CN117170335B - Cooperative control platform for complex product production line of parts - Google Patents
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Abstract
The invention discloses a cooperative control platform for a production line of a complex product of parts, belonging to the technical field of production control; by carrying out modularized monitoring, data processing and data integration calculation on the target production links, different process states of individual parts produced by different target production links can be obtained; specific abnormal types of corresponding abnormal processes are determined by implementing different dimension abnormal self-tests on different abnormal processes of the target production links, and active cooperative control and alarm prompt are implemented on the determined abnormal processes of different production links; the method and the device are used for solving the technical problems that in the existing scheme, modularization and multi-dimensional monitoring data mining are not implemented on different production links in a production line, abnormal self-detection cannot be implemented on abnormal data obtained through monitoring, so that the monitoring data of the different production links of the production line are poor in utilization effect, and the overall effect of cooperative control of the different production links of the production line is poor.
Description
Technical Field
The invention relates to the technical field of production control, in particular to a cooperative control platform for a production line of a complex product of a part.
Background
The cooperative control of the component production line means that the high-efficiency cooperative and optimal control among all links is realized in the component production process by means of data sharing, real-time communication, coordination decision-making and the like, and the aims of improving the overall efficiency of the production line, reducing the cost and ensuring the product quality and the delivery cycle are fulfilled.
When the existing collaborative control scheme of the complex product production line of the parts is implemented, most of the collaborative control scheme stays on monitoring, comparing and visually alarming prompt of real-time production data, or training and predicting prompt of data of monitoring statistics are carried out through an existing neural network model, modularization and multi-dimensional mining of monitoring data are not implemented on different production links in the production line, abnormal self-checking cannot be implemented on abnormal data obtained through monitoring, so that the monitoring data utilization effect of different production links of the production line is poor, and the overall effect of collaborative control of different production links of the production line is poor.
Disclosure of Invention
The invention aims to provide a cooperative control platform for a complex product production line of parts, which is used for solving the technical problems that in the prior art, modularization and multi-dimensional monitoring data mining are not implemented on different production links in a production line, abnormal self-checking cannot be implemented on abnormal data obtained through monitoring, so that the utilization effect of the monitoring data of the different production links in the production line is poor, and the overall effect of cooperative control of the different production links in the production line is poor.
The aim of the invention can be achieved by the following technical scheme:
a cooperative control platform for a complex product production line of parts, comprising:
the local production monitoring analysis module is used for monitoring and data statistics of different production links and production individual parts of a production line where the part complex product is located, and carrying out local transition state evaluation and production state evaluation on the local production monitoring data according to the local production monitoring data of the different production links to obtain local production monitoring analysis data consisting of transfer influence analysis data and production influence analysis data, and uploading the local production monitoring analysis data to the cooperative control center;
the local production monitoring self-checking module is used for implementing abnormal self-checking of different dimensions according to the abnormal labels in the local production monitoring analysis data to obtain local production monitoring self-checking data consisting of first self-checking analysis data and second self-checking analysis data and uploading the local production monitoring self-checking data to the cooperative control center; the different dimensions comprise an external dimension and an internal dimension of the target production link;
the production link cooperative control module is used for implementing dynamic cooperative control and alarm prompt on individual part transportation and production among different production links according to the local production monitoring analysis data and the local production monitoring self-checking data corresponding to all production links on the production line; comprising the following steps:
Acquiring transfer influence analysis data and production influence analysis data in local production monitoring analysis data corresponding to different production links on a production line, and traversing the transfer influence analysis data and the production influence analysis data respectively, wherein if a transfer abnormal label, a retention abnormal label or a production abnormal label exists in the traversing result, the corresponding production link is marked as a transfer abnormal link, a retention abnormal link or a production abnormal link according to the transfer abnormal label, the retention abnormal label or the production abnormal label;
acquiring first self-checking analysis data and second self-checking analysis data corresponding to the transfer abnormal link according to the local production monitoring self-checking data, traversing, and implementing a corresponding transfer emergency scheme, a retention emergency scheme or a production emergency scheme according to the traversing result of the first self-checking analysis data;
and carrying out abnormal alarm prompt of the corresponding flow according to the result of the first self-checking analysis data traversal; and simultaneously implementing a network emergency scheme corresponding to the abnormal flow according to the result of the second self-checking analysis data traversal.
Preferably, all production links on the production line are acquired, and are numbered according to the production sequence of the production line and are marked as i, i=1, 2,3, … …, n; n is a positive integer;
When monitoring the local processes of producing individual parts in different production links, marking the monitored production links as target production links, and marking the upstream production links and the downstream production links of the target production links as first auxiliary production links and second auxiliary production links respectively;
acquiring the time of transferring the part to be processed from the first auxiliary production link to the target production link through a monitoring sensor and a timer, marking the time as a first starting time T0i1, and acquiring the time of starting processing of the part on the target production link, marking the time as a second starting time T0i2;
when the parts are processed on the target production link and transferred to the second secondary production link, acquiring the time when the parts finish processing on the target production link and marking the time as a first finish time T1i1, and acquiring the time when the parts are transferred away from the target production link and marking the time as a second finish time T1i2;
calculating a time length between the first starting time and a time when the part leaves the first auxiliary production link and marking the time length as a link transferring time length Tzs =t0i1-T0 i0; t0i0 is the time when the part leaves the first secondary production link; calculating a duration between the first end time and the second start time and marking as a production duration tss=t1i1-T0 i2; calculating a duration between the second end time and the first start time and labeled as a retention duration Tjs =t1i2-T0 i1;
And extracting the values of the corresponding link transfer time, production time and retention time when all the parts are produced in the target production link, and respectively sequencing and combining the values to obtain local production monitoring data consisting of a transfer time sequence, a production time sequence and a retention time sequence.
Preferably, when local transition state evaluation is sequentially implemented on individual parts produced in different production links, link transfer duration Tzs in a corresponding transfer time sequence of the individual parts, production duration Tss in the production time sequence and retention duration Tjs in the retention time sequence are acquired; calculating and obtaining a transport influence factor delta corresponding to the part in the target production link through a formula delta=g1× Tzs/Tzs +g2× (Tjs-Tss)/Tzs 1; wherein g1 and g2 are proportionality coefficients, g1 is more than 1, g2 is more than 0 and less than 0.1, tzs0 is the standard link transfer time length of the individual parts between the target production link and the first auxiliary production link, and Tzs1 is the standard production retention time length of the individual parts in the target production link;
when the transfer state between the target production link and the first auxiliary production link and the retention state of the target production link are analyzed according to the transfer influence factors, corresponding transfer influence thresholds are obtained according to the model of the parts and the serial numbers of the target production links, and the transfer influence factors are compared with the transfer influence thresholds to obtain transfer influence analysis data composed of transfer normal labels, retention abnormal labels or transfer abnormal labels.
Preferably, when local production state evaluation is sequentially implemented on different production links, calculating and obtaining a production influence factor gamma corresponding to a part in a target production link through a formula gamma= (Tss/Tss 0) -1; wherein Tss0 is the standard production time length of the part in the target production link;
when analyzing the production state of the target production link according to the production influence factor, if the production influence factor is 0, generating a normal production label; if the production influence factor is not 0, generating a production abnormal label; the production-normal label or the production-abnormal label constitutes production-influence analysis data.
Preferably, the step of acquiring the first self-test analysis data includes:
acquiring transfer influence analysis data and production influence analysis data in local production monitoring analysis data corresponding to different production links on a production line, traversing the transfer influence analysis data and the production influence analysis data respectively, and generating an external transfer self-checking instruction, an external retention self-checking instruction or an external production self-checking instruction if retention abnormality labels, transfer abnormality labels or production abnormality labels exist in the traversed transfer influence analysis data or the production influence analysis data;
acquiring transfer network delay between a corresponding target production link and a first auxiliary production link according to the external transfer self-checking instruction, and respectively acquiring retention network delay and production network delay when the target production link is produced according to the external retention self-checking instruction and the external production self-checking instruction; comparing the transit network delay, the retention network delay or the production network delay with a corresponding transit network delay threshold, retention network delay threshold or production network delay threshold respectively;
If the transit network delay is not greater than the transit network delay threshold, the retention network delay is not greater than the retention network delay threshold and the production network delay is not greater than the production network delay threshold, generating a transit network normal label, a retention network normal label and a production network normal label;
otherwise, generating a transit network anomaly tag, a retention network anomaly tag and a production network anomaly tag;
the transit network normal label, the retention network normal label or the production network normal label, the transit network abnormal label, the retention network abnormal label or the production network abnormal label form first self-checking analysis data.
Preferably, the step of acquiring the second self-test analysis data includes:
acquiring transfer influence analysis data and production influence analysis data in local production monitoring analysis data corresponding to different production links on a production line, traversing the transfer influence analysis data and the production influence analysis data respectively, and generating an internal transfer self-checking instruction, an internal retention self-checking instruction or an internal production self-checking instruction if a transfer abnormal label, a retention abnormal label or a production abnormal label exists in the traversed transfer influence analysis data;
and in a preset monitoring period, carrying out traversal statistics on the transportation influence analysis data and the production influence analysis data of the subsequent production parts of the target production link according to the internal transportation self-checking instruction, the internal detention self-checking instruction or the internal production self-checking instruction to obtain second self-checking analysis data consisting of a stable transportation abnormal label, a discontinuous transportation abnormal label or a burst transportation abnormal label, a stable detention abnormal label, a discontinuous detention abnormal label or a burst detention abnormal label, and a stable production abnormal label, a discontinuous production abnormal label or a burst production abnormal label.
Preferably, if continuous transfer abnormal labels, retention abnormal labels or production abnormal labels exist when parts are produced in the subsequent target production link, stable transfer abnormal labels, stable retention abnormal labels or stable production abnormal labels are generated;
if discontinuous transfer abnormal labels, retention abnormal labels or production abnormal labels exist in the production of parts in the subsequent target production link, generating discontinuous transfer abnormal labels, discontinuous retention abnormal labels or discontinuous production abnormal labels;
if the transfer abnormal label, the retention abnormal label or the production abnormal label does not exist in the production of the parts in the subsequent target production link, the burst transfer abnormal label, the burst abnormal label or the burst production abnormal label is generated.
Preferably, first self-checking analysis data and second self-checking analysis data corresponding to a transfer abnormal link are acquired according to local production monitoring self-checking data, the first self-checking analysis data and the second self-checking analysis data are traversed, and a corresponding transfer emergency scheme, a retention emergency scheme or a production emergency scheme is implemented according to the stable transfer abnormal label, the stable retention abnormal label or the stable production abnormal label acquired by traversing the first self-checking analysis data;
and performing an abnormal alarm prompt of a corresponding process according to the intermittent transfer abnormal label or the burst transfer abnormal label, the intermittent retention abnormal label or the burst retention abnormal label, the intermittent production abnormal label or the burst production abnormal label which are obtained by traversing the first self-checking analysis data.
Preferably, according to the transit network anomaly label, the retention network anomaly label or the production network anomaly control obtained by traversing the second self-checking analysis data, the network emergency scheme corresponding to the anomaly flow is implemented by the retention anomaly link or the production anomaly link.
In order to solve the above problems, the present invention also provides a storage medium including at least one processor; and a memory communicatively coupled to the at least one processor;
the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor, so that the at least one processor can execute the cooperative control platform of the complex product production line of the component.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, through implementing monitoring and data processing on the transfer flow, the production flow and the retention flow of different production links, each item of data of the monitoring statistics is standardized and normalized, finer modularized monitoring analysis can be implemented on different flows of different production links, and meanwhile, the accuracy of the subsequent monitoring data analysis with different dimensions can be improved; when the modularized monitoring and the data analysis are implemented on the target production link, the data integration calculation and analysis are further implemented on the transfer flow, the retention flow and the production flow of the target production link, so that the flow state of the production individual parts of the local production link can be obtained, meanwhile, reliable local data support can be provided for the overall abnormal state analysis and the cooperative control of the flow of the subsequent target production link, and the diversity of the data monitoring and the comprehensiveness of the data analysis are improved; by implementing different dimension anomaly self-detection on different anomaly flows of the target production links, specific anomaly types of corresponding anomaly flows can be determined, reliable data support can be provided for management control and alarm prompt of subsequent corresponding flows, accuracy and reliability of modularized monitoring and processing control of different production links are improved, and by implementing active cooperative control and alarm prompt on the determined anomaly flows of different production links, mining and processing of modularized and multidimensional monitoring data of different production links in a production line are realized, and overall effect of cooperative control of different production links of the production line is improved.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a block diagram of a cooperative control platform for a complex product production line of components of the present invention.
FIG. 2 is a block flow diagram of a cooperative control platform for a complex product production line of the present invention.
FIG. 3 is a block flow diagram of a process for sequentially performing a partial transient state evaluation of individual components produced in different production links in accordance with the present invention.
FIG. 4 is a block flow diagram of a process for sequentially performing local production state evaluations of different production links in accordance with the present invention.
Fig. 5 is a schematic structural diagram of a computer device for implementing a cooperative control platform of a complex product production line of parts.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which are obtained by persons skilled in the art without any inventive effort, are within the scope of the present invention based on the embodiments of the present invention.
Example 1:
as shown in fig. 1 to 2, the invention relates to a cooperative control platform for a complex product production line of parts, which comprises a local production monitoring analysis module and a cooperative control center;
The local production monitoring analysis module is used for monitoring and data statistics of different production links of a production line where the part complex product is located and production individual parts, and carrying out local transition state evaluation and production state evaluation on the local production monitoring data according to the local production monitoring data of the different production links to obtain local production monitoring analysis data; comprising the following steps:
acquiring all production links on a production line, numbering all production links according to the production sequence of the production line, and marking the production links as i, i=1, 2,3, … … and n; n is a positive integer;
when monitoring the local processes of producing individual parts in different production links, marking the monitored production links as target production links, and marking the upstream production links and the downstream production links of the target production links as first auxiliary production links and second auxiliary production links respectively;
the method comprises the steps of monitoring local processes of producing individual parts in different production links, realizing modularized monitoring and data analysis in different production links, and providing reliable data support for carrying out refined analysis and abnormal self-checking on different processes in different production links;
Acquiring the time of transferring the part to be processed from the first auxiliary production link to the target production link through a monitoring sensor and a timer, marking the time as a first starting time T0i1, and acquiring the time of starting processing of the part on the target production link, marking the time as a second starting time T0i2;
the monitoring sensor can be an infrared sensor and a microwave radar sensor and is used for monitoring the conveying and transferring of the parts; the units of the first start time and the second start time are accurate to seconds;
when the parts are processed on the target production link and transferred to the second secondary production link, acquiring the time when the parts finish processing on the target production link and marking the time as a first finish time T1i1, and acquiring the time when the parts are transferred away from the target production link and marking the time as a second finish time T1i2; the units of the first end time and the second end time are equally accurate to seconds;
calculating a time length between the first starting time and a time when the part leaves the first auxiliary production link and marking the time length as a link transferring time length Tzs =t0i1-T0 i0; t0i0 is the time when the part leaves the first secondary production link; calculating a duration between the first end time and the second start time and marking as a production duration tss=t1i1-T0 i2; calculating a duration between the second end time and the first start time and labeled as a retention duration Tjs =t1i2-T0 i1;
Extracting the values of the corresponding link transfer time, production time and retention time when all parts are produced in the target production link, and respectively sequencing and combining to obtain local production monitoring data consisting of a transfer time sequence, a production time sequence and a retention time sequence;
in the embodiment of the invention, through implementing monitoring and data processing on the transfer flow, the production flow and the retention flow of different production links, each item of data of the monitoring statistics is standardized and normalized, finer modularized monitoring analysis can be implemented on different flows of different production links, and meanwhile, the accuracy of the subsequent monitoring data analysis with different dimensions can be improved.
As shown in fig. 3, when the local transition state evaluation is sequentially performed on the individual components produced in different production links, link transfer duration Tzs in the corresponding transfer time sequence of the individual components, production duration Tss in the production time sequence and retention duration Tjs in the retention time sequence are obtained; calculating and obtaining a transport influence factor delta corresponding to the part in the target production link through a formula delta=g1× Tzs/Tzs +g2× (Tjs-Tss)/Tzs 1; wherein g1 and g2 are proportionality coefficients, g1 is more than 1, g2 is more than 0 and less than 0.1, tzs0 is the standard link transfer duration of an individual part between a target production link and a first auxiliary production link, tzs is the standard production retention duration of the individual part in the target production link, and the standard link transfer duration and the standard production retention duration are determined according to production design parameters of the corresponding production link and the part;
It should be explained that the transfer influencing factor is a numerical value for analyzing whether the transfer state and the retention state of the target production link are normal or not by integrating and calculating various data of the transfer flow and the retention flow of the target production link;
when analyzing the transfer state between the target production link and the first auxiliary production link and the retention state of the target production link according to the transfer influence factor, acquiring a corresponding transfer influence threshold according to the model of the part and the number of the target production link, and comparing the transfer influence factor with the transfer influence threshold; a transport effect threshold value of g1+g2; because Tzs/Tzs 0=1, (Tjs-Tss)/Tzs 1=1 when the transport state is normal and the retention state is normal;
if the transfer influence factor is equal to the transfer influence threshold, judging that the transfer state between the target production link and the first auxiliary production link and the retention state of the target production link are normal and generating a transfer normal label;
if the transfer influence factor is smaller than the transfer influence threshold, judging that the retention state of the target production link is abnormal and generating a retention abnormal label;
if the transfer influence factor is larger than the transfer influence threshold, judging that the transfer state between the target production link and the first auxiliary production link is abnormal and generating a transfer abnormal label;
The transfer normal label, the retention abnormal label or the transfer abnormal label form transfer influence analysis data;
in the embodiment of the invention, the transfer influence factors are obtained by integrating and calculating the data of the transfer flow and the retention flow of the target production link, whether the transfer state and the retention state corresponding to the target production link are normal or not can be obtained by analyzing the transfer influence factors, meanwhile, reliable local data support can be provided for the analysis of the abnormal state and the abnormal type of the retention state of the subsequent transfer link, and the diversity of monitoring data mining and utilization of the transfer aspect and the retention aspect of the target production link is improved.
As shown in fig. 4, when local production state evaluation is sequentially performed on different production links, a production influence factor gamma corresponding to a target production link of a part is obtained through calculation of a formula gamma= (Tss/Tss 0) -1; wherein Tss0 is the standard production time length of the part in the target production link, and the standard production time length is determined according to the production design parameters of the corresponding production link and the part;
the production influence factor is a numerical value for calculating production data of the target production link processing part to analyze the production state of the target production link processing part;
When the production state of the target production link is analyzed according to the production influence factor, if the production influence factor is 0, judging that the production state of the target production link production part is normal and generating a production normal label;
if the production influence factor is not 0, judging that the production state of the production part in the target production link is abnormal and generating a production abnormal label;
the production normal label or the production abnormal label forms production influence analysis data;
the transfer influence analysis data and the production influence analysis data form local production monitoring analysis data and are uploaded to a cooperative control center;
in the embodiment of the invention, when the modularized monitoring and the data analysis are implemented on the target production link, the data integration calculation and analysis are further implemented on the transfer flow, the retention flow and the production flow of the target production link, so that the flow state of the production individual parts of the local production link can be obtained, meanwhile, the reliable local data support can be provided for the overall abnormal state analysis and the cooperative control of the flow of the subsequent target production link, and the diversity of the data monitoring and the comprehensiveness of the data analysis are improved.
Example 2:
on the basis of the technical scheme disclosed in the embodiment 1, the method further comprises the following steps:
The local production monitoring self-checking module is used for implementing abnormal self-checking of different dimensions according to the abnormal labels in the local production monitoring analysis data to obtain local production monitoring self-checking data consisting of first self-checking analysis data and second self-checking analysis data and uploading the local production monitoring self-checking data to the cooperative control center; comprising the following steps:
the local production monitoring self-checking module comprises a local production monitoring external self-checking unit and a local production monitoring internal self-checking unit;
the method comprises the steps that a local production monitoring external self-checking unit is used for acquiring transfer influence analysis data and production influence analysis data in local production monitoring analysis data corresponding to different production links on a production line and traversing the transfer influence analysis data and the production influence analysis data respectively, and if a retention abnormal label, a transfer abnormal label or a production abnormal label exists in the traversed transfer influence analysis data, an external transfer self-checking instruction, an external retention self-checking instruction or an external production self-checking instruction is generated;
acquiring transfer network delay between a corresponding target production link and a first auxiliary production link according to the external transfer self-checking instruction, and respectively acquiring retention network delay and production network delay when the target production link is produced according to the external retention self-checking instruction and the external production self-checking instruction;
Wherein, the transfer network delay, the retention network delay and the production network delay corresponding to the target production link can be determined by the production design parameters of the corresponding production link and the parts;
comparing the transit network delay, the retention network delay or the production network delay with a corresponding transit network delay threshold, retention network delay threshold or production network delay threshold respectively;
if the transit network delay is not greater than the transit network delay threshold, the retention network delay is not greater than the retention network delay threshold and the production network delay is not greater than the production network delay threshold, generating a transit network normal label, a retention network normal label and a production network normal label;
otherwise, generating a transit network anomaly tag, a retention network anomaly tag and a production network anomaly tag;
the transit network normal label, the retention network normal label or the production network normal label, the transit network abnormal label, the retention network abnormal label or the production network abnormal label form first self-checking analysis data;
when there is an abnormality in different processes in the target production link, there may be an influence caused by a network delay, and the abnormality self-checking analysis is performed on the process abnormality obtained by the early analysis from the network delay, so that the diversity of the abnormal process solution is improved.
The method comprises the steps that a local production monitoring internal self-checking unit is used for obtaining transfer influence analysis data and production influence analysis data in local production monitoring analysis data corresponding to different production links on a production line and traversing the transfer influence analysis data and the production influence analysis data respectively, and if a transfer abnormal label, a retention abnormal label or a production abnormal label exists in the traversed transfer influence analysis data, an internal transfer self-checking instruction, an internal retention self-checking instruction or an internal production self-checking instruction is generated;
in a preset monitoring period, the monitoring period can be determined by the efficiency of producing parts in a target production link, and traversing statistics is carried out on transfer influence analysis data and production influence analysis data of subsequently produced parts in the target production link according to an internal transfer self-checking instruction, an internal retention self-checking instruction or an internal production self-checking instruction;
if continuous transfer abnormal labels, retention abnormal labels or production abnormal labels exist in the production of parts in the subsequent target production link, generating stable transfer abnormal labels, stable retention abnormal labels or stable production abnormal labels;
if discontinuous transfer abnormal labels, retention abnormal labels or production abnormal labels exist in the production of parts in the subsequent target production link, generating discontinuous transfer abnormal labels, discontinuous retention abnormal labels or discontinuous production abnormal labels;
If no transfer abnormal label, retention abnormal label or production abnormal label exists in the production of the parts in the subsequent target production link, a burst transfer abnormal label, burst abnormal label or burst production abnormal label is generated;
it should be noted that, when it is monitored that there is an abnormality in different processes of the target production link, due to the contingency and instability of the abnormality, it is necessary to further perform a trace analysis on the abnormality type existing in the abnormal process, so as to provide reliable data support for management control and alarm prompt of the subsequent abnormal process;
a stable transport abnormal label, a discontinuous transport abnormal label or a burst transport abnormal label, a stable retention abnormal label, a discontinuous retention abnormal label or a burst retention abnormal label, and a stable production abnormal label, a discontinuous production abnormal label or a burst production abnormal label form second self-checking analysis data;
the first self-checking analysis data and the second self-checking analysis data form local production monitoring self-checking data;
in the embodiment of the invention, by implementing the anomaly self-detection of different dimensionalities on different anomaly flows of the target production links, the specific anomaly type of the corresponding anomaly flow can be determined, and reliable data support can be provided for the management control and the alarm prompt of the subsequent corresponding flow, so that the accuracy and the reliability of the modularized monitoring and the processing control of different production links are improved.
The production link cooperative control module is used for implementing dynamic cooperative control and alarm prompt on individual part transportation and production among different production links according to the local production monitoring analysis data and the local production monitoring self-checking data corresponding to all production links on the production line; comprising the following steps:
acquiring transfer influence analysis data and production influence analysis data in local production monitoring analysis data corresponding to different production links on a production line, and traversing the transfer influence analysis data and the production influence analysis data respectively, wherein if a transfer abnormal label, a retention abnormal label or a production abnormal label exists in the traversing result, the corresponding production link is marked as a transfer abnormal link, a retention abnormal link or a production abnormal link according to the transfer abnormal label, the retention abnormal label or the production abnormal label;
according to the local production monitoring self-checking data, first self-checking analysis data and second self-checking analysis data corresponding to the transfer abnormal link are obtained and traversed, and according to the stable transfer abnormal label, the stable retention abnormal label or the stable production abnormal label obtained by traversing the first self-checking analysis data, a corresponding transfer emergency scheme, a retention emergency scheme or a production emergency scheme is implemented;
and performing an abnormal alarm prompt of a corresponding process according to the intermittent transfer abnormal label or the burst transfer abnormal label, the intermittent retention abnormal label or the burst retention abnormal label, the intermittent production abnormal label or the burst production abnormal label which are obtained by traversing the first self-checking analysis data;
It should be noted that, because of the extremely large uncertainty of the intermittent and sudden anomalies, the method is not suitable for implementing an active cooperative control scheme, and is suitable for actively alarming to prompt a specific anomaly position to inform a professional technician to process;
meanwhile, traversing the acquired transit network anomaly labels, detention network anomaly labels or production network anomalies according to the second self-checking analysis data to control corresponding transit anomalies, detention anomalies or production anomalies to implement network emergency schemes of corresponding anomaly flows;
the transfer emergency scheme, the retention emergency scheme or the production emergency scheme is used for enabling the transfer flow, the retention flow or the production flow of the corresponding target production link to be recovered to be normal through an automation technology, and the network emergency scheme is used for enabling the network delay to be recovered to be normal through the automation technology;
in addition, the specific contents of the transferring emergency scheme, the retention emergency scheme or the production emergency scheme and the network emergency scheme can be determined according to the production link emergency scheme and the network emergency scheme of the existing production line, and the corresponding emergency scheme can be customized by a person skilled in the art by combining the existing production technology and the network technology according to the production requirements of the parts of the specific production.
In the embodiment of the invention, the active cooperative control and the alarm prompt are implemented on the abnormal flow of the determined different production links, so that the modular and multi-dimensional mining and processing of the monitoring data of the different production links in the production line are realized, and the overall effect of the cooperative control of the different production links of the production line is improved.
In addition, the formulas related in the above are all formulas for removing dimensions and taking numerical calculation, and are one formula which is obtained by acquiring a large amount of data and performing software simulation through simulation software and is closest to the actual situation.
Example 3:
fig. 5 is a schematic structural diagram of a computer device for implementing a cooperative control platform of a complex product production line of a component according to an embodiment of the present invention.
The computer device may include a processor, memory and a bus, and may also include a computer program stored in the memory and executable on the processor, such as a program for a complex part production line cooperative control platform.
The memory includes at least one type of readable storage medium, including flash memory, a removable hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory may in some embodiments be an internal storage unit of a computer device, such as a removable hard disk of the computer device. The memory may also be an external storage device of the computer device in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc. that are provided on the computer device. Further, the memory may also include both internal storage units and external storage devices of the computer device. The memory can be used for storing application software installed on the computer equipment and various data, such as codes of programs of a cooperative control platform of a complex product production line of parts, and the like, and can be used for temporarily storing data which is output or is to be output.
The processor may in some embodiments be comprised of integrated circuits, for example, a single packaged integrated circuit, or may be comprised of multiple integrated circuits packaged in the same location or in different locations, including one or more central processing units (Central Processing unit, CPU), microprocessors, digital processing chips, graphics processors, combinations of various control chips, and the like. The processor is a Control Unit (Control Unit) of the computer device, connects the respective components of the entire computer device using various interfaces and lines, executes or executes programs or modules stored in the memory (for example, programs of a complex product line cooperative Control platform of a component, etc.), and invokes data stored in the memory to execute various positions of the computer device and process data.
The bus may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between said memory and at least one processor or the like.
Fig. 5 shows only a computer device having components, and it will be understood by those skilled in the art that the structure shown in fig. 5 is not limiting of the computer device and may include fewer or more components than shown, or may combine certain components, or a different arrangement of components.
For example, although not shown, the computer device may further include a power source (such as a battery) for powering the various components, preferably the power source may be logically connected to the at least one processor by a power management device such that charge management, discharge management, and power consumption management are achieved by the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The computer device may also include various sensors, bluetooth modules, wi-Fi modules, etc., which are not described in detail herein.
Further, the computer device may also include a network interface, which may optionally include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), typically used to establish a communication connection between the computer device and other computer devices.
The computer device may optionally further comprise a user interface, which may be a Display, an input unit such as a Keyboard (Keyboard), or a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the computer device and for displaying a visual user interface.
It should be understood that the above-described embodiments are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
A program of a cooperative control platform of a complex product line of parts stored in a memory of a computer device is a combination of a plurality of instructions.
Specifically, the specific implementation method of the above instruction by the processor may refer to descriptions of related steps in the corresponding embodiments of fig. 1 to fig. 4, which are not repeated herein.
Further, the modules/units integrated with the computer device may be stored in a computer readable storage medium if implemented in the form of software location units and sold or used as stand-alone products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).
The invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of a computer device, causes a computer to perform the method of the invention.
In the several embodiments provided in the present invention, it should be understood that the disclosed method may be implemented in other manners. For example, the above-described embodiments of the invention are merely illustrative, e.g., the division of modules is merely a logical location division, and other manners of division may be implemented in practice.
The modules illustrated as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each location module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in hardware plus software location modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (10)
1. A spare part complex product production line cooperative control platform, its characterized in that includes:
the local production monitoring analysis module is used for monitoring and data statistics of different production links and production individual parts of a production line where the part complex product is located, and carrying out local transition state evaluation and production state evaluation on the local production monitoring data according to the local production monitoring data of the different production links to obtain local production monitoring analysis data consisting of transfer influence analysis data and production influence analysis data, and uploading the local production monitoring analysis data to the cooperative control center;
The local production monitoring self-checking module is used for implementing abnormal self-checking of different dimensions according to the abnormal labels in the local production monitoring analysis data to obtain local production monitoring self-checking data consisting of first self-checking analysis data and second self-checking analysis data and uploading the local production monitoring self-checking data to the cooperative control center; the different dimensions comprise an external dimension and an internal dimension of the target production link;
the production link cooperative control module is used for implementing dynamic cooperative control and alarm prompt on individual part transportation and production among different production links according to the local production monitoring analysis data and the local production monitoring self-checking data corresponding to all production links on the production line; comprising the following steps:
acquiring transfer influence analysis data and production influence analysis data in local production monitoring analysis data corresponding to different production links on a production line, and traversing the transfer influence analysis data and the production influence analysis data respectively, wherein if a transfer abnormal label, a retention abnormal label or a production abnormal label exists in the traversing result, the corresponding production link is marked as a transfer abnormal link, a retention abnormal link or a production abnormal link according to the transfer abnormal label, the retention abnormal label or the production abnormal label;
acquiring and traversing first self-checking analysis data and second self-checking analysis data corresponding to the transportation abnormal link according to the local production monitoring self-checking data, and implementing a network emergency scheme corresponding to the abnormal flow according to the traversing result of the first self-checking analysis data; implementing a corresponding transportation emergency scheme, a retention emergency scheme or a production emergency scheme according to the result of the second self-checking analysis data traversal;
And carrying out abnormal alarm prompt of the corresponding flow according to the result of the second self-checking analysis data traversal.
2. The cooperative control platform for a complex product production line of components according to claim 1, wherein all production links on the production line are acquired, and are numbered according to the production sequence of the production line and are marked as i, i=1, 2,3, … …, n; n is a positive integer;
when monitoring the local processes of producing individual parts in different production links, marking the monitored production links as target production links, and marking the upstream production links and the downstream production links of the target production links as first auxiliary production links and second auxiliary production links respectively;
acquiring the time of transferring the part to be processed from the first auxiliary production link to the target production link through a monitoring sensor and a timer, marking the time as a first starting time T0i1, and acquiring the time of starting processing of the part on the target production link, marking the time as a second starting time T0i2;
when the parts are processed on the target production link and transferred to the second secondary production link, acquiring the time when the parts finish processing on the target production link and marking the time as a first finish time T1i1, and acquiring the time when the parts are transferred away from the target production link and marking the time as a second finish time T1i2;
Calculating a time length between the first starting time and a time when the part leaves the first auxiliary production link and marking the time length as a link transferring time length Tzs =t0i1-T0 i0; t0i0 is the time when the part leaves the first secondary production link; calculating a duration between the first end time and the second start time and marking as a production duration tss=t1i1-T0 i2; calculating a duration between the second end time and the first start time and labeled as a retention duration Tjs =t1i2-T0 i1;
and extracting the values of the corresponding link transfer time, production time and retention time when all the parts are produced in the target production link, and respectively sequencing and combining the values to obtain local production monitoring data consisting of a transfer time sequence, a production time sequence and a retention time sequence.
3. The cooperative control platform for the complex product production line of parts according to claim 2, wherein when the local transition state evaluation is sequentially performed on individual parts produced in different production links, link transfer duration Tzs in a corresponding transfer time sequence of the individual parts, production duration Tss in the production time sequence and retention duration Tjs in the retention time sequence are obtained; calculating and obtaining a transport influence factor delta corresponding to the part in the target production link through a formula delta=g1× Tzs/Tzs +g2× (Tjs-Tss)/Tzs 1; wherein g1 and g2 are proportionality coefficients, g1 is more than 1, g2 is more than 0 and less than 0.1, tzs0 is the standard link transfer time length of the individual parts between the target production link and the first auxiliary production link, and Tzs1 is the standard production retention time length of the individual parts in the target production link;
When the transfer state between the target production link and the first auxiliary production link and the retention state of the target production link are analyzed according to the transfer influence factors, corresponding transfer influence thresholds are obtained according to the model of the parts and the serial numbers of the target production links, and the transfer influence factors are compared with the transfer influence thresholds to obtain transfer influence analysis data composed of transfer normal labels, retention abnormal labels or transfer abnormal labels.
4. The cooperative control platform for the complex product production line of the parts according to claim 3, wherein when local production state evaluation is sequentially carried out on different production links, a production influence factor gamma corresponding to the parts in a target production link is obtained through calculation according to a formula gamma= (Tss/Tss 0) -1; wherein Tss0 is the standard production time length of the part in the target production link;
when analyzing the production state of the target production link according to the production influence factor, if the production influence factor is 0, generating a normal production label; if the production influence factor is not 0, generating a production abnormal label; the production-normal label or the production-abnormal label constitutes production-influence analysis data.
5. The cooperative control platform for a complex product manufacturing line of components of claim 1, wherein the step of obtaining the first self-test analysis data comprises:
Acquiring transfer influence analysis data and production influence analysis data in local production monitoring analysis data corresponding to different production links on a production line, traversing the transfer influence analysis data and the production influence analysis data respectively, and generating an external transfer self-checking instruction, an external retention self-checking instruction or an external production self-checking instruction if retention abnormality labels, transfer abnormality labels or production abnormality labels exist in the traversed transfer influence analysis data or the production influence analysis data;
acquiring transfer network delay between a corresponding target production link and a first auxiliary production link according to the external transfer self-checking instruction, and respectively acquiring retention network delay and production network delay when the target production link is produced according to the external retention self-checking instruction and the external production self-checking instruction; comparing the transit network delay, the retention network delay or the production network delay with a corresponding transit network delay threshold, retention network delay threshold or production network delay threshold respectively;
if the transit network delay is not greater than the transit network delay threshold, the retention network delay is not greater than the retention network delay threshold and the production network delay is not greater than the production network delay threshold, generating a transit network normal label, a retention network normal label and a production network normal label;
Otherwise, generating a transit network anomaly tag, a retention network anomaly tag and a production network anomaly tag;
the transit network normal label, the retention network normal label or the production network normal label, the transit network abnormal label, the retention network abnormal label or the production network abnormal label form first self-checking analysis data.
6. The cooperative control platform for a complex product manufacturing line of components as set forth in claim 1 or 5, wherein the step of obtaining the second self-test analysis data includes:
acquiring transfer influence analysis data and production influence analysis data in local production monitoring analysis data corresponding to different production links on a production line, traversing the transfer influence analysis data and the production influence analysis data respectively, and generating an internal transfer self-checking instruction, an internal retention self-checking instruction or an internal production self-checking instruction if a transfer abnormal label, a retention abnormal label or a production abnormal label exists in the traversed transfer influence analysis data;
and in a preset monitoring period, carrying out traversal statistics on the transportation influence analysis data and the production influence analysis data of the subsequent production parts of the target production link according to the internal transportation self-checking instruction, the internal detention self-checking instruction or the internal production self-checking instruction to obtain second self-checking analysis data consisting of a stable transportation abnormal label, a discontinuous transportation abnormal label or a burst transportation abnormal label, a stable detention abnormal label, a discontinuous detention abnormal label or a burst detention abnormal label, and a stable production abnormal label, a discontinuous production abnormal label or a burst production abnormal label.
7. The cooperative control platform for a complex product production line of components according to claim 6, wherein if continuous transfer anomaly tags, retention anomaly tags or production anomaly tags exist in the production of components in the subsequent target production link, stable transfer anomaly tags, stable retention anomaly tags or stable production anomaly tags are generated;
if discontinuous transfer abnormal labels, retention abnormal labels or production abnormal labels exist in the production of parts in the subsequent target production link, generating discontinuous transfer abnormal labels, discontinuous retention abnormal labels or discontinuous production abnormal labels;
if the transfer abnormal label, the retention abnormal label or the production abnormal label does not exist in the production of the parts in the subsequent target production link, the burst transfer abnormal label, the burst abnormal label or the burst production abnormal label is generated.
8. The cooperative control platform of the complex product production line of the parts according to claim 1 is characterized in that first self-checking analysis data and second self-checking analysis data corresponding to a transfer abnormal link are acquired according to local production monitoring self-checking data and traversed, and a network emergency scheme corresponding to an abnormal flow is implemented according to the transfer network abnormal label, the retention network abnormal label or the production network abnormal label acquired by traversing the first self-checking analysis data.
9. The cooperative control platform of the complex product production line of parts according to claim 8, wherein the stabilized transport exception tag, the stabilized retention exception tag or the stabilized production exception tag obtained by traversing according to the second self-checking analysis data implement a corresponding transport emergency scheme, retention emergency scheme or production emergency scheme;
and performing an abnormal alarm prompt of a corresponding process according to the intermittent transfer abnormal label or the burst transfer abnormal label, the intermittent retention abnormal label or the burst retention abnormal label, the intermittent production abnormal label or the burst production abnormal label which are obtained by traversing the second self-checking analysis data.
10. A storage medium comprising at least one processor; and a memory communicatively coupled to the at least one processor;
wherein the memory stores a computer program executable by the at least one processor to enable the at least one processor to execute a part complex product line cooperative control platform according to any one of claims 1 to 9.
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