Automatic equipment abnormal shutdown time data cleaning method

Abstract

The invention discloses an automatic equipment abnormal downtime data cleaning method, which comprises the following steps: collecting automatic equipment abnormal downtime data, and classifying the data according to downtime types; and classifying the acquired abnormal shutdown time data according to overlapped scenes, and cleaning the scene data according to set priorities to obtain complete abnormal shutdown time data records and abnormal shutdown types under the scenes. According to the method, time overlapping scene classification, data processing priority determination, data deduplication, time conformity verification and other processing are performed on the abnormal shutdown data acquired by the automation equipment, so that all abnormal shutdown times are real and available, and effective support is provided for data analysis of equipment fault time, equipment fault rate, MTTRMTBF, TOP loss, OEE indexes and the like.

Description

Technical Field

[0001] The invention relates to the technical field of data processing, in particular to a method for cleaning abnormal downtime data of automation equipment. Background Art

[0002] The downtime loss of automation equipment is divided into four situations: active downtime, passive downtime, material blocking downtime and material waiting downtime. However, there will be scenarios where downtime loss time overlaps with planned downtime, equipment does not stop when a fault signal is triggered, multiple fault signals are triggered continuously, passive downtime leads to active downtime, active downtime triggers passive downtime, material blocking time overlaps with material waiting time, and active and passive downtime overlaps with material blocking and material waiting time. The collected downtime data cannot be used directly and cannot generate value. Summary of the invention

[0003] In order to solve the above problems, the present invention proposes a method for cleaning abnormal downtime data of automation equipment, which sorts out data overlapping scenarios, cleans the data according to processing priorities, and finally verifies data compliance.

[0004] To achieve the above object, the present invention is achieved through the following technical solutions: The present invention provides a method for cleaning abnormal downtime data of automation equipment, comprising: Collect abnormal downtime data of automation equipment and classify the data according to the abnormal downtime type; The collected abnormal downtime data is divided into different scenarios according to the abnormal downtime types and overlapping modes; The data in each scenario is cleaned according to the set priority to obtain complete abnormal downtime data records and abnormal downtime types in each scenario.

[0005] Preferably, classifying the data according to the shutdown type includes: The data is divided into four abnormal shutdown types: passive shutdown, active shutdown, material blocking shutdown and waiting for material shutdown.

[0006] In this preferred solution, by dividing the abnormal downtime data into four abnormal downtime types: passive shutdown, active shutdown, material blockage shutdown and waiting for material shutdown, the abnormal shutdown data is stored by type, providing a basis for subsequent equipment failure improvement and efficiency improvement.

[0007] Preferably, the collected abnormal downtime data is divided into different scenarios according to abnormal downtime types and overlapping modes, including: Scenario 1: Abnormal downtime overlaps with planned downtime; Scenario 2: During the passive shutdown process, there is a situation where only a triggering passive shutdown signal is generated but the device does not shut down; Scenario 3: Multiple faults are triggered continuously during the passive shutdown process, and there is an inclusion or intersection relationship between the multiple faults; Scenario 4: Passive downtime occurs during active downtime; Scenario 5: Passive shutdown leads to active shutdown; Scenario 6: The blocking time and the waiting time overlap; Scenario 7: During passive or active shutdown, the material blocking / waiting signal is triggered at the same time.

[0008] In this preferred solution, by sorting and classifying the abnormal downtime data according to the downtime type and overlapping mode, almost all data overlapping situations are covered, which is conducive to screening the data in the time overlapping area and obtaining valuable downtime data.

[0009] Preferably, the method further comprises setting the priority as follows: Set the priority according to scene 1 to scene 7: priority 1 to 7.

[0010] Preferably, the data in each scenario is cleaned in the order of priority 1 to 7 to obtain complete abnormal downtime data records and abnormal downtime types in each scenario. The cleaning process is as follows: Scenario 1: All abnormal downtime data collected during the planned downtime will be eliminated, and abnormal downtime data will not be retained during the planned downtime; Scenario 2: The passive shutdown data of the time period when the passive shutdown signal is received but does not cause the equipment to shut down is eliminated, and the passive shutdown data of the time period that causes the equipment to shut down is retained; the abnormal shutdown type is determined to be a passive shutdown; Scenario 3: In the passive shutdown state, the start time and cause of the first equipment fault signal and the end time of the equipment fault signal that exists at the end of the entire passive shutdown state are retained; the abnormal shutdown type is determined to be a passive shutdown; Scenario 4: When the active shutdown continues, the start time, reason, and end time of the active shutdown are retained; the abnormal shutdown type is determined to be an active shutdown; Scenario 5: The passive downtime overlaps with the active downtime, and the equipment failure is resolved before or at the end of the active downtime. The start time and cause of the first equipment failure signal and the end time of the active downtime are retained; the abnormal downtime type is determined to be passive downtime; Scenario 6: The material blocking time and the material waiting time overlap, and the material blocking downtime data and the non-overlapping material waiting downtime data are retained; Scenario 7: including: A. Passive shutdown and blocking / waiting time have intersections, and the passive shutdown time data and non-overlapping blocking / waiting time data are retained; B. Active shutdown and blocking / waiting time have intersections, and the active shutdown time data and non-overlapping blocking / waiting time data are retained.

[0011] In this preferred solution, by screening and cleaning the abnormal downtime data in each overlapping scenario, all the final abnormal downtime data can be true and available, providing effective support for data analysis such as equipment failure time, equipment failure rate, MTTR\MTBF, TOP loss, OEE indicators, etc.

[0012] Preferably, the scenario six includes two situations: A. The blocking time and the waiting time overlap, and the blocking signal is triggered first; in this case, the blocking start time and end time are retained, the shutdown reason is blocking, and the abnormal shutdown type is blocking shutdown; if the blocking time completely includes the waiting time, the waiting data is not recorded; if the blocking does not completely include the waiting time, the end of the overlapping part is used as the starting point of the waiting time, and the end of the non-overlapping part of the waiting time is used as the waiting end time, the shutdown reason is waiting, and the shutdown type is waiting shutdown; B. The blocking time and the waiting time overlap, and the waiting signal is triggered first; in this case, the blocking start time and end time are retained. Time, the reason for shutdown is material blockage, and the type of abnormal shutdown is shutdown due to material blockage; if the waiting time completely includes the blocking time, the waiting time is divided into two pieces of data, the first piece of data: retain the starting time of waiting, and the beginning of the overlapping part is used as the end point of the waiting time, the reason for shutdown is waiting, and the type of abnormal shutdown is shutdown due to waiting; the second piece of data: retain the ending time of waiting, and the end of the overlapping part is used as the starting point of the waiting time, the reason for shutdown is waiting, and the type of abnormal shutdown is shutdown due to waiting; if the waiting time does not completely include the blocking time, retain the starting time of waiting, and the beginning of the overlapping part is used as the end time of waiting, the reason for shutdown is not waiting, and the type of abnormal shutdown is not shutdown due to waiting.

[0013] Preferably, in the scenario seven, the data cleaning method is: A. The passive shutdown and the blockage / waiting time overlap, in which case the start time, cause and end time of the equipment fault signal are retained, and the abnormal shutdown type is passive shutdown; if the passive shutdown completely includes blockage / waiting, the blockage / waiting data is not recorded; if the passive shutdown does not completely include blockage / waiting, the start time, cause and end time of the blockage / waiting are calculated after excluding the time that coincides with the passive shutdown; B. The active shutdown and the blockage / waiting time overlap, in which case the start time, cause and end time of the equipment active signal are retained, and the abnormal shutdown type is active shutdown; if the active shutdown completely includes blockage / waiting, the blockage / waiting data is not recorded; if the active shutdown does not completely include blockage / waiting, the start time, cause and end time of the blockage / waiting are calculated after excluding the time that coincides with the active shutdown.

[0014] Preferably, the complete abnormal downtime data record includes: abnormal downtime cause, start time, end time, interval time, abnormal downtime type and basic data; the interval time refers to the end time-start time; the basic data refers to the equipment code, equipment name and equipment manufacturer corresponding to the abnormal data.

[0015] Preferably, the method further comprises, after the data cleaning is completed, performing time conformity verification in the following manner: The calculation time compliance is: Time compliance = (actual C / T × output + abnormal downtime loss time) / verification time period = (theoretical cycle time × output + passive downtime + active downtime + blocking time + waiting time) / verification time period; Among them, C / T is the interval between two consecutive products coming off the line under the continuous and stable production state of the equipment; the output number is the number of products coming off the line during the verification time period; the verification time period is the selected calendar time excluding the time outside the planned downtime; If the time conformity is 100%, the data cleaning result is accurate; otherwise, data cleaning is performed again.

[0016] In this preferred solution, the data cleaning results are verified based on time compliance to ensure that the results of the data cleaning process are correct and to avoid data missing, cleaning data errors, and incomplete elimination of duplicate values.

[0017] The beneficial effects of the present invention are: The present invention proposes a method for cleaning abnormal downtime data of automation equipment. By classifying the time overlapping scenarios of the abnormal downtime data collected by the automation equipment, determining the data processing priority, deduplicating the data and verifying the time conformity, all abnormal downtime can be realized to be real and available, providing effective support for data analysis such as equipment failure time, equipment failure rate, mean repair time MTTR, mean failure interval time MTBF, key operation loss, and equipment comprehensive efficiency.

[0018] The invention has low investment, is easy to standardize and is convenient for large-scale promotion. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A schematic diagram of a method for cleaning abnormal downtime data of automation equipment provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The specific implementation of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The embodiments described below with reference to the accompanying drawings are illustrative and intended to be used to explain the present invention, but should not be construed as limiting the present invention.

[0021] It should be emphasized here that the step marks mentioned below are not intended to limit the order of the steps, but it should be understood that the steps can be executed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be executed simultaneously.

[0022] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0023] The specific embodiments of the present invention are described in further detail below in conjunction with the accompanying drawings. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention. Example

[0024] This embodiment 1 provides a method for cleaning abnormal downtime data of automation equipment, see Figure 1 , the method comprising: Collect abnormal downtime data of automation equipment, and divide the data into four types of downtime: passive downtime, active downtime, material blocking downtime and material waiting downtime. Among them, passive downtime refers to the downtime automatically triggered by equipment failure; active downtime refers to the situation where the equipment is manually adjusted to the downtime state; material blocking downtime refers to the situation where the material port does not discharge continuously or the material port does not feed continuously. A complete abnormal downtime data record includes: abnormal downtime start time, end time and downtime reason. Each downtime type forms multiple downtime records due to different downtime reasons; Classify the abnormal downtime data according to overlapping scenarios and filter the abnormal downtime data under the corresponding scenarios; The filtered abnormal downtime data is processed according to the set priority.

[0025] It should be noted that, because each abnormal downtime data is collected independently, the abnormal downtime data of the four types of downtime will overlap with the planned downtime. In addition, when some passive downtime signals are triggered, the equipment does not stop, there will be time overlap between multiple fault signals and the four types of abnormal downtime data. The above situation will cause the sum of the collected abnormal downtime data to be greater than the actual total downtime. Therefore, this embodiment cleans the collected abnormal downtime data.

[0026] In this embodiment, the abnormal downtime data is classified according to overlapping scenarios, and the abnormal downtime data under the corresponding scenarios is filtered, and the priority is set, as follows: A. Priority 1: Abnormal downtime overlaps with planned downtime. Planned downtime refers to the time when production plans are adjusted or production is not carried out regularly, such as eating and resting. During planned downtime, equipment maintenance, inspection, and testing may occur, and the equipment needs to be powered on. At this time, abnormal downtime data will be collected normally. Therefore, it is necessary to deduplicate abnormal downtime and planned downtime, and all abnormal downtime data collected during planned downtime will not be calculated.

[0027] For example, if the day shift's planned calendar time is 8:00-20:00, and the production is stopped from 10:00-11:00 due to plan adjustment, the data of abnormal downtime occurring in the time period of 10:00-11:00 will be eliminated, and only the data of abnormal downtime occurring in the time periods of 8:00-10:00 and 11:00-20:00 will be screened and deduplicated.

[0028] Abnormal downtime data screening method: All abnormal downtime data collected during the planned downtime will be eliminated, that is, abnormal downtime data will not be retained during the planned downtime.

[0029] Abnormal shutdown type None.

[0030] B. Priority 2: When some of the passive stop signals are triggered, the device will not stop. The equipment will trigger a passive stop signal to warn, but the equipment does not need to stop, such as when the NG station is about to be full of material, the material is about to run out, or the correction sensor has too much dust and needs to be dusted. Because these passive stop signals do not cause the equipment to stop, the passive stop data that warns needs to be eliminated at this time.

[0031] Abnormal downtime data screening method: The passive downtime data of the time period in which the passive downtime signal warning is received but does not cause equipment downtime will be eliminated, and the passive downtime data of the time period that causes equipment downtime will be retained.

[0032] Abnormal shutdown type: passive shutdown.

[0033] C. Priority 3: Multiple passive shutdowns are triggered continuously. Equipment failure A and equipment failure B have an intersection, equipment failure A includes equipment failure B, or there is an inclusion or intersection relationship between multiple equipment failures.

[0034] Abnormal downtime data screening method: In the passive downtime continuous state, take the start time and cause of the first equipment fault signal and the end time of the equipment fault signal that exists at the end of the entire passive downtime continuous state to form a complete abnormal downtime data.

[0035] The abnormal shutdown type is passive shutdown.

[0036] D. Priority 4: Passive downtime occurs during active downtime. When manual shutdown is required due to equipment maintenance, product switching, etc., the operator switches the equipment state from automatic to manual (active shutdown). During this time, multiple equipment fault signals may be triggered (mechanism failure or door opening and closing, etc.).

[0037] Abnormal downtime data screening method: When the active downtime continues, take the active downtime start time, cause and end time to form a complete abnormal downtime data.

[0038] The abnormal shutdown type is active shutdown.

[0039] E. Priority 5: Passive shutdown leads to active shutdown, Because the passive shutdown is triggered, the operator needs to switch the equipment to manual state (active shutdown state) to perform equipment maintenance and other work. There are mainly two situations: E1. Passive downtime includes active downtime: the equipment failure is resolved when the system is restored to automatic mode.

[0040] E2. Passive downtime overlaps with active downtime: after switching to manual mode, the equipment failure is resolved before resuming automatic mode.

[0041] Abnormal downtime data screening method: In the passive shutdown state, the start time and cause of the first equipment fault signal and the end time of the active shutdown are taken to form a complete abnormal downtime data.

[0042] The abnormal shutdown type is passive shutdown.

[0043] F. Priority 6: The material blocking time and the material waiting time overlap, mainly including the following two situations: F1. The material blocking time and the material waiting time intersect (the material blocking is triggered first): Abnormal downtime data screening method: retain the start and end time of material blockage, the reason for shutdown is material blockage, and the type of abnormal shutdown is shutdown due to material blockage; if the material blockage time completely includes the waiting time for materials, the waiting time data will not be recorded; if the material blockage does not completely include the waiting time for materials, the end of the overlapping part will be used as the starting point of the waiting time for materials, and the end of the non-overlapping part of the waiting time for materials will be used as the end time of waiting time for materials, the reason for shutdown is waiting for materials, and the type of shutdown is shutdown due to waiting for materials.

[0044] F2, the material blocking time and the material waiting time overlap (the material waiting time is triggered first): Abnormal downtime data screening method: retain the start time and end time of material blocking, the reason for the shutdown is material blocking, and the abnormal shutdown type is material blocking shutdown; if the waiting time completely includes the material blocking time, the waiting time is divided into two pieces of data, the first piece of data: retain the waiting start time, the beginning of the overlapping part is used as the end point of the waiting time, the reason for the shutdown is waiting, and the abnormal shutdown type is waiting for material shutdown; the second piece of data: retain the waiting end time, the end of the overlapping part is used as the starting point of the waiting time, the reason for the shutdown is waiting, and the abnormal shutdown type is waiting for material shutdown. If the waiting time does not completely include the material blocking time, retain the waiting start time, the beginning of the overlapping part is used as the waiting end time, the reason for the shutdown is not waiting, and the abnormal shutdown type is waiting for material shutdown.

[0045] G. Priority 7: When the passive or active shutdown triggers the blocking or waiting signal at the same time, there are mainly two situations: G1. Passive shutdown and material blocking / waiting time overlap: Abnormal downtime data screening method: In this case, the start time, cause and end time of the equipment fault signal are retained, and the abnormal shutdown type is passive shutdown; if the passive shutdown completely includes material blockage / waiting for material, the blockage / waiting for material data is not recorded; if the passive shutdown does not completely include material blockage / waiting for material, the start time, cause and end time of the blockage / waiting for material are calculated after excluding the time overlapping with the passive shutdown.

[0046] G2. Active shutdown and material blocking / waiting time overlap: Abnormal downtime data screening method: retain the start time, cause and end time of the equipment's active shutdown signal, and the abnormal shutdown type is active shutdown; if the active shutdown completely includes material blockage / waiting for material, the material blockage / waiting for material data will not be recorded; if the active shutdown does not completely include material blockage / waiting for material, the start time, cause and end time of the material blockage / waiting for material will be calculated after excluding the time that coincides with the active shutdown.

[0047] In this embodiment, data processing is performed in sequence according to the above-mentioned priorities 1-7. If there are multiple abnormal data at the same time, that is, overlap, it is necessary to process them step by step, first process the priority 1, then process the priority 2, and so on. Each step is a process of deduplication of two overlapping times. After the 7th priority data is cleaned, the final result is formed: abnormal shutdown reason, start time, end time, interval time, abnormal shutdown type and basic data storage (different from the original collected data), etc. The interval time refers to the end time-start time, and the basic data refers to the basic information such as the equipment code, equipment name, equipment manufacturer, etc. corresponding to the 1 abnormal data (abnormal cause, start and end time, interval time, abnormal shutdown type).

[0048] In this embodiment, the logical deduplication of each priority level is as follows: Priority 1: Standardize the collected abnormal downtime within the load time period, because for OEE calculation, abnormal data within planned downtime is not needed and meaningless.

[0049] Priority 2: Output will only be affected if it causes equipment shutdown. Some alarms are just alarm prompts and do not cause equipment shutdown, so they are excluded.

[0050] Priority 3: Passive shutdowns are repeated with passive shutdowns. Duplicate data is removed first, and then deduplicated with other types of abnormal data.

[0051] Priority 4: Active shutdown is caused by maintenance, 5S and other reasons. Although the passive shutdown signal is triggered due to door opening during the shutdown process, the root cause is still the active shutdown, so the whole process is counted as an active shutdown.

[0052] Priority 5: Active shutdown caused by passive shutdown equipment failure. Although the equipment is actively shut down, the root cause is still the equipment failure, so the entire process is considered a passive shutdown.

[0053] Priority 6: The four abnormal priorities are passive shutdown or active shutdown > material blocking shutdown > waiting for material shutdown. Priority 4 and 5 are used to handle the overlap of active and passive shutdown, and priority 6 is used to handle the overlap of blocking and waiting for material.

[0054] Priority 7: De-duplicate the priority logic for processing active and passive > blocked materials.

[0055] Furthermore, after data cleaning is completed, time compliance verification is performed as follows: The calculation time compliance is: Time compliance = (actual C / T × output + abnormal downtime loss time) / verification time period = (theoretical cycle time × output + passive downtime + active downtime + blocking time + waiting time) / verification time period = 100%.

[0056] Among them, C / T is the interval between two consecutive products off the line under the continuous and stable production state of the equipment (this data is measured during continuous production without abnormal shutdown before time compliance verification, which is a reflection of the current stable production capacity of the equipment); The output number is the number of products that come off the production line during the verification period; The abnormal downtime loss time is the sum of the passive downtime, active downtime and material blocking time after data cleaning; The verification time period is the time period selected to verify time compliance when the equipment can produce normally, that is, the calendar time excluding the time outside the planned downtime, that is, the load time period. If the calendar time is 8:00-8:00 the next day, 18:00-19:00 is the planned downtime, then other time periods can be used as time compliance verification time periods.

[0057] If the time conformity is 100%, it proves that the data cleaning result is accurate; if the time conformity is less than 100%, it proves that there are omissions in data collection or errors in the cleaned data, and the process should return to the data collection and data cleaning process inspection steps; if the time conformity is greater than 100%, it proves that the data cleaning is wrong and duplicate values ​​are not completely eliminated, and the process should return to the data cleaning process inspection steps.

[0058] For example: Between 8:00 and 10:00, 500 pcs of battery cells were produced, the actual C / T was 13s, the passive shutdown was 500s (after data cleaning), the active shutdown was 100s (after data cleaning), the material blocking was 60s (after data cleaning), and the material waiting was 40s (after data cleaning).

[0059] Then the time compliance = (500*13+700) / 7200=100%.

[0060] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for cleaning abnormal downtime data of automation equipment, characterized in that: include: Collect abnormal downtime data of automation equipment and classify the data according to the abnormal downtime type; The collected abnormal downtime data is divided into different scenarios according to the abnormal downtime types and overlapping modes; The data in each scenario is cleaned according to the set priority to obtain complete abnormal downtime data records and abnormal downtime types in each scenario.

2. The method for cleaning abnormal downtime data of automation equipment according to claim 1, characterized in that: The data is classified according to the downtime type, including: The data is divided into four abnormal shutdown types: passive shutdown, active shutdown, material blocking shutdown and waiting for material shutdown.

3. The method for cleaning abnormal downtime data of automation equipment according to claim 2, characterized in that: The collected abnormal downtime data is divided into different scenarios according to the abnormal downtime type and overlapping mode, including: Scenario 1: Abnormal downtime overlaps with planned downtime; Scenario 2: During the passive shutdown process, there is a situation where only a triggering passive shutdown signal is generated but the device does not shut down; Scenario 3: Multiple faults are triggered continuously during the passive shutdown process, and there is an inclusion or intersection relationship between the multiple faults; Scenario 4: Passive downtime occurs during active downtime; Scenario 5: Passive shutdown leads to active shutdown; Scenario 6: The blocking time and the waiting time overlap; Scenario 7: During passive or active shutdown, the material blocking / waiting signal is triggered at the same time.

4. The method for cleaning abnormal downtime data of automation equipment according to claim 3, characterized in that: The method also includes setting the priority as follows: Set the priority according to scene 1 to scene 7: priority 1 to 7.

5. The method for cleaning abnormal downtime data of automation equipment according to claim 4, characterized in that: Clean the data in each scenario in the order of priority 1 to 7 to obtain complete abnormal downtime data records and abnormal downtime types in each scenario. The cleaning process is as follows: Scenario 1: All abnormal downtime data collected during the planned downtime will be eliminated, and abnormal downtime data will not be retained during the planned downtime; Scenario 2: The passive shutdown data of the time period when the passive shutdown signal is received but does not cause the equipment to shut down is eliminated, and the passive shutdown data of the time period that causes the equipment to shut down is retained; Determine the abnormal shutdown type as passive shutdown; Scenario 3: In the passive shutdown state, the start time and cause of the first equipment fault signal and the end time of the equipment fault signal that exists at the end of the entire passive shutdown state are retained; the abnormal shutdown type is determined to be a passive shutdown; Scenario 4: When the active shutdown continues, the start time, reason, and end time of the active shutdown are retained; the abnormal shutdown type is determined to be an active shutdown; Scenario 5: The passive downtime overlaps with the active downtime, and the equipment failure is resolved before or at the end of the active downtime. The start time and cause of the first equipment failure signal and the end time of the active downtime are retained; the abnormal downtime type is determined to be passive downtime; Scenario 6: The material blocking time and the material waiting time overlap, and the material blocking downtime data and the non-overlapping material waiting downtime data are retained; Scenario 7: including: A. Passive downtime and material blocking / waiting time overlap, and the passive downtime data and non-overlapping material blocking / waiting downtime data are retained; B. If the active shutdown time overlaps with the material blocking / waiting time, the active shutdown time data and the non-overlapping material blocking / waiting time data will be retained.

6. The method for cleaning abnormal downtime data of automation equipment according to claim 5, characterized in that: The data cleaning of scenario six includes two situations: A. The blocking time and the waiting time overlap, and the blocking signal is triggered first; in this case, the start time and end time of the blocking are retained, the reason for the shutdown is blocking, and the abnormal shutdown type is blocking shutdown; if the blocking time completely includes the waiting time, the waiting data is not recorded; if the blocking does not completely include the waiting time, the end of the overlapping part is used as the starting point of the waiting time, and the end of the non-overlapping waiting time is used as the end time of the waiting time, the reason for the shutdown is waiting, and the shutdown type is waiting shutdown; B. The blocking time and the waiting time overlap, and the waiting signal is triggered first; in this case, the start time and end time of the blocking are retained. Time, the reason for shutdown is material blockage, and the type of abnormal shutdown is shutdown due to material blockage; if the waiting time completely includes the blocking time, the waiting time is divided into two pieces of data, the first piece of data: retain the starting time of waiting, and the beginning of the overlapping part is used as the end point of the waiting time, the reason for shutdown is waiting, and the type of abnormal shutdown is shutdown due to waiting; the second piece of data: retain the ending time of waiting, and the end of the overlapping part is used as the starting point of the waiting time, the reason for shutdown is waiting, and the type of abnormal shutdown is shutdown due to waiting; if the waiting time does not completely include the blocking time, retain the starting time of waiting, and the beginning of the overlapping part is used as the end time of waiting, the reason for shutdown is not waiting, and the type of abnormal shutdown is not shutdown due to waiting.

7. The method for cleaning abnormal downtime data of automation equipment according to claim 5, characterized in that: In the scenario seven, the data cleaning method is: A. The passive shutdown and the blockage / waiting time overlap. In this case, the start time, cause and end time of the equipment fault signal are retained, and the abnormal shutdown type is passive shutdown; if the passive shutdown completely includes blockage / waiting, the blockage / waiting data is not recorded; if the passive shutdown does not completely include blockage / waiting, the start time, cause and end time of the blockage / waiting are calculated after excluding the time overlapping with the passive shutdown; B. The active shutdown and the blockage / waiting time overlap. In this case, the start time, cause and end time of the equipment active signal are retained, and the abnormal shutdown type is active shutdown; if the active shutdown completely includes blockage / waiting, the blockage / waiting data is not recorded; if the active shutdown does not completely include blockage / waiting, the start time, cause and end time of the blockage / waiting are calculated after excluding the time overlapping with the active shutdown.

8. The method for cleaning abnormal downtime data of automation equipment according to claim 5, characterized in that: The complete abnormal downtime data record includes: abnormal downtime reason, start time, end time, interval time, abnormal downtime type and basic data; the interval time refers to the end time-start time; the basic data refers to the equipment code, equipment name and equipment manufacturer corresponding to the abnormal data.

9. The method for cleaning abnormal downtime data of automation equipment according to claim 5, characterized in that: The method further includes, after the data cleaning is completed, performing time compliance verification in the following manner: The calculation time compliance is: Time compliance = (actual C / T × output + abnormal downtime loss time) / verification time period = (theoretical cycle time × output + passive downtime + active downtime + blocking time + waiting time) / verification time period; Among them, C / T is the interval between two consecutive products coming off the line under the continuous and stable production state of the equipment; the output number is the number of products coming off the line during the verification time period; the verification time period is the selected calendar time excluding the time outside the planned downtime; If the time conformity is 100%, the data cleaning result is accurate; otherwise, data cleaning is performed again.

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