Station beat recognition production line and method

Abstract

The invention discloses a station beat recognition production line and method, the production line comprises a plurality of stations, and each station is used for processing a workpiece; a plurality of electronic fences, each electronic fence is arranged on one station, and the electronic fences are used for identifying the position of the station; a plurality of positioning modules, each workpiece is provided with one positioning module, and the positioning module is used for identifying the position of the workpiece; and the beat processing module is used for acquiring beat data of the workpiece on each station and carrying out abnormal station identification and abnormal production line identification according to the beat data. Therefore, automatic statistical output of the takt of each station can be realized, the operation time of the workpiece at each station can be checked in real time, and an abnormal station and an abnormal production line can be automatically identified.

Description

Technical Field

[0001] The present invention relates to the field of production and processing technology, and in particular to a workstation rhythm recognition production line and method. Background Art

[0002] At present, the rhythm of the workstation-based rhythmic assembly line is statistically analyzed in the form of manual reporting. There are problems such as untimely reporting and low data utilization value. When there is a bottleneck in the production line and the efficiency does not meet expectations, process personnel need to be arranged to report on site. The response speed is slow, and abnormal workstations cannot be discovered in time, affecting the efficiency of the production line. Summary of the Invention

[0003] In view of the above problems, the present invention provides a workstation beat identification production line and method, which can realize automatic statistical output of each workstation beat, real-time calculation of the workpiece operation time at each workstation, and automatic identification of abnormal workstations and abnormal production lines.

[0004] According to a first aspect of the present invention, a workstation beat recognition production line is provided, comprising:

[0005] Multiple workstations, each of which is used to perform processing operations on the workpiece;

[0006] A plurality of electronic fences, each electronic fence is set at a work station, and the electronic fence is used to identify the location of the work station;

[0007] A plurality of positioning modules, each of which is provided with one positioning module, and is used to identify the position of the workpiece;

[0008] The beat processing module is used to obtain the beat data of the workpiece at each workstation and identify abnormal workstations and abnormal production lines based on the beat data.

[0009] Optionally, the beat processing module includes:

[0010] An acquisition submodule, used for acquiring beat data of the workpiece at each workstation;

[0011] The identification submodule is used to calculate the processing time of the workpiece at each workstation and the production line balance rate based on the beat data; identify abnormal workstations based on the processing time of the workpiece at each workstation, and identify abnormal production lines based on the production line balance rate.

[0012] Optionally, the identification submodule includes:

[0013] A first calculation unit is used to calculate the processing time of the workpiece at each workstation according to the beat data;

[0014] a second calculation unit, configured to calculate a production line balance rate of the production line according to a processing time of the workpiece at each workstation;

[0015] a first abnormality identification unit, configured to compare the processing time of the workpiece at each workstation with the design time corresponding to the workstation, and determine that the workstation is an abnormal workstation if the processing time of the workpiece is greater than the design time corresponding to the workstation;

[0016] The second abnormality identification unit is used to compare the balance rate of the production line with a balance reference value, and if the balance rate of the production line is less than the balance reference value, determine that the production line is an abnormal production line.

[0017] Optionally, the identification submodule further includes:

[0018] The threshold calculation unit is used to obtain historical production line balance data obtained when the target parameters of the production line meet the target conditions within a historical time period, and determine the balance reference value based on the historical production line balance data.

[0019] Optionally, the target parameters of the production line include equipment parameters, workpiece parameters, process parameters, environmental parameters and detection parameters of the production line.

[0020] Optionally, the first calculation unit is used to determine the entry time and exit time of the workpiece at each workstation according to the beat data;

[0021] The processing time of the workpiece at each workstation is calculated based on the entry time and exit time of the workpiece at each workstation.

[0022] Optionally, the second calculation unit is used to determine the maximum processing time from the processing time of the workpiece at each workstation; calculate the sum of the processing time according to the processing time of the workpiece at each workstation; and calculate the production line balance rate of the production line based on the sum of the processing time and the maximum processing time.

[0023] Optionally, the workpiece is a processed part of a railway freight car.

[0024] According to a second aspect of the present invention, a workstation beat recognition method is provided, which is used in the aforementioned workstation beat recognition production line, and the method comprises:

[0025] Acquire the beat data of the workpiece at each workstation;

[0026] According to the beat data, the processing time of the workpiece at each workstation and the production line balance rate are calculated; abnormal workstations are identified according to the processing time of the workpiece at each workstation, and abnormal production lines are identified according to the production line balance rate.

[0027] According to a third aspect of the present invention, a controller is provided, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the aforementioned workstation rhythm recognition method when executing the computer program.

[0028] The above one or more technical solutions in the embodiments of this specification have at least the following technical effects:

[0029] The embodiments of this specification provide a production line and method for identifying workstation beats. The production line includes multiple workstations, each used to perform workpiece processing operations; multiple electronic fences, each set at a workstation, used to identify the location of the workstation; multiple positioning modules, one set at each workpiece, used to identify the location of the workpiece; and a beat processing module for obtaining the beat data of the workpiece at each workstation and, based on the beat data, identifying abnormal workstations and abnormal production lines. In this way, automatic statistical output of the beat of each workstation is achieved, real-time calculation of the workpiece's operating time at each workstation is achieved, and abnormal workstations and abnormal production lines are automatically identified.

[0030] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. Throughout the drawings, the same reference figures denote the same components. In the drawings:

[0032] Figure 1 A flow chart of a workstation rhythm recognition method in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0033] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0034] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are intended to fall within the scope of protection of the present invention.

[0035] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not require further definition or explanation in subsequent drawings.

[0036] In the description of the present invention, it should also be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0037] An embodiment of the present invention provides a workstation rhythm recognition production line, comprising:

[0038] Multiple workstations, each of which is used to perform processing operations on the workpiece;

[0039] A plurality of electronic fences, each electronic fence is set at a work station, and the electronic fence is used to identify the location of the work station;

[0040] A plurality of positioning modules, each of which is provided with one positioning module, and is used to identify the position of the workpiece;

[0041] The beat processing module is used to obtain the beat data of the workpiece at each workstation and identify abnormal workstations and abnormal production lines based on the beat data.

[0042] The production line is equipped with multiple workstations, the physical locations of which are set, and the workpieces will be processed in sequence through these workstations.

[0043] Specifically, the processing operations at these workstations vary greatly depending on the specific production scenario. For example, in the production of parts for railway freight cars, one workstation might focus on precision machining of metal blanks, using lathes, milling machines, and other equipment to cut the blanks into semi-finished parts with specific shapes and precision requirements. In the electronics manufacturing sector, a workstation might perform placement of electronic components, with workers or automated equipment precisely attaching tiny resistors, capacitors, and other components to printed circuit boards. These workstations are arranged in an orderly fashion according to the logical sequence of the production process, working closely together to gradually transform the workpiece from raw material to finished product. The processing quality and efficiency of each workstation directly impact the smoothness of the entire production process and the ultimate quality of the product.

[0044] Electronic fences are designed to accurately define and manage the locations of workstations, and an electronic fence is installed at each workstation. These electronic fences use advanced electronic sensing technology and can identify the location of their corresponding workstations with extremely high accuracy. During actual operation, the electronic fence forms an invisible boundary area around the workstation by transmitting and receiving signals of specific frequencies. Once an object enters or leaves this boundary area, the electronic fence can quickly capture the signal changes and transmit the relevant information to the control system of the production line. In an embodiment of the present invention, when a workpiece to be processed is transported to the electronic fence area of ​​a certain workstation, the electronic fence will send a "workpiece entering the workstation" signal to record beat data such as the workpiece's residence time at the workstation, providing an accurate time node basis for subsequent beat statistics and analysis.

[0045] The positioning module is designed to grasp the position dynamics of the workpiece on the production line in real time. In this embodiment, a positioning module is installed on each workpiece. These positioning modules use advanced positioning means such as UWB (ultra-wideband) positioning technology, Bluetooth positioning technology or GPS (global positioning system, often used in combination with indoor positioning enhancement technology in indoor positioning scenarios), and have powerful position recognition capabilities. Taking the UWB positioning module as an example, it uses the precise ranging principle of ultra-wideband signals and interacts with multiple positioning base stations in the workshop to calculate the specific position coordinates of the workpiece in three-dimensional space in real time and accurately. Regardless of whether the workpiece is in a stationary state waiting for processing on the production line or is quickly transferred between different workstations, the positioning module can continuously and stably transmit the position information of the workpiece to the management system of the production line, so that the operator can understand the position status of the workpiece at any time, providing key data support for production scheduling and monitoring.

[0046] The beat processing module is the core control hub of the entire workstation beat recognition production line. It is responsible for acquiring beat data for workpieces at each workstation and conducting in-depth analysis and judgment based on this data. During the production process, the beat processing module interacts with real-time data from the electronic fence and positioning modules to accurately obtain key beat data, such as the workpiece's entry and exit times at each workstation. The module then uses built-in complex algorithms and data analysis models to perform a series of calculations and logical judgments based on this beat data. It calculates the workpiece processing time at each workstation and compares it with the preset design time. If the processing time exceeds the design time, the workstation is identified as an abnormal workstation. Causes of abnormal workstations may include equipment failure, unreasonable operating procedures, or insufficient worker proficiency. The beat processing module also comprehensively analyzes the beat data from all workstations to calculate the line balance rate and compares it with a preset balance benchmark. If the line balance rate falls below the benchmark, it indicates imbalanced resource allocation or poor process transitions, and the line is identified as abnormal. In this way, the beat processing module can promptly identify potential problems in the production process and provide accurate decision-making basis for production managers so that they can quickly take corresponding measures to adjust and optimize, ensuring that the production line always maintains an efficient and stable operation state.

[0047] Specifically, the beat processing module mentioned above includes:

[0048] An acquisition submodule, used for acquiring beat data of the workpiece at each workstation;

[0049] The identification submodule is used to calculate the processing time of the workpiece at each workstation and the production line balance rate based on the beat data; identify abnormal workstations based on the processing time of the workpiece at each workstation, and identify abnormal production lines based on the production line balance rate.

[0050] In this embodiment, specifically, the identification submodule includes:

[0051] A first calculation unit calculates the time when the workpiece enters and exits each workstation; and calculates the processing time of the workpiece at each workstation based on the time when the workpiece enters and exits each workstation.

[0052] a second calculation unit, configured to calculate a production line balance rate of the production line according to a processing time of the workpiece at each workstation;

[0053] a first abnormality identification unit, configured to compare the processing time of the workpiece at each workstation with the design time corresponding to the workstation, and determine that the workstation is an abnormal workstation if the processing time of the workpiece is greater than the design time corresponding to the workstation;

[0054] The second abnormality identification unit is used to compare the balance rate of the production line with a balance reference value, and if the balance rate of the production line is less than the balance reference value, determine that the production line is an abnormal production line.

[0055] The acquisition submodule plays a role in data collection and acquisition. This module possesses powerful data acquisition capabilities. By establishing real-time communication with the electronic fence installed at each workstation and the positioning module attached to each workpiece, it accurately collects the workpiece's beat data at each workstation. In actual production scenarios, as a workpiece moves through various workstations on the production line, the positioning module continuously tracks the workpiece's location information, while the electronic fence accurately records the instants when the workpiece enters and leaves the corresponding workstation. The acquisition submodule captures this information transmitted by the electronic fence and positioning module in real time, including the time the workpiece enters and leaves the workstation.

[0056] The identification submodule is mainly responsible for data analysis and abnormality judgment. Based on the beat data provided by the acquisition submodule, the identification submodule performs calculation and analysis. On the one hand, the first calculation unit of the identification submodule will accurately calculate the processing time of the workpiece at each workstation based on the beat data. By calculating the difference between the time the workpiece enters the workstation and the time it leaves the workstation, the actual processing time of the workpiece at each workstation, that is, the processing time, is obtained. On the other hand, the second calculation unit of the identification submodule is also used to calculate the balance rate of the production line. It comprehensively analyzes the processing time data of each workstation, first finds the maximum value of the processing time of all workstations, and then calculates the sum of the processing time of each workstation. Then, based on the sum of the time and the maximum value, combined with the number of workstations on the production line, the balance rate of the production line is calculated by the following calculation formula:

[0057] k=((TT1+TT2+TT3+TT4+...+TTn) / (TTmax×n))×100%.

[0058] Where k is the production line balance rate, n is the number of workstations, TTn is the processing time of the workpiece at the nth workstation, and TTmax is the maximum processing time of all workstations.

[0059] After calculating the workpiece processing time at each workstation and the production line balance rate, the identification submodule immediately enters the abnormality detection phase. For each workstation, the identification submodule's first abnormality detection unit compares the calculated workpiece processing time with the pre-set standard processing time for that workstation. If the workpiece processing time at a particular workstation exceeds the designed time, the identification submodule identifies that workstation as abnormal and issues a timely abnormality alert. This abnormality detection process not only helps production managers quickly identify production bottlenecks but also provides clear direction for subsequent equipment maintenance, operational process optimization, and other tasks. For the entire production line, the identification submodule's second abnormality detection unit compares the calculated production line balance rate with a pre-set balance reference value. If the line balance rate is lower than the balance reference value, this indicates an imbalance in workload between the workstations on the production line, with some workstations potentially experiencing idle resources or overload. The identification submodule then determines the production line as abnormal. At this time, the identification submodule will generate a detailed exception report, including key information such as the comparative analysis of the processing time of the workstation on the horizontal production line, the deviation of the production line balance rate, etc., providing strong data support for production management personnel to formulate targeted production line optimization strategies, and helping the production line to resume efficient and stable operation as soon as possible.

[0060] Optionally, the identification submodule further includes:

[0061] The threshold calculation unit is used to obtain historical production line balance data obtained when the target parameters of the production line meet the target conditions within a historical time period, and determine the balance reference value based on the historical production line balance data.

[0062] In this embodiment, the historical time period selected can be determined based on a combination of factors, including the production characteristics of the production line, the workpiece processing cycle, and the stability of past data. For production lines with a fast production pace and short product iteration cycles, data from the past month or quarter may be selected as a historical reference; while for production lines with complex production processes and slow product updates, data from the past six months or even a year may be used. By selecting historical time periods in this targeted manner, it is possible to ensure that the acquired data is both timely and fully reflects the long-term operating status of the production line.

[0063] The "target parameters" of the production line cover information in multiple dimensions. Equipment parameters include but are not limited to the operating speed, power, temperature, etc. of each production equipment. Workpiece parameters involve the material, size, weight and other properties of the workpiece. Process parameters include various process methods and parameter settings used in the production process, such as reaction temperature and pressure in chemical production, and cutting speed and feed rate in mechanical processing. Environmental parameters refer to environmental factors such as temperature, humidity, and light intensity in the production workshop. These factors play an important role in the production process and product quality in some production scenarios with high environmental requirements, such as food processing and precision instrument manufacturing. Detection parameters are data related to product quality obtained through various types of detection equipment, such as product dimensional deviation, surface roughness, performance indicators, etc.

[0064] Target conditions are specific requirements and restrictions for these target parameters. For example, the target conditions for equipment parameters might be set to ensure that the equipment's operating speed is within ±10% of the rated speed, and that power fluctuations do not exceed 5% of the rated power, thereby ensuring stable operation. Target conditions for workpiece parameters are determined based on product design requirements, such as the requirement that workpiece dimensional tolerances must be controlled within ±0.1 mm. Target conditions for process parameters are derived from long-term production practice and process research. For example, in welding, the welding temperature must be maintained within a specific range to ensure weld quality. Only when these target parameters simultaneously meet the corresponding target conditions will the resulting production line balance data be considered by the threshold calculation unit.

[0065] After acquiring historical production line balance data that meets the target criteria, the threshold calculation unit can calculate statistics such as the mean, median, and standard deviation of this historical data. The mean provides an understanding of the approximate balance level of the production line in a stable state; the median reflects the middle of the data, minimizing the influence of extreme values; and the standard deviation measures the dispersion, or fluctuation, of the data. Data modeling can also be used to deeply mine and analyze historical data using machine learning algorithms or mathematical models. For example, a regression analysis model can be used to identify the mathematical relationship between target parameters and the production line balance rate, thereby predicting the production line balance rate under different scenarios and providing a more scientific basis for determining the balance baseline value.

[0066] In summary, the embodiments of this specification provide a workstation beat recognition production line, which includes multiple workstations, each of which is used to perform processing operations on a workpiece; multiple electronic fences, each of which is set at a workstation, and the electronic fence is used to identify the position of the workstation; multiple positioning modules, one of which is set on each workpiece, and the positioning module is used to identify the position of the workpiece; a beat processing module, which is used to obtain the beat data of the workpiece at each workstation and, based on the beat data, identify abnormal workstations and abnormal production lines. In this way, automatic statistical output of the beat of each workstation is achieved, real-time accounting of the workpiece's operating time at each workstation is calculated, and abnormal workstations and abnormal production lines are automatically identified.

[0067] Based on the same inventive concept, combined Figure 1 The flowchart, an embodiment of the present invention further provides a workstation beat recognition method, which is used in the aforementioned workstation beat recognition production line. The method includes steps 101 and 102:

[0068] Step 101: Acquire the beat data of the workpiece at each workstation;

[0069] Step 102: Calculate the processing time of the workpiece at each workstation and the production line balance rate based on the beat data; identify abnormal workstations based on the processing time of the workpiece at each workstation, and identify abnormal production lines based on the production line balance rate.

[0070] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific steps of the workstation rhythm recognition method described above can refer to the aforementioned embodiment and will not be elaborated here.

[0071] In summary, the embodiments of this specification provide a method for identifying the workstation beat. The production line includes multiple workstations, each of which is used to perform processing operations on a workpiece; multiple electronic fences, each of which is set at a workstation and used to identify the position of the workstation; multiple positioning modules, one of which is set on each workpiece and used to identify the position of the workpiece; and a beat processing module, which is used to obtain the beat data of the workpiece at each workstation and, based on the beat data, identify abnormal workstations and abnormal production lines. In this way, automatic statistical output of the beat of each workstation is achieved, real-time calculation of the workpiece's operating time at each workstation is achieved, and abnormal workstations and abnormal production lines are automatically identified.

[0072] Based on the same inventive concept, an embodiment of the present invention also provides a controller, which includes a memory, a processor and a communication unit. The memory stores machine-readable instructions executable by the processor. When the controller is running, the processor and the memory communicate through a bus, the processor executes the machine-readable instructions, and executes the workstation rhythm recognition method.

[0073] The memory, processor, and communication unit components are electrically connected to each other, directly or indirectly, to enable signal transmission or interaction. For example, these components can be electrically connected to each other via one or more communication buses or signal lines. The controller also includes at least one software function module that can be stored in the memory in the form of software or firmware. The processor is responsible for executing the executable module stored in the memory.

[0074] Among them, the memory can be, but is not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.

[0075] In some embodiments, the processor is used to perform one or more functions described in this embodiment. In some embodiments, the processor may include one or more processing cores (eg, a single-core processor (S) or a multi-core processor (S)).

[0076] In this embodiment, the memory is used to store the program, and the processor is used to execute the program after receiving the execution instruction. The process definition method disclosed in any implementation of this embodiment can be applied to the processor or implemented by the processor.

[0077] The communication unit is used to establish a communication connection between the controller and other devices through the network, and to send and receive data through the network.

[0078] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working process of the controller described above can refer to the corresponding process in the aforementioned method, and will not be elaborated here.

[0079] The above are merely various embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A station beat recognition production line, characterized in that: include: Multiple workstations, each of which is used to perform processing operations on the workpiece; A plurality of electronic fences, each electronic fence is set at a work station, and the electronic fence is used to identify the location of the work station; A plurality of positioning modules, each of which is provided with one positioning module, and is used to identify the position of the workpiece; The beat processing module is used to obtain the beat data of the workpiece at each workstation and identify abnormal workstations and abnormal production lines based on the beat data.

2. The production line according to claim 1, characterized in that: The beat processing module includes: An acquisition submodule, used for acquiring beat data of the workpiece at each workstation; The identification submodule is used to calculate the processing time of the workpiece at each workstation and the production line balance rate based on the beat data; identify abnormal workstations based on the processing time of the workpiece at each workstation, and identify abnormal production lines based on the production line balance rate.

3. The production line according to claim 2, characterized in that: The identification submodule includes: A first calculation unit is used to calculate the processing time of the workpiece at each workstation according to the beat data; a second calculation unit, configured to calculate a production line balance rate of the production line according to a processing time of the workpiece at each workstation; a first abnormality identification unit, configured to compare the processing time of the workpiece at each workstation with the design time corresponding to the workstation, and determine that the workstation is an abnormal workstation if the processing time of the workpiece is greater than the design time corresponding to the workstation; The second abnormality identification unit is used to compare the balance rate of the production line with a balance reference value, and if the balance rate of the production line is less than the balance reference value, determine that the production line is an abnormal production line.

4. The production line according to claim 3, characterized in that: The identification submodule further includes: The threshold calculation unit is used to obtain historical production line balance data obtained when the target parameters of the production line meet the target conditions within a historical time period, and determine the balance reference value based on the historical production line balance data.

5. The production line according to claim 4, characterized in that: The target parameters of the production line include equipment parameters, workpiece parameters, process parameters, environmental parameters and detection parameters of the production line.

6. The production line according to claim 3, characterized in that: The first calculation unit is used to determine the entry time and exit time of the workpiece at each workstation according to the beat data; The processing time of the workpiece at each workstation is calculated based on the entry time and exit time of the workpiece at each workstation.

7. The production line according to claim 3, characterized in that: The second calculation unit is used to determine the maximum processing time of the workpiece at each workstation; calculate the sum of the processing time according to the processing time of the workpiece at each workstation; and calculate the production line balance rate of the production line according to the sum of the processing time and the maximum processing time.

8. The production line according to claim 1, characterized in that: The workpiece is a processed part of a railway freight car.

9. A method for identifying a workstation rhythm, characterized in that: Using the workstation beat recognition production line according to any one of claims 1 to 8, the method comprises: Acquire the beat data of the workpiece at each workstation; According to the beat data, the processing time of the workpiece at each workstation and the production line balance rate are calculated; abnormal workstations are identified according to the processing time of the workpiece at each workstation, and abnormal production lines are identified according to the production line balance rate.

10. A controller, characterized in that: The controller includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the workstation rhythm recognition method according to claim 9 is implemented.

Images