CN117092953A - Production data acquisition management and control system based on industrial Internet of things - Google Patents
Production data acquisition management and control system based on industrial Internet of things Download PDFInfo
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract
The invention discloses a production data collection management and control system based on an industrial Internet of things, which relates to the technical field of production data collection management and control, and solves the technical problems that in the prior art, production flows cannot be classified according to data collection analysis, the qualification of the production flows cannot be guaranteed, meanwhile, each type of flow cannot be subjected to targeted management and control, different management and control are carried out on different types of flows, the faults of the production flows are reduced, the production efficiency of the industrial production flows is improved, meanwhile, the corresponding fault types of the industrial production flows are analyzed, so that the data monitoring efficiency of the industrial production process is improved, and the qualification of the industrial production is guaranteed; the feasibility of the current industrial production is judged according to the current production flow data, so that the production flow is completed when the feasibility does not meet the requirement, and the production is still carried out when the feasibility is low, thereby avoiding the occurrence of unnecessary cost while the product qualification rate is low.
Description
Technical Field
The invention relates to the technical field of production data acquisition management and control, in particular to a production data acquisition management and control system based on an industrial Internet of things.
Background
The internet of things is a network which is used for connecting any article with the internet through information sensing equipment according to a stipulated protocol and carrying out information exchange and communication so as to realize intelligent identification, positioning, tracking, monitoring and management; in popular terms, the internet of things is an extension and expansion of the internet, the core and the foundation of the internet are still the internet, the user side of the internet of things not only comprises people but also comprises articles, the internet of things realizes information exchange and communication between the people and the articles, and the internet of things is one of important technologies in the industrial field and can analyze, manage and control industrial production through data acquisition;
however, in the prior art, before data acquisition is performed in industrial production, transparency analysis cannot be performed on the data, so that timeliness of acquiring the data in real time is poor; meanwhile, the production flow cannot be classified according to data acquisition and analysis, the qualification of the production flow cannot be guaranteed, meanwhile, the flow of each type cannot be controlled in a targeted manner, and in addition, the production flow cannot be analyzed according to data analysis, so that the maintenance cannot be carried out in a targeted manner;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to solve the problems, and provides a production data acquisition management and control system based on the industrial Internet of things, which is used for analyzing the transparency of the process of industrial production in the current execution process and judging whether the real-time transparency of the production process meets the requirement, so that the timeliness of data acquisition is ensured, and the situation that the timeliness of data acquisition does not meet the requirement, so that the deviation of the production state of the current analysis is caused and the data acquisition efficiency is reduced is prevented; and carrying out fault emergency analysis on the current industrial production flow, judging whether the emergency anti-interference capability of the adjacent flow is qualified after the flow fails, thereby accurately analyzing the stability of the industrial production flow and controlling the corresponding flow through data acquisition analysis.
The aim of the invention can be achieved by the following technical scheme:
the utility model provides a production data collection management and control system based on industry thing networking, includes the server, and the server communication is connected with:
the flow transparency analysis unit is used for performing flow transparency analysis on industrial production in the current execution process, generating a collected data high risk signal and a collected data low risk signal through analysis, and sending the collected data high risk signal and the collected data low risk signal to the server; after receiving the low risk signal of the collected data, the server takes the data collected in the industrial production process as a monitoring control basis;
the process fault emergency analysis unit is used for carrying out fault emergency analysis on the current industrial production process, dividing industrial production into i process steps, i is a natural number larger than 1, dividing the industrial production process into a fault-initiating process, a sudden fault-initiating process, an affected process and a fault-non-initiating process according to the industrial production process analysis, and sending the fault-initiating process to the server;
the production fault type analysis unit is used for analyzing the corresponding fault types of the industrial production process, dividing the fault process into an aperiodic fault process and a periodic fault process according to the analysis of the production fault types, and carrying out targeted maintenance according to the fault process of the corresponding type;
the production feasibility evaluation unit is used for carrying out feasibility evaluation on real-time industrial production, generating a line-setting signal and a line normal signal through feasibility evaluation analysis, and sending the line-setting signal and the line normal signal to the server.
As a preferred embodiment of the present invention, the process of operation of the flow transparency analysis unit is as follows:
analyzing the industrial production time period, collecting the time difference between real-time statistical progress and actual progress in the industrial production process in the industrial production time period and the interval duration between the real-time process execution data generation time and the process execution data acquisition time in the industrial production process execution process, and comparing the time difference with a time difference threshold and an interval duration threshold respectively:
if the time difference between the real-time statistical progress and the actual progress in the industrial production process exceeds a time difference threshold in the industrial production time period or the interval duration between the real-time execution data generation time of the process and the process execution data acquisition time exceeds an interval duration threshold in the industrial production process execution process, generating an acquisition data high risk signal and sending the acquisition data high risk signal to a server; if the time difference between the real-time statistical progress and the actual progress in the industrial production process in the industrial production time period does not exceed the time difference threshold, and the interval duration between the real-time execution data generation time of the process and the process execution data acquisition time in the industrial production process execution process does not exceed the interval duration threshold, generating an acquisition data low risk signal and sending the acquisition data low risk signal to a server.
As a preferred embodiment of the present invention, the operation of the process fault emergency analysis unit is as follows:
collecting the qualification rate floating spans of all flow products in the industrial production process, judging that the current flow is low in execution efficiency if the corresponding qualification rate floating spans exceed a floating span threshold value, and marking the current flow as a fault flow; if the corresponding qualification rate floating span does not exceed the floating span threshold value, judging that the current flow has high execution efficiency, and marking the current flow as a normal flow;
analyzing by taking the fault flow as a center, collecting the increase speed of the execution qualification rate floating frequency of the current fault flow corresponding to the adjacent previous flow and the execution qualification rate floating probability of the current fault flow corresponding to the adjacent next flow, and comparing the increase speed threshold and the floating probability threshold respectively:
if the increase speed of the execution qualification rate floating frequency of the current fault flow corresponding to the adjacent previous flow exceeds the increase speed threshold, marking the corresponding adjacent previous flow as a fault flow which can be caused;
if the increase speed of the execution qualification rate floating frequency of the current fault flow corresponding to the adjacent previous flow does not exceed the increase speed threshold value, marking the corresponding current flow as a sudden fault flow;
if the execution qualification rate floating probability of the current fault flow corresponding to the adjacent post flow exceeds a floating probability threshold, marking the corresponding adjacent post flow as an affected flow;
if the execution qualification rate floating probability of the current fault flow corresponding to the adjacent post flow does not exceed the floating probability threshold, marking the corresponding current flow as a non-triggerable fault flow.
As a preferred embodiment of the present invention, the operation of the production failure type analysis unit is as follows:
when the industrial production process is marked as a fault process, marking the corresponding time as a fault generation time, acquiring a fault maintenance period according to the fault generation time to the fault elimination time, acquiring interval duration of adjacent fault maintenance periods in the industrial production time period, acquiring interval duration differences according to the interval duration of each adjacent fault maintenance period, analyzing the fault maintenance period and the interval duration differences, and marking the current fault process as a periodic fault process if the interval duration difference floating value does not exceed a floating value threshold after the fault maintenance period is completed; if the interval duration difference value floating value exceeds the floating value threshold after the fault maintenance period is completed, marking the current fault flow as an aperiodic fault flow;
when the periodic fault flow fails, if the interval time between the current fault time and the historical latest fault time is within the corresponding time threshold range, judging the current fault as the periodic fault, and taking the periodic fault type corresponding to the current periodic fault flow as a preferred fault source searching object; if the interval time between the current fault time and the historical latest fault time is not in the corresponding time threshold range, judging the current fault as an aperiodic fault, and taking the historical burst fault type of the current periodic fault flow as a preferred fault source searching object.
As a preferred embodiment of the invention, the production feasibility assessment unit operates as follows:
the method comprises the steps of collecting the shortening speed of a periodic fault flow corresponding to a fault period and the increasing speed of a fault frequency corresponding to an aperiodic fault flow in an industrial production time period, and comparing the shortening speed with a period shortening speed threshold and the increasing speed threshold respectively:
if the shortening speed of the periodic fault flow corresponding to the fault period exceeds a period shortening speed threshold value or the fault frequency increasing speed of the non-periodic fault flow exceeds a frequency increasing speed threshold value in the industrial production time period, judging that the current industrial production feasibility is low, generating a line rectifying signal and sending the line rectifying signal to a server; if the shortening speed of the periodic fault flow corresponding to the fault period does not exceed the period shortening speed threshold value and the frequency increasing speed of the fault frequency corresponding to the non-periodic fault flow does not exceed the frequency increasing speed threshold value in the industrial production time period, judging that the current industrial production feasibility is high, generating a production line normal signal and sending the production line normal signal to a server.
Compared with the prior art, the invention has the beneficial effects that:
1. in the invention, the industrial production in the current execution process is subjected to flow transparency analysis, and whether the real-time transparency of the production flow meets the requirement is judged, so that the timeliness of data acquisition is ensured, and the situation that the timeliness of data acquisition does not meet the requirement is prevented from causing deviation of the production state of the current analysis and the data acquisition efficiency is reduced; performing fault emergency analysis on the current industrial production flow, judging whether the emergency anti-interference capability of the adjacent flow is qualified after the flow fails, thereby accurately analyzing the stability of the industrial production flow, and managing and controlling the corresponding flow through data acquisition analysis;
2. according to the invention, different management and control are carried out on different types of processes, so that faults of the production process are reduced, the production efficiency is improved, meanwhile, the corresponding fault types of the industrial production process are analyzed, so that the maintenance is carried out pertinently according to the fault types, the data monitoring efficiency of the industrial production process is improved, and the qualification of the industrial production is ensured; the feasibility of the current industrial production is judged according to the current production flow data, so that the production flow is completed when the feasibility does not meet the requirement, the risk of production flow faults is reduced, production is still carried out when the feasibility is low, the product percent of pass is low, and meanwhile unnecessary cost is generated.
Drawings
The present invention is further described below with reference to the accompanying drawings for the convenience of understanding by those skilled in the art.
FIG. 1 is a schematic block diagram of a production data acquisition management and control system based on the industrial Internet of things of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
Referring to fig. 1, a production data collection management and control system based on an industrial internet of things comprises a server, wherein the server is in communication connection with a flow transparency analysis unit, a flow fault emergency analysis unit, a production feasibility assessment unit and a production fault type analysis unit, and the server is in two-way communication connection with the flow transparency analysis unit, the flow fault emergency analysis unit, the production feasibility assessment unit and the production fault type analysis unit;
in the industrial production process, the industrial production process is required to be monitored through data acquisition, the production process is embodied in a data form, the quality of the industrial production process can be judged through data analysis, meanwhile, the timely data acquisition can reduce the fault influence degree of the industrial production, and the working efficiency of the industrial production process is ensured while the smooth operation of the industrial process is ensured; therefore, in the industrial production execution process, the server generates a flow transparency analysis signal and sends the flow transparency analysis signal to the flow transparency analysis unit, and after the flow transparency analysis unit receives the flow transparency analysis signal, the industrial production in the current execution process is subjected to flow transparency analysis to judge whether the real-time transparency of the production flow meets the requirement, so that the timeliness of data acquisition is ensured, the situation that the timeliness of data acquisition does not meet the requirement is prevented, so that deviation of the production state of the current analysis is caused, and the data acquisition efficiency is reduced;
analyzing the industrial production time period, collecting the time difference between the real-time statistical progress and the actual progress in the industrial production process in the industrial production time period and the interval duration between the real-time execution data generation time and the process execution data collection time in the industrial production process execution process, and comparing the time difference between the real-time statistical progress and the actual progress in the industrial production process in the industrial production time period and the interval duration between the real-time execution data generation time and the process execution data collection time in the industrial production process execution process with a time difference threshold and an interval duration threshold respectively:
it can be understood that the real-time statistical progress can be performed according to the execution time of the procedure in the flow, that is, the corresponding time difference can be expressed as the progress of the current time and the corresponding time difference of the execution time of the corresponding progress; the execution data is represented as data of a process corresponding to the flow, namely, data of real-time production quantity of the process, reworked product quantity and the like;
if the time difference between the real-time statistical progress and the actual progress in the industrial production process exceeds a time difference threshold value or the interval duration between the real-time execution data generation time of the process and the process execution data acquisition time exceeds an interval duration threshold value in the industrial production process execution process, judging that the transparency of the current industrial production process is low, generating an acquisition data high-risk signal and sending the acquisition data high-risk signal to a server, and after receiving the acquisition data high-risk signal, the server performs integer processing on the acquisition of the industrial production process data in the current industrial production time, so that the data updating time is improved and the timeliness of the data is ensured;
if the time difference between the real-time statistical progress and the actual progress in the industrial production process in the industrial production time period does not exceed the time difference threshold, and the interval duration between the real-time execution data generation time of the process and the process execution data acquisition time in the industrial production process execution process does not exceed the interval duration threshold, judging that the transparency of the current industrial production process is high, generating an acquisition data low risk signal and sending the acquisition data low risk signal to a server;
after receiving the low risk signal of the collected data, the server takes the data collected in the industrial production process as a monitoring and controlling basis, the server generates a flow fault emergency analysis signal and sends the flow fault emergency analysis signal to a flow fault emergency analysis unit, and after receiving the flow fault emergency analysis signal, the flow fault emergency analysis unit carries out fault emergency analysis on the current industrial production flow and judges whether the emergency anti-interference capability of the adjacent flow is qualified after the flow fails, so that the stability of the industrial production flow is accurately analyzed, and the corresponding flow is controlled through the collected data analysis;
dividing industrial production into i flow processes, wherein i is a natural number greater than 1, collecting the qualification rate floating spans of all flow products in the industrial production process, judging that the current flow is low in execution efficiency if the corresponding qualification rate floating spans exceed a floating span threshold value, and marking the current flow as a fault flow; if the corresponding qualification rate floating span does not exceed the floating span threshold value, judging that the current flow has high execution efficiency, and marking the current flow as a normal flow;
analyzing by taking the fault flow as a center, collecting the increase speed of the execution qualification rate floating frequency of the current fault flow corresponding to the adjacent previous flow and the execution qualification rate floating probability of the current fault flow corresponding to the adjacent next flow, and comparing the increase speed of the execution qualification rate floating frequency of the current fault flow corresponding to the adjacent previous flow and the execution qualification rate floating probability of the current fault flow corresponding to the adjacent next flow with an increase speed threshold and a floating probability threshold respectively:
if the increase speed of the execution qualification rate floating frequency of the current fault flow corresponding to the adjacent previous flow exceeds the increase speed threshold, marking the corresponding adjacent previous flow as a fault flow which can be caused; if the increase speed of the execution qualification rate floating frequency of the current fault flow corresponding to the adjacent previous flow does not exceed the increase speed threshold value, marking the corresponding current flow as a sudden fault flow; if the execution qualification rate floating probability of the current fault flow corresponding to the adjacent post flow exceeds a floating probability threshold, marking the corresponding adjacent post flow as an affected flow; if the execution qualification rate floating probability of the current fault flow corresponding to the adjacent post flow does not exceed the floating probability threshold, marking the corresponding current flow as a non-triggerable fault flow;
the method comprises the steps that a fault flow which can be caused, a sudden fault flow, an affected flow and a non-fault flow are sent to a server, after the server receives the fault flow which can be caused, the sudden fault flow, the affected flow and the non-fault flow, the corresponding type of flow is managed and controlled, the monitoring strength of the fault flow which can be caused is enhanced, the fault risk of the fault flow which can be caused is reduced, and after the fault flow which can be caused is broken down, the adjacent back flows which can be caused are controlled, and the products for reworking the adjacent back flows are reduced; meanwhile, the working intensity of the sudden fault flow is controlled and the qualification probability of the equipment is improved; monitoring adjacent pre-flows of the affected flows, and controlling the execution rate of the affected flows if abnormality exists;
after the process fault emergency analysis is completed, the server generates an emergency operation model risk signal and sends the emergency operation model risk signal to the production fault type analysis unit, and the production fault type analysis unit analyzes the corresponding fault type of the industrial production process after receiving the emergency operation model risk signal, so that the maintenance is performed according to the pertinence of the fault type, the data monitoring efficiency of the industrial production process is improved, and the qualification of industrial production is ensured;
when the industrial production process is marked as a fault process, marking the corresponding time as a fault generation time, acquiring a fault maintenance period according to the fault generation time to the fault elimination time, acquiring interval duration of adjacent fault maintenance periods in the industrial production time period, acquiring interval duration differences according to the interval duration of each adjacent fault maintenance period, analyzing the fault maintenance period and the interval duration differences, and marking the current fault process as a periodic fault process if the interval duration difference floating value does not exceed a floating value threshold after the fault maintenance period is completed; if the interval duration difference value floating value exceeds the floating value threshold after the fault maintenance period is completed, marking the current fault flow as an aperiodic fault flow;
when the periodic fault flow fails, if the interval time between the current fault time and the historical latest fault time is within the corresponding time threshold range, judging the current fault as the periodic fault, and taking the periodic fault type corresponding to the current periodic fault flow as a preferred fault source searching object; if the interval time between the current fault time and the historical latest fault time is not in the corresponding time threshold range, judging the current fault as an aperiodic fault, and taking the historical burst fault type of the current periodic fault flow as a preferred fault source searching object; the fault type is expressed as a process corresponding equipment fault or an artificial operation fault;
the server generates a production feasibility evaluation signal and sends the production feasibility evaluation signal to the production feasibility evaluation unit, and after the production feasibility evaluation unit receives the production feasibility evaluation signal, the production feasibility evaluation unit evaluates the feasibility of the real-time industrial production and judges the feasibility of the current industrial production according to the current production flow data, so that the production flow is regulated when the feasibility does not meet the requirement, the risk of production flow faults is reduced, production is still carried out when the feasibility is low, the product qualification rate is low, and meanwhile, unnecessary cost is generated;
the method comprises the steps of collecting the shortening speed of a corresponding fault period of a periodic fault flow and the increasing speed of a fault frequency of a corresponding non-periodic fault flow in an industrial production time period, and comparing the shortening speed of the corresponding fault period of the periodic fault flow and the increasing speed of the fault frequency of the corresponding non-periodic fault flow in the industrial production time period with a period shortening speed threshold and a frequency increasing speed threshold respectively:
if the shortening speed of the periodic fault flow corresponding to the fault period exceeds a period shortening speed threshold value or the increasing speed of the fault frequency corresponding to the non-periodic fault flow exceeds a frequency increasing speed threshold value in the industrial production time period, judging that the current industrial production feasibility is low, generating a line setting signal and sending the line setting signal to a server, and after receiving the line setting signal, carrying out line setting on real-time industrial production, wherein the line setting comprises production equipment maintenance, production process setting, production intensity setting and the like in the prior art;
if the shortening speed of the periodic fault flow corresponding to the fault period does not exceed the period shortening speed threshold value and the frequency increasing speed of the fault frequency corresponding to the non-periodic fault flow does not exceed the frequency increasing speed threshold value in the industrial production time period, judging that the current industrial production feasibility is high, generating a production line normal signal and sending the production line normal signal to a server.
When the system is used, the process transparency analysis unit is used for carrying out process transparency analysis on industrial production in the current execution process, and the high risk signal and the low risk signal of the acquired data are generated through analysis and sent to the server; after receiving the low risk signal of the collected data, the server takes the data collected in the industrial production process as a monitoring control basis; performing fault emergency analysis on the current industrial production process by a process fault emergency analysis unit, dividing industrial production into i process steps, wherein i is a natural number greater than 1, dividing the industrial production process into a fault-initiating process, a sudden fault-initiating process, an affected process and a fault-non-initiating process according to the industrial production process analysis, and sending the fault-initiating processes to a server; analyzing the corresponding fault types of the industrial production process by a production fault type analysis unit, dividing the fault process into an aperiodic fault process and a periodic fault process according to the analysis of the production fault types, and carrying out targeted maintenance according to the fault process of the corresponding type; and carrying out feasibility assessment on real-time industrial production through a production feasibility assessment unit, generating a line integer signal and a line normal signal through feasibility assessment analysis, and sending the line integer signal and the line normal signal to a server.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (5)
1. Production data collection management and control system based on industry thing networking, characterized by, including the server, the server communication is connected with:
the flow transparency analysis unit is used for performing flow transparency analysis on industrial production in the current execution process, generating a collected data high risk signal and a collected data low risk signal through analysis, and sending the collected data high risk signal and the collected data low risk signal to the server; after receiving the low risk signal of the collected data, the server takes the data collected in the industrial production process as a monitoring control basis;
the process fault emergency analysis unit is used for carrying out fault emergency analysis on the current industrial production process, dividing industrial production into i process steps, i is a natural number larger than 1, dividing the industrial production process into a fault-initiating process, a sudden fault-initiating process, an affected process and a fault-non-initiating process according to the industrial production process analysis, and sending the fault-initiating process to the server;
the production fault type analysis unit is used for analyzing the corresponding fault types of the industrial production process, dividing the fault process into an aperiodic fault process and a periodic fault process according to the analysis of the production fault types, and carrying out targeted maintenance according to the fault process of the corresponding type;
the production feasibility evaluation unit is used for carrying out feasibility evaluation on real-time industrial production, generating a line-setting signal and a line normal signal through feasibility evaluation analysis, and sending the line-setting signal and the line normal signal to the server.
2. The industrial internet of things-based production data collection management system of claim 1, wherein the process transparency analysis unit operates as follows:
analyzing the industrial production time period, collecting the time difference between real-time statistical progress and actual progress in the industrial production process in the industrial production time period and the interval duration between the real-time process execution data generation time and the process execution data acquisition time in the industrial production process execution process, and comparing the time difference with a time difference threshold and an interval duration threshold respectively:
if the time difference between the real-time statistical progress and the actual progress in the industrial production process exceeds a time difference threshold in the industrial production time period or the interval duration between the real-time execution data generation time of the process and the process execution data acquisition time exceeds an interval duration threshold in the industrial production process execution process, generating an acquisition data high risk signal and sending the acquisition data high risk signal to a server; if the time difference between the real-time statistical progress and the actual progress in the industrial production process in the industrial production time period does not exceed the time difference threshold, and the interval duration between the real-time execution data generation time of the process and the process execution data acquisition time in the industrial production process execution process does not exceed the interval duration threshold, generating an acquisition data low risk signal and sending the acquisition data low risk signal to a server.
3. The industrial internet of things-based production data collection management system of claim 1, wherein the process of operation of the process fault emergency analysis unit is as follows:
collecting the qualification rate floating spans of all flow products in the industrial production process, judging that the current flow is low in execution efficiency if the corresponding qualification rate floating spans exceed a floating span threshold value, and marking the current flow as a fault flow; if the corresponding qualification rate floating span does not exceed the floating span threshold value, judging that the current flow has high execution efficiency, and marking the current flow as a normal flow;
analyzing by taking the fault flow as a center, collecting the increase speed of the execution qualification rate floating frequency of the current fault flow corresponding to the adjacent previous flow and the execution qualification rate floating probability of the current fault flow corresponding to the adjacent next flow, and comparing the increase speed threshold and the floating probability threshold respectively:
if the increase speed of the execution qualification rate floating frequency of the current fault flow corresponding to the adjacent previous flow exceeds the increase speed threshold, marking the corresponding adjacent previous flow as a fault flow which can be caused;
if the increase speed of the execution qualification rate floating frequency of the current fault flow corresponding to the adjacent previous flow does not exceed the increase speed threshold value, marking the corresponding current flow as a sudden fault flow;
if the execution qualification rate floating probability of the current fault flow corresponding to the adjacent post flow exceeds a floating probability threshold, marking the corresponding adjacent post flow as an affected flow;
if the execution qualification rate floating probability of the current fault flow corresponding to the adjacent post flow does not exceed the floating probability threshold, marking the corresponding current flow as a non-triggerable fault flow.
4. The industrial internet of things-based production data collection management system of claim 1, wherein the production fault type analysis unit operates as follows:
when the industrial production process is marked as a fault process, marking the corresponding time as a fault generation time, acquiring a fault maintenance period according to the fault generation time to the fault elimination time, acquiring interval duration of adjacent fault maintenance periods in the industrial production time period, acquiring interval duration differences according to the interval duration of each adjacent fault maintenance period, analyzing the fault maintenance period and the interval duration differences, and marking the current fault process as a periodic fault process if the interval duration difference floating value does not exceed a floating value threshold after the fault maintenance period is completed; if the interval duration difference value floating value exceeds the floating value threshold after the fault maintenance period is completed, marking the current fault flow as an aperiodic fault flow;
when the periodic fault flow fails, if the interval time between the current fault time and the historical latest fault time is within the corresponding time threshold range, judging the current fault as the periodic fault, and taking the periodic fault type corresponding to the current periodic fault flow as a preferred fault source searching object; if the interval time between the current fault time and the historical latest fault time is not in the corresponding time threshold range, judging the current fault as an aperiodic fault, and taking the historical burst fault type of the current periodic fault flow as a preferred fault source searching object.
5. The industrial internet of things-based production data collection management system of claim 1, wherein the production feasibility assessment unit operates as follows:
the method comprises the steps of collecting the shortening speed of a periodic fault flow corresponding to a fault period and the increasing speed of a fault frequency corresponding to an aperiodic fault flow in an industrial production time period, and comparing the shortening speed with a period shortening speed threshold and the increasing speed threshold respectively:
if the shortening speed of the periodic fault flow corresponding to the fault period exceeds a period shortening speed threshold value or the fault frequency increasing speed of the non-periodic fault flow exceeds a frequency increasing speed threshold value in the industrial production time period, judging that the current industrial production feasibility is low, generating a line rectifying signal and sending the line rectifying signal to a server; if the shortening speed of the periodic fault flow corresponding to the fault period does not exceed the period shortening speed threshold value and the frequency increasing speed of the fault frequency corresponding to the non-periodic fault flow does not exceed the frequency increasing speed threshold value in the industrial production time period, judging that the current industrial production feasibility is high, generating a production line normal signal and sending the production line normal signal to a server.
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| CN202311165894.5A CN117092953A (en) | 2023-09-11 | 2023-09-11 | Production data acquisition management and control system based on industrial Internet of things |
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| CN117873007A (en) * | 2024-03-11 | 2024-04-12 | 成都秦川物联网科技股份有限公司 | Manufacturing flow management method, system, equipment and medium based on industrial Internet of things |
| CN117873007B (en) * | 2024-03-11 | 2024-05-24 | 成都秦川物联网科技股份有限公司 | Manufacturing flow management method, system, equipment and medium based on industrial Internet of things |
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