Mold full life cycle management system based on internet of things

Abstract

The application discloses a mold full life cycle management system based on Internet of Things and relates to the technical field of mold management, and comprises the following steps: acquiring front and rear associated parameters and front and rear associated features of processes in each stage of the full life cycle of a mold; and dynamically maintaining equipment in the processes based on real-time parameters; the mold full life cycle management system is used to solve the problem that the existing mold full life cycle management method is one-sided in that the state of the mold is only predicted from the collection of single data, and when the process in which the mold is located changes and other variables affect the state of the mold, the relationship between the single data and the variables cannot be effectively judged, the state prediction of the mold is deviated, and the mold cannot be effectively managed based on the subsequent state of the mold.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of mold management, specifically a mold full life cycle management system based on the Internet of Things. BACKGROUND

[0002] Mold full life cycle management refers to the systematic and digital management of the entire process from design, manufacturing, use to scrap of the mold, in order to improve production efficiency, quality control and resource utilization, and the core goal is to realize mold state transparency through digital means, optimize quality, cost and delivery cycle, and reduce equipment idle and scrap risk.

[0003] The existing mold full life cycle management method based on the Internet of Things is usually aimed at single data collection, and on this basis, an optimization method is proposed, such as for wear data, by obtaining the wear amount at different times in the full life cycle, the health status of the mold is recorded, so as to realize the full life cycle management of the mold. Although this improved method can avoid accidents caused by the wear state of the mold in advance, it is one-sided to predict the state of the mold from single data collection, when the process of the mold changes, other variables affect the state of the mold, and the relationship between single data and variables cannot be effectively judged, resulting in deviation in the prediction of the state of the mold, and the problem of being unable to effectively manage the subsequent state of the mold, such as the patent application with publication number CN119888277A, which discloses a mold full life cycle digital management method. This scheme can see different wear amounts in the full life cycle of mold production and service through digital comparison, so as to find out the allowable difference value suitable for the wear change of the mold, record the health status of the mold, and avoid downtime accidents caused by mold failure in advance. The improvement of other mold full life cycle management methods based on the Internet of Things is usually in the aspect of database updating, and still cannot solve the problem that it is one-sided to predict the state of the mold from single data collection, when the process of the mold changes, other variables affect the state of the mold, and the relationship between single data and variables cannot be effectively judged, resulting in deviation in the prediction of the state of the mold, and the problem of being unable to effectively manage the subsequent state of the mold. Therefore, it is necessary to improve the existing mold full life cycle management method. SUMMARY

[0004] The present application aims to at least solve one of the technical problems in the prior art by proposing a mold full life cycle management system based on the Internet of Things, which is used to solve the problem that the existing mold full life cycle management method is relatively one-sided in predicting the state of the mold only from the collection of single data, and when the process changes, other variables affect the state of the mold, and the relationship between single data and variables cannot be effectively judged, resulting in deviation in predicting the state of the mold, and the mold cannot be effectively managed based on the subsequent state of the mold.

[0005] To achieve the above-mentioned purpose, the present application provides a mold full life cycle management system based on the Internet of Things, which comprises a process mold analysis module, a stage process correlation module and a cycle dynamic maintenance module.

[0006] The process mold analysis module is used to analyze the process of all stages in the full life cycle of the mold, and based on the analysis result, the front and rear associated processes of each stage are obtained, and the front and rear associated parameters of each process are obtained.

[0007] The stage process correlation module is used to analyze the front and rear associated parameters of each process, and based on the analysis result, the front and rear associated features of each process are obtained.

[0008] The cycle dynamic maintenance module is used to obtain the real-time parameters of the equipment in all stages in the full life cycle of the mold using the Internet of Things, and based on the real-time parameters and the front and rear associated features of each process, the equipment in the process is dynamically maintained.

[0009] Further, the process mold analysis module comprises a process mold analysis unit, which is configured with a process mold analysis strategy, and the process mold analysis strategy comprises:

[0010] All stages in the full life cycle of the mold are sequentially recorded as mold management stage MG1 to mold management stage MG n For any one mold management stage, all processes for processing the mold in the mold management stage are obtained, and based on the execution order of all processes in the mold management stage, all processes are sequentially recorded as mold process MY1 to mold process MY t ;

[0011] All mold processes of all mold management stages are obtained, and all mold processes are analyzed using a process parameter analysis method, and the front and rear associated parameters of each process are obtained.

[0012] Further, the process parameter analysis method comprises:

[0013] For any one mold process α: record all mold processes except the mold process α in the mold management stage β where the mold process α is located as to-be-associated processes; record the time when the mold process α is executed after the mold management stage β as T;

[0014] For any one to-be-associated process: when the to-be-associated process is executed after the mold management stage β starts, and the time is less than T, record the to-be-associated process as a front-associated process; when the to-be-associated process is executed after the mold management stage β starts, and the time is greater than or equal to T, record the to-be-associated process as a rear-associated process.

[0015] Further, the process parameter analysis method further comprises:

[0016] For any one to-be-associated process: when the to-be-associated process is a front-associated process, record the to-be-associated process as a directional process, and record the mold process α as a change direction process; when the to-be-associated process is a rear-associated process, record the to-be-associated process as a change direction process, and record the mold process as a directional process.

[0017] Record the parameters allowed to be collected by the Internet of Things in real time in the directional process as directional collection parameters, and record the parameters allowed to be collected by the Internet of Things in real time in the change direction process as change direction collection parameters; respectively acquire the use range of the directional collection parameters and the change direction collection parameters in the process, and record them as directional parameter range and change direction collection range respectively.

[0018] Further, the process parameter analysis method further comprises:

[0019] For any one directional collection parameter, based on the historical record data of the mold full life cycle, acquire all values of the directional collection parameter that have been selected to be used in the directional parameter range, and record them from small to large as directional allowed values DY1 to directional allowed value DY e ; based on AI, acquire the association logic of all change direction collection parameters and directional collection parameters respectively, based on the association logic, acquire the influence parameters of each change direction collection parameter and directional collection parameter after association, and record them as change direction influence parameters BY1 to change direction influence parameter BY p , where p is the number of change direction collection parameters;

[0020] For any one directional allowed value DY q and any one change direction influence parameter BY u : establish a plane rectangular coordinate system and record it as a directional analysis coordinate system, where the units of the X-axis and the Y-axis of the directional analysis coordinate system are the units of the change direction influence parameter BY u and the units of the change direction influence parameter BY u corresponding change direction collection parameter respectively, where u is a positive integer less than or equal to p and greater than or equal to 1.

[0021] Further, the process parameter analysis method further comprises:

[0022] Based on the Internet of Things, the directional analysis coordinate system is obtained under the standard condition, and the directional allowance DY is obtained q Invariable, and the variable direction influence parameter BY u When the variable direction collection parameter corresponding to the variable direction collection parameter increases, the variable direction influence parameter BY u And the variable direction influence parameter BY u The relationship curve of the corresponding variable direction collection parameter is recorded as the directional analysis curve.

[0023] Obtain the variable direction influence parameter BY u In the range allowed to be used in the process, and record it as the variable direction influence range; obtain the variable direction maintenance curve in the directional analysis curve, wherein the abscissa of all points in the variable direction maintenance curve is outside the variable direction influence range.

[0024] Further, the process parameter analysis method further comprises:

[0025] Obtain the variable direction maintenance curve of all variable direction influence parameters corresponding to each directional allowance and directional collection parameter; when any one directional allowance has any one corresponding variable direction maintenance curve, record the directional collection parameter as the front correlation parameter of the variable direction collection parameter, and record the variable direction collection parameter as the post correlation parameter of the directional collection parameter.

[0026] Obtain the front correlation parameter and the post correlation parameter corresponding to all to-be-associated processes of the mold process α, and obtain the front correlation parameter and the post correlation parameter of all mold processes based on the processing mode of the mold process α.

[0027] Further, the stage process correlation module comprises a stage process correlation unit, and the stage process correlation unit is configured with a stage process correlation strategy, and the stage process correlation strategy comprises:

[0028] For any one mold process α: for any one front correlation parameter of the mold process α: obtain the variable direction collection parameter corresponding to the front correlation parameter in the mold process α, and record the value of the ordinate at the intersection of the directional analysis curve corresponding to the variable direction collection parameter and the variable direction maintenance curve as the identification feature of the variable direction collection parameter, and record the directional allowance corresponding to the directional analysis curve as the identification feature of the front correlation parameter.

[0029] Obtain the identification features of the variable direction collection parameter and the identification features of the front correlation parameter corresponding to all front correlation parameters of the mold process α, and record them as the front correlation features of the mold process.

[0030] Further, the stage process correlation strategy further comprises:

[0031] For any one post-association parameter of the mold process α: obtain the directional acquisition parameter corresponding to the variable-direction maintenance curve in the mold process α, and record the directional allowable value corresponding to the variable-direction maintenance curve as the identification feature of the directional acquisition parameter, and record the value of the ordinate at the intersection of the variable-direction maintenance curve and the directional analysis curve as the identification feature of the post-association parameter;

[0032] Obtain the identification features of the directional acquisition parameters corresponding to all post-association parameters of the mold process α and the identification features of the post-association parameters, and record them as the post-association features of the mold process.

[0033] Further, the periodic dynamic maintenance module includes a periodic dynamic maintenance unit, which is configured with a periodic dynamic maintenance strategy, and the periodic dynamic maintenance strategy includes:

[0034] Using the Internet of Things to obtain all parameters in all stages of the mold full life cycle that are allowed to be collected by the Internet of Things in real time, and record each parameter as a real-time parameter; for any one mold process α: when any one pre-association parameter of the mold process α satisfies the real-time parameter of the variable-direction acquisition parameter corresponding to the pre-association parameter and the real-time parameter of the pre-association parameter, respectively equal to the identification feature of the variable-direction acquisition parameter corresponding to the pre-association parameter and the identification feature of the pre-association parameter, record the variable-direction influence parameter corresponding to the horizontal coordinate in the directional analysis curve corresponding to the variable-direction acquisition parameter as the to-be-maintained parameter, and maintain the equipment associated with the to-be-maintained parameter based on the Internet of Things;

[0035] When any one post-association parameter of the mold process α satisfies the real-time parameter of the directional acquisition parameter corresponding to the post-association parameter and the real-time parameter of the post-association parameter, respectively equal to the identification feature of the directional acquisition parameter corresponding to the post-association parameter and the identification feature of the post-association parameter, record the variable-direction influence parameter corresponding to the horizontal coordinate in the directional analysis curve corresponding to the directional acquisition parameter with the real-time parameter of the directional acquisition parameter as the directional allowable value as the to-be-maintained parameter, and maintain the equipment associated with the to-be-maintained parameter based on the Internet of Things.

[0036] The beneficial effects of the present application are as follows: firstly, the process of all stages in the whole life cycle of the mold is analyzed, and based on the analysis result, the preceding associated process and the subsequent associated process of the process in each stage are obtained, and the preceding associated parameter and the subsequent associated parameter of each process are obtained, which has the advantages that, by obtaining the preceding associated process and the subsequent associated process of the process in each stage, and further obtaining the preceding associated parameter and the subsequent associated parameter of each process, the parameters that are linked with the parameters in the process when the mold is produced to each process are obtained, so that when the data in each process is analyzed subsequently, the subsequent state of the mold is accurately predicted based on the preceding associated parameter and the subsequent associated parameter, thereby effective management is carried out;

[0037] The preceding associated parameter and the subsequent associated parameter of each process are also analyzed, and based on the analysis result, the preceding associated feature and the subsequent associated feature of each process are obtained; finally, the real-time parameters of the equipment in all stages in the whole life cycle of the mold are obtained by using the Internet of Things, and based on the real-time parameters and the preceding associated feature and the subsequent associated feature of each process, the equipment in the process is dynamically maintained, which has the advantages that, by obtaining the preceding associated feature and the subsequent associated feature of each process, the parameters that can be linked in each process and the corresponding threshold value are integrated, so that the subsequent state of the mold is more efficiently predicted in the execution process of each process after the real-time parameters are obtained. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 It is a principle block diagram of the system of the present application;

[0039] Figure 2 It is a schematic diagram of the directional analysis curve of the present application;

[0040] Figure 3 It is a schematic diagram of the directional analysis curve of the present application; DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0042] Please refer to Figure 1 The present application provides a mold whole life cycle management system based on the Internet of Things, which comprises a process mold analysis module, a stage process association module and a cycle dynamic maintenance module.

[0043] The process mold analysis module is used to analyze the process of all stages in the entire life cycle of the mold, and based on the analysis results, obtain the pre-process and post-process related processes of each stage, and obtain the pre-process related parameters and post-process related parameters of each process.

[0044] The process mold analysis module includes a process mold analysis unit, which is configured with process mold analysis strategies. These strategies include:

[0045] All stages in the entire life cycle of a mold are sequentially labeled as mold management stage MG1 to mold management stage MG2. n For any given mold management stage, obtain all processes that handle the mold within that stage, and based on the execution order of all processes in the mold management stage, sequentially label all processes as mold process MY1 to mold process MY2. t ;

[0046] In the specific implementation process, for example, in a data analysis, if the mold being analyzed is a stamping mold, then through process analysis, it can be found that the various stages in the stamping mold are the design and development stage, the manufacturing and processing stage, the mass service stage, and the maintenance stage. Therefore, the above four can be successively recorded as mold management stage MG1 to mold management stage MG4, that is, the value of n is 4.

[0047] For example, in the analysis process of this embodiment, the design and development stage of the above four stages is analyzed, and the processes included in the design and development stage are obtained through data acquisition: cutting edge structure design, mold clearance design and guide mechanism design; then the above three processes can be recorded as mold process MY1 to mold process MY3 in sequence, that is, the value of t is 3;

[0048] Obtain the mold processes for all stages of mold management, analyze all mold processes using process parameter analysis, and obtain the pre-process and post-process related parameters for each process.

[0049] The process parameter analysis method includes: For any mold process α: In the mold management stage β where mold process α is located, all mold processes other than mold process α are recorded as processes to be associated; The execution time of mold process α after the start of mold management stage β is recorded as T;

[0050] For any process to be associated: if the execution time of the process to be associated is less than T after the start of the mold management stage β, the process to be associated is recorded as the preceding associated process; if the execution time of the process to be associated is greater than or equal to T after the start of the mold management stage β, the process to be associated is recorded as the following associated process.

[0051] In the specific implementation process, if the to-be-associated process analyzed is blade edge structure design, by analyzing the design and development stage where the to-be-associated process is located, when the design and development stage starts, the start time of the mold gap design and the guide mechanism design is after the start time of the blade edge structure design, so the mold gap design and the guide mechanism design can be recorded as the post-associated process of the blade edge structure design.

[0052] The process parameter analysis method further includes: for any one to-be-associated process: when the to-be-associated process is a pre-associated process, recording the to-be-associated process as a directional process and recording the mold process a as a variable direction process; when the to-be-associated process is a post-associated process, recording the to-be-associated process as a variable direction process and recording the mold process as a directional process.

[0053] In the specific implementation process, by marking the directional process and the variable direction process, the purpose is to mark the process that has been determined and the process that may have variables. For example, for blade edge development and design and mold gap design, during the design and development stage, the start time of the mold gap design is after the start time of the blade edge structure design, so when the blade edge structure design starts, the parameters in the mold gap design will affect the mold obtained from the blade edge structure design as variables. Therefore, at this time, the blade edge structure design should be recorded as a directional process, that is, a process whose parameters have been determined, and the mold gap design should be recorded as a variable direction process, that is, a process whose parameters may change, and then subsequent analysis is performed. In summary, in the analysis process of the present embodiment, because the mold gap design and the guide mechanism design are recorded as the post-associated process of the blade edge structure design, during the analysis, the mold gap design and the guide mechanism design are variable direction processes, and the blade edge structure design is a directional process.

[0054] The parameters in the directional process that are allowed to be collected in real time by the Internet of Things are recorded as directional collection parameters, and the parameters in the variable direction process that are allowed to be collected in real time by the Internet of Things are recorded as variable direction collection parameters. The use range of the directional collection parameters and the variable direction collection parameters in the process is obtained respectively and recorded as a directional parameter range and a variable direction collection range.

[0055] The process parameter analysis method further includes: for any one directional collection parameter, based on the historical record data of the mold full life cycle, obtaining all the values of the directional collection parameter that have been selected for use in the directional parameter range, and recording them in order from small to large as directional allowed values DY1 to directional allowed values DY e ; based on AI, obtaining the association logic of all variable direction collection parameters and directional collection parameters, obtaining the influence parameters of each variable direction collection parameter and directional collection parameter after association based on the association logic, and recording them in order as variable direction influence parameters BY1 to variable direction influence parameters BY p , where p is the number of variable direction collection parameters.

[0056] In the implementation process, such as in the analysis process of the present embodiment, one directional collection parameter is the blade wear in the blade structure design, and one variable directional collection parameter is the stamping speed in the die gap design process. If the blade wear is large and the stamping speed is large, the wear rate of the blade will increase, so at this time the frequency of lubrication should be increased to reduce the wear rate of the blade. Therefore, through the above analysis, the influence parameter obtained by the correlation between the blade wear and the stamping speed is the lubrication frequency, so the lubrication frequency can be used as a variable directional influence parameter. For other variable directional collection parameters when the blade wear is used as a directional collection parameter, such as stamping angle, die gap, and stamping force, the corresponding variable directional influence parameters can be obtained by simulating the design and development stage through AI.

[0057] For any one directional allowable value DY q and any one variable directional influence parameter BY u : a plane rectangular coordinate system is established and is denoted as a directional analysis coordinate system, wherein the units of the X-axis and the Y-axis of the directional analysis coordinate system are the units of the variable directional influence parameter BY u and the units of the variable directional collection parameter corresponding to the variable directional influence parameter BY u , wherein u is a positive integer less than or equal to p and greater than or equal to 1.

[0058] The process parameter analysis method further comprises: based on the Internet of Things, obtaining the relationship curve between the variable directional influence parameter BY q and the variable directional collection parameter corresponding to the variable directional influence parameter BY u when the directional allowable value DY u is unchanged and the variable directional collection parameter corresponding to the variable directional influence parameter BY u increases within the variable directional collection range in the directional analysis coordinate system, and denoted as a directional analysis curve.

[0059] In the implementation process, the standard condition is that the variable directional influence parameter BY u corresponding to the variable directional collection parameter increases within the variable directional collection range, and other parameters and the environment of the process are within the specified range. For example, in the analysis of the present embodiment, the directional collection parameter and the variable directional collection parameter analyzed are the blade wear and the stamping speed, and one directional allowable value obtained is 0.006 mm. The variable directional collection range of the stamping speed is [20 times / min, 40 times / min]. Therefore, when the blade wear in the blade structure design is 0.006 mm, the relationship curve between the stamping speed and the lubrication frequency should be obtained when the stamping speed increases within [20 times / min, 40 times / min], that is, the directional analysis curve DF in Figure 2 .

[0060] acquiring the variable direction influence parameter BY u a variable direction influence range is allowed to be used in the process, and is denoted as the variable direction influence range; a variable direction maintenance curve in the directional analysis curve is acquired, wherein the abscissa of all points in the variable direction maintenance curve is outside the variable direction influence range;

[0061] In the specific implementation process, by acquiring the variable direction maintenance curve in the directional analysis curve, the judgment condition for whether the mold needs to be maintained based on the actual situation of the real-time parameter after the real-time parameter is acquired can be obtained, that is, when the value of the variable direction influence parameter is in the variable direction maintenance curve, the mold needs to be maintained based on the variable direction influence parameter; if the variable direction influence parameter is the lubrication frequency, and the value of the variable direction influence parameter is in the variable direction maintenance curve, it indicates that the lubrication frequency exceeds the allowed range to be used, which will affect the wear state of the blade edge, and therefore the worn blade edge should be replaced or manually lubricated.

[0062] The process parameter analysis method further includes: acquiring a variable direction maintenance curve of all variable direction influence parameters corresponding to each directional allowable value and the directional collection parameter; when there is any one corresponding variable direction maintenance curve for any one directional allowable value, the directional collection parameter is recorded as the front correlation parameter of the variable direction collection parameter, and the variable direction collection parameter is recorded as the rear correlation parameter of the directional collection parameter;

[0063] In the specific implementation process, only the directional collection parameter with the variable direction maintenance curve is used as the front correlation parameter, and the reason is that if all directional allowable values in the directional collection parameter do not have corresponding variable direction maintenance curves, it indicates that the directional collection parameter does not have a correlated parameter, or the directional collection parameter and its correlated parameter U will not be in the variable direction influence range during use, that is, even if the parameter U in the subsequent process is changed, it cannot affect the equipment or mold related to the parameter U, and therefore the directional collection parameter without the corresponding variable direction maintenance curve does not need to be marked;

[0064] The front correlation parameter and the rear correlation parameter corresponding to all to-be-correlated processes of the mold process a are acquired, and based on the processing mode of the mold process a, the front correlation parameter and the rear correlation parameter of all mold processes are acquired.

[0065] The stage process correlation module is used to analyze the front correlation parameter and the rear correlation parameter of each process, and based on the analysis result, the front correlation feature and the rear correlation feature of each process are acquired.

[0066] The stage process correlation module comprises a stage process correlation unit, and the stage process correlation unit is configured with a stage process correlation strategy.

[0067] In the analysis process of the embodiment, for the front correlation parameter "blade wear", the blade wear corresponds to the variable direction maintenance curve in the curve WE in Figure 3 , and the curve WE is a part of the directional analysis curve DF in Figure 2 , and Figure 3 The dashed curve in the curve WE is a curve in the directional analysis curve except the variable direction maintenance curve, so the ordinate 29 times / min and 33 times / min of the points ST1 and ST2 can be taken as the identification features of the variable direction acquisition parameter "punching speed", and the directional allowable value 0.006 mm of the blade wear can be taken as the identification features of the front correlation parameter;

[0068] The identification features of the variable direction acquisition parameters corresponding to all the front correlation parameters of the mold process α and the identification features of the front correlation parameters are obtained and recorded as the front correlation features of the mold process.

[0069] The stage process correlation strategy further comprises: for any one rear correlation parameter of the mold process α: obtaining the directional acquisition parameter of the variable direction maintenance curve corresponding to the rear correlation parameter in the mold process α, and recording the directional allowable value corresponding to the variable direction maintenance curve as the identification features of the directional acquisition parameter, and recording the value of the ordinate at the intersection of the variable direction maintenance curve and the directional analysis curve as the identification features of the rear correlation parameter;

[0070] The identification features of the directional acquisition parameters corresponding to all the rear correlation parameters of the mold process α and the identification features of the rear correlation parameters are obtained and recorded as the rear correlation features of the mold process.

[0071] The periodic dynamic maintenance module is used for obtaining real-time parameters of equipment in all stages in the whole life cycle of the mold using the Internet of Things, and performing dynamic maintenance on the equipment in the process based on the real-time parameters and the front correlation features and the rear correlation features of each process.

[0072] The periodic dynamic maintenance module comprises a periodic dynamic maintenance unit, and the periodic dynamic maintenance unit is configured with a periodic dynamic maintenance strategy, and the periodic dynamic maintenance strategy comprises:

[0073] The parameters allowed to be collected by the Internet of Things in the equipment in all stages in the whole life cycle of the mold are obtained, and are recorded as real-time parameters of each parameter; for any mold process a: when any one of the front-end associated parameters of the mold process a satisfies the real-time parameters of the corresponding variable collection parameters of the front-end associated parameters and the real-time parameters of the front-end associated parameters, respectively equal to the identification features of the corresponding variable collection parameters of the front-end associated parameters and the identification features of the front-end associated parameters, the variable influence parameter corresponding to the variable collection parameter in the directional analysis curve is recorded as the to-be-maintained parameter, and the equipment associated with the to-be-maintained parameter is maintained based on the Internet of Things;

[0074] In the specific implementation process, such as in a data analysis, in the design and development stage, the real-time parameters of the front-end associated parameter "blade wear" corresponding to the variable collection parameter "punching speed" and the real-time parameters of the blade wear are 29 times / min and 0.006 mm, respectively, and 29 times / min and 0.006 mm are equal to the identification features of the corresponding variable collection parameters of the blade wear and the identification features of the front-end associated parameters obtained in the above analysis, which indicates that the variable influence parameter "lubrication frequency" will be outside its corresponding variable influence range, so the lubrication frequency should be recorded as the to-be-maintained parameter, and the equipment associated with the lubrication frequency is maintained based on the Internet of Things, such as replacing the worn blade or manual lubrication;

[0075] When any one of the post-end associated parameters of the mold process a satisfies the real-time parameters of the corresponding directional collection parameters of the post-end associated parameters and the real-time parameters of the post-end associated parameters, respectively equal to the identification features of the corresponding directional collection parameters of the post-end associated parameters and the identification features of the post-end associated parameters, the variable influence parameter corresponding to the variable collection parameter in the directional analysis curve with the real-time parameter of the directional collection parameter as the directional allowed value is recorded as the to-be-maintained parameter, and the equipment associated with the to-be-maintained parameter is maintained based on the Internet of Things.

[0076] Working principle: first, analyze the processes of all stages in the whole life cycle of the mold, and obtain the front-end associated processes and post-end associated processes of the processes in each stage based on the analysis results, and obtain the front-end associated parameters and post-end associated parameters of each process; then analyze the front-end associated parameters and post-end associated parameters of each process, and obtain the front-end associated features and post-end associated features of each process based on the analysis results; finally, obtain the real-time parameters of the equipment in all stages in the whole life cycle of the mold using the Internet of Things, and based on the real-time parameters and the front-end associated features and post-end associated features of each process, the equipment in the process is dynamically maintained.

[0077] Through the description of the above embodiments, the embodiments of the present application can be provided as a method, a system or a computer program product. Based on such understanding, the above technical solutions can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in various embodiments or some parts of the embodiments.

[0078] In the embodiments provided by the present application, it should be understood that the disclosed system or method can be implemented in other manners. The embodiments described above are merely schematic, and should not be construed as limiting. For example, the division of the modules or the units is merely logical function division, and there can be other division manners in actual implementation. For example, a plurality of modules or units can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different modules can be indirect couplings or communication connections through some interfaces, and there can be electric, mechanical or other forms.

[0079] Finally, it should be noted that the above-mentioned embodiments are merely used to illustrate the technical solutions of the present application, rather than limit them; even if the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some technical features; and these modifications or replacements do not cause the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A mold lifecycle management system based on the Internet of Things, characterized in that, It includes a process mold analysis module, a stage process association module, and a cycle dynamic maintenance module; The process mold analysis module is used to analyze the process of all stages in the entire life cycle of the mold, and based on the analysis results, obtain the pre-process and post-process related processes of each stage, and obtain the pre-process related parameters and post-process related parameters of each process. The stage process association module is used to analyze the pre-association parameters and post-association parameters of each process, and obtain the pre-association features and post-association features of each process based on the analysis results; The periodic dynamic maintenance module is used to acquire real-time parameters of equipment in all stages of the mold's entire life cycle using the Internet of Things, and to perform dynamic maintenance on the equipment in the process based on the real-time parameters and the pre-process and post-process correlation features of each process. The stage process association module includes stage process association units, each configured with a stage process association strategy. These strategies include: For any mold process α: For any pre-correlation parameter of mold process α: Obtain the directional acquisition parameter corresponding to the directional maintenance curve in mold process α, and record the value of the ordinate at the intersection of the directional analysis curve and the directional maintenance curve corresponding to the directional acquisition parameter as the identification feature of the directional acquisition parameter, and record the directional allowable value corresponding to the directional analysis curve as the identification feature of the pre-correlation parameter. Obtain the identification features of the variable acquisition parameters corresponding to all the preceding associated parameters of the mold process α, as well as the identification features of the preceding associated parameters, and record them as the preceding associated features of the mold process; The process mold analysis module includes a process mold analysis unit, which is configured with process mold analysis strategies. These strategies include: All stages in the entire life cycle of a mold are sequentially labeled from MG1 to MG2. n For any given mold management stage, obtain all processes that handle the mold within that stage, and based on the execution order of all processes in the mold management stage, sequentially label all processes as mold process MY1 to mold process MY2. t ; Obtain the mold processes for all mold management stages, analyze all mold processes using process parameter analysis, and obtain the pre-process and post-process related parameters for each process. Process parameter analysis methods include: For any mold process α: in the mold management stage β where mold process α is located, all mold processes other than mold process α are recorded as processes to be associated; the time when mold process α is executed after the start of mold management stage β is recorded as T; For any process to be associated: if the execution time of the process to be associated is less than T after the start of the mold management stage β, the process to be associated is recorded as the preceding associated process; if the execution time of the process to be associated is greater than or equal to T after the start of the mold management stage β, the process to be associated is recorded as the following associated process. For any process to be associated: when the process to be associated is a preceding process, the process to be associated is recorded as an orienting process, and the mold process α is recorded as a changing process; when the process to be associated is a following process, the process to be associated is recorded as a changing process, and the mold process is recorded as an orienting process. In the directional process, parameters that can be collected in real time by the Internet of Things are denoted as directional acquisition parameters, and in the variable process, parameters that can be collected in real time by the Internet of Things are denoted as variable acquisition parameters; the application range of directional acquisition parameters and variable acquisition parameters in the process are obtained respectively, and denoted as directional parameter range and variable acquisition range respectively. For any given orientation acquisition parameter, based on historical data throughout the mold's entire lifecycle, obtain all selected and used values ​​of the orientation acquisition parameter within its range, and record them in ascending order as the orientation allowable value DY1 to the orientation allowable value DY. e Based on AI, the correlation logic of all directional acquisition parameters and directional acquisition parameters is obtained. Based on the correlation logic, the influence parameters after the correlation between each directional acquisition parameter and directional acquisition parameter is obtained, and they are sequentially denoted as directional influence parameter BY1 to directional influence parameter BY. p Where p is the number of directional acquisition parameters; For any directional allowable value DY q And any one of the directional influence parameters BY u Establish a Cartesian coordinate system, denoted as the orientation analysis coordinate system, where the units of the X-axis and Y-axis of the orientation analysis coordinate system are respectively the units of the directional influence parameter BY. u The unit and the direction-changing influence parameter BY u The unit of the corresponding directional acquisition parameter, where u is a positive integer less than or equal to p and greater than or equal to 1; Based on the Internet of Things, the allowable orientation value DY under standard conditions is obtained within the orientation analysis coordinate system. q The parameter BY remains unchanged and has a directional influence. u When the corresponding directional acquisition parameter increases within the directional acquisition range, the directional influence parameter BY... u With the change of direction influence parameter BY u The corresponding relationship curve of the variable acquisition parameters is recorded as the directional analysis curve; Obtain the directional influence parameters BY u The range that is allowed to be used in the process is denoted as the change of influence range; the change of maintenance curve in the directional analysis curve is obtained, wherein the abscissa of all points in the change of maintenance curve is outside the change of influence range; Obtain the directional maintenance curves of all directional influence parameters corresponding to each directional allowable value and directional acquisition parameter; when any directional allowable value has any corresponding directional maintenance curve, record the directional acquisition parameter as the pre-correlation parameter of the directional acquisition parameter and record the directional acquisition parameter as the post-correlation parameter of the directional acquisition parameter. Obtain the pre-association parameters and post-association parameters corresponding to mold process α and all processes to be associated. Based on the processing method of mold process α, obtain the pre-association parameters and post-association parameters of all mold processes.

2. The IoT-based mold lifecycle management system according to claim 1, characterized in that, The stage-based process association strategy also includes: For any post-correlation parameter of mold process α: obtain the directional acquisition parameter of the mold process α corresponding to the post-correlation parameter and the directional allowable value corresponding to the directional maintenance curve, and record the value of the ordinate at the intersection of the directional maintenance curve and the directional analysis curve as the identification feature of the post-correlation parameter. Obtain the identification features of the directional acquisition parameters and the identification features of the post-correlation parameters corresponding to all post-correlation parameters of mold process α, and record them as the post-correlation features of mold process.

3. The IoT-based mold lifecycle management system according to claim 2, characterized in that, The periodic dynamic maintenance module includes a periodic dynamic maintenance unit, which is configured with a periodic dynamic maintenance strategy. The periodic dynamic maintenance strategy includes: The Internet of Things (IoT) is used to acquire parameters that can be collected in real time within the equipment during all stages of the mold's entire lifecycle, and these parameters are recorded as real-time parameters for each parameter. For any mold process α: when any pre-associated parameter of mold process α satisfies that the real-time parameter of the variable acquisition parameter corresponding to the pre-associated parameter and the real-time parameter of the pre-associated parameter are equal to the identification features of the variable acquisition parameter corresponding to the pre-associated parameter and the identification features of the pre-associated parameter, respectively, the variable influence parameter corresponding to the horizontal axis in the directional analysis curve corresponding to the variable acquisition parameter is recorded as the parameter to be maintained, and the equipment associated with the parameter to be maintained is maintained based on the IoT. When any post-correlation parameter of the mold process α satisfies that the real-time parameter of the directional acquisition parameter corresponding to the post-correlation parameter and the real-time parameter of the post-correlation parameter are equal to the identification features of the directional acquisition parameter corresponding to the post-correlation parameter and the identification features of the post-correlation parameter, respectively, the directional influence parameter corresponding to the horizontal axis in the directional analysis curve with the real-time parameter of the directional acquisition parameter as the directional allowable value is recorded as the parameter to be maintained, and the equipment associated with the parameter to be maintained is maintained based on the Internet of Things.

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