Full-automatic steel drum production system

Abstract

The invention relates to the technical field of steel drum production, in particular to a full-automatic steel drum production system which comprises an automatic drum manufacturing equipment module, a conveying and storing device module, a first feedback module, a second feedback module, a warehouse logistics module and a central control module. The system is connected with an automatic barrel making equipment module, a conveying and storing device module, a first feedback module, a second feedback module and a warehouse logistics module, and is used for receiving a first feedback result, a second feedback result and a third feedback result; performing single analysis on each received feedback result to determine an abnormal condition of each module, and determining a single adjustment measure for each module according to a single analysis result; and determining whether to start an overall shutdown check based on the single analysis result.

Description

Technical Field

[0001] The invention relates to the technical field of steel drum production, in particular to a full-automatic steel drum production system. Background Art

[0002] The traditional steel barrel production system may lead to low production efficiency due to bottlenecks, equipment failures or process abnormalities in the production process, and requires a lot of manual intervention, resulting in low overall production efficiency; during the production process, if equipment failures or transmission abnormalities cannot be responded to and handled in a timely manner, it will seriously affect the production progress; the traditional production system may lack effective coordination and communication between the modules, resulting in low overall operating efficiency.

[0003] Chinese patent application publication number CN108098263A discloses a steel drum production process, comprising the following steps: S1, placing a steel strip coil into a feeding mechanism, which gradually pulls the steel strip coil forward from the starting end to extend it; S2, the gradually extended and continuously moving forward steel strip is gradually rolled in the length direction and in the width direction by a rolling system; S3, the rolled steel strip is laser welded and sealed; S4, the welded steel strip is laser cut into multiple sections according to the required height of the steel drum to form multiple prototype steel drums; S5, the prototype steel drum is subjected to edge bending, rib expansion and corrugation treatment; S6, the two ends of the prototype steel drum are sealed with a sealing gasket, a certain amount of compressed air is injected, and whether bubbles are generated in the welded prototype steel drum; S7, the prototype steel drum is coated.

[0004] It can be seen that the current fully automatic steel barrel production system has problems such as low production efficiency, lax quality control, untimely fault response, poor system coordination, and insufficient data analysis and decision support. Summary of the invention

[0005] To this end, the purpose of the present invention is to provide a fully automatic steel barrel production system to overcome the problems of low production efficiency, lax quality control, untimely fault response, poor system coordination, and insufficient data analysis and decision support in the current fully automatic steel barrel production system.

[0006] To achieve the above object, the present invention provides a fully automatic steel drum production system, comprising: An automatic barrel making equipment module, which is used to pre-treat the initial raw materials to obtain the raw materials to be produced, sequentially shape the raw materials to be produced to obtain a first target semi-finished product, curl the first target semi-finished product to obtain a second target semi-finished product, and weld the second target semi-finished product to obtain a target finished product; A first feedback module, which is used to receive production abnormality information of the automatic barrel making equipment module during the production process, analyze the production abnormality information, and determine a first feedback result according to the analysis result; The production abnormality information includes: various temperature production abnormality parameters and various pressure production abnormality parameters; A transmission and storage device module, which is used to orderly transmit and store the raw materials to be produced, the target semi-finished products and the target finished products obtained by the automatic barrel making equipment module during the production process; A second feedback module, which is used to receive transmission abnormality information of the transmission storage device module during the transmission process, analyze the transmission abnormality information, and determine a second feedback result according to the analysis result; The transmission abnormality information includes: each vibration transmission abnormality parameter and each path transmission abnormality parameter; A storage logistics module, which is used to receive the real-time storage capacity of the transmission storage device module during the storage process, and determine a third feedback result according to the real-time storage capacity; The central control module is connected to the automatic barrel making equipment module, the conveying and storage device module, the first feedback module, the second feedback module and the warehousing and logistics module respectively, and is used to receive the first feedback result, the second feedback result and the third feedback result; perform a single analysis on each feedback result received to determine the abnormal situation of each module, determine a single adjustment measure for each module according to the single analysis result; and determine whether to start the overall shutdown inspection based on the single analysis result.

[0007] Furthermore, the automatic barrel making equipment module includes: a verification unit and a judgment unit; The verification unit is used to obtain the receiving quality and pre-processing quality of the initial raw material, and to verify whether the receiving quality and the pre-processing quality are qualified; The judgment unit is used to obtain the actual number of qualified items in the receiving quality and the pre-processing quality, and determine whether to start the formal production mode according to the actual number of qualified items.

[0008] Further, the first feedback module includes: a first receiving unit, a type identification unit and a first determination unit; The first receiving unit is configured to periodically obtain the production abnormality information during the production process at a preset initial receiving interval; The first type identification unit is used to classify the production abnormality information to determine whether the abnormal type of each production abnormality parameter is an equipment failure parameter or a process abnormality parameter; The first determination unit is used to determine that the first feedback result is production parameter adjustment or equipment maintenance or equipment update according to the classification result of the first type identification unit.

[0009] Further, the first receiving unit includes: a first acquisition subunit and a first abnormal subunit; The first acquisition subunit is used to acquire actual production information according to the initial receiving interval; The actual production information includes: actual production parameters of each temperature and actual production parameters of each pressure; The first abnormal sub-unit is used to determine whether each actual production parameter is a production abnormality parameter according to each actual production parameter and a preset production parameter standard variation range.

[0010] Further, the one type of identification unit includes: a preliminary classification subunit, an identification subunit and a correction subunit; The preliminary classification subunit is used to preliminarily classify the production abnormality information according to the abnormality type to obtain parameters of each type; The identification subunit is used to identify the classification result of the preliminary classification subunit to obtain the actual number of types; The correction subunit is used to determine whether to start a receiving cycle correction mode according to the actual number of types; Among them, each type of parameter includes: the equipment failure parameter and the process abnormality parameter.

[0011] Furthermore, the type one identification unit further includes: a marking subunit; The marking subunit is used to perform feature recognition on the classification results of the preliminary classification subunit to extract key production features, and to perform feature marking on the classification results according to the key production features; The key production features include: occurrence timestamp and occurrence frequency.

[0012] Further, the first determination unit includes: a calculation subunit, a determination subunit and a first output subunit; The calculation subunit is used to calculate an initial production anomaly score according to the classification result of the preliminary classification subunit combined with the actual number of types, and to correct the initial production anomaly score according to the feature marking result of the marking subunit to obtain an actual production anomaly score; The determination subunit is used to determine the actual production abnormality level according to the actual production abnormality score; The first output subunit is used to determine the first feedback result according to the actual production abnormality level.

[0013] Further, the second feedback module includes: a second receiving unit, a second type identification unit and a second determination unit; The second receiving unit is configured to periodically obtain the transmission abnormality information during the transmission process at the initial receiving interval; The second type identification unit is used to preliminarily classify each vibration transmission abnormality parameter and each path transmission abnormality parameter to obtain a conveyor belt fault parameter and a conveying abnormality parameter, and to perform feature identification on the preliminary classification result to obtain a conveying key feature, and to perform feature marking on the preliminary classification result according to the conveying key feature; The second determination unit is used to determine that the second feedback result is a conveyor belt maintenance or a transmission path inspection or a conveyor belt update according to the feature marking result of the second type identification unit; The key features of the transmission include: a fault location mark and a fault time mark.

[0014] Further, the storage logistics module includes: a storage subunit, a comparison subunit and a third determination subunit; The storage subunit is used to obtain the real-time storage quantity of each target semi-finished product; The comparison subunit is used to compare each real-time storage amount to determine whether it meets the overall production standard; The overall production standard is that the fluctuation difference between the real-time storage volume of each target semi-finished product is within the preset standard production fluctuation range; The third determining subunit is used to determine, according to the comparison result of the comparing subunit, that the third feedback result is to adjust the production power of the equipment or to adjust the production plan.

[0015] Furthermore, the central control module includes: a production control unit, a transmission control unit, a storage control unit, an overall analysis unit and an instruction output unit; The production control unit is configured to receive the first feedback result and make corresponding production process adjustments according to the first feedback result; The transmission control unit is configured to receive the second feedback result and perform corresponding transmission adjustment according to the second feedback result; The storage control unit is used to receive the third feedback result and make corresponding production plan adjustments according to the third feedback result; The overall analysis unit is used to integrate the adjustment conditions of each control unit and analyze the integration result to determine whether to issue an alarm signal; The instruction output unit is used to receive the alarm signal and start the overall shutdown inspection according to the alarm signal.

[0016] Compared with the prior art, the invention has the beneficial effect that, through the automated barrel making equipment module, the whole process from raw material pretreatment to finished product production is automated, manual intervention is reduced, and production speed and efficiency are improved. At the same time, the transmission and storage device module ensures the smooth transmission and storage of materials in the production process, avoiding production delays caused by material stagnation or confusion. The first feedback module and the second feedback module respectively monitor the abnormal conditions in the production process and the transmission process, and timely discover and feedback problems through feature recognition, which helps to quickly locate the source of the problem, take corresponding measures, reduce production interruptions and failure time, and improve production stability and reliability. The warehousing and logistics module adjusts the warehousing strategy according to the real-time storage capacity to ensure the effective management of materials and finished products and quickly respond to market demand, which helps to reduce inventory backlog and waste, improve inventory turnover, and reduce warehousing costs. The central control module, as the core of the system, integrates the feedback information of each module, and formulates and adjusts the production strategy through a combination of single analysis and overall analysis. The intelligent decision support mechanism can more accurately reflect the actual production situation, improve the scientificity and effectiveness of decision-making, and provide strong support for the continuous optimization and upgrading of enterprises. It can quickly respond to market changes and customer needs, and achieve rapid production and delivery by flexibly adjusting production plans and resource allocation.

[0017] By strictly checking the receiving quality and pre-processing quality of the initial raw materials, we ensure that only qualified raw materials enter the production process, effectively avoiding product defects caused by raw material quality problems, and improving the quality and reliability of the final product. The decision whether to start the formal production mode is based on the actual number of qualified projects and the target production plan. This mechanism enhances the controllability and flexibility of the production process, allowing timely adjustments when potential problems (such as unqualified raw material quality or unqualified pre-processing) are discovered, avoiding ineffective production or waste of resources. Through automated and intelligent verification and judgment processes, human intervention and errors are reduced, and production efficiency is improved. At the same time, the formal production mode is started based on qualified pre-processing results and sufficient raw material quantities. It ensures the continuity and stability of the production process and reduces production delays caused by waiting or interruptions. During the preprocessing process, the raw materials are accurately measured and preliminarily cut, bent and other operations are performed to form raw materials to be produced that are suitable for subsequent molding processes. Precise control helps to optimize the utilization of raw materials, reduce waste, and reduce production costs. When the actual number of qualified items does not meet the requirements or the quantity of raw materials is insufficient, it can respond quickly and take corresponding adjustments or processing measures. By combining multiple factors such as receiving quality, preprocessing quality, target production plan and current raw material quantity for comprehensive judgment, it can more accurately decide whether to start the formal production mode. The decision-making process based on comprehensive information improves the scientificity and accuracy of the decision.

[0018] The production abnormality information is obtained periodically through the preset initial receiving interval (5-10 minutes, and can be adaptively adjusted), which ensures the real-time nature of the feedback mechanism, helps to promptly discover and respond to problems in the production process, avoid the expansion of problems or cause greater losses, and uses a class of identification units to accurately classify and feature abnormal information, which improves the accuracy of abnormality handling. By distinguishing between equipment failure parameters and process abnormality parameters, the cause of the problem can be more accurately located, providing strong support for subsequent treatment measures. The entire feedback mechanism realizes intelligent and automated processing procedures, reduces the need for manual intervention, and improves work efficiency. The receiving cycle is dynamically adjusted according to the actual number of types, and the feedback mechanism is self-optimized, which helps to improve the response speed when abnormalities occur frequently and reduce the system burden when abnormalities are less, thereby improving the flexibility and adaptability of the system. Through detailed classification and scoring of production abnormalities, refined management of the production process is achieved; different types of abnormalities are assigned different weights, so that The scoring results are more in line with the actual situation. The classification results are marked with features, and key production features (occurrence timestamp and frequency) are extracted, which helps to deeply understand the nature and trend of anomalies and provide data support for subsequent improvements and optimizations. The corresponding feedback results (production parameter adjustment, equipment maintenance, equipment update) are determined according to the anomaly score and level, achieving efficient problem solving. Different feedback results correspond to different treatment measures, which helps to quickly resume production and reduce downtime. The priority setting of feedback results (from production parameter adjustment to equipment update) ensures the rationality and efficiency of problem handling. First, try to solve the problem by adjusting the production parameters. If it is ineffective, further consider equipment maintenance or update, avoiding unnecessary waste of resources. By promptly discovering and solving abnormal problems in the production process, the accumulation and expansion of problems are avoided, which helps to improve production efficiency and product quality. A stable production process can reduce the scrap rate and improve the product qualification rate, thereby enhancing the market competitiveness of the enterprise. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a structural schematic diagram of a fully automatic steel drum production system according to an embodiment of the present invention; Figure 2 This is a structural schematic diagram of a first feedback module in a fully automatic steel drum production system according to an embodiment of the present invention; Figure 3 This is a schematic structural diagram of a type of identification unit in a first feedback module in a fully automatic steel drum production system according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of a central control module in a fully automatic steel drum production system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0021] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0022] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0023] See also Figure 1-Figure 4 As shown, Figure 1 This is a structural schematic diagram of a fully automatic steel drum production system according to an embodiment of the present invention; Figure 2 This is a structural schematic diagram of a first feedback module in a fully automatic steel drum production system according to an embodiment of the present invention; Figure 3 This is a schematic structural diagram of a type of identification unit in a first feedback module in a fully automatic steel drum production system according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of a central control module in a fully automatic steel drum production system according to an embodiment of the present invention.

[0024] The present invention provides a fully automatic steel drum production system, comprising: An automatic barrel making equipment module, which is used to pre-treat the initial raw materials to obtain the raw materials to be produced, sequentially shape the raw materials to be produced to obtain a first target semi-finished product, curl the first target semi-finished product to obtain a second target semi-finished product, and weld the second target semi-finished product to obtain a target finished product; A first feedback module, which is used to receive production abnormality information of the automatic barrel making equipment module during the production process, analyze the production abnormality information, and determine a first feedback result according to the analysis result; The production abnormality information includes: various temperature production abnormality parameters and various pressure production abnormality parameters; A transmission and storage device module, which is used to orderly transmit and store the raw materials to be produced, the target semi-finished products and the target finished products obtained by the automatic barrel making equipment module during the production process; A second feedback module, which is used to receive transmission abnormality information of the transmission storage device module during the transmission process, analyze the transmission abnormality information, and determine a second feedback result according to the analysis result; The transmission abnormality information includes: each vibration transmission abnormality parameter and each path transmission abnormality parameter; A storage logistics module, which is used to receive the real-time storage capacity of the transmission storage device module during the storage process, and determine a third feedback result according to the real-time storage capacity; The central control module is connected to the automatic barrel making equipment module, the conveying and storage device module, the first feedback module, the second feedback module and the warehousing and logistics module respectively, and is used to receive the first feedback result, the second feedback result and the third feedback result; perform a single analysis on each feedback result received to determine the abnormal situation of each module, determine a single adjustment measure for each module according to the single analysis result; and determine whether to start the overall shutdown inspection based on the single analysis result.

[0025] Specifically, the embodiment of the present invention realizes the full automation from raw material pretreatment to finished product production through the automated barrel making equipment module, reduces manual intervention, and improves production speed and efficiency. At the same time, the transmission and storage device module ensures the smooth transmission and storage of materials in the production process, avoiding production delays caused by material stagnation or confusion. The first feedback module and the second feedback module respectively monitor the abnormal conditions in the production process and the transmission process, and timely discover and feedback problems through feature recognition, which helps to quickly locate the source of the problem, take corresponding measures, reduce production interruptions and failure time, and improve production stability and reliability. The warehousing and logistics module adjusts the warehousing strategy according to the real-time storage capacity to ensure the effective management of materials and finished products and quickly respond to market demand, which helps to reduce inventory backlog and waste, improve inventory turnover, and reduce warehousing costs. The central control module, as the core of the system, integrates the feedback information of each module, and formulates and adjusts the production strategy through a combination of single analysis and overall analysis. The intelligent decision support mechanism can more accurately reflect the actual production situation, improve the scientificity and effectiveness of decision-making, and provide strong support for the continuous optimization and upgrading of enterprises. It can quickly respond to market changes and customer needs, and achieve rapid production and delivery by flexibly adjusting production plans and resource allocation.

[0026] Specifically, in this embodiment, the automatic barrel making equipment module includes: a verification unit and a judgment unit; The verification unit is used to obtain the receiving quality and pre-processing quality of the initial raw material, and to verify whether the receiving quality and the pre-processing quality are qualified; The judgment unit is used to obtain the actual number of qualified items in the receiving quality and the pre-processing quality, and determine whether to start the formal production mode according to the actual number of qualified items.

[0027] Specifically, the automatic barrel making equipment module in this embodiment receives the initial raw materials, performs material testing on the initial raw materials, confirms whether the composition, hardness, and toughness meet the production standards, and avoids product quality problems caused by using unqualified materials; The material detection result is the reception quality; The pre-treatment process includes: cleaning the received raw materials to remove impurities such as oil and dust on the surface to ensure the cleanliness of the surface of the initial raw materials; using measuring equipment to check whether the size and shape of the initial raw materials meet the production requirements, including length, width, and thickness, to ensure the smooth progress of the subsequent processing; according to production needs, the initial raw materials are preliminarily cut and bent to form raw materials to be produced that are suitable for subsequent molding processes; Based on the fact that both the receiving quality and the pre-processing quality are qualified, that is, when the actual number of qualified items is 2, the judgment unit determines to start the formal production mode, thereby ensuring the continuity and stability of the production process; When the actual number of qualified items is less than 2, the judgment unit determines not to start the formal production mode and re-performs preprocessing.

[0028] Specifically, the embodiments of the present invention ensure that only qualified raw materials enter the production process by strictly verifying the receiving quality and pre-processing quality of the initial raw materials, effectively avoiding product defects caused by raw material quality problems, and improving the quality and reliability of the final product. Whether to start the formal production mode is determined based on the actual number of qualified projects and the target production plan. This mechanism enhances the controllability and flexibility of the production process, allows timely adjustments when potential problems (such as unqualified raw material quality or unqualified pre-processing) are discovered, and avoids ineffective production or waste of resources. Through automated and intelligent verification and judgment processes, manual intervention and errors are reduced, and production efficiency is improved. At the same time, based on qualified pre-processing results and sufficient The quantity of raw materials starts the formal production mode, which ensures the continuity and stability of the production process and reduces production delays caused by waiting or interruptions. In the preprocessing process, the raw materials are accurately measured and preliminarily cut, bent and other operations are carried out to form raw materials to be produced that are suitable for subsequent molding processes. Precise control helps to optimize the utilization of raw materials, reduce waste, and reduce production costs. When the actual number of qualified items does not meet the requirements or the quantity of raw materials is insufficient, it can respond quickly and take corresponding adjustments or processing measures. By combining the receiving quality, preprocessing quality and multiple factors for comprehensive judgment, it can more accurately decide whether to start the formal production mode. The decision-making process based on comprehensive information improves the scientificity and accuracy of the decision.

[0029] Specifically, in this embodiment, the first feedback module includes: a first receiving unit, a type identification unit and a first determination unit; The first receiving unit is configured to periodically obtain the production abnormality information during the production process at a preset initial receiving interval; The first type identification unit is used to classify the production abnormality information to determine whether the abnormal type of each production abnormality parameter is an equipment failure parameter or a process abnormality parameter; The first determination unit is used to determine that the first feedback result is a production parameter adjustment or equipment maintenance or equipment update according to the classification result of the first type identification unit; In this embodiment, the initial receiving interval is set to 5-10 minutes; and adaptive selection and adjustment are performed according to the actual production accuracy; The first receiving unit includes: a first acquisition subunit and a first abnormal subunit; The first acquisition subunit is used to acquire actual production information according to the initial receiving interval; The actual production information includes: actual production parameters of each temperature and actual production parameters of each pressure; The first abnormal subunit is used to determine whether each actual production parameter is a production abnormality parameter according to each actual production parameter and a preset production parameter standard variation interval; In this embodiment, the standard variation intervals of production parameters corresponding to the actual production parameters obtained in different production processes are set differently; for example, the standard variation intervals of temperature production parameters corresponding to the hemming process are affected by the material, size, production process and equipment used of the steel drum; a suitable standard variation interval of temperature production parameters is selected to avoid overheating, oxidation or even melting of the material when the temperature is too high, and brittleness and difficulty in forming of the material when the temperature is too low; When the actual temperature production parameter is lower than the minimum value of the standard variation range of the temperature production parameter, the first abnormal subunit determines it as the abnormal production parameter; When the actual temperature production parameter is higher than the maximum value of the standard variation range of the temperature production parameter, the first abnormal subunit determines that it is the abnormal production parameter; The first type of identification unit includes: a preliminary classification subunit, an identification subunit, a correction subunit and a marking subunit; The preliminary classification subunit is used to preliminarily classify the production abnormality information according to the abnormality type to obtain parameters of each type; The identification subunit is used to identify the classification result of the preliminary classification subunit to obtain the actual number of types; The correction subunit is used to determine whether to start a receiving cycle correction mode according to the actual number of types; Among them, each type of parameter includes: the equipment failure parameter and the process abnormality parameter; When the classification result of the preliminary classification subunit is that both the equipment fault parameter and the process abnormality parameter exist, the identification subunit determines that the actual number of types is 2; The correction subunit determines whether to turn on the receiving cycle correction mode based on the actual number of types being 2; In this embodiment, if there is a temperature production abnormality parameter, the preliminary classification subunit determines that the temperature production abnormality parameter is the process abnormality parameter; If there is a pressure production abnormality parameter, the preliminary classification subunit determines that the pressure production abnormality parameter is the equipment failure parameter; The marking subunit is used to perform feature recognition on the classification results of the preliminary classification subunit to extract key production features, and to perform feature marking on the classification results according to the key production features; Wherein, the key production features include: occurrence timestamp and occurrence frequency; The marking subunit determines the occurrence frequency according to the occurrence timestamp, When the occurrence frequency is greater than or equal to a preset standard frequency, the marking subunit determines to perform a characteristic marking of the occurrence frequency; When the occurrence frequency is less than a preset standard frequency, the marking subunit determines not to perform a characteristic marking of the occurrence frequency; In this embodiment, the standard frequency is set to 2 times / 10 minutes; The first determination unit includes: a calculation subunit, a determination subunit and a first output subunit; The calculation subunit is used to calculate an initial production anomaly score according to the classification result of the preliminary classification subunit combined with the actual number of types, and to correct the initial production anomaly score according to the feature marking result of the marking subunit to obtain an actual production anomaly score; The determination subunit is used to determine the actual production abnormality level according to the actual production abnormality score; The first output subunit is used to determine the first feedback result according to the actual production abnormality level.

[0030] Specifically, in this embodiment, the first receiving unit is the front end of the entire feedback mechanism, which is responsible for periodically acquiring various abnormal information in the production process from the production system at a preset initial receiving interval (such as every 5 minutes, every 10 minutes, etc.); such abnormal information may include but is not limited to equipment failure alarms, process parameters deviating from set values, and sudden interruptions in the production process; by regularly collecting such information, the first receiving unit ensures the timeliness and comprehensiveness of the feedback system; a type of identification unit is the core processing part of the feedback mechanism, which is responsible for in-depth processing of the received production abnormality information; the unit is composed of several sub-units to achieve accurate classification, analysis and feature recognition of abnormal information; The preliminary classification subunit first performs preliminary classification according to the type of abnormal information, simplifying the complex abnormal information into various types of parameters that are easy to manage and analyze; based on the preliminary classification, the identification subunit further identifies the classification results and confirms the actual number of occurrences or degrees of each type of parameter, that is, the actual number of types; ensuring the accuracy and pertinence of subsequent analysis; based on the actual number of types obtained by the identification subunit, the correction subunit will evaluate whether it is necessary to turn on the receiving cycle correction mode; if a certain type of abnormality occurs frequently, it may be necessary to shorten the receiving interval to increase the response speed; conversely, if the abnormality is less, the receiving interval can be appropriately extended to reduce the system burden; the marking subunit performs feature recognition on the classified abnormal information and extracts key features such as occurrence timestamp and occurrence frequency; this helps to more deeply understand the nature and trend of the abnormality and provide strong support for subsequent analysis and decision-making; at the same time, the marking subunit will also feature mark the classification results based on these features for subsequent processing and query; The first determination unit is responsible for determining a first feedback result according to a processing result of a type of identification unit; The calculation subunit calculates the initial production anomaly score according to the classification result of the preliminary classification subunit combined with the actual number of types; Determining the number of equipment failure parameters and the number of process abnormality parameters according to the classification results of the preliminary classification subunit; In the process of determining the initial production anomaly score by combining the number of equipment failure parameters and the number of process abnormality parameters with the number of actual types, the calculation subunit sets a first weight, a second weight and an actual type quantity weight for the number of equipment failure parameters, the number of process abnormality parameters and the actual type number respectively; During the specific implementation process, the first weight corresponding to the number of equipment fault parameters is set to 0.8; the second weight corresponding to the number of process abnormal parameters is set to 0.7; the actual type quantity weight corresponding to the actual type number is set to 0.8; the product of the number of equipment fault parameters and the first weight corresponding thereto is calculated to obtain the first abnormality score, and the product of the number of process abnormal parameters and the second weight corresponding thereto is calculated to obtain the second abnormality score; the sum of the first abnormality score and the second abnormality score is calculated and compensated by the actual type quantity weight to obtain the initial production abnormality score; The initial production abnormality score reflects the abnormality level in the current production process; The calculation subunit will correct the initial score according to the characteristic marking result provided by the marking subunit to obtain a more accurate and actual production anomaly score that conforms to the actual situation; In a specific implementation process, the occurrence frequency is determined according to the characteristic marking result provided by the marking subunit; the actual production abnormality score is determined according to the product of the occurrence frequency and the initial production abnormality score, so as to realize the correction of the initial production abnormality score; The determination subunit determines the actual production abnormality level according to the actual production abnormality score; The actual production abnormality level in this embodiment may be quantitative (such as 1-5 levels) or qualitative (such as slight, general, severe, etc.), which is used to indicate the severity of the current production abnormality; this embodiment does not make specific limitations; The first output subunit outputs a first feedback result as production parameter adjustment or equipment maintenance or equipment update from low to high according to the severity of the actual production abnormality level determined by the determination subunit.

[0031] Specifically, the embodiment of the present invention periodically obtains production abnormality information through a preset initial receiving interval (5-10 minutes, and can be adaptively adjusted), thereby ensuring the real-time nature of the feedback mechanism, helping to promptly discover and respond to problems in the production process, and avoiding the expansion of problems or greater losses. A type of identification unit is used to accurately classify and feature the abnormal information, thereby improving the accuracy of abnormality processing. By distinguishing between equipment failure parameters and process abnormality parameters, the cause of the problem can be more accurately located, providing strong support for subsequent processing measures. The entire feedback mechanism realizes an intelligent and automated processing flow, reduces the need for manual intervention, and improves work efficiency. The receiving cycle is dynamically adjusted according to the actual number of types, thereby realizing self-optimization of the feedback mechanism, helping to improve the response speed when abnormalities occur frequently, and reducing the system burden when abnormalities are less, thereby improving the flexibility and adaptability of the system. By performing detailed classification and scoring of production abnormalities, refined management of the production process is achieved, and different types of abnormalities are assigned different The weight makes the scoring result more in line with the actual situation, the classification results are marked with features, and the key production features (occurrence timestamp and frequency) are extracted, which helps to deeply understand the nature and trend of anomalies and provide data support for subsequent improvements and optimizations. The corresponding feedback results (production parameter adjustment, equipment maintenance, equipment update) are determined according to the anomaly score and level, which achieves efficient problem solving. Different feedback results correspond to different treatment measures, which helps to quickly resume production and reduce downtime. The priority setting of feedback results (from production parameter adjustment to equipment update) ensures the rationality and efficiency of problem handling. First, try to solve the problem by adjusting the production parameters. If it is ineffective, further consider equipment maintenance or update, avoiding unnecessary waste of resources. By promptly discovering and solving abnormal problems in the production process, the accumulation and expansion of problems are avoided, which helps to improve production efficiency and product quality. A stable production process can reduce the scrap rate and improve the product qualification rate, thereby enhancing the market competitiveness of the enterprise.

[0032] Specifically, in this embodiment, the second feedback module includes: a second receiving unit, a second type identification unit, and a second determination unit; The second receiving unit is configured to periodically obtain the transmission abnormality information during the transmission process at the initial receiving interval; The second type identification unit is used to preliminarily classify each vibration transmission abnormality parameter and each path transmission abnormality parameter to obtain a conveyor belt fault parameter and a conveying abnormality parameter, and to perform feature identification on the preliminary classification result to obtain a conveying key feature, and to perform feature marking on the preliminary classification result according to the conveying key feature; The second determination unit is used to determine that the second feedback result is a conveyor belt maintenance or a transmission path inspection or a conveyor belt update according to the feature marking result of the second type identification unit; The key features of the transmission include: a fault location mark and a fault time mark.

[0033] In this embodiment, the second feedback module monitors and provides feedback for abnormalities in the transmission process; The second receiving unit, as the front end of the second feedback module, periodically obtains transmission abnormality information from the transmission system at the same initial receiving interval as the first feedback module (5-10 minutes, and can be adaptively adjusted); including abnormal vibration of the conveyor belt, blockage of the transmission path, and abnormal speed. By regularly collecting this information, the second receiving unit ensures that the feedback system is aware of transmission abnormalities in a timely manner; The second-class identification unit performs preliminary classification on the received transmission abnormality information, which includes: each vibration transmission abnormality parameter and each path transmission abnormality parameter, so as to distinguish the conveyor belt fault parameter and the transmission abnormality parameter; based on the preliminary classification, the second-class identification unit performs feature recognition on the classification result to extract the key transmission feature, which includes the fault location mark and the fault time mark. The second determination unit determines the second feedback result according to the feature marking result of the second type identification unit; the second determination unit determines whether it is necessary to perform conveyor belt maintenance, transmission path inspection or conveyor belt update according to the key conveying feature; During the specific implementation process, if the fault location frequently appears in a specific area of ​​the conveyor belt and the fault time is relatively concentrated, then it is likely that there is a problem with the conveyor belt itself and it needs to be repaired or replaced; if the fault location is scattered and random, but the fault time is concentrated in a certain time period, then there may be a problem in a certain link in the transmission path (such as a sensor, controller), which requires inspection and maintenance; if the conveyor belt has been used for many years and faults occur frequently, then you may need to consider updating the conveyor belt to improve transmission efficiency and stability.

[0034] Specifically, the warehousing logistics module in this embodiment includes: a storage subunit, a comparison subunit and a third determination subunit; The storage subunit is used to obtain the real-time storage quantity of each target semi-finished product; The comparison subunit is used to compare each real-time storage amount to determine whether it meets the overall production standard; The overall production standard is that the fluctuation difference between the real-time storage volume of each target semi-finished product is within the preset standard production fluctuation range; The third determining subunit is used to determine, according to the comparison result of the comparing subunit, that the third feedback result is to adjust the production power of the equipment or to adjust the production plan.

[0035] In a specific implementation process, when the fluctuation difference corresponding to any two types of target semi-finished products is not within the standard output fluctuation range, the third determination subunit determines that it does not meet the overall production standard; When the fluctuation difference corresponding to any two types of target semi-finished products is within the standard output fluctuation range, the third determination subunit determines that the overall production standard is met; The third determination subunit obtains the number of items in each target semi-finished product whose fluctuation difference is not within the standard output fluctuation range; and determines the third feedback result to adjust the equipment production power or adjust the production plan based on the number of items.

[0036] In the specific implementation process, the storage subunit acquires and updates the storage quantity information of each target semi-finished product in real time; automatic data collection is realized through sensors, RFID tag readers, barcode scanning devices, etc. integrated in the warehouse management system, which are not specifically limited in this embodiment; the storage subunit summarizes and organizes the collected real-time storage quantity data, and transmits it to the subsequent comparison subunit for analysis; after the comparison subunit receives the real-time storage quantity data from the storage subunit, it immediately starts the comparison mechanism; compares the real-time storage quantity fluctuation differences between the target semi-finished products to determine whether these fluctuations remain within the preset standard output fluctuation range; the standard output fluctuation range is set according to the total amount of raw materials to be produced to ensure that the inventory level can meet the production demand without causing unnecessary backlog or shortage; During the specific implementation process, the comparison subunit will calculate the storage volume fluctuation difference between each two types of target semi-finished products one by one, and compare it with the standard output fluctuation range; if all fluctuation differences are within the range, it indicates that the current inventory status meets the overall production standard; on the contrary, if the fluctuation difference between any two types of target semi-finished products exceeds the range, it is determined to be non-compliant with the overall production standard; when the comparison subunit completes the comparison and determines the inventory status, the third determination subunit will further determine specific feedback measures based on the determination result; count the number of target semi-finished product items whose fluctuation difference is not within the standard output fluctuation range; based on the number of items being less than or equal to the preset standard number of items, the third determination subunit adjusts the production power of related equipment to speed up or slow down the production speed of a specific semi-finished product, so that its inventory level quickly returns to the standard range; based on the number of items being greater than the standard number of items, the third determination subunit makes more comprehensive production plan adjustments, including reallocating production resources, optimizing production processes, and adjusting production sequences, to ensure that the inventory levels of each target semi-finished product can reach the standard state synchronously.

[0037] Specifically, the central control module in this embodiment includes: a production control unit, a transmission control unit, a storage control unit, an overall analysis unit and an instruction output unit; The production control unit is configured to receive the first feedback result and make corresponding production process adjustments according to the first feedback result; The transmission control unit is configured to receive the second feedback result and perform corresponding transmission adjustment according to the second feedback result; The storage control unit is used to receive the third feedback result and make corresponding production plan adjustments according to the third feedback result; The overall analysis unit is used to integrate the adjustment conditions of each control unit and analyze the integration result to determine whether to issue an alarm signal; The instruction output unit is used to receive the alarm signal and start the overall shutdown inspection according to the alarm signal.

[0038] In the specific implementation process, the overall analysis unit integrates the adjustment conditions of each control unit. If all control units have adjustment conditions, it is determined to send the alarm signal.

[0039] In the specific implementation process, the production control unit receives the first feedback result from the production line. According to the first feedback result, the production control unit will quickly analyze and make corresponding production process adjustment decisions, such as adjusting equipment parameters, switching production modes, suspending or restarting the production line, etc., to ensure the stability of the production process and product quality; the transmission control unit is used to control the material transmission link on the production line; receive the second feedback result from the material transmission system, reflecting the material flow speed, congestion of the transmission path, and fault information of the transmission equipment; based on the second feedback result, the transmission control unit will make corresponding transmission adjustments, such as optimizing the transmission path, adjusting the transmission speed, and starting the backup transmission line to ensure that the material can flow smoothly and efficiently to the next production link; the storage control unit is responsible for monitoring and managing the semi-finished product and finished product inventory in the production process; receive the third feedback result from the warehousing and logistics module, the third feedback result reflects the real-time storage volume of each target semi-finished product, inventory fluctuations, and whether it meets the overall production standards; the storage control unit makes corresponding production plan adjustments according to the third feedback result, such as adjusting the production batch size, optimizing the production sequence, starting or suspending the production of specific products, to ensure that the inventory level can keep pace with production demand; The overall analysis unit integrates the adjustment conditions of each control unit and conducts a comprehensive and in-depth analysis of the integration results to evaluate the overall operating status of the current production system and identify potential problems and risks; if the overall analysis unit finds that each control unit has an adjustment condition, and these adjustments indicate that the production system may be in an unstable or abnormal state, then it will determine to send an alarm signal; based on an alarm signal, an emergency notification will be made to the production management; when the command output unit receives the alarm signal sent by the overall analysis unit, the command output unit will respond immediately and start an overall shutdown inspection according to the preset emergency handling process, so as to prevent the production system from further deteriorating or more serious failures, identify the root cause of the problem through a comprehensive shutdown inspection, and take corresponding repair measures.

[0040] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0041] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A fully automatic steel drum production system, characterized in that: include: An automatic barrel making equipment module, which is used to pre-treat the initial raw materials to obtain the raw materials to be produced, sequentially shape the raw materials to be produced to obtain a first target semi-finished product, curl the first target semi-finished product to obtain a second target semi-finished product, and weld the second target semi-finished product to obtain a target finished product; A first feedback module, which is used to receive production abnormality information of the automatic barrel making equipment module during the production process, analyze the production abnormality information, and determine a first feedback result according to the analysis result; The production abnormality information includes: various temperature production abnormality parameters and various pressure production abnormality parameters; A transmission and storage device module, which is used to orderly transmit and store the raw materials to be produced, the target semi-finished products and the target finished products obtained by the automatic barrel making equipment module during the production process; A second feedback module, which is used to receive transmission abnormality information of the transmission storage device module during the transmission process, analyze the transmission abnormality information, and determine a second feedback result according to the analysis result; The transmission abnormality information includes: each vibration transmission abnormality parameter and each path transmission abnormality parameter; A storage logistics module, which is used to receive the real-time storage capacity of the transmission storage device module during the storage process, and determine a third feedback result according to the real-time storage capacity; The central control module is connected to the automatic barrel making equipment module, the conveying and storage device module, the first feedback module, the second feedback module and the warehousing and logistics module respectively, and is used to receive the first feedback result, the second feedback result and the third feedback result; perform a single analysis on each received feedback result to determine the abnormal situation of each module, determine a single adjustment measure for each module according to the single analysis result; and determine whether to start the overall shutdown inspection based on the single analysis result.

2. The fully automatic steel drum production system according to claim 1 is characterized in that: The automatic barrel making equipment module includes: a verification unit and a judgment unit; The verification unit is used to obtain the receiving quality and pre-processing quality of the initial raw material, and to verify whether the receiving quality and the pre-processing quality are qualified; The judgment unit is used to obtain the actual number of qualified items in the receiving quality and the pre-processing quality, and determine whether to start the formal production mode according to the actual number of qualified items.

3. The fully automatic steel drum production system according to claim 2 is characterized in that: The first feedback module includes: a first receiving unit, a type identification unit and a first determining unit; The first receiving unit is configured to periodically obtain the production abnormality information during the production process at a preset initial receiving interval; The first type identification unit is used to classify the production abnormality information to determine whether the abnormal type of each production abnormality parameter is an equipment failure parameter or a process abnormality parameter; The first determination unit is used to determine that the first feedback result is production parameter adjustment or equipment maintenance or equipment update according to the classification result of the first type identification unit.

4. The fully automatic steel drum production system according to claim 3 is characterized in that: The first receiving unit includes: a first acquisition subunit and a first abnormal subunit; The first acquisition subunit is used to acquire actual production information according to the initial receiving interval; The actual production information includes: actual production parameters of each temperature and actual production parameters of each pressure; The first abnormal sub-unit is used to determine whether each actual production parameter is a production abnormality parameter according to each actual production parameter and a preset production parameter standard variation range.

5. The fully automatic steel drum production system according to claim 4 is characterized in that: The first type of identification unit includes: a preliminary classification subunit, an identification subunit and a correction subunit; The preliminary classification subunit is used to preliminarily classify the production abnormality information according to the abnormality type to obtain parameters of each type; The identification subunit is used to identify the classification result of the preliminary classification subunit to obtain the actual number of types; The correction subunit is used to determine whether to start a receiving cycle correction mode according to the actual number of types; Among them, each type of parameter includes: the equipment failure parameter and the process abnormality parameter.

6. The fully automatic steel drum production system according to claim 5, characterized in that: The first type of identification unit also includes: a marking subunit; The marking subunit is used to perform feature recognition on the classification results of the preliminary classification subunit to extract key production features, and to perform feature marking on the classification results according to the key production features; The key production features include: occurrence timestamp and occurrence frequency.

7. The fully automatic steel drum production system according to claim 6, characterized in that: The first determination unit includes: a calculation subunit, a determination subunit and a first output subunit; The calculation subunit is used to calculate an initial production anomaly score according to the classification result of the preliminary classification subunit combined with the actual number of types, and to correct the initial production anomaly score according to the feature marking result of the marking subunit to obtain an actual production anomaly score; The determination subunit is used to determine the actual production abnormality level according to the actual production abnormality score; The first output subunit is used to determine the first feedback result according to the actual production abnormality level.

8. The fully automatic steel drum production system according to claim 7, characterized in that: The second feedback module includes: a second receiving unit, a second type identification unit, and a second determination unit; The second receiving unit is configured to periodically obtain the transmission abnormality information during the transmission process at the initial receiving interval; The second type identification unit is used to preliminarily classify each vibration transmission abnormality parameter and each path transmission abnormality parameter to obtain a conveyor belt fault parameter and a conveying abnormality parameter, and to perform feature identification on the preliminary classification result to obtain a conveying key feature, and to perform feature marking on the preliminary classification result according to the conveying key feature; The second determination unit is used to determine that the second feedback result is a conveyor belt maintenance or a transmission path inspection or a conveyor belt update according to the feature marking result of the second type identification unit; The key features of the transmission include: a fault location mark and a fault time mark.

9. The fully automatic steel drum production system according to claim 8, characterized in that: The storage logistics module includes: a storage subunit, a comparison subunit and a third determination subunit; The storage subunit is used to obtain the real-time storage quantity of each target semi-finished product; The comparison subunit is used to compare each real-time storage amount to determine whether it meets the overall production standard; The overall production standard is that the fluctuation difference between the real-time storage volume of each target semi-finished product is within the preset standard production fluctuation range; The third determining subunit is used to determine, according to the comparison result of the comparing subunit, that the third feedback result is to adjust the production power of the equipment or to adjust the production plan.

10. The fully automatic steel drum production system according to claim 9, characterized in that: The central control module includes: a production control unit, a transmission control unit, a storage control unit, an overall analysis unit and an instruction output unit; The production control unit is configured to receive the first feedback result and make corresponding production process adjustments according to the first feedback result; The transmission control unit is configured to receive the second feedback result and perform corresponding transmission adjustment according to the second feedback result; The storage control unit is used to receive the third feedback result and make corresponding production plan adjustments according to the third feedback result; The overall analysis unit is used to integrate the adjustment conditions of each control unit and analyze the integration result to determine whether to issue an alarm signal; The instruction output unit is used to receive the alarm signal and start the overall shutdown inspection according to the alarm signal.

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