A component production detection system and method using data analysis technology

Abstract

The application relates to the technical field of part production detection, in particular to a part production detection system and method applying data analysis technology, which comprises the following steps: analyzing the fault influence degree between different industrial equipment, calculating the equipment influence value between the industrial equipment, and screening the historical fault records of the industrial equipment; analyzing the part fault states of each part of the industrial equipment under different service time lengths, calculating the characteristic fault probability value of each part of the industrial equipment, calculating the marked fault value of the industrial equipment in the current period, obtaining the marked fault value of each industrial equipment in the current period, analyzing the fault states of the equipment states of each industrial equipment in the current period, obtaining the target industrial equipment, obtaining the target industrial equipment in the current period, and intelligently managing the part production detection of the industrial production line in the current period.

Description

Technical Field

[0001] This invention relates to the field of parts production and inspection technology, specifically to a parts production and inspection system and method that applies data analysis technology. Background Technology

[0002] Data analytics is a set of methods and tools used to discover, interpret, and communicate hidden patterns, relationships, and insights within data. It involves using statistical analysis, machine learning, data mining, and visualization techniques to process large amounts of data and extract valuable information to support decision-making and problem-solving. Therefore, it has been increasingly applied to the production inspection of parts in industrial production lines. Data analytics allows for real-time monitoring and prediction of parts during the production process, identifying potential problems and making timely adjustments to avoid defective products and reduce production interruptions. Furthermore, data analytics can help detect and analyze quality problems and defects in the parts production process and identify factors that may lead to quality issues. However, currently, the analysis of the equipment status of industrial equipment responsible for inspecting parts is not very comprehensive, even though the equipment status is crucial in parts production inspection. This can lead to equipment problems affecting the efficiency of parts production inspection and even potentially resulting in the production and sale of a large number of defective parts, seriously impacting enterprise production and development. Summary of the Invention

[0003] The purpose of this invention is to provide a parts production inspection system and method that applies data analysis technology to solve the problems mentioned in the background art.

[0004] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a component production inspection method applying data analysis technology, the method comprising:

[0005] Step S100: Construct a component production and testing cloud platform, obtain historical fault records of industrial equipment that performs component production and testing on the industrial production line, analyze the degree of fault impact between different industrial equipment, calculate the equipment impact value between industrial equipment, and filter the historical fault records of each industrial equipment.

[0006] Step S200: Based on the historical fault records of the industrial equipment, analyze the fault status of each part of the industrial equipment under different usage periods, and calculate the characteristic fault probability value of each part of the industrial equipment.

[0007] Step S300: Monitor the status of equipment parts of industrial equipment in the current cycle, and calculate the marked fault value of industrial equipment in the current cycle based on the characteristic fault probability value of equipment parts to industrial equipment;

[0008] Step S400: Obtain the marked fault value of the industrial equipment in the current cycle, analyze the fault status of the industrial equipment in the current cycle, obtain the target industrial equipment, and perform intelligent management of the component production and inspection of the industrial production line in the current cycle.

[0009] Furthermore, step S100 includes:

[0010] Step S101: Record and collect the process of industrial production line producing and testing parts within the historical period, obtain the historical fault records of industrial equipment that produces and tests parts on the industrial production line, obtain the time point when each industrial equipment is judged to be faulty in each historical fault record, and 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.

[0011] Step S102: Acquire each faulty industrial equipment within the first time period. Based on the time point when each industrial equipment is determined to be faulty, randomly select any one of the industrial equipment determined to be faulty within the first time period as the first faulty industrial equipment.

[0012] Step S103: Select the first faulty industrial equipment from the first time period, and select any one of the faulty industrial equipment after it has been determined to be faulty, and record it as the second faulty industrial equipment.

[0013] Step S104: Obtain the first time period containing the first faulty industrial equipment and the second faulty industrial equipment, and extract the time distance between the time points when the first faulty industrial equipment and the second faulty industrial equipment are determined to be faulty. 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 the first duration.

[0014] Step S105: Set a first quantity threshold. When the total number of industrial devices containing the first faulty industrial device and the second faulty industrial device in the first time period is greater than the first quantity threshold, the second faulty industrial device is recorded as the faulty industrial device. Set a second quantity threshold. When the total number of industrial devices containing the first faulty industrial device and the second faulty industrial device in the first time period is less than the first quantity threshold but greater than the second quantity threshold, calculate the equipment impact value between the first faulty industrial device and the second faulty industrial device.

[0015] ;

[0016] in, The first duration is the i-th time interval between the first faulty industrial equipment and the second faulty industrial equipment. The total number of industrial equipment in the first time period containing both the first and second faulty industrial equipment.

[0017] Step S106: Set the equipment influence value threshold. When the equipment influence value between the first faulty industrial equipment and the second faulty industrial equipment is greater than the equipment influence 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.

[0018] Step S107: Set the first unit duration, and record the time when the industrial equipment was determined to be faulty in the historical fault records as the fault time point corresponding to the historical fault record; when the industrial equipment is the second faulty industrial equipment, and the time 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 faulty industrial equipment is less than the first unit duration, remove the certain historical fault record of the industrial equipment; and aggregate all the historical fault records of the industrial equipment.

[0019] In the above steps, the failure of one piece of industrial equipment may lead to the failure of other industrial equipment. However, for industrial equipment that is damaged due to the influence of other industrial equipment, the correlation between the various parts of the equipment cannot be determined. Therefore, in order to remove the affected historical fault records, the time difference between the time points when two pieces of industrial equipment are determined to be faulty is examined in units of time. The historical fault records corresponding to the industrial equipment affected by other industrial equipment are removed to ensure the accuracy of the data in the judgment of the various parts of the industrial equipment.

[0020] Furthermore, step S200 includes:

[0021] Step S201: Use sensors to monitor the usage status of each part of the industrial equipment and acquire the usage time of each part of the industrial equipment. Extract the usage time of each faulty part of the industrial equipment from the historical fault records of the industrial equipment.

[0022] Step S202: Obtain the usage time threshold of each part of the industrial equipment that is preset when the industrial equipment leaves the factory. When the usage time of a certain faulty part of the industrial equipment in a certain historical fault record is greater than the usage time threshold of the corresponding part of the faulty part, the faulty part is recorded as a characteristic faulty part.

[0023] Step S203: Obtain the characteristic fault equipment parts corresponding to each historical fault record of the industrial equipment; arbitrarily select a characteristic fault equipment part from the historical fault record and record it as the main characteristic fault equipment part; extract the time points of each equipment part of the industrial equipment that were determined to be fault equipment parts from the historical fault record.

[0024] Step S204: From the historical fault records of each faulty equipment part, select the faulty equipment parts that were identified after the time point when the main characteristic faulty equipment part was identified as a faulty part, and record them as suspected faulty equipment parts; when the time point when the main characteristic faulty equipment part was identified as a faulty part in each historical fault record of the industrial equipment is before the time point when the suspected faulty equipment part was identified as a faulty part, determine that the fault of the suspected faulty equipment part is affected by the main characteristic faulty equipment part, and record the suspected passive faulty equipment part as the faulty equipment part.

[0025] Step S205: When a historical fault record of an industrial equipment contains both a main faulty equipment part and a faulty equipment part, the usage time of the faulty equipment part in a historical fault record is removed.

[0026] Step S206: Obtain the number of historical fault records of the industrial equipment to which the equipment part belongs when it is determined to be faulty, calculate the characteristic fault probability value of the equipment part under different usage durations, and calculate the characteristic fault probability value of the equipment part when the usage duration is k units of time:

[0027] ;

[0028] in, This refers to the total number of historical fault records for each industrial piece of equipment to which the equipment part belongs when the equipment part is determined to be faulty. This refers to the total number of historical fault records for each piece of equipment in the industrial equipment to which the equipment part belongs, where the equipment part's usage time is within k units of time.

[0029] Furthermore, step S300 includes:

[0030] Step S301: Record the minimum value of the usage time of each faulty equipment part as the characteristic fault duration of the equipment part, and obtain the characteristic fault probability value of each faulty equipment part in the industrial equipment when the usage time is different unit durations.

[0031] Step S302: Monitor the equipment status of the industrial equipment that performs production testing on the parts in the current cycle, and obtain the usage time of each part of the industrial equipment in the current cycle, wherein the duration of the current cycle is one unit duration;

[0032] Step S303: If, within the current period, the usage time of a certain equipment part of an industrial equipment is greater than the characteristic fault duration of that equipment part, based on the equipment part, the characteristic fault probability values ​​of each equipment part of the industrial equipment are obtained and aggregated to obtain the characteristic fault probability set of the industrial equipment within the current period. ,in, These represent the characteristic fault probability values ​​of the 1st, 2nd, ..., yth equipment parts of the industrial equipment within the current period;

[0033] Step S304: Calculate the marked fault value of the industrial equipment in the current period. .

[0034] Furthermore, step S400 includes:

[0035] Step S401: Set the marked fault value threshold for each industrial device, obtain the marked fault value of each industrial device that performs production inspection on parts in the current cycle of the industrial production line, 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 the target industrial device.

[0036] Step S402: Set the characteristic fault probability threshold for equipment parts. When the characteristic fault probability value of a certain equipment part is greater than the characteristic fault probability threshold in the current period, the equipment part is recorded as the target equipment part.

[0037] Step S403: Obtain each target equipment part within the target industrial equipment, obtain several target industrial equipments among the various industrial equipments that conduct production testing on the parts on the industrial production line in the current cycle, and several target equipment parts among the several industrial equipments;

[0038] Step S404: Send a prompt to the industrial equipment management backend to remind staff to inspect the target industrial equipment within the current cycle, replace several target parts within the target industrial equipment, and perform intelligent management of the production and testing of parts on the industrial production line within the current cycle.

[0039] To better implement the above methods, a parts production inspection system is also proposed, which includes a screening module, a characteristic fault probability value module, a fault value marking module, and an intelligent management module.

[0040] The filtering module is used to analyze the degree of fault impact between different industrial equipment, calculate the equipment impact value between industrial equipment, and filter the historical fault records of each industrial equipment.

[0041] The Feature Fault Probability Value module is used to analyze the fault status of various equipment parts under different usage periods of industrial equipment and calculate the feature fault probability value of each equipment part to the industrial equipment.

[0042] The fault value marking module is used to monitor the status of equipment parts of industrial equipment in the current cycle, and calculate the marked fault value of industrial equipment in the current cycle based on the characteristic fault probability value of equipment parts to industrial equipment.

[0043] The intelligent management module is used to analyze the fault status of each industrial device in the current cycle, obtain the target industrial device, acquire each target industrial device in the current cycle, and perform intelligent management of each industrial device in the current cycle.

[0044] Furthermore, the filtering module includes a device impact value unit and a historical usage record unit;

[0045] 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 the time distance between the time points when the first faulty industrial equipment and the second faulty industrial equipment are determined to be faulty is recorded as the first duration.

[0046] The historical usage record unit is used to record the time when the industrial equipment was determined to be faulty in the historical fault record as the fault time point corresponding to the historical fault record; and to collect all the historical fault records retained by the industrial equipment.

[0047] Furthermore, the feature failure probability value module includes a usage duration unit and a feature failure probability value unit;

[0048] The usage duration unit is used to obtain the usage duration of each component of industrial equipment, and to extract the usage duration of each faulty component in the industrial equipment from the historical fault records of the industrial equipment.

[0049] The characteristic fault probability value unit is used to obtain the number of historical fault records of the industrial equipment to which the component is identified as faulty within each unit of time, and to calculate the characteristic fault probability value of the equipment parts in the industrial equipment under different usage periods.

[0050] Furthermore, the fault value marking module includes an equipment monitoring unit and a fault value marking unit;

[0051] The equipment monitoring unit is used to monitor various components of industrial equipment using sensors and to obtain the usage time of each component.

[0052] The fault value marking unit is used to calculate the marked fault value of industrial equipment in the current cycle.

[0053] Furthermore, the intelligent management module includes an intelligent equipment management unit;

[0054] The intelligent equipment management unit is used to obtain the marked fault values ​​of each industrial equipment that performs production testing 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 industrial equipment is marked as the target industrial equipment. The unit obtains each target component in the target industrial equipment and sends a prompt to the industrial equipment management backend, reminding the staff to carry out maintenance on the target industrial equipment in the current cycle and replace several target components in the target industrial equipment. The unit performs intelligent management of the production testing of parts in the current cycle of the industrial production line.

[0055] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: The present invention realizes intelligent management of the production and inspection of parts in industrial production lines. By analyzing the equipment status and predicting the faults of the industrial equipment responsible for the production and inspection of parts, preventive maintenance can be carried out. By predicting the faults of equipment parts, potential fault risks can be discovered in advance, and timely repairs or replacements can be carried out to avoid downtime and production interruptions caused by equipment part failures. Thus, it is possible to discover potential fault risks of industrial equipment in advance during the production and inspection of parts, and to carry out timely repairs or replacements to avoid downtime and production interruptions caused by equipment part failures. Attached Figure Description

[0056] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0057] Figure 1 This is a flowchart of a parts production inspection system and method that applies data analysis technology according to the present invention;

[0058] Figure 2 This is a schematic diagram of a component production and testing system and method that applies data analysis technology according to the present invention. Detailed Implementation

[0059] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0060] Please see Figures 1-2The present invention provides a technical solution: a method for component production inspection using data analysis technology, the method comprising:

[0061] Step S100: Construct a component production and testing cloud platform, obtain historical fault records of industrial equipment that performs component production and testing on the industrial production line, analyze the degree of fault impact between different industrial equipment, calculate the equipment impact value between industrial equipment, and filter the historical fault records of each industrial equipment.

[0062] Step S100 includes:

[0063] Step S101: Record and collect the process of industrial production line producing and testing parts within the historical period, obtain the historical fault records of industrial equipment that produces and tests parts on the industrial production line, obtain the time point when each industrial equipment is judged to be faulty in each historical fault record, and 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.

[0064] Step S102: Acquire each faulty industrial equipment within the first time period. Based on the time point when each industrial equipment is determined to be faulty, randomly select any one of the industrial equipment determined to be faulty within the first time period as the first faulty industrial equipment.

[0065] Step S103: Select the first faulty industrial equipment from the first time period, and select any one of the faulty industrial equipment after it has been determined to be faulty, and record it as the second faulty industrial equipment.

[0066] Step S104: Obtain the first time period containing the first faulty industrial equipment and the second faulty industrial equipment, and extract the time distance between the time points when the first faulty industrial equipment and the second faulty industrial equipment are determined to be faulty. 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 the first duration.

[0067] Step S105: Set a first quantity threshold. When the total number of industrial devices containing the first faulty industrial device and the second faulty industrial device in the first time period is greater than the first quantity threshold, the second faulty industrial device is recorded as the faulty industrial device. Set a second quantity threshold. When the total number of industrial devices containing the first faulty industrial device and the second faulty industrial device in the first time period is less than the first quantity threshold but greater than the second quantity threshold, calculate the equipment impact value between the first faulty industrial device and the second faulty industrial device.

[0068] ;

[0069] in, The first duration is the i-th time interval between the first faulty industrial equipment and the second faulty industrial equipment. The total number of industrial equipment in the first time period containing both the first and second faulty industrial equipment.

[0070] Step S106: Set the equipment influence value threshold. When the equipment influence value between the first faulty industrial equipment and the second faulty industrial equipment is greater than the equipment influence 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.

[0071] Step S107: Set the first unit duration, and record the time when the industrial equipment was determined to be faulty in the historical fault records as the fault time point corresponding to the historical fault record; when the industrial equipment is the second faulty industrial equipment, and the time 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 faulty industrial equipment is less than the first unit duration, remove the certain historical fault record of the industrial equipment; and aggregate all the historical fault records of the industrial equipment.

[0072] Step S200: Based on the historical fault records of the industrial equipment, analyze the fault status of each part of the industrial equipment under different usage periods, and calculate the characteristic fault probability value of each part of the industrial equipment.

[0073] Step S200 includes:

[0074] Step S201: Use sensors to monitor the usage status of each part of the industrial equipment and acquire the usage time of each part of the industrial equipment. Extract the usage time of each faulty part of the industrial equipment from the historical fault records of the industrial equipment.

[0075] Step S202: Obtain the usage time threshold of each part of the industrial equipment that is preset when the industrial equipment leaves the factory. When the usage time of a certain faulty part of the industrial equipment in a certain historical fault record is greater than the usage time threshold of the corresponding part of the faulty part, the faulty part is recorded as a characteristic faulty part.

[0076] Step S203: Obtain the characteristic fault equipment parts corresponding to each historical fault record of the industrial equipment; arbitrarily select a characteristic fault equipment part from the historical fault record and record it as the main characteristic fault equipment part; extract the time points of each equipment part of the industrial equipment that were determined to be fault equipment parts from the historical fault record.

[0077] Step S204: From the historical fault records of each faulty equipment part, select the faulty equipment parts that were identified after the time point when the main characteristic faulty equipment part was identified as a faulty part, and record them as suspected faulty equipment parts; when the time point when the main characteristic faulty equipment part was identified as a faulty part in each historical fault record of the industrial equipment is before the time point when the suspected faulty equipment part was identified as a faulty part, determine that the fault of the suspected faulty equipment part is affected by the main characteristic faulty equipment part, and record the suspected passive faulty equipment part as the faulty equipment part.

[0078] Step S205: When a historical fault record of an industrial equipment contains both a main faulty equipment part and a faulty equipment part, the usage time of the faulty equipment part in a historical fault record is removed.

[0079] Step S206: Obtain the number of historical fault records of the industrial equipment to which the equipment part belongs when it is determined to be faulty, calculate the characteristic fault probability value of the equipment part under different usage durations, and calculate the characteristic fault probability value of the equipment part when the usage duration is k units of time:

[0080] ;

[0081] in, This refers to the total number of historical fault records for each industrial piece of equipment to which the equipment part belongs when the equipment part is determined to be faulty. This refers to the total number of historical fault records for each piece of equipment in the industrial equipment to which the equipment part belongs, where the equipment part's usage time is within k units of time.

[0082] For example, when a piece of equipment is determined to be faulty, the total number of historical fault records of the various industrial equipment to which the piece of equipment belongs. The total number of historical fault records for each industrial equipment to which the equipment part belongs, where the equipment part's usage time is within 4 unit time periods. The value is 20; calculate the characteristic failure probability value of the equipment part when its usage time is 4 units. ;

[0083] Step S300: Monitor the status of equipment parts of industrial equipment in the current cycle, and calculate the marked fault value of industrial equipment in the current cycle based on the characteristic fault probability value of equipment parts to industrial equipment;

[0084] Step S300 includes:

[0085] Step S301: Record the minimum value of the usage time of each faulty equipment part as the characteristic fault duration of the equipment part, and obtain the characteristic fault probability value of each faulty equipment part in the industrial equipment when the usage time is different unit durations.

[0086] Step S302: Monitor the equipment status of the industrial equipment that performs production testing on the parts in the current cycle, and obtain the usage time of each part of the industrial equipment in the current cycle, wherein the duration of the current cycle is one unit duration;

[0087] Step S303: If, within the current period, the usage time of a certain equipment part of an industrial equipment is greater than the characteristic fault duration of that equipment part, based on the equipment part, the characteristic fault probability values ​​of each equipment part of the industrial equipment are obtained and aggregated to obtain the characteristic fault probability set of the industrial equipment within the current period. ,in, These represent the characteristic fault probability values ​​of the 1st, 2nd, ..., yth equipment parts of the industrial equipment within the current period;

[0088] Step S304: Calculate the marked fault value of the industrial equipment in the current period. ;

[0089] Step S400: Obtain the marked fault value of the industrial equipment in the current cycle, analyze the fault status of the industrial equipment in the current cycle, obtain the target industrial equipment, obtain the target industrial equipment in the current cycle, and perform intelligent management of the component production and inspection of the industrial production line in the current cycle.

[0090] Step S400 includes:

[0091] Step S401: Set the marked fault value threshold for each industrial device, obtain the marked fault value of each industrial device that performs production inspection on parts in the current cycle of the industrial production line, 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 the target industrial device.

[0092] Step S402: Set the characteristic fault probability threshold for equipment parts. When the characteristic fault probability value of a certain equipment part is greater than the characteristic fault probability threshold in the current period, the equipment part is recorded as the target equipment part.

[0093] Step S403: Obtain each target equipment part within the target industrial equipment, obtain several target industrial equipments among the various industrial equipments that conduct production testing on the parts on the industrial production line in the current cycle, and several target equipment parts among the several industrial equipments;

[0094] Step S404: Send a prompt to the industrial equipment management backend to remind staff to inspect the target industrial equipment within the current cycle, replace several target parts within the target industrial equipment, and intelligently manage the production and testing of parts on the industrial production line within the current cycle.

[0095] To better implement the above methods, a parts production inspection system is also proposed, which includes a screening module, a characteristic fault probability value module, a fault value marking module, and an intelligent management module.

[0096] The filtering module is used to analyze the degree of fault impact between different industrial equipment, calculate the equipment impact value between industrial equipment, and filter the historical fault records of each industrial equipment.

[0097] The Feature Fault Probability Value module is used to analyze the fault status of various equipment parts under different usage periods of industrial equipment and calculate the feature fault probability value of each equipment part to the industrial equipment.

[0098] The fault value marking module is used to monitor the status of equipment parts of industrial equipment in the current cycle, and calculate the marked fault value of industrial equipment in the current cycle based on the characteristic fault probability value of equipment parts to industrial equipment.

[0099] The intelligent management module is used to analyze the fault status of each industrial device in the current cycle, obtain the target industrial device, acquire each target industrial device in the current cycle, and perform intelligent management of each industrial device in the current cycle.

[0100] The filtering module includes a device impact value unit and a historical usage record unit.

[0101] 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 the time distance between the time points when the first faulty industrial equipment and the second faulty industrial equipment are determined to be faulty is recorded as the first duration.

[0102] The historical usage record unit is used to record the time when the industrial equipment was determined to be faulty in the historical fault record as the fault time point corresponding to the historical fault record; and to collect all the historical fault records retained by the industrial equipment.

[0103] The feature fault probability value module includes a usage duration unit and a feature fault probability value unit.

[0104] The usage duration unit is used to obtain the usage duration of each component of industrial equipment, and to extract the usage duration of each faulty component in the industrial equipment from the historical fault records of the industrial equipment.

[0105] The characteristic fault probability value unit is used to obtain the number of historical fault records of the industrial equipment to which the component is identified as faulty within each unit of time, and to calculate the characteristic fault probability value of the equipment parts in the industrial equipment under different usage times.

[0106] The fault value marking module includes an equipment monitoring unit and a fault value marking unit.

[0107] The equipment monitoring unit is used to monitor various components of industrial equipment using sensors and to obtain the usage time of each component.

[0108] The fault value marking unit is used to calculate the marked fault value of industrial equipment in the current cycle;

[0109] The intelligent management module includes an intelligent equipment management unit;

[0110] The intelligent equipment management unit is used to obtain the marked fault values ​​of each industrial equipment that performs production testing 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 industrial equipment is marked as the target industrial equipment. The unit obtains each target component in the target industrial equipment and sends a prompt to the industrial equipment management backend, reminding the staff to carry out maintenance on the target industrial equipment in the current cycle and replace several target components in the target industrial equipment. The unit performs intelligent management of the production testing of parts in the current cycle of the industrial production line.

[0111] It should be noted that, in this document, relational terms such as "the first" and "the second" are used merely to distinguish one entity or operation from another, without necessarily requiring or implying any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0112] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A parts production inspection method using data analysis technology, characterized by, The method comprises: Step S100: constructing a spare part production detection cloud platform, obtaining historical failure records of industrial equipment for producing and detecting spare parts on an industrial production line, analyzing the failure influence degree between different industrial equipment, calculating the equipment influence value between the industrial equipment, and screening each historical failure record of the industrial equipment; Step S200: based on each historical failure record of the industrial equipment, analyzing the part failure state of each equipment part of the industrial equipment under different use time lengths, and calculating the characteristic failure probability value of each equipment part to the industrial equipment; Step S300: monitoring the equipment part state of the industrial equipment in the current period, and based on the characteristic failure probability value of the equipment part to the industrial equipment, calculating the marked failure value of the industrial equipment in the current period; Step S400: obtaining the marked failure value of the industrial equipment in the current period, analyzing the failure state of the equipment state of the industrial equipment in the current period, obtaining the target industrial equipment, obtaining the target industrial equipment in the current period, and intelligently managing the spare part production detection of the industrial production line in the current period; The step S200 comprises: Step S201: using a sensor to monitor the use state of each equipment part of the industrial equipment, and obtaining the use time length of each equipment part of the industrial equipment, extracting the use time length of each failure equipment part in the industrial equipment from each historical failure record of the industrial equipment; Step S202: obtaining the pre-set use time length threshold of each equipment part of the industrial equipment when the industrial equipment is shipped, and when the use time length of a certain failure equipment part of the industrial equipment in a certain historical failure record is greater than the use time length threshold of the certain failure equipment part, the certain failure equipment part is recorded as a characteristic failure equipment part; Step S203: obtaining the characteristic failure equipment part corresponding to each historical failure record of the industrial equipment, selecting a certain characteristic failure equipment part from the historical failure record as a main characteristic failure equipment part, and extracting the time point of each equipment part of the industrial equipment being judged as a failure equipment part from the historical failure record; Step S204: selecting a failure equipment part after the main characteristic failure equipment part is judged as a failure time point from each failure equipment part of the historical failure record as a suspected characteristic failure equipment part, and when the main characteristic failure equipment part is judged as a failure time point in each historical failure record of the industrial equipment, the suspected characteristic failure equipment part is judged as being influenced by the main characteristic failure equipment part, and the suspected passive failure equipment part is recorded as a characteristic failure equipment part; Step S205: when a certain historical failure record of the industrial equipment has a main characteristic failure equipment part and a characteristic failure equipment part, the use time length of the characteristic failure equipment part in the certain historical failure record is excluded. Step S206: When the equipment part is determined to be faulty, the number of historical fault records of the industrial equipment to which the equipment part belongs is obtained, the characteristic failure probability value of the equipment part under different use durations is calculated, and the characteristic failure probability value of the equipment part when the use duration is k units of time is calculated: ； wherein, the total number of historical failure records of each industrial equipment to which the equipment part belongs when the equipment part is determined to be faulty; the total number of historical failure records of each industrial equipment to which the equipment part belongs when the equipment part is determined to be faulty; 2. The method of claim 1, wherein the method is characterized by: The step S100 comprises: Step S101: The process of detecting and producing the parts in the historical period is recorded and collected, the historical fault records of the industrial equipment for detecting and producing the parts on the industrial production line are obtained, the time points when each industrial equipment is determined to be faulty are obtained, and when the time points when a plurality of industrial equipment is determined to be faulty are in the same period, the same period is recorded as a first period; Step S102: Each faulty industrial equipment in the first period is obtained, and based on the time points when each industrial equipment is determined to be faulty, an arbitrary industrial equipment is selected from each industrial equipment determined to be faulty in the first period as a first faulty industrial equipment; Step S103: An arbitrary faulty industrial equipment is selected from the first faulty industrial equipment and each faulty industrial equipment determined to be faulty in the first period, and the faulty industrial equipment is recorded as a second faulty industrial equipment; Step S104: The first period containing the first faulty industrial equipment and the second faulty industrial equipment is obtained, and the time distance between the time points when the first faulty industrial equipment and the second faulty industrial equipment are determined to be faulty is extracted, and the time distance between the time points when the first faulty industrial equipment and the second faulty industrial equipment are determined to be faulty is recorded as a first duration; Step S105: A first quantity threshold is set, when the total number of the first periods 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 a faulty industrial equipment; a second quantity threshold is set, when the total number of the first periods containing the first faulty industrial equipment and the second faulty industrial equipment is less than the first quantity threshold and greater than the second quantity threshold, the equipment influence value between the first faulty industrial equipment and the second faulty industrial equipment is calculated: ； wherein, is the ith first duration between the first failed industrial equipment and the second failed industrial equipment; is the total number of first durations containing the first failed industrial equipment and the second failed industrial equipment; Step S106: A device influence value threshold is set, when the equipment influence value between the first faulty industrial equipment and the second faulty industrial equipment is greater than the device influence value threshold, it is judged that the second faulty industrial equipment is affected by the first faulty industrial equipment when the second faulty industrial equipment fails, otherwise, it is determined that the second faulty industrial equipment has nothing to do with the first faulty industrial equipment when the second faulty industrial equipment fails; Step S107: A first unit duration is set, the time points when the industrial equipment is determined to be faulty in the historical fault records are recorded as the fault time points corresponding to the historical fault records; when the industrial equipment is the second faulty industrial equipment, and the duration between the fault time point corresponding to a certain historical fault record of the industrial equipment and the fault time point corresponding to the certain historical fault record of the first faulty industrial equipment is less than the first unit duration, the certain historical fault record of the industrial equipment is excluded; and each historical fault record of the industrial equipment is collected.

3. The method of claim 2, wherein the method is characterized by: The step S300 comprises: Step S301: the minimum value of the use time length of each fault equipment part is recorded as the characteristic fault time length of the equipment part, and the characteristic fault probability value of each fault equipment part in the industrial equipment at different unit time lengths is obtained; Step S302: the equipment state of the industrial equipment for production detection of parts in the current period is monitored, and the use time length of each equipment part of the industrial equipment in the current period is obtained, wherein the time length of the current period is one unit time length; Step S303: When the use duration of a certain device part of the industrial equipment in the current period is greater than the characteristic failure duration of the certain device part, the characteristic failure probability values of each device part of the industrial equipment are obtained based on the device part and collected to obtain a characteristic failure probability set of the industrial equipment in the current period wherein, respectively represent the characteristic failure probability values of the 1st, 2nd, …, yth device parts of the industrial equipment in the current period. Step S304: calculating a marked failure value of the industrial equipment in the current period .

4. The method of claim 3, wherein the method is characterized by, The step S400 includes: Step S401: setting the mark fault value threshold of each industrial equipment, obtaining the mark fault value of each industrial equipment for production detection of parts in the current period of the industrial production line, and recording a certain industrial equipment as a target industrial equipment when the mark fault value of a certain industrial equipment in the current period is greater than the preset mark fault threshold; Step S402: setting the characteristic fault probability threshold of the equipment part, and recording a certain equipment part as a target equipment part when the characteristic fault probability value of a certain equipment part in the current period is greater than the characteristic fault probability value threshold; Step S403: obtaining each target equipment part in the target industrial equipment, obtaining a plurality of target industrial equipment for production detection of parts in the current period of the industrial production line, and a plurality of target equipment parts in the plurality of industrial equipment; Step S404: issuing a prompt to the industrial equipment management background, reminding the staff to overhaul the target industrial equipment in the current period, replacing a plurality of target parts in the target industrial equipment, and intelligently managing the production detection of parts in the current period of the industrial production line.

5. A component production inspection system for use in a component production inspection method using a data analysis technique according to any one of claims 1 to 4, characterized by The part production detection system includes a screening module, a characteristic fault probability value module, a mark fault value module, and an intelligent management module; The screening module is used to analyze the fault influence degree between different industrial equipment, calculate the equipment influence value between industrial equipment, and screen the historical fault records of industrial equipment; The characteristic fault probability value module is used to analyze the part fault state of each equipment part of the industrial equipment at different use time lengths, and calculate the characteristic fault probability value of each equipment part to the industrial equipment; The mark fault value module is used to monitor the equipment part state of the industrial equipment in the current period, and calculate the mark fault value of the industrial equipment in the current period based on the characteristic fault probability value of the equipment part to the industrial equipment; The intelligent management module is used to analyze the fault state of the equipment state of each industrial equipment in the current period, obtain the target industrial equipment, and intelligently manage each industrial equipment in the current period.

6. The system for detecting production of parts according to claim 5, wherein The screening module includes an equipment influence value unit and a historical use record unit; The equipment influence value unit is used to obtain the time distance between the time points when the first fault industrial equipment and the second fault industrial equipment are determined to be faulty, and record the time distance between the time points when the first fault industrial equipment and the second fault industrial equipment are determined to be faulty as the first time length; The historical use record unit is configured to record a time point when the industrial equipment is determined to be faulty in the historical fault record as a fault time point corresponding to the historical fault record, and collect each historical fault record reserved by the industrial equipment.

7. The system for detecting production of parts according to claim 5, wherein The characteristic fault probability value module includes a use duration unit and a characteristic fault probability value unit. The use duration unit is configured to obtain use durations of each component of the industrial equipment, and extract the use durations of each faulty component in the industrial equipment from each historical fault record of the industrial equipment. The characteristic fault probability value unit is configured to obtain a number of historical fault records of the industrial equipment when each component is determined to be faulty in each unit duration, and calculate characteristic fault probability values of each component of the industrial equipment under different use durations.

8. The system for detecting production of parts according to claim 5, wherein The marked fault value module includes a device monitoring unit and a marked fault value unit. The device monitoring unit is configured to monitor each component of the industrial equipment using a sensor, and obtain use durations of each component of the industrial equipment. The marked fault value unit is configured to calculate a marked fault value of the industrial equipment in a current period.

9. The system for detecting production of parts according to claim 5, wherein, The intelligent management module includes a device intelligent management unit. The device intelligent management unit is configured to obtain the marked fault values of each industrial equipment for component production detection of the industrial production line in a current period, record an industrial equipment as a target industrial equipment when the marked fault value of the industrial equipment in the current period is greater than a preset marked fault threshold, obtain each target component in the target industrial equipment, send a prompt to an industrial equipment management background, remind a worker to overhaul the target industrial equipment in the current period, replace a plurality of target components in the target industrial equipment, and intelligently manage component production detection of the industrial production line in the current period.

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