Part production detection system and method applying data analysis technology

Abstract

The invention relates to the technical field of part production detection, in particular to a part production detection system and method applying a data analysis technology, and the method comprises the steps: analyzing the fault influence degree between different industrial devices, calculating the device influence value between the industrial devices, and screening each historical fault record of the industrial devices; analyzing the part fault state of each equipment part of the industrial equipment under different use durations, and calculating the feature fault probability value of each equipment part to the industrial equipment; calculating a marked fault value of the industrial equipment in the current period; the method comprises the following steps: acquiring a marked fault value of each industrial device in a current period, performing fault state analysis on the device state of each industrial device in the current period to obtain a target industrial device, acquiring the target industrial device in the current period, and performing intelligent management on part production detection of an industrial production line in the current period.

Description

Technical Field

[0001] The present invention relates to the technical field of parts production detection, and in particular to a parts production detection system and method using data analysis technology. Background Art

[0002] Data analysis technology is a method and tool for discovering, interpreting and communicating hidden patterns, relationships and insights in data. It involves the use of statistical analysis, machine learning, data mining and visualization technology to process large amounts of data and extract valuable information to support decision making and problem solving. Therefore, it has been gradually applied to the production and inspection of parts in industrial production lines. Through data analysis technology, parts in the production process can be monitored and predicted in real time, potential problems can be discovered and adjusted in time to avoid the generation of defective products and reduce production interruptions. In addition, data analysis technology can also help detect and analyze quality problems and defects in the production process of parts and components, and identify factors that may cause quality problems. However, at present, in the process of parts production and inspection, the equipment status analysis of industrial equipment responsible for parts and components is not very perfect, but the equipment status of industrial equipment is very important in the process of parts production and inspection. This will lead to equipment problems of industrial equipment, affecting the efficiency of parts production and inspection, and may even lead to a large number of problematic parts being produced and sold, seriously affecting the production and development of enterprises. Summary of the invention

[0003] The purpose of the present invention is to provide a parts production detection system and method using data analysis technology to solve the problems raised in the above background technology.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions: a component production detection method using data analysis technology, the method comprising: Step S100: Build a parts production and testing cloud platform, obtain historical fault records of industrial equipment that performs production and testing of parts on industrial production lines, analyze the degree of fault impact between different industrial equipment, calculate the equipment impact value between industrial equipment, and screen each historical fault record of industrial equipment; Step S200: Based on each historical fault record of the industrial equipment, analyze the fault status of each equipment part of the industrial equipment at different usage times, and calculate the characteristic fault probability value of each equipment part to the industrial equipment; Step S300: monitoring the status of equipment parts of the industrial equipment in the current cycle, and calculating the marked fault value of the industrial equipment in the current cycle based on the characteristic fault probability value of the equipment parts to the industrial equipment; Step S400: Obtain the marked fault value of the industrial equipment in the current cycle, analyze the fault status of the equipment status of the industrial equipment in the current cycle, obtain the target industrial equipment, obtain the target industrial equipment in the current cycle, and intelligently manage the production and inspection of parts of the industrial production line in the current cycle.

[0005] Furthermore, step S100 includes: Step S101: Record and collect the process of producing and testing parts on the industrial production line within the historical period, obtain the historical fault records of the industrial equipment that produces and tests the parts on the industrial production line, and obtain the time point when each industrial equipment is judged to be faulty in each historical fault record. When the time points when several industrial equipment are judged to be faulty are in the same time period, the same time period is recorded as the first time period; Step S102: Acquire each faulty industrial device in the first time period, and randomly select any one industrial device from each industrial device determined to be faulty in the first time period as the first faulty industrial device based on the time point when each industrial device is determined to be faulty; Step S103: selecting a first faulty industrial device from the first time period, and selecting any one faulty industrial device from each faulty industrial device that is determined to be faulty, and recording it as a second faulty industrial device; Step S104: obtaining a first time period containing a first faulty industrial device and a second faulty industrial device, and extracting a time distance between time points when the first faulty industrial device and the second faulty industrial device are determined to be faulty, and recording the time distance between time points when the first faulty industrial device and the second faulty industrial device are determined to be faulty as a first time length; Step S105: Set a first quantity threshold. When the total number of the first time period containing the first faulty industrial equipment and the second faulty industrial equipment is greater than the first quantity threshold, the second faulty industrial equipment is recorded as the faulty industrial equipment. Set a second quantity threshold. When the total number of the first time period containing the first faulty industrial equipment and the second faulty industrial equipment is less than the first quantity threshold but greater than the second quantity threshold, calculate the equipment impact value between the first faulty industrial equipment and the second faulty industrial equipment: ; in, is the i-th first duration between the first faulty industrial equipment and the second faulty industrial equipment; is the total number of the first time period containing the first faulty industrial equipment and the second faulty industrial equipment; Step S106: setting an equipment impact value threshold, when the equipment impact value between the first faulty industrial equipment and the second faulty industrial equipment is greater than the equipment impact value threshold, it is determined that the fault of the second faulty industrial equipment is affected by the first faulty industrial equipment, otherwise, it is determined that the fault of the second faulty industrial equipment is unrelated to the first faulty industrial equipment; Step S107: setting a first unit time length, recording the time point when the industrial equipment is judged to be faulty in the historical fault record as the fault time point corresponding to the historical fault record; when the industrial equipment is the second fault industrial equipment, and the time length of the distance between the fault time point corresponding to a certain historical fault record of the industrial equipment and the fault time point corresponding to a certain historical fault record of the first fault industrial equipment is less than the first unit time length, the certain historical fault record of the industrial equipment is removed; and the various historical fault records retained by the industrial equipment are collected; In the above steps, the damage of a certain industrial equipment may cause other industrial equipment to be damaged. However, for the industrial equipment damaged by other industrial equipment, the correlation between the various equipment parts cannot be determined. Therefore, in order to eliminate the affected historical fault records, the time difference between the time points when the two industrial equipment are judged to be faulty is examined as a unit time length, and the historical fault records corresponding to the industrial equipment affected by other industrial equipment are eliminated to ensure the accuracy of the data in the judgment of the various equipment parts of the industrial equipment.

[0006] Further, step S200 includes: Step S201: using sensors to monitor the usage status of each equipment part of the industrial equipment, and obtaining the usage time of each equipment part of the industrial equipment, and extracting the usage time of each faulty equipment part in the industrial equipment from each historical fault record of the industrial equipment; Step S202: obtaining a usage time threshold of each equipment part of the industrial equipment that is preset when the industrial equipment leaves the factory. When the usage time of a certain faulty equipment part of the industrial equipment in a certain historical fault record is greater than the usage time threshold of the corresponding equipment part of the certain faulty equipment part, the certain faulty equipment part is recorded as a characteristic faulty equipment part. Step S203: Acquire characteristic faulty equipment parts corresponding to each historical fault record of the industrial equipment, arbitrarily select a characteristic faulty equipment part from the historical fault record, and record it as the main characteristic faulty equipment part; extract each equipment part of the industrial equipment from the historical fault record, and the time point when it is determined to be a faulty equipment part; Step S204: From each faulty equipment part in the historical fault records, select the faulty equipment part after the time point when the main characteristic faulty equipment part is determined to be a fault, and record it as the suspected characteristic faulty equipment part; when the time point when the main characteristic faulty equipment part is determined to be a fault in each historical fault record of the industrial equipment is before the time point when the suspected characteristic faulty equipment part is determined to be a fault, it is determined that the fault of the suspected characteristic faulty equipment part is affected by the main characteristic faulty equipment part, and the suspected passive faulty equipment part is recorded as the characteristic faulty equipment part; Step S205: when a certain historical fault record of industrial equipment contains a main characteristic fault equipment part and a characteristic fault equipment part, the usage time of the characteristic fault equipment part in the certain historical fault record is eliminated; Step S206: When the equipment part is judged to be faulty, the number of historical fault records of the industrial equipment to which it belongs is obtained, and the characteristic fault probability value of the equipment part under different usage time is calculated, and the characteristic fault probability value of the equipment part when the usage time is k unit time is calculated: ; in, When an equipment part is judged to be faulty, the total number of historical fault records of each industrial equipment to which the equipment part belongs; It is the total number of historical failure records of each industrial equipment to which the equipment parts belong, with the service life of the equipment parts within k unit time.

[0007] Furthermore, step S300 includes: Step S301: Record the minimum value of each usage time of the faulty equipment parts as the characteristic fault time of the equipment parts, and obtain the characteristic fault probability value of each faulty equipment part in the industrial equipment when the usage time is different unit time; Step S302: monitoring the equipment status of the industrial equipment that performs production inspection on the parts in the current cycle, and obtaining the usage time of each equipment part of the industrial equipment in the current cycle, wherein the duration of the current cycle is a unit duration; Step S303: When the usage time of a certain equipment part of the industrial equipment in the current cycle is greater than the characteristic failure time of a certain equipment part, based on the equipment parts, the characteristic failure probability values ​​of each equipment part of the industrial equipment are obtained and aggregated to obtain the characteristic failure probability set of the industrial equipment in the current cycle. ,in, Respectively represent the characteristic failure probability values ​​of the 1st, 2nd, ..., yth equipment parts of the industrial equipment in the current cycle; Step S304: Calculate the marked fault value of the industrial equipment in the current cycle .

[0008] Furthermore, step S400 includes: Step S401: setting a marked fault value threshold for each industrial device, obtaining a marked fault value of each industrial device that performs production inspection on parts in the industrial production line in the current cycle, and when the marked fault value of a certain industrial device in the current cycle is greater than the preset marked fault threshold, the certain industrial device is recorded as a target industrial device; Step S402: setting a characteristic failure probability threshold of a device part, when the characteristic failure probability value of a device part in the current cycle is greater than the characteristic failure probability value threshold, the device part is recorded as a target device part; Step S403: acquiring each target equipment part in the target industrial equipment, acquiring several target industrial equipment in each industrial equipment that performs production inspection on parts on the industrial production line in the current cycle, and several target equipment parts in several industrial equipment; Step S404: Send a prompt to the industrial equipment management background to remind the staff to repair the target industrial equipment within the current cycle, replace several target parts in the target industrial equipment, and intelligently manage the production and inspection of parts of the industrial production line within the current cycle.

[0009] In order to better implement the above method, a parts production detection system is also proposed, which includes a screening module, a characteristic fault probability value module, a marking fault value module, and an intelligent management module; The screening module is used to analyze the impact of faults between different industrial equipment, calculate the equipment impact value between industrial equipment, and screen the historical fault records of industrial equipment; The characteristic failure probability value module is used to analyze the failure status of each equipment part of the industrial equipment at different usage times and calculate the characteristic failure probability value of each equipment part to the industrial equipment; A marked fault value module is used to monitor the status of equipment parts of industrial equipment in the current cycle, and calculate the marked fault value of the industrial equipment in the current cycle based on the characteristic fault probability value of the equipment parts to the industrial equipment; The equipment intelligent management module is used to analyze the fault status of each industrial equipment in the current cycle, obtain the target industrial equipment, obtain each target industrial equipment in the current cycle, and intelligently manage each industrial equipment in the current cycle.

[0010] Further, the screening module includes a device impact value unit and a historical usage record unit; The equipment impact value unit is used to obtain the time distance between the time points when the first faulty industrial equipment and the second faulty industrial equipment are determined to be faulty, and record the time distance between the time points when the first faulty industrial equipment and the second faulty industrial equipment are determined to be faulty as a first duration; The historical usage record unit is used to record the time point when the industrial equipment is judged to be faulty in the historical fault record as the fault time point corresponding to the historical fault record; and to collect various historical fault records retained by the industrial equipment.

[0011] Furthermore, the characteristic fault probability value module includes a usage time unit and a characteristic fault probability value unit; The usage time unit is used to obtain the usage time of each component of the industrial equipment, and extract the usage time of each fault component in the industrial equipment from each historical fault record of the industrial equipment; The characteristic failure probability value unit is used to obtain the number of historical failure records of the industrial equipment to which the component belongs when it is judged to be faulty within each unit time, and calculate the characteristic failure probability values ​​of the equipment parts in the industrial equipment under different usage time.

[0012] Further, the marking fault value module includes a device monitoring unit and a marking fault value unit; An equipment monitoring unit is used to monitor various components of industrial equipment using sensors to obtain the usage time of each component of the industrial equipment; The mark fault value unit is used to calculate the mark fault value of the industrial equipment in the current cycle.

[0013] Further, the device intelligent management module includes a device intelligent management unit; The equipment intelligent management unit is used to obtain the marked fault value of each industrial equipment that performs production inspection on parts in the current cycle of the industrial production line. When the marked fault value of a certain industrial equipment in the current cycle is greater than the preset marked fault threshold, the certain industrial equipment is recorded as the target industrial equipment, and each target part in the target industrial equipment is obtained. A prompt is sent to the industrial equipment management background to remind the staff to inspect the target industrial equipment and replace several target parts in the target industrial equipment in the current cycle, so as to intelligently manage the production inspection of parts of the industrial production line in the current cycle.

[0014] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention realizes intelligent management of production inspection of parts and components in industrial production lines, and can perform preventive maintenance by analyzing the equipment status and fault prediction of industrial equipment responsible for production inspection of parts and components. By predicting the failure of equipment parts, potential failure risks can be discovered in advance, and repairs or replacements can be performed in time to avoid shutdowns and production interruptions of industrial equipment due to equipment part failures. This enables the potential failure risks of industrial equipment to be discovered in advance during the production inspection of parts and components, and repairs or replacements can be performed in time to avoid shutdowns and production interruptions of equipment due to parts and components failures. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings are used to provide a further understanding of the present invention and constitute part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a method flow chart of a component production detection system and method using data analysis technology of the present invention; Figure 2 It is a module schematic diagram of a parts production detection system and method using data analysis technology in the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] See also Figure 1-Figure 2 The present invention provides a technical solution: a component production detection method using data analysis technology, the method comprising: Step S100: Build a parts production and testing cloud platform, obtain historical fault records of industrial equipment that performs production and testing of parts on industrial production lines, analyze the degree of fault impact between different industrial equipment, calculate the equipment impact value between industrial equipment, and screen each historical fault record of industrial equipment; Wherein, step S100 includes: Step S101: Record and collect the process of producing and testing parts on the industrial production line within the historical period, obtain the historical fault records of the industrial equipment that produces and tests the parts on the industrial production line, and obtain the time point when each industrial equipment is judged to be faulty in each historical fault record. When the time points when several industrial equipment are judged to be faulty are in the same time period, the same time period is recorded as the first time period; Step S102: Acquire each faulty industrial device in the first time period, and randomly select any one industrial device from each industrial device determined to be faulty in the first time period as the first faulty industrial device based on the time point when each industrial device is determined to be faulty; Step S103: selecting a first faulty industrial device from the first time period, and selecting any one faulty industrial device from each faulty industrial device that is determined to be faulty, and recording it as a second faulty industrial device; Step S104: obtaining a first time period containing a first faulty industrial device and a second faulty industrial device, and extracting a time distance between time points when the first faulty industrial device and the second faulty industrial device are determined to be faulty, and recording the time distance between time points when the first faulty industrial device and the second faulty industrial device are determined to be faulty as a first time length; Step S105: Set a first quantity threshold. When the total number of the first time period containing the first faulty industrial equipment and the second faulty industrial equipment is greater than the first quantity threshold, the second faulty industrial equipment is recorded as the faulty industrial equipment. Set a second quantity threshold. When the total number of the first time period containing the first faulty industrial equipment and the second faulty industrial equipment is less than the first quantity threshold but greater than the second quantity threshold, calculate the equipment impact value between the first faulty industrial equipment and the second faulty industrial equipment: ; in, is the i-th first duration between the first faulty industrial equipment and the second faulty industrial equipment; is the total number of the first time period containing the first faulty industrial equipment and the second faulty industrial equipment; Step S106: setting an equipment impact value threshold, when the equipment impact value between the first faulty industrial equipment and the second faulty industrial equipment is greater than the equipment impact value threshold, it is determined that the fault of the second faulty industrial equipment is affected by the first faulty industrial equipment, otherwise, it is determined that the fault of the second faulty industrial equipment is unrelated to the first faulty industrial equipment; Step S107: setting a first unit time length, recording the time point when the industrial equipment is judged to be faulty in the historical fault record as the fault time point corresponding to the historical fault record; when the industrial equipment is the second fault industrial equipment, and the time length of the distance between the fault time point corresponding to a certain historical fault record of the industrial equipment and the fault time point corresponding to a certain historical fault record of the first fault industrial equipment is less than the first unit time length, the certain historical fault record of the industrial equipment is removed; and the various historical fault records retained by the industrial equipment are collected; Step S200: Based on each historical fault record of the industrial equipment, analyze the fault status of each equipment part of the industrial equipment at different usage times, and calculate the characteristic fault probability value of each equipment part to the industrial equipment; Wherein, step S200 includes: Step S201: using sensors to monitor the usage status of each equipment part of the industrial equipment, and obtaining the usage time of each equipment part of the industrial equipment, and extracting the usage time of each faulty equipment part in the industrial equipment from each historical fault record of the industrial equipment; Step S202: obtaining a usage time threshold of each equipment part of the industrial equipment that is preset when the industrial equipment leaves the factory. When the usage time of a certain faulty equipment part of the industrial equipment in a certain historical fault record is greater than the usage time threshold of the corresponding equipment part of the certain faulty equipment part, the certain faulty equipment part is recorded as a characteristic faulty equipment part. Step S203: Acquire characteristic faulty equipment parts corresponding to each historical fault record of the industrial equipment, arbitrarily select a characteristic faulty equipment part from the historical fault record, and record it as the main characteristic faulty equipment part; extract each equipment part of the industrial equipment from the historical fault record, and the time point when it is determined to be a faulty equipment part; Step S204: From each faulty equipment part in the historical fault records, select the faulty equipment part after the time point when the main characteristic faulty equipment part is determined to be a fault, and record it as the suspected characteristic faulty equipment part; when the time point when the main characteristic faulty equipment part is determined to be a fault in each historical fault record of the industrial equipment is before the time point when the suspected characteristic faulty equipment part is determined to be a fault, it is determined that the fault of the suspected characteristic faulty equipment part is affected by the main characteristic faulty equipment part, and the suspected passive faulty equipment part is recorded as the characteristic faulty equipment part; Step S205: when a certain historical fault record of industrial equipment contains a main characteristic fault equipment part and a characteristic fault equipment part, the usage time of the characteristic fault equipment part in the certain historical fault record is eliminated; Step S206: When the equipment part is judged to be faulty, the number of historical fault records of the industrial equipment to which it belongs is obtained, and the characteristic fault probability value of the equipment part under different usage time is calculated, and the characteristic fault probability value of the equipment part when the usage time is k unit time is calculated: ; in, When an equipment part is judged to be faulty, the total number of historical fault records of each industrial equipment to which the equipment part belongs; is the total number of historical failure records of each industrial equipment to which the equipment parts belong, with the service life of the equipment parts within k unit time; For example, when a device part is judged to be faulty, the total number of historical fault records of each industrial device to which the device part belongs 50; the total number of historical failure records of each industrial equipment to which the equipment parts belong, with a service life within 4 unit time =20; calculate the characteristic failure probability value of the equipment parts when the service life is 4 units ; Step S300: monitoring the status of equipment parts of the industrial equipment in the current cycle, and calculating the marked fault value of the industrial equipment in the current cycle based on the characteristic fault probability value of the equipment parts to the industrial equipment; Wherein, step S300 includes: Step S301: Record the minimum value of each usage time of the faulty equipment parts as the characteristic fault time of the equipment parts, and obtain the characteristic fault probability value of each faulty equipment part in the industrial equipment when the usage time is different unit time; Step S302: monitoring the equipment status of the industrial equipment that performs production inspection on the parts in the current cycle, and obtaining the usage time of each equipment part of the industrial equipment in the current cycle, wherein the duration of the current cycle is a unit duration; Step S303: When the usage time of a certain equipment part of the industrial equipment in the current cycle is greater than the characteristic failure time of a certain equipment part, based on the equipment parts, the characteristic failure probability values ​​of each equipment part of the industrial equipment are obtained and aggregated to obtain the characteristic failure probability set of the industrial equipment in the current cycle. ,in, Respectively represent the characteristic failure probability values ​​of the 1st, 2nd, ..., yth equipment parts of the industrial equipment in the current cycle; Step S304: Calculate the marked fault value of the industrial equipment in the current cycle ; Step S400: Obtain the marked fault value of the industrial equipment in the current cycle, analyze the fault status of the equipment status of the industrial equipment in the current cycle, obtain the target industrial equipment, obtain the target industrial equipment in the current cycle, and intelligently manage the production and detection of parts of the industrial production line in the current cycle; Wherein, step S400 includes: Step S401: setting a marked fault value threshold for each industrial device, obtaining a marked fault value of each industrial device that performs production inspection on parts in the industrial production line in the current cycle, and when the marked fault value of a certain industrial device in the current cycle is greater than the preset marked fault threshold, the certain industrial device is recorded as a target industrial device; Step S402: setting a characteristic failure probability threshold of a device part, when the characteristic failure probability value of a device part in the current cycle is greater than the characteristic failure probability value threshold, the device part is recorded as a target device part; Step S403: acquiring each target equipment part in the target industrial equipment, acquiring several target industrial equipment in each industrial equipment that performs production inspection on parts on the industrial production line in the current cycle, and several target equipment parts in several industrial equipment; Step S404: Send a prompt to the industrial equipment management background to remind the staff to repair the target industrial equipment in the current cycle, replace several target parts in the target industrial equipment, and intelligently manage the production and testing of parts of the industrial production line in the current cycle; In order to better implement the above method, a parts production detection system is also proposed, which includes a screening module, a characteristic fault probability value module, a marking fault value module, and an intelligent management module; The screening module is used to analyze the impact of faults between different industrial equipment, calculate the equipment impact value between industrial equipment, and screen the historical fault records of industrial equipment; The characteristic failure probability value module is used to analyze the failure status of each equipment part of the industrial equipment at different usage times and calculate the characteristic failure probability value of each equipment part to the industrial equipment; A marked fault value module is used to monitor the status of equipment parts of industrial equipment in the current cycle, and calculate the marked fault value of the industrial equipment in the current cycle based on the characteristic fault probability value of the equipment parts to the industrial equipment; The equipment intelligent management module is used to analyze the equipment status of each industrial equipment in the current cycle, obtain the target industrial equipment, obtain each target industrial equipment in the current cycle, and intelligently manage each industrial equipment in the current cycle; Among them, the screening module includes a device impact value unit and a historical usage record unit; The equipment impact value unit is used to obtain the time distance between the time points when the first faulty industrial equipment and the second faulty industrial equipment are determined to be faulty, and record the time distance between the time points when the first faulty industrial equipment and the second faulty industrial equipment are determined to be faulty as a first duration; The historical use recording unit is used to record the time point when the industrial equipment is judged to be faulty in the historical fault record as the fault time point corresponding to the historical fault record; and to collect various historical fault records retained by the industrial equipment; Among them, the characteristic fault probability value module includes a usage time unit and a characteristic fault probability value unit; The usage time unit is used to obtain the usage time of each component of the industrial equipment, and extract the usage time of each fault component in the industrial equipment from each historical fault record of the industrial equipment; The characteristic failure probability value unit is used to obtain the number of historical failure records of the industrial equipment to which the component belongs when it is judged to be a failure within each unit time, and calculate the characteristic failure probability value of the equipment parts in the industrial equipment under different usage time; Wherein, the marking fault value module includes a device monitoring unit and a marking fault value unit; An equipment monitoring unit is used to monitor various components of industrial equipment using sensors to obtain the usage time of each component of the industrial equipment; A marked fault value unit, used for calculating a marked fault value of the industrial equipment in a current cycle; Wherein, the equipment intelligent management module includes an equipment intelligent management unit; The equipment intelligent management unit is used to obtain the marked fault value of each industrial equipment that performs production inspection on parts in the current cycle of the industrial production line. When the marked fault value of a certain industrial equipment in the current cycle is greater than the preset marked fault threshold, the certain industrial equipment is recorded as the target industrial equipment, and each target part in the target industrial equipment is obtained. A prompt is sent to the industrial equipment management background to remind the staff to inspect the target industrial equipment and replace several target parts in the target industrial equipment in the current cycle, so as to intelligently manage the production inspection of parts of the industrial production line in the current cycle.

[0018] It should be noted that, in this article, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

Claims

1. A component production detection method using data analysis technology, characterized in that: The method comprises: Step S100: construct a parts production and testing cloud platform, obtain historical fault records of industrial equipment that performs production and testing of parts on the industrial production line, analyze the degree of fault impact between different industrial equipment, calculate the equipment impact value between industrial equipment, and screen each historical fault record of industrial equipment; Step S200: Based on each historical fault record of the industrial equipment, analyze the fault status of each equipment part of the industrial equipment at different usage times, and calculate the characteristic fault probability value of each equipment part to the industrial equipment; Step S300: monitoring the status of equipment parts of the industrial equipment in the current cycle, and calculating the marked fault value of the industrial equipment in the current cycle based on the characteristic fault probability value of the equipment parts to the industrial equipment; Step S400: Obtain the marked fault value of the industrial equipment in the current cycle, analyze the fault status of the equipment status of the industrial equipment in the current cycle, obtain the target industrial equipment, obtain the target industrial equipment in the current cycle, and intelligently manage the production and inspection of parts of the industrial production line in the current cycle.

2. The component production detection method using data analysis technology according to claim 1, characterized in that: The step S100 includes: Step S101: Record and collect the process of producing and testing parts on the industrial production line within the historical period, obtain the historical fault records of the industrial equipment that produces and tests the parts on the industrial production line, and obtain the time point when each industrial equipment is judged to be faulty in each historical fault record. When the time points when several industrial equipment are judged to be faulty are in the same time period, the same time period is recorded as the first time period; Step S102: Acquire each faulty industrial device in the first time period, and randomly select any one industrial device from each industrial device determined to be faulty in the first time period as the first faulty industrial device based on the time point when each industrial device is determined to be faulty; Step S103: selecting a first faulty industrial device from the first time period, and selecting any one faulty industrial device from each faulty industrial device that is determined to be faulty, and recording it as a second faulty industrial device; Step S104: obtaining a first time period containing a first faulty industrial device and a second faulty industrial device, and extracting a time distance between time points when the first faulty industrial device and the second faulty industrial device are determined to be faulty, and recording the time distance between time points when the first faulty industrial device and the second faulty industrial device are determined to be faulty as a first time length; Step S105: Set a first quantity threshold. When the total number of the first time period containing the first faulty industrial equipment and the second faulty industrial equipment is greater than the first quantity threshold, the second faulty industrial equipment is recorded as the faulty industrial equipment. Set a second quantity threshold. When the total number of the first time period containing the first faulty industrial equipment and the second faulty industrial equipment is less than the first quantity threshold but greater than the second quantity threshold, calculate the equipment impact value between the first faulty industrial equipment and the second faulty industrial equipment: ； in, is the i-th first duration between the first faulty industrial equipment and the second faulty industrial equipment; is the total number of the first time period containing the first faulty industrial equipment and the second faulty industrial equipment; Step S106: setting an equipment impact value threshold, when the equipment impact value between the first faulty industrial equipment and the second faulty industrial equipment is greater than the equipment impact value threshold, it is determined that the fault of the second faulty industrial equipment is affected by the first faulty industrial equipment, otherwise, it is determined that the fault of the second faulty industrial equipment is unrelated to the first faulty industrial equipment; Step S107: Set a first unit time length, and record the time point when the industrial equipment is judged to be faulty in the historical fault record as the fault time point corresponding to the historical fault record; when the industrial equipment is a second fault industrial equipment, and the fault time point corresponding to a certain historical fault record of the industrial equipment is less than the first unit time length from the fault time point corresponding to a certain historical fault record of the first fault industrial equipment, the certain historical fault record of the industrial equipment is deleted; and the various historical fault records retained by the industrial equipment are aggregated.

3. The component production detection method using data analysis technology according to claim 2 is characterized in that: The step S200 includes: Step S201: using sensors to monitor the usage status of each equipment part of the industrial equipment, and obtaining the usage time of each equipment part of the industrial equipment, and extracting the usage time of each faulty equipment part in the industrial equipment from each historical fault record of the industrial equipment; Step S202: obtaining a usage time threshold of each equipment part of the industrial equipment that is preset when the industrial equipment leaves the factory. When the usage time of a certain faulty equipment part of the industrial equipment in a certain historical fault record is greater than the usage time threshold of the corresponding equipment part of the certain faulty equipment part, the certain faulty equipment part is recorded as a characteristic faulty equipment part. Step S203: Acquire characteristic faulty equipment parts corresponding to each historical fault record of the industrial equipment, arbitrarily select a characteristic faulty equipment part from the historical fault record, and record it as the main characteristic faulty equipment part; extract each equipment part of the industrial equipment from the historical fault record, and the time point when it is determined to be a faulty equipment part; Step S204: From each faulty equipment part in the historical fault records, select the faulty equipment part after the time point when the main characteristic faulty equipment part is determined to be a fault, and record it as the suspected characteristic faulty equipment part; when the time point when the main characteristic faulty equipment part is determined to be a fault in each historical fault record of the industrial equipment is before the time point when the suspected characteristic faulty equipment part is determined to be a fault, it is determined that the fault of the suspected characteristic faulty equipment part is affected by the main characteristic faulty equipment part, and the suspected passive faulty equipment part is recorded as the characteristic faulty equipment part; Step S205: when a certain historical fault record of industrial equipment contains a main characteristic fault equipment part and a characteristic fault equipment part, the usage time of the characteristic fault equipment part in the certain historical fault record is eliminated; Step S206: When the equipment part is judged to be faulty, the number of historical fault records of the industrial equipment to which it belongs is obtained, and the characteristic fault probability value of the equipment part under different usage time is calculated, and the characteristic fault probability value of the equipment part when the usage time is k unit time is calculated: ； in, The total number of historical fault records of each industrial equipment to which the equipment part belongs when the equipment part is determined to be faulty; It is the total number of historical fault records of each industrial equipment to which the equipment part belongs, in which the service life of the equipment part is within k unit time lengths.

4. The equipment parts production detection method using data analysis technology according to claim 3 is characterized in that: The step S300 includes: Step S301: Record the minimum value of each usage time of the faulty equipment parts as the characteristic fault time of the equipment parts, and obtain the characteristic fault probability value of each faulty equipment part in the industrial equipment when the usage time is different unit time; Step S302: monitoring the equipment status of the industrial equipment that performs production inspection on the parts in the current cycle, and obtaining the usage time of each equipment part of the industrial equipment in the current cycle, wherein the duration of the current cycle is a unit duration; Step S303: When the usage time of a certain equipment part of the industrial equipment in the current cycle is greater than the characteristic failure time of the certain equipment part, based on the equipment part, the characteristic failure probability values ​​of each equipment part of the industrial equipment are obtained and aggregated to obtain the characteristic failure probability set of the industrial equipment in the current cycle. ,in, Respectively represent the characteristic failure probability values ​​of the 1st, 2nd, ..., yth equipment parts of the industrial equipment in the current cycle; Step S304: Calculate the marked fault value of the industrial equipment in the current cycle .

5. The component production detection method using data analysis technology according to claim 4 is characterized in that: The step S400 includes: Step S401: setting a marked fault value threshold for each industrial device, obtaining a marked fault value of each industrial device that performs production inspection on parts in the industrial production line in the current cycle, and when the marked fault value of a certain industrial device in the current cycle is greater than the preset marked fault threshold, the certain industrial device is recorded as a target industrial device; Step S402: setting a characteristic failure probability threshold of a device part, when the characteristic failure probability value of a device part in the current cycle is greater than the characteristic failure probability value threshold, the device part is recorded as a target device part; Step S403: Acquire each target equipment part in the target industrial equipment, acquire several target industrial equipment among various industrial equipment that perform production inspection on parts on the industrial production line in the current cycle, and several target equipment parts among the several industrial equipment; Step S404: Send a prompt to the industrial equipment management background to remind the staff to repair the target industrial equipment within the current cycle, replace several target parts in the target industrial equipment, and intelligently manage the production and inspection of parts of the industrial production line within the current cycle.

6. A parts production detection system applied to a parts production detection method using data analysis technology as described in any one of claims 1 to 5, characterized in that: The parts production detection system includes a screening module, a characteristic fault probability value module, a marking fault value module, and an intelligent management module; The screening module is used to analyze the degree of fault impact between different industrial equipment, calculate the equipment impact value between industrial equipment, and screen each historical fault record of industrial equipment; The characteristic failure probability value module is used to analyze the failure states of various equipment parts of industrial equipment at different usage times and calculate the characteristic failure probability value of each equipment part to the industrial equipment; The marked fault value module is used to monitor the status of equipment parts of industrial equipment in the current cycle, and calculate the marked fault value of the industrial equipment in the current cycle based on the characteristic fault probability value of the equipment parts to the industrial equipment; The equipment intelligent management module is used to analyze the fault status of each industrial equipment in the current cycle, obtain the target industrial equipment, obtain each target industrial equipment in the current cycle, and intelligently manage each industrial equipment in the current cycle.

7. The parts production detection system according to claim 6, characterized in that: The screening module includes a device impact value unit and a historical usage record unit; The equipment impact value unit is used to obtain the time distance between the time points when the first faulty industrial equipment and the second faulty industrial equipment are determined to be faulty, and record the time distance between the time points when the first faulty industrial equipment and the second faulty industrial equipment are determined to be faulty as a first duration; The historical usage recording unit is used to record the time point when the industrial equipment is determined to be faulty in the historical fault record as the fault time point corresponding to the historical fault record; and to collect various historical fault records retained by the industrial equipment.

8. The parts production inspection system according to claim 6, characterized in that: The characteristic fault probability value module includes a usage time unit and a characteristic fault probability value unit; The usage time unit is used to obtain the usage time of each component of the industrial equipment, and extract the usage time of each faulty component in the industrial equipment from each historical fault record of the industrial equipment; The characteristic failure probability value unit is used to obtain the number of historical failure records of the industrial equipment to which the component belongs when the component is determined to be faulty within each unit time, and calculate the characteristic failure probability values ​​of the equipment parts in the industrial equipment under different usage time.

9. The parts production detection system according to claim 6, characterized in that: The marking fault value module includes a device monitoring unit and a marking fault value unit; The equipment monitoring unit is used to monitor various components of the industrial equipment using sensors to obtain the usage time of each component of the industrial equipment; The marked fault value unit is used to calculate the marked fault value of the industrial equipment in the current cycle.

10. The parts production detection system according to claim 6, characterized in that: The device intelligent management module includes a device intelligent management unit; The equipment intelligent management unit is used to obtain the marked fault value of each industrial equipment that performs production inspection on parts in the industrial production line in the current cycle. When the marked fault value of a certain industrial equipment in the current cycle is greater than a preset marked fault threshold, the certain industrial equipment is recorded as the target industrial equipment, and each target part in the target industrial equipment is obtained. A prompt is sent to the industrial equipment management background to remind the staff to inspect the target industrial equipment in the current cycle, replace several target parts in the target industrial equipment, and intelligently manage the production inspection of parts in the industrial production line in the current cycle.

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