production automation control of claim 1, further comprising: Automatically coupling, by the real-time internet of things, a real-time location tag within the first geofence with the vehicle in response to determining that the vehicle entered the first geofence, including associating a tag identifier of the real-time location tag with the vehicle identifier.
6. The method for vehicle production automation control of claim 1, further comprising: And the real-time internet of things is used for responding to the fact that the vehicle enters the second geofence, and sending a first message to a real-time positioning tag coupled with the vehicle, wherein the first message is used for reducing the working frequency range of the real-time positioning tag to save electric power.
7. The method for vehicle production automation control of claim 1, further comprising: In response to determining that the vehicle entered the third geofence and determining that a real-time location tag coupled with a production tool entered the collision zone of the vehicle, by the real-time internet of things, sending a second message to the production tool, the second message including vehicle-specific information for instructing the production tool to perform a production operation for the vehicle, Wherein the collision zone of the vehicle is a physical area of predetermined three-dimensional size referenced to the location of a real-time locating tag coupled to the vehicle.
8. A system for vehicle production automation control, comprising: real-time internet of things configured to: A first request is received from a programmable logic controller, the first request including location information, Determining a geofence associated with the location information based on the location information, the geofence being a physical space defined in three-dimensional coordinates, Determining a vehicle identifier of a vehicle within the determined geofence, wherein The vehicle identifier is associated with a real-time location tag coupled to the vehicle, and Transmitting the determined vehicle identifier to the programmable logic controller, and The controller may be configured to control the operation of the programmable logic controller, the programmable logic controller is configured to: comparing the received vehicle identifier with a predetermined vehicle identifier, and Based on the result of the comparison, it is determined whether to trigger an operational event.
9. The system for vehicle production automation control of claim 8, wherein the programmable logic controller is further configured to: In response to the comparison being affirmative, triggering a subsequent production operation associated with the vehicle; In response to the comparison being negative, successively sending up to N subsequent requests including the location information to the real-time Internet of things until a vehicle identifier is received from the real-time Internet of things and the comparison being affirmative, where N is a predetermined integer greater than or equal to 1, and And stopping the subsequent production operation associated with the vehicle in response to the vehicle identifier still not being received from the real-time internet of things after the N subsequent requests are sent or the comparison result still being negative.
10. A computer readable storage medium having stored thereon computer readable program instructions which, when executed by one or more processors, perform the method of any of claims 1-7.

Description

Method, system and medium for vehicle production automation control Technical Field The present disclosure relates to automated production, and more particularly to methods, systems, and media for automated control of vehicle production. Background The concept of intelligent factories is becoming popular, and the core is to realize intelligent management of production process through high integration. In the product manufacturing process, raw material control and flow management are two key links. The traditional production management mode is difficult to master the details of raw material consumption and production flow in real time, and the application of the Internet of things technology, particularly the radio frequency identification (Radio Frequency Identification, RFID) technology, provides an effective solution to the problems. The RFID technology can track and record the loss information of the raw materials and the current production flow and steps in real time through a wireless communication mode. The application of the technology enables enterprises to master the live condition of the whole manufacturing process, including key information such as raw material use condition, production progress, product quality and the like. Meanwhile, the RFID technology can also grasp the current condition of system equipment in time, reduce deviation caused by system faults and improve the stability and reliability of the production process. The relevant data generated in the manufacturing process can be kept in a database, so that complete information support is provided for a manager, and subsequent production planning and decision-making are facilitated. The accumulation and analysis of the data are beneficial to optimizing the production flow, improving the utilization rate of resources and reducing the production cost. The intelligent manufacturing realizes the automation of the production process, so that a manager can monitor the working state and performance of the equipment at any time. Through the monitoring data that gathers, can carry out preventive maintenance to equipment, reduce the risk of unexpected shut down, improve production efficiency. The intelligent manufacturing system has an automatic sensing function, and can reasonably distribute the working time and progress of the equipment by utilizing the collected data. The intelligent scheduling and distribution is beneficial to improving the flexibility and response speed of the production line and adapting to changeable production requirements. The intelligent manufacturing process directly monitors the machine and the production line through the computer platform system, and is particularly suitable for being applied to precise industries with extremely high environmental requirements, such as semiconductor chip manufacturing. In these industries, an extremely clean dust-free environment is a fundamental requirement for production, and human factors may increase the complexity of the product manufacturing process. Therefore, highly automated intelligent manufacturing is the first choice for these high-tech vendors. In the automotive industry, the real-time requirements for vehicle arrival are extremely high, and timely feedback to the material system is required to perform accurate material allocation and production scheduling. Therefore, the RFID technology is widely applied in the automobile industry, and can provide real-time position information of vehicles on a production line, so that smoothness and high efficiency of a production flow are ensured. However, the application of RFID technology in automotive manufacturing lines, while providing many advantages, presents technical problems and limitations. For example, RFID technology is limited by the read range. The read range of RFID readers is limited, especially passive RFID tags are typically short in read distance. The reading distance of the low-frequency RFID is shorter than 10 cm, the reading distance of the high-frequency RFID is generally within 1 meter, and the reading distance of the ultrahigh-frequency RFID can reach 3 to 5 meters, and the maximum reading distance can reach 20 meters. This means that in some cases, the data can be successfully read only if the RFID tag is within the effective range of the reader. This may affect the accuracy and timeliness of the real-time positioning. For another example, RFID tags are classified into active tags and passive tags. Active tags have a longer read range but are costly, while passive tags rely on the activation of a signal from a reader, the read range being limited by a number of factors such as the operating frequency of the tag and environmental interference. In addition, the transmission of RFID signals may be disturbed by materials such as metal and liquid, which may lead to a read failure or a reduced read range. In the automobile manufacturing process, various interference sources may exist in the production environmen