Copper wire lamp production process optimization method and equipment

Abstract

The present application is applicable to the technical field of production process optimization, and in particular to a method and device for optimizing the production process of copper wire lamps, the method comprising: obtaining a parameter adjustment record that matches the type of copper wire lamp being produced; receiving a parameter adjustment request for the copper wire lamp; determining a first probability that the parameter corresponding to the parameter adjustment request is adjusted based on the parameter adjustment record; determining first adjustment information based on the parameter adjustment record and the parameter adjustment request; determining a second probability that the parameter adjustment request is valid based on the first adjustment information and the first probability; and adjusting the parameters of the production equipment of the current production link according to the parameter adjustment request when the parameter adjustment request is determined to be valid based on the parameter adjustment record and the second probability. The method for optimizing the production process of copper wire lamps provided in the embodiment of the present application can solve the problem that the adjustment of the parameters of the copper wire lamp production equipment is not accurate and flexible enough in the optimization of the production process of copper wire lamps.

Description

Technical Field

[0001] The present application belongs to the technical field of production process optimization, and in particular, relates to a method and equipment for optimizing the production process of copper wire lamps. Background Art

[0002] Copper wire lamp production process optimization refers to the systematic improvement and upgrading of the original copper wire lamp production process, including optimizing raw material selection, improving production processes, introducing advanced equipment and technology, strengthening personnel training and management, and improving quality control systems.

[0003] In the prior art, the production process optimization of copper wire lamps mainly relies on the operator's experience and judgment, and the adjustment of the parameters of the copper wire lamp production equipment lacks systematicity and accuracy, resulting in low production efficiency. Different types of copper wire lamps require different production equipment parameters, but the existing production process lacks flexibility and adaptability, and it is difficult to meet the production needs of different types of copper wire lamps, resulting in waste and unstable quality in the production process. Therefore, the current optimization of the copper wire lamp production process has the problem of insufficient accuracy and flexibility in adjusting the parameters of the copper wire lamp production equipment. Summary of the invention

[0004] The embodiments of the present application provide a method and device for optimizing the production process of a copper wire lamp, which can solve the problem of inaccurate and inflexible adjustment of parameters of the copper wire lamp production equipment in the optimization of the production process of a copper wire lamp.

[0005] In a first aspect, an embodiment of the present application provides a method for optimizing a copper wire lamp production process, comprising:

[0006] Obtaining a parameter adjustment record that matches the type of copper wire lamp being produced; wherein the parameter adjustment record includes the time of parameter adjustment, the production link corresponding to the parameter adjustment, the parameters before and after the adjustment, and the yield before and after the adjustment, the parameters include at least one of temperature, time and speed, and the production link is wire drawing, annealing, winding or baking;

[0007] Receive a parameter adjustment request for the copper wire lamp; wherein the parameter adjustment request is a parameter adjustment information request for production equipment in a current production link;

[0008] Determining, based on the parameter adjustment record, a first probability that a parameter corresponding to the parameter adjustment request is adjusted;

[0009] Determine first adjustment information based on the parameter adjustment record and the parameter adjustment request; wherein the first adjustment information includes at least one of range adjustment information and associated adjustment information, the range adjustment information is used to reflect the adjustment range of the parameter of the parameter adjustment request, and the associated adjustment information is used to reflect the parameter in the parameter adjustment record that has an associated relationship with the parameter of the parameter adjustment request;

[0010] determining a second probability that the parameter adjustment request is valid based on the first adjustment information and the first probability;

[0011] When it is determined that the parameter adjustment request is valid based on the parameter adjustment record and the second probability, the parameters of the production equipment in the current production link are adjusted according to the parameter adjustment request.

[0012] The above technical solutions in the embodiments of the present application have at least the following technical effects:

[0013] The copper wire lamp production process optimization method provided in the embodiment of the present application obtains a parameter adjustment record that matches the type of copper wire lamp being produced; receives a parameter adjustment request for the copper wire lamp; determines a first probability that the parameter corresponding to the parameter adjustment request is adjusted based on the parameter adjustment record; determines first adjustment information based on the parameter adjustment record and the parameter adjustment request; determines a second probability that the parameter adjustment request is valid based on the first adjustment information and the first probability; and when the parameter adjustment request is determined to be valid based on the parameter adjustment record and the second probability, adjusts the parameters of the production equipment in the current production link according to the parameter adjustment request. Therefore, the copper wire lamp production process optimization method provided in the embodiment of the present application can achieve precise control and optimization of parameters and improve production efficiency by determining that the parameter adjustment request for the copper wire lamp is valid based on the parameter adjustment record and the second probability, and accurately adjusting the parameters of the production equipment; and flexibly adjusting the parameters of the production equipment according to the needs of different types of copper wire lamps to improve product quality.

[0014] In a possible implementation manner of the first aspect, determining, based on the parameter adjustment record, a first probability that a parameter corresponding to the parameter adjustment request is adjusted includes:

[0015] Determine the probability distribution of each parameter being adjusted in each production link according to the parameter adjustment record;

[0016] Determining a third probability that the parameter corresponding to the parameter adjustment request is adjusted in the current production link according to the probability distribution of each parameter being adjusted in each production link;

[0017] Determining, according to the parameter adjustment record, a fourth probability that the parameter corresponding to the parameter adjustment request is adjusted in all production links;

[0018] The first probability is obtained by taking a weighted average of the third probability and the fourth probability.

[0019] In a possible implementation manner of the first aspect, the determining the first adjustment information based on the parameter adjustment record and the parameter adjustment request includes:

[0020] Determine the effective adjustment record of the current production link based on the parameter adjustment record; wherein the effective adjustment record refers to a record in which the yield after the parameter adjustment is higher than the yield before the adjustment in the parameter adjustment record;

[0021] determining the range adjustment information based on the valid adjustment record;

[0022] Determine a frequent item set of parameter adjustment based on the parameter adjustment record; wherein the frequent item set is a set of parameter combinations that appear more than a threshold number of times in the parameter adjustment record, and the parameter combination includes different combinations of parameters of each production link of each batch of copper wire lamps in the parameter adjustment record;

[0023] Determining association rules based on the frequent item sets; wherein the association rules are used to reflect the adjustment order or dependency relationship between different parameters;

[0024] If the parameter of the parameter adjustment request does not have the association rule, determining the range adjustment information as the first adjustment information;

[0025] If the parameter of the parameter adjustment request has the association rule, the association adjustment information is determined based on the association rule.

[0026] In a possible implementation manner of the first aspect, determining a valid adjustment record of a current production link based on the parameter adjustment record includes:

[0027] Determine the yield of each parameter before and after adjustment of the current production link in the parameter adjustment record based on the parameter adjustment record;

[0028] Compare the yield of each parameter in the current production link after adjustment in the parameter adjustment record with the yield before adjustment;

[0029] If the yield rate of the parameter adjustment in the current production link after the adjustment is less than or equal to the yield rate before the adjustment in the parameter adjustment record, the corresponding parameter adjustment record is determined as an invalid adjustment record;

[0030] If the yield rate of the parameters of the current production link after adjustment in the parameter adjustment record is greater than the yield rate before adjustment, the corresponding parameter adjustment record is determined as the valid adjustment record.

[0031] In a possible implementation manner of the first aspect, determining the range adjustment information based on the valid adjustment record includes:

[0032] Compare the adjusted parameters of the current production link in the effective adjustment record with the corresponding preset parameters of the current production link of the copper wire lamp to obtain the adjustment direction and adjustment range of each parameter of the current production link;

[0033] The range adjustment information is determined based on the adjustment direction and adjustment range of each parameter in the current production link.

[0034] In a possible implementation manner of the first aspect, determining, based on the first adjustment information and the first probability, a second probability that the parameter adjustment request is valid includes:

[0035] Obtaining a degree of deviation between the range adjustment information and the parameter adjustment request based on the first adjustment information;

[0036] Determining whether the parameter of the parameter adjustment request has the association rule with the parameter of the parameter adjustment record of the copper wire lamp based on the first adjustment information;

[0037] If the parameter of the parameter adjustment request and the parameter of the parameter adjustment record of the copper wire lamp have the association rule, adjusting the first probability based on the deviation and the association rule to obtain the second probability;

[0038] If the parameter of the parameter adjustment request does not have the association rule with the parameter of the parameter adjustment record of the copper wire lamp, the first probability is adjusted based on the deviation to obtain the second probability.

[0039] In a possible implementation manner of the first aspect, after obtaining the deviation between the range adjustment information and the parameter adjustment request based on the first adjustment information, the method further includes:

[0040] If the deviation exceeds the deviation threshold, a secondary confirmation message is sent;

[0041] Whether the parameter adjustment request is valid is determined according to the return value of the secondary confirmation information.

[0042] In a possible implementation manner of the first aspect, when it is determined that the parameter adjustment request is valid based on the parameter adjustment record and the second probability, before adjusting the parameters of the production equipment of the current production link according to the parameter adjustment request, the method further includes:

[0043] Determine, based on the parameter adjustment record, a first time interval and a first similarity between the parameter adjustment request and the valid adjustment record having the shortest time interval with the parameter adjustment request;

[0044] determining, based on the parameter adjustment record, a second time interval and a second similarity between the parameter adjustment request and the invalid adjustment record having the shortest time interval with the parameter adjustment request;

[0045] Obtaining a time interval weight according to the first time interval and the second time interval;

[0046] Obtaining a similarity weight according to the first similarity and the second similarity;

[0047] Determine a comprehensive evaluation value based on the second probability, the time interval weight and the similarity weight;

[0048] If the comprehensive evaluation value exceeds the evaluation threshold, it is determined that the parameter adjustment request is valid.

[0049] In a possible implementation manner of the first aspect, obtaining a time interval weight according to the first time interval and the second time interval includes:

[0050] Obtaining an adjustment factor according to the first time interval and the second time interval;

[0051] The initial weight of the time interval is adjusted according to the adjustment factor to obtain the time interval weight.

[0052] In a possible implementation manner of the first aspect, obtaining a similarity weight according to the first similarity and the second similarity includes:

[0053] Determining whether the first similarity and the second similarity exceed a similarity threshold;

[0054] If both the first similarity and the second similarity exceed the similarity threshold or do not exceed the similarity threshold, determining the initial similarity weight as the similarity weight;

[0055] If the first similarity exceeds the similarity threshold and the second similarity does not exceed the similarity threshold, increasing the initial similarity weight and obtaining the similarity weight;

[0056] If the first similarity does not exceed the similarity threshold and the second similarity exceeds the similarity threshold, the initial similarity weight is reduced to obtain the similarity weight.

[0057] In a second aspect, an embodiment of the present application provides a copper wire lamp production process optimization device, comprising:

[0058] An acquisition module is used to acquire a parameter adjustment record that matches the type of copper wire lamp being produced; wherein the parameter adjustment record includes the time of parameter adjustment, the production link corresponding to the parameter adjustment, the parameters before and after the adjustment, and the yield before and after the adjustment, the parameters include at least one of temperature, time and speed, and the production link is wire drawing, annealing, winding or baking;

[0059] A receiving module, used for receiving a parameter adjustment request of the copper wire lamp; wherein the parameter adjustment request is used for requesting adjustment of parameters of production equipment in the current production link;

[0060] A first probability module, configured to determine, based on the parameter adjustment record, a first probability that a parameter corresponding to the parameter adjustment request is adjusted;

[0061] a first adjustment information module, configured to determine first adjustment information based on the parameter adjustment record and the parameter adjustment request; wherein the first adjustment information includes at least one of range adjustment information and associated adjustment information, the range adjustment information is used to reflect the adjustment range of the parameter of the parameter adjustment request, and the associated adjustment information is used to reflect the parameter in the parameter adjustment record that has an associated relationship with the parameter of the parameter adjustment request;

[0062] a second probability module, configured to determine a second probability that the parameter adjustment request is valid based on the first adjustment information and the first probability;

[0063] An adjustment module is used to adjust the parameters of the production equipment in the current production link according to the parameter adjustment request when it is determined that the parameter adjustment request is valid based on the parameter adjustment record and the second probability.

[0064] In a third aspect, an embodiment of the present application provides a copper wire lamp production process optimization device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the method described in any one of the first aspects above.

[0065] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of the first aspects above is implemented.

[0066] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on a copper wire lamp production process optimization device, the copper wire lamp production process optimization device executes any one of the methods in the first aspect above.

[0067] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0069] Figure 1 It is a schematic diagram of a process for optimizing a copper wire lamp production process provided by an embodiment of the present application;

[0070] Figure 2 It is a schematic diagram of the implementation process of step S300 in the copper wire lamp production process optimization method provided in one embodiment of the present application;

[0071] Figure 3 It is a schematic diagram of the implementation process of steps S400, S410 and S420 in the copper wire lamp production process optimization method provided in one embodiment of the present application;

[0072] Figure 4 It is a schematic diagram of the implementation process of steps S500 and S510 in the copper wire lamp production process optimization method provided in one embodiment of the present application;

[0073] Figure 5 It is a schematic diagram of the implementation process of step S600 in the copper wire lamp production process optimization method provided in one embodiment of the present application;

[0074] Figure 6 It is a schematic diagram of the implementation process of step S603 in the copper wire lamp production process optimization method provided in one embodiment of the present application;

[0075] Figure 7 It is a schematic diagram of the implementation process of step S604 in the copper wire lamp production process optimization method provided in one embodiment of the present application;

[0076] Figure 8 It is a structural schematic diagram of a copper wire lamp production process optimization device provided in an embodiment of the present application;

[0077] Fig. 9 It is a structural schematic diagram of the copper wire lamp production process optimization equipment provided in the embodiment of the present application. DETAILED DESCRIPTION

[0078] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0079] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0080] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0081] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0082] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0083] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0084] In the related art, the production process optimization of copper wire lamps mainly relies on the operator's experience and judgment, and the adjustment of the parameters of the copper wire lamp production equipment lacks systematicity and accuracy, resulting in low production efficiency. Different types of copper wire lamps require different production equipment parameters, but the existing production process lacks flexibility and adaptability, and it is difficult to meet the production needs of different types of copper wire lamps, resulting in waste and unstable quality in the production process. Therefore, the current optimization of the copper wire lamp production process has the problem that the parameter adjustment of the production equipment is not accurate and flexible enough.

[0085] To solve the above problems, the embodiments of the present application provide a method and device for optimizing the production process of copper wire lamps. In the method, a parameter adjustment record matching the type of copper wire lamp being produced is obtained; a parameter adjustment request for the copper wire lamp is received; a first probability that the parameter corresponding to the parameter adjustment request is adjusted is determined based on the parameter adjustment record; a first adjustment information is determined based on the parameter adjustment record and the parameter adjustment request; a second probability that the parameter adjustment request is valid is determined based on the first adjustment information and the first probability; and when the parameter adjustment request is determined to be valid based on the parameter adjustment record and the second probability, the parameters of the production equipment in the current production link are adjusted according to the parameter adjustment request. Therefore, the method for optimizing the production process of copper wire lamps provided in the embodiments of the present application can achieve precise control and optimization of the parameters and improve production efficiency by determining that the parameter adjustment request for the copper wire lamp is valid based on the parameter adjustment record and the second probability, and accurately adjusting the parameters of the production equipment; and flexibly adjusting the parameters of the production equipment according to the needs of different types of copper wire lamps to improve product quality.

[0086] The copper wire lamp production process optimization method provided in the embodiment of the present application can be applied to the copper wire lamp production process optimization equipment. At this time, the copper wire lamp production process optimization equipment is the executor of the copper wire lamp production process optimization method provided in the embodiment of the present application. The embodiment of the present application does not impose any restrictions on the specific type of the copper wire lamp production process optimization equipment.

[0087] For example, the copper wire lamp production process optimization device can be a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a mobile phone, a tablet computer, a wearable device, a vehicle-mounted device, an augmented reality (AR) / virtual reality (VR) device, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), a desktop computer, a smart screen, a smart TV, a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a vehicle networking terminal, a computer, a laptop computer, a handheld communication device, a handheld computing device, a satellite wireless device, etc., but not limited to these.

[0088] In order to better understand the copper wire lamp production process optimization method provided in the embodiment of the present application, the specific implementation process of the copper wire lamp production process optimization method provided in the embodiment of the present application is exemplarily introduced below.

[0089] Figure 1 A schematic flow chart of a copper wire lamp production process optimization method provided in an embodiment of the present application is shown, and the copper wire lamp production process optimization method includes:

[0090] S100, obtaining a parameter adjustment record that matches the type of copper wire lamp being produced. The parameter adjustment record includes the time of parameter adjustment, the production link corresponding to the parameter adjustment, the parameters before and after the adjustment, and the yield before and after the adjustment. The parameters include at least one of temperature, time, and speed. The production link is wire drawing, annealing, winding, or baking.

[0091] It can be understood that the parameter adjustment record is the historical parameter adjustment data of the copper wire lamp of the same type as the copper wire lamp being produced.

[0092] For example, the type of copper wire lamp being produced may be determined by a production plan or a production instruction.

[0093] Exemplarily, a database containing parameter adjustment records can be used, the type of copper wire lamp being produced can be used as a screening condition, and the parameter adjustment records matching the type of copper wire lamp being produced can be retrieved from the database using SQL query.

[0094] S200, receiving a parameter adjustment request of a copper wire lamp, wherein the parameter adjustment request is used to request adjustment of parameters of production equipment in the current production link.

[0095] Exemplarily, parameter adjustment requests may originate from a variety of devices and systems. For example, a copper wire lamp production process optimization device may receive parameter adjustment requests from a terminal (eg, a mobile phone) or a production device in the current production link.

[0096] Exemplarily, the parameter adjustment request may be manually input or manually triggered, but is not limited thereto.

[0097] S300: Determine, based on the parameter adjustment record, a first probability that a parameter corresponding to the parameter adjustment request is adjusted.

[0098] Exemplarily, the probability that the parameter corresponding to the parameter adjustment request is adjusted in the current production link and the probability that the parameter corresponding to the parameter adjustment request is adjusted in all production links can be determined based on the parameter adjustment record, and the obtained probabilities are weighted averaged to obtain the first probability.

[0099] In one possible implementation, see Figure 2 S300, determining a first probability that a parameter corresponding to the parameter adjustment request is adjusted based on the parameter adjustment record, including:

[0100] S310, determining the probability distribution of each parameter being adjusted in each production link according to the parameter adjustment record.

[0101] For example, the number of times each parameter is adjusted in each production link can be counted according to the parameter adjustment record, and the number of times each parameter is adjusted in each production link is divided by the total number of times all parameters are adjusted in the production link to obtain the probability distribution of each parameter being adjusted in each production link. For example, the probability distribution of each parameter being adjusted in each production link is shown in Table 1 below.

[0102]

[0103] Table 1

[0104] S320: Determine a third probability that a parameter corresponding to the parameter adjustment request is adjusted in the current production link according to the probability distribution of each parameter being adjusted in each production link.

[0105] Exemplarily, the probability of each parameter being adjusted in the current production link, ie, the third probability, can be found based on the probability distribution of each parameter being adjusted in each production link.

[0106] S330: Determine, according to the parameter adjustment record, a fourth probability that a parameter corresponding to the parameter adjustment request is adjusted in all production links.

[0107] Exemplarily, the fourth probability may be obtained by dividing the total number of times each parameter is adjusted in all production links by the total number of times all parameters are adjusted in all production links according to the parameter adjustment records.

[0108] S340: Take a weighted average of the third probability and the fourth probability to obtain a first probability.

[0109] Exemplarily, a weighted average method may be used to obtain a first probability that a parameter corresponding to a parameter adjustment request is adjusted based on the third probability and the fourth probability. Among them, P(Y j |X) is the third probability, P(Y j ) is the fourth probability, and j represents the index of the parameter.

[0110] Through the above steps S310 to S340, based on the parameter adjustment record, combined with the current production link and the parameters to be adjusted, the first probability of the parameter adjustment request corresponding to the parameter being adjusted can be calculated, which is helpful to realize the intelligent and automatic parameter adjustment and improve production efficiency and product quality. It takes into account both the specific situation of the current production link and the historical trend of the entire production process, which is conducive to improving the accuracy and adaptability of subsequent predictions and decisions.

[0111] S400, determining first adjustment information based on the parameter adjustment record and the parameter adjustment request, wherein the first adjustment information includes at least one of range adjustment information and associated adjustment information, the range adjustment information is used to reflect the adjustment range of the parameter of the parameter adjustment request, and the associated adjustment information is used to reflect the parameter in the parameter adjustment record that is associated with the parameter of the parameter adjustment request.

[0112] Exemplarily, effective adjustment records in which the yield after parameter adjustment is higher than the yield before adjustment and association rules between different parameters can be determined based on parameter adjustment records, range adjustment information can be determined based on effective adjustment records, and association adjustment information can be determined based on parameter adjustment requests and association rules.

[0113] In one possible implementation, see Figure 3 S400, determining first adjustment information based on the parameter adjustment record and the parameter adjustment request, including:

[0114] S410, determining effective adjustment records of the current production link based on the parameter adjustment records, wherein the effective adjustment records refer to the records in which the yield after the parameter adjustment is higher than the yield before the adjustment.

[0115] Exemplarily, based on the parameter adjustment record, the yields before and after the adjustment of each parameter in the current production link in the parameter adjustment record can be compared to obtain an effective adjustment record of the current production link.

[0116] Optionally, see Figure 3 , S410, determining the effective adjustment record of the current production link based on the parameter adjustment record, including:

[0117] S411, determining the yield of each parameter before and after adjustment of the current production link in the parameter adjustment record based on the parameter adjustment record.

[0118] Exemplarily, the yields of various parameters before and after the adjustment of the current production link are extracted from the parameter adjustment record. For example, the yields of various parameters before and after the adjustment of the current production link are shown in Table 2 below.

[0119] Adjust batch Parameter name Yield before adjustment Adjusted yield 1 Temperature (T) 90％ 92％ 2 Time(S) 88％ 87％ 3 Speed ​​(V) 91％ 91％ … … … …

[0120] Table 2

[0121] S412, comparing the yield of each parameter of the current production link after adjustment in the parameter adjustment record with the yield before adjustment.

[0122] For example, for each adjustment of each parameter of the current production link in the parameter adjustment record, the yield after adjustment can be compared with the yield before adjustment. For example, the yields before and after adjustment of each parameter of the current production link are shown in Table 2 above, and the yields after adjustment of each parameter of the current production link in the parameter adjustment record can be compared with the yields before adjustment to obtain Table 3 below.

[0123] Adjust batch Parameter name Yield before adjustment Adjusted yield Poor yield 1 Temperature (T) 90％ 92％ 2％ 2 Time(S) 88％ 87％ -1％ 3 Speed ​​(V) 91％ 91％ 0％ … … … … …

[0124] Table 3

[0125] S413: If the yield rate of the parameters of the current production link after adjustment in the parameter adjustment record is less than or equal to the yield rate before adjustment, the corresponding parameter adjustment record is determined as an invalid adjustment record.

[0126] For example, if the yield rate of the parameters of the current production link after adjustment in the parameter adjustment record is less than or equal to the yield rate before adjustment, then the corresponding parameter adjustment record is an invalid adjustment record. For example, the yield rate of each parameter of the current production link after adjustment in the parameter adjustment record is compared with the yield rate before adjustment to obtain the above Table 3, and the invalid adjustment record with a negative yield difference or 0 can be obtained as shown in the following Table 4.

[0127]

[0128] Table 4

[0129] S414: If the yield rate of the current production link after parameter adjustment in the parameter adjustment record is greater than the yield rate before adjustment, the corresponding parameter adjustment record is determined as a valid adjustment record.

[0130] For example, if the yield rate of the parameters of the current production link after adjustment in the parameter adjustment record is greater than the yield rate before adjustment, then the corresponding parameter adjustment record is a valid adjustment record. For example, by comparing the yield rate of each parameter of the current production link after adjustment with the yield rate before adjustment in the parameter adjustment record to obtain the above Table 3, the valid adjustment record with a positive yield difference can be obtained as shown in the following Table 5.

[0131]

[0132] Table 5

[0133] Through the above steps S411 to S414, parameter adjustment records that have a positive impact on the production process (i.e., effective adjustment records) can be effectively screened out, and adjustment records that do not bring positive effects or may even have negative effects (i.e., invalid adjustment records) can be excluded, which is beneficial to improving production efficiency and product quality, and provides important data support for the subsequent determination of range adjustment information and related adjustment information.

[0134] S420: Determine range adjustment information based on the valid adjustment record.

[0135] It can be understood that the range adjustment information is to compare the adjusted parameters of the current production link in the effective adjustment record with the preset parameters of the current production link of the corresponding copper wire lamp to obtain the maximum number corresponding to the increase and decrease of each parameter in the current production link.

[0136] Exemplarily, the adjusted parameters of the current production link in the effective adjustment record may be compared with the preset parameters of the current production link of the corresponding copper wire lamp to obtain the range adjustment information.

[0137] Optionally, see Figure 3 , S420, determining range adjustment information based on the valid adjustment record, including:

[0138] S421, comparing the adjusted parameters of the current production link in the effective adjustment record with the preset parameters of the current production link of the corresponding copper wire lamp to obtain the adjustment direction and adjustment range of each parameter of the current production link.

[0139] It can be understood that the adjustment direction is to compare the adjusted parameters of the current production link in the effective adjustment record with the preset parameters of the current production link of the corresponding copper wire lamp to obtain whether the changes of various parameters in the current production link are increased or decreased. The adjustment range refers to the specific values ​​that need to be adjusted for each parameter in the current production link.

[0140] Exemplarily, the adjusted parameters of the current production link in the effective adjustment record can be subtracted from the preset parameters of the current production link of the corresponding copper wire lamp to obtain the adjustment direction and adjustment range of each parameter of the current production link as shown in Table 6 below.

[0141]

[0142] S422, determining range adjustment information based on the adjustment direction and adjustment range of each parameter in the current production link.

[0143] For example, the maximum value of each parameter in the current production link in each adjustment direction can be determined according to the adjustment direction and adjustment range of each parameter in the current production link to obtain the range adjustment information.

[0144]

[0145] Through the above steps S421 to S422, the differences between various parameters of the current production link and the preset standards can be accurately identified, and the specific adjustment direction and adjustment range can be determined, thereby generating range adjustment information, which can provide clear guidance for the actual operation of the production line, reduce the operation difficulty and error rate, and help ensure the stable operation of the production line and improve product quality and production efficiency.

[0146] S430, determining frequent item sets of parameter adjustment based on the parameter adjustment record, wherein the frequent item set is a collection of parameter combinations that appear more than a threshold number of times in the parameter adjustment record, and the parameter combination includes different combinations of parameters of each production link of each batch of copper wire lamps in the parameter adjustment record.

[0147] It can be understood that the number threshold is that the number of occurrences of the parameter combination in the parameter adjustment record does not exceed a preset specified value. The preset specified value can be set by ordinary technicians in this field according to actual needs and is not limited here.

[0148] For example, a reasonable number threshold can be determined based on historical data and industry standards. For example, the number threshold is set to 5 times, and the parameter combination is shown in Table 7 below. The frequent item set can be [(T A , S A ), (T B , S B ),

[0149] (S L , S W )].

[0150]

[0151] Table 7

[0152] S440, determining association rules based on frequent item sets, wherein the association rules are used to reflect the adjustment order or dependency relationship between different parameters.

[0153] For example, for each parameter combination X in the frequent item set, all possible non-empty true subsets Y of each parameter combination X are generated to form a rule "Y→XY", and the confidence P(XY|Y) is calculated, that is, the probability that XY also appears when Y is known to appear. The rule with a confidence greater than a preset threshold is an association rule. For example, the preset threshold of the confidence is 0.5, and the parameter combination is shown in Table 7 above. For the parameter combination (T A , S A ): Non-empty proper subsets Y have: {T A}, {S A}, the rule formed is: {T A}→{S A}, {S A}→{T A}, for the rule {T A}→{S A}, calculated in the containing {T A} parameter adjustment record, it also includes {S A} parameter adjustment record ratio, confidence = (including {T A , S A} parameter adjustment records) / (including {T A} parameter adjustment record number) = 0.6; for rule {S A}→{T A}, calculated in the containing {S A} parameter adjustment record, it also includes {T A} parameter adjustment record ratio, confidence = (including {T A , S A} parameter adjustment records) / (including {S A} parameter adjustment record number) = 0.5, then the rule {T A}→{S A} is an association rule.

[0154] S450: If there is no association rule for the parameter of the parameter adjustment request, determine the range adjustment information as the first adjustment information.

[0155] It can be understood that if there is no association rule for the parameter of the parameter adjustment request, there is no association adjustment information, and the first adjustment information only includes the range adjustment information.

[0156] S460: If there is an association rule for the parameter of the parameter adjustment request, determine the association adjustment information based on the association rule.

[0157] It can be understood that if there is an association rule for the parameter of the parameter adjustment request, the association adjustment information is determined based on the association rule, and the first adjustment information includes range adjustment information and association adjustment information.

[0158] Exemplarily, the parameter of the parameter adjustment request may be a time parameter of the winding link. For example, there is an association rule {S L}→{S W}, where S L is the time parameter of the winding link, S W is the time parameter of the wire drawing process, then the associated adjustment information is [{S L}→{S W}].

[0159] Through the above steps S410 to S460, the adjustment range of the parameters can be determined, the correlation between the parameters and the adjustment sequence can be identified, and the production parameter adjustment strategy can be optimized, which is not only conducive to improving production efficiency, but also can reduce the risk of production failures and quality problems caused by improper parameter adjustment.

[0160] S500: Determine a second probability that the parameter adjustment request is valid based on the first adjustment information and the first probability.

[0161] Exemplarily, the deviation between the range adjustment information and the parameter adjustment request and the association rule of the parameters of the parameter adjustment request may be determined based on the first adjustment information, and the first probability may be adjusted according to the deviation and the association rule to obtain the second probability.

[0162] In one possible implementation, see Figure 4 S500, determining a second probability that the parameter adjustment request is valid based on the first adjustment information and the first probability, including:

[0163] S510: Obtain a deviation between the range adjustment information and the parameter adjustment request based on the first adjustment information.

[0164] It can be understood that the deviation refers to the degree of difference between the parameter adjustment request and the range adjustment information.

[0165] Exemplarily, the difference between the parameter of the parameter adjustment request and the corresponding preset parameter can be determined through the parameter adjustment request, and then the deviation can be determined by comparing the difference with the corresponding parameter range of the range adjustment information in the first adjustment information. For example, the temperature range of the range adjustment information is [-5°C, +15°C], and the difference between the temperature parameter of the parameter adjustment request and the corresponding preset temperature parameter is +18°C, which exceeds +15°C. The proportion of the excess part relative to the entire range (from -5 to +15, that is, the amplitude of 20) is 15%, that is, the deviation is 15%.

[0166] Optionally, see Figure 4 S510, after obtaining the deviation between the range adjustment information and the parameter adjustment request based on the first adjustment information, the method further includes:

[0167] S5101: If the deviation exceeds the deviation threshold, a second confirmation message is sent.

[0168] It can be understood that the deviation threshold is that the deviation between the range adjustment information and the parameter adjustment request does not exceed a preset specified value. The preset specified value can be set by ordinary technicians in this field according to actual needs and is not limited here.

[0169] Exemplarily, if the deviation between the range adjustment information and the parameter adjustment request exceeds a preset deviation threshold (eg, 50%), the copper wire lamp production process optimization device will send a secondary confirmation message.

[0170] It can be understood that the secondary confirmation information is a notification of a parameter adjustment request containing a deviation from the range adjustment information that exceeds a preset deviation threshold. For example, the secondary confirmation information is: "The temperature parameter is adjusted from X℃ to Y℃, and the time parameter is adjusted from Z minutes to W minutes, which exceeds the preset deviation threshold. Please confirm whether to execute this parameter adjustment request."

[0171] Exemplarily, the secondary confirmation information can be sent by the copper wire lamp production process optimization equipment to the production line monitoring system (for example, the production line monitoring system is a central control room or remote monitoring platform that can receive signals from the copper wire lamp production process optimization equipment and display them to relevant operators or managers), or directly notify the relevant operators or managers by email, text message, etc., requiring the relevant operators or managers to confirm the rationality of the parameter adjustment request or make necessary adjustments.

[0172] S5102: Determine whether the parameter adjustment request is valid according to the return value of the secondary confirmation information.

[0173] It can be understood that the return value of the secondary confirmation information refers to the response of the relevant personnel to the secondary confirmation information.

[0174] Exemplarily, the return value can be a simple "yes" or "no", indicating whether the parameter adjustment request is valid. For example, if the relevant personnel reply "yes", it means that the parameter adjustment request is valid, and the parameter adjustment request will continue to be executed, that is, the parameter value in the parameter adjustment request will be applied to the copper wire lamp production equipment, and the parameter adjustment request can be recorded at the same time; if the reply is "no", it means that the parameter adjustment request is invalid, the parameter adjustment request can be rejected, the original parameters remain unchanged, and the relevant personnel (such as the request initiator, management personnel, etc.) are notified, indicating that the parameter adjustment request has been rejected, and it is recommended to resubmit a reasonable parameter adjustment request.

[0175] Through the above steps S5101 to S5102, the deviation threshold and the secondary confirmation mechanism are introduced to ensure that the parameter adjustment request is fully verified and confirmed before being executed, thereby reducing adjustment errors caused by misoperation or misunderstanding, improving the accuracy of adjustment, and avoiding production failures or safety accidents caused by improper parameter adjustment, thereby improving production efficiency and safety.

[0176] S520: Determine, based on the first adjustment information, whether the parameters of the parameter adjustment request have an association rule with the parameters of the parameter adjustment record of the copper wire lamp.

[0177] It can be understood that whether the parameter of the parameter adjustment request has an association rule with the parameter of the copper wire lamp being produced that has been adjusted before receiving the parameter adjustment request is determined based on the association adjustment information in the first adjustment information.

[0178] For example, the parameter of the parameter adjustment request may be the time parameter of the winding link, and the parameter of the parameter adjustment record of the copper wire lamp may be the time parameter of the wire drawing link. For example, the associated adjustment information is [{S L}→{S W},......], then there is an association rule {S L}→{S W}, where S W is the time parameter of the winding link, which is S L There are association rules between the time parameters of the wire drawing process, the parameters of the parameter adjustment request and the parameters of the parameter adjustment record of the copper wire lamp.

[0179] S530: If there is an association rule between the parameter of the parameter adjustment request and the parameter of the parameter adjustment record of the copper wire lamp, the first probability is adjusted based on the deviation and the association rule to obtain a second probability.

[0180] It can be understood that if there is an association rule between the parameters of the parameter adjustment request and the parameters of the parameter adjustment record of the copper wire lamp, the first probability can be adjusted based on the association rule and the deviation to obtain the second probability.

[0181] For example, the association rule adjustment amount can be obtained based on the association rule, the deviation adjustment amount can be obtained based on the deviation, and the first probability can be adjusted according to the association rule adjustment amount and the deviation adjustment amount to obtain the second probability. For example, the first probability is 0.7, the parameters of the parameter adjustment request include the speed parameter and the time parameter of the winding link, and there is an association rule that {S L}→{S W}, the association rule strength coefficient is 0.2, the association rule adjustment amount = 0.2×1 = 0.2; the deviation of the speed parameter is 20%, the deviation of the time parameter is 30%, the deviation influence coefficient is 0.3, the deviation adjustment amount = 0.3×(20%+30%)=0.15, then the second probability = the first probability + association rule adjustment amount - deviation adjustment amount = 0.7+0.2-0.15=0.75.

[0182] S540: If there is no association rule between the parameters of the parameter adjustment request and the parameters of the parameter adjustment record of the copper wire lamp, the first probability is adjusted based on the deviation to obtain a second probability.

[0183] It can be understood that if there is no association rule between the parameters of the parameter adjustment request and the parameters of the parameter adjustment record of the copper wire lamp, the first probability is adjusted only based on the deviation to obtain the second probability.

[0184] Exemplarily, a deviation influence coefficient may be preset, and a deviation adjustment amount may be obtained according to the deviation and the deviation influence coefficient (e.g., deviation adjustment amount = deviation influence coefficient × ∑ deviation of each parameter), and the first probability may be adjusted according to the deviation adjustment amount to obtain a second probability (e.g., second probability = first probability - deviation adjustment amount). For example, the first probability is 0.7, the parameters of the parameter adjustment request include a temperature parameter and a time parameter, the deviation of the temperature parameter is 20%, the deviation of the time parameter is 30%, the deviation influence coefficient is 0.3, the deviation adjustment amount = 0.3 × (20% + 30%) = 0.15, and the second probability = first probability - deviation adjustment amount = 0.7 - 0.15 = 0.55.

[0185] Through the above steps S510 to S540, considering the deviation between the parameter adjustment request and the range adjustment information, as well as the association rule between the parameter adjustment request and the parameter adjustment record, the necessity and rationality of the parameter adjustment request can be judged more accurately, which is conducive to realizing an automated parameter adjustment process.

[0186] S600: When it is determined that the parameter adjustment request is valid based on the parameter adjustment record and the second probability, adjust the parameters of the production equipment in the current production link according to the parameter adjustment request.

[0187] For example, when it is determined that the parameter adjustment request is valid based on the parameter adjustment record and the second probability, the copper wire lamp production process optimization device adjusts the production equipment parameters in the current production link according to the parameter adjustment request.

[0188] In one possible implementation, see Figure 5S600, when it is determined based on the parameter adjustment record and the second probability that the parameter adjustment request is valid, before adjusting the parameters of the production equipment of the current production link according to the parameter adjustment request, the method further includes:

[0189] S601: Determine, based on the parameter adjustment record, a first time interval and a first similarity between a parameter adjustment request and a valid adjustment record having a shortest time interval with the parameter adjustment request.

[0190] Exemplarily, the first time interval between the parameter adjustment request and the valid adjustment record with the shortest time interval with the parameter adjustment request can be calculated based on the adjustment time in the parameter adjustment record. The parameter adjustment request can be converted into the corresponding first feature vector using word embedding technology (such as Word2Vec, BERT, etc.) or feature engineering methods (such as one-hot encoding, TF-IDF, etc.), and the valid adjustment record can be converted into the corresponding second feature vector, and the ratio between the modulus of the first feature vector and the modulus of the second feature vector is calculated. The smaller ratio is the first similarity. For example, the production process includes wire drawing, annealing, winding and baking, which can be represented by 1, 2, 3, and 4 respectively; the parameters include temperature, time, and speed, which can be represented by 1, 2, and 3 respectively. Each parameter is standardized (for example, Z-Score standardization, Decimal Scaling standardization, etc.), the first eigenvector can be [2, 1, 7.8, 9.8] (annealing = 2, temperature = 1, standardized pre-adjustment parameter = 7.8, standardized adjusted parameter = 9.8), the second eigenvector can be [2, 1, 8, 8.8] (annealing = 2, temperature = 1, pre-adjustment parameter (°C) = 8, adjusted parameter (°C) = 8.8), the ratio between the modulus of the first eigenvector and the modulus of the second eigenvector is calculated, and the smaller ratio is the first similarity.

[0191] S602: Determine, based on the parameter adjustment record, a second time interval and a second similarity between the parameter adjustment request and the invalid adjustment record having the shortest time interval with the parameter adjustment request.

[0192] Exemplarily, the second time interval between the parameter adjustment request and the invalid adjustment record with the shortest time interval with the parameter adjustment request can be calculated based on the adjustment time in the parameter adjustment record. Word embedding technology (such as Word2Vec, BERT, etc.) or feature engineering methods (such as one-hot encoding, TF-IDF, etc.) can be used to convert the parameter adjustment request into a corresponding first feature vector, and the invalid adjustment record into a corresponding third feature vector, and the ratio between the modulus of the first feature vector and the modulus of the third feature vector is calculated, and the smaller ratio is the second similarity.

[0193] S603: Obtain a time interval weight according to the first time interval and the second time interval.

[0194] Exemplarily, the initial weight of the time interval can be adjusted by comparing the magnitudes of the first time interval and the second time interval to obtain the time interval weight.

[0195] Optionally, please refer to Figure 6 , S603. Obtaining the time interval weight according to the first time interval and the second time interval includes:

[0196] S6031. Obtaining an adjustment factor according to the first time interval and the second time interval.

[0197] Exemplarily, the adjustment factor can be determined by comparing the magnitudes of the first time interval and the second time interval. For example, the first time interval t1 = 50 min, the second time interval t2 = 80 min, the adjustment factor parameters α = 0.2, β = 0.1, t1 < t2, and the adjustment factor is 1 + 0.2 = 1.2.

[0198] S6032. Adjusting the initial weight of the time interval according to the adjustment factor to obtain the time interval weight.

[0199] Exemplarily, the time interval weight can be obtained by multiplying the adjustment factor by the initial weight of the time interval. For example, the adjustment factor is 1.2 and the initial weight of the time interval is 0.5, then the time interval weight = 1.2 × 0.5 = 0.6.

[0200] Through the above steps S6031 to S6032, by comparing the first time interval and the second time interval and applying the adjustment factor, the time interval weight can be dynamically adjusted according to the relative length of the time interval, enabling more flexible adaptation to different situations.

[0201] S604. Obtaining the similarity weight according to the first similarity and the second similarity.

[0202] Exemplarily, the initial similarity weight can be adjusted according to the first similarity and the second similarity to obtain the similarity weight.

[0203] Optionally, please refer to Figure 7 , S604. Obtaining the similarity weight according to the first similarity and the second similarity includes:

[0204] S6041. Judging whether the first similarity and the second similarity exceed the similarity threshold.

[0205] It can be understood that the similarity threshold is a preset specified value that the first similarity and the second similarity do not exceed, and this preset specified value can be set by those of ordinary skill in the art according to actual needs and is not uniquely limited herein.

[0206] For example, a reasonable similarity threshold can be determined based on historical data and industry standards. For example, the similarity threshold is set to 0.7. The first similarity and the second similarity can be compared with the similarity threshold.

[0207] S6042: If both the first similarity and the second similarity exceed the similarity threshold or both do not exceed the similarity threshold, determine the initial similarity weight as the similarity weight.

[0208] It can be understood that if both similarities exceed the similarity threshold or do not exceed the similarity threshold, the similarity weight is the initial similarity weight. For example, similarity weight = initial similarity weight = 0.5.

[0209] S6043: If the first similarity exceeds the similarity threshold and the second similarity does not exceed the similarity threshold, the initial similarity weight is increased to obtain a similarity weight.

[0210] For example, if the first similarity exceeds the similarity threshold and the second similarity does not exceed the similarity threshold, then the initial similarity weight is increased. For example, similarity weight=initial similarity weight+increase amplitude=0.5+0.1=0.6.

[0211] S6044: If the first similarity does not exceed the similarity threshold and the second similarity exceeds the similarity threshold, the initial similarity weight is reduced to obtain a similarity weight.

[0212] For example, if the first similarity exceeds the similarity threshold and the second similarity exceeds the similarity threshold, the initial similarity weight is reduced. For example, similarity weight = initial similarity weight - reduction amplitude = 0.5 - 0.1 = 0.4.

[0213] Through the above steps S6041 to S6044, the initial similarity weight is strategically adjusted according to the comparison results of the first similarity and the second similarity with the similarity threshold, so as to obtain a more accurate similarity weight, thereby providing a more reliable basis for subsequent decision-making.

[0214] S605: Determine a comprehensive evaluation value based on the second probability, the time interval weight, and the similarity weight.

[0215] For example, the second probability, the time interval weight and the similarity weight can be multiplied to obtain a comprehensive evaluation value. For example, the second probability = 0.75, the time interval weight = 0.6, and the similarity weight = 0.6, then the comprehensive evaluation value = the second probability × the time interval weight × the similarity weight = 0.75 × 0.6 × 0.6 = 0.27.

[0216] S606: If the comprehensive evaluation value exceeds the evaluation threshold, it is determined that the parameter adjustment request is valid.

[0217] It can be understood that the evaluation threshold is a comprehensive evaluation value that does not exceed a preset specified value. The preset specified value can be set by ordinary technicians in the field according to actual needs and is not a sole limitation here.

[0218] For example, a reasonable evaluation threshold may be determined based on historical data and industry standards. For example, the evaluation threshold is set to 0.2, and the comprehensive evaluation value is 0.27, then the parameter adjustment request is determined to be valid.

[0219] Through the above steps S601 to S606, the two factors of time interval and similarity can be comprehensively considered, and the effectiveness of the parameter adjustment request can be evaluated based on the second probability, time interval weight and similarity weight. By introducing time interval weight and similarity weight, the decision accuracy can be improved, the parameter adjustment strategy can be optimized, the waste of resources can be reduced and the level of automation can be improved.

[0220] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0221] Corresponding to the copper wire lamp production process optimization method described in the above embodiment, the embodiment of the present application also provides a copper wire lamp production process optimization device, and each module of the device can implement each step of the copper wire lamp production process optimization method. Figure 8 A structural block diagram of a copper wire lamp production process optimization device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0222] Reference Figure 8 , the device comprises:

[0223] An acquisition module is used to acquire a parameter adjustment record that matches the type of copper wire lamp being produced; wherein the parameter adjustment record includes the time of parameter adjustment, the production link corresponding to the parameter adjustment, the parameters before and after the adjustment, and the yield before and after the adjustment, the parameters include at least one of temperature, time and speed, and the production link is wire drawing, annealing, winding or baking;

[0224] A receiving module, used for receiving a parameter adjustment request of the copper wire lamp; wherein the parameter adjustment request is used for requesting to adjust the parameters of the production equipment in the current production link;

[0225] A first probability module, configured to determine, based on the parameter adjustment record, a first probability that a parameter corresponding to the parameter adjustment request is adjusted;

[0226] a first adjustment information module, configured to determine first adjustment information based on the parameter adjustment record and the parameter adjustment request; wherein the first adjustment information includes at least one of range adjustment information and associated adjustment information, the range adjustment information is used to reflect the adjustment range of the parameter of the parameter adjustment request, and the associated adjustment information is used to reflect the parameter in the parameter adjustment record that has an associated relationship with the parameter of the parameter adjustment request;

[0227] a second probability module, configured to determine a second probability that the parameter adjustment request is valid based on the first adjustment information and the first probability;

[0228] An adjustment module is used to adjust the parameters of the production equipment in the current production link according to the parameter adjustment request when it is determined that the parameter adjustment request is valid based on the parameter adjustment record and the second probability.

[0229] It should be noted that the information interaction, execution process and other contents between the above-mentioned modules are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0230] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned device can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0231] The present application also provides a copper wire lamp production process optimization device, Fig. 9 This is a schematic diagram of the structure of a copper wire lamp production process optimization device provided in one embodiment of the present application. Fig. 9 As shown, the copper wire lamp production process optimization device 6 of this embodiment includes: at least one processor 60 ( Fig. 9 Only one is shown), at least one memory 61 ( Fig. 9Only one is shown) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, the copper wire lamp production process optimization device 6 implements the steps in any of the above-mentioned copper wire lamp production process optimization method embodiments, or the copper wire lamp production process optimization device 6 implements the functions of each module / unit in the above-mentioned device embodiments.

[0232] Exemplarily, the computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete the present application. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program 62 in the copper wire lamp production process optimization device 6.

[0233] The copper wire lamp production process optimization device 6 can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The copper wire lamp production process optimization device can include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art can understand that Fig. 9 It is only an example of the copper wire lamp production process optimization device 6 and does not constitute a limitation of the copper wire lamp production process optimization device 6. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, buses, etc.

[0234] The processor 60 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0235] In some embodiments, the memory 61 may be an internal storage unit of the copper wire lamp production process optimization device 6, such as a hard disk or memory of the copper wire lamp production process optimization device 6. In other embodiments, the memory 61 may also be an external storage device of the copper wire lamp production process optimization device 6, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the copper wire lamp production process optimization device 6. Further, the memory 61 may also include both an internal storage unit and an external storage device of the copper wire lamp production process optimization device 6. The memory 61 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 61 may also be used to temporarily store production data that has been output or is to be output.

[0236] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in any of the above method embodiments are implemented.

[0237] An embodiment of the present application provides a computer program product. When the computer program product is run on a copper wire lamp production process optimization device, the copper wire lamp production process optimization device implements the steps in any of the above method embodiments.

[0238] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device that can carry the computer program code to the copper wire lamp production process optimization device / copper wire lamp production process optimization equipment, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0239] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0240] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0241] In the embodiments provided in the present application, it should be understood that the disclosed copper wire lamp production process optimization device / copper wire lamp production process optimization equipment and method can be implemented in other ways. For example, the copper wire lamp production process optimization device / copper wire lamp production process optimization equipment embodiment described above is only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0242] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0243] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for optimizing the production process of copper wire lamps, characterized in that: include: Obtaining a parameter adjustment record that matches the type of copper wire lamp being produced; wherein the parameter adjustment record includes the time of parameter adjustment, the production link corresponding to the parameter adjustment, the parameters before and after the adjustment, and the yield before and after the adjustment, the parameters include at least one of temperature, time and speed, and the production link is wire drawing, annealing, winding or baking; Receive a parameter adjustment request for the copper wire lamp; wherein the parameter adjustment request is used to request adjustment of parameters of production equipment in a current production link; Determining, based on the parameter adjustment record, a first probability that a parameter corresponding to the parameter adjustment request is adjusted; Determine first adjustment information based on the parameter adjustment record and the parameter adjustment request; wherein the first adjustment information includes at least one of range adjustment information and associated adjustment information, the range adjustment information is used to reflect the adjustment range of the parameter of the parameter adjustment request, and the associated adjustment information is used to reflect the parameter in the parameter adjustment record that has an associated relationship with the parameter of the parameter adjustment request; determining a second probability that the parameter adjustment request is valid based on the first adjustment information and the first probability; When it is determined that the parameter adjustment request is valid based on the parameter adjustment record and the second probability, the parameters of the production equipment in the current production link are adjusted according to the parameter adjustment request.

2. The copper wire lamp production process optimization method according to claim 1, characterized in that: The determining, based on the parameter adjustment record, a first probability that a parameter corresponding to the parameter adjustment request is adjusted includes: Determine the probability distribution of each parameter being adjusted in each production link according to the parameter adjustment record; Determining a third probability that the parameter corresponding to the parameter adjustment request is adjusted in the current production link according to the probability distribution of each parameter being adjusted in each production link; Determining, according to the parameter adjustment record, a fourth probability that the parameter corresponding to the parameter adjustment request is adjusted in all production links; The first probability is obtained by taking a weighted average of the third probability and the fourth probability.

3. The copper wire lamp production process optimization method according to claim 1, characterized in that: The determining the first adjustment information based on the parameter adjustment record and the parameter adjustment request includes: Determine the effective adjustment record of the current production link based on the parameter adjustment record; wherein the effective adjustment record refers to a record in which the yield after the parameter adjustment is higher than the yield before the adjustment in the parameter adjustment record; determining the range adjustment information based on the valid adjustment record; Determine a frequent item set of parameter adjustment based on the parameter adjustment record; wherein the frequent item set is a set of parameter combinations that appear more than a threshold number of times in the parameter adjustment record, and the parameter combination includes different combinations of parameters of each production link of each batch of copper wire lamps in the parameter adjustment record; Determining association rules based on the frequent item sets; wherein the association rules are used to reflect the adjustment order or dependency relationship between different parameters; If the parameter of the parameter adjustment request does not have the association rule, determining the range adjustment information as the first adjustment information; If the parameter of the parameter adjustment request has the association rule, the association adjustment information is determined based on the association rule.

4. The copper wire lamp production process optimization method according to claim 3, characterized in that: The determining of the effective adjustment record of the current production link based on the parameter adjustment record includes: Determine the yield of each parameter before and after adjustment of the current production link in the parameter adjustment record based on the parameter adjustment record; Compare the yield of each parameter in the current production link after adjustment in the parameter adjustment record with the yield before adjustment; If the yield rate of the parameter adjustment in the current production link after the adjustment is less than or equal to the yield rate before the adjustment in the parameter adjustment record, the corresponding parameter adjustment record is determined as an invalid adjustment record; If the yield rate of the parameters of the current production link after adjustment in the parameter adjustment record is greater than the yield rate before adjustment, the corresponding parameter adjustment record is determined as the valid adjustment record.

5. The copper wire lamp production process optimization method according to claim 3, characterized in that: The determining the range adjustment information based on the valid adjustment record includes: Compare the adjusted parameters of the current production link in the effective adjustment record with the corresponding preset parameters of the current production link of the copper wire lamp to obtain the adjustment direction and adjustment range of each parameter of the current production link; The range adjustment information is determined based on the adjustment direction and adjustment range of each parameter in the current production link.

6. The copper wire lamp production process optimization method according to claim 3, characterized in that: The determining, based on the first adjustment information and the first probability, a second probability that the parameter adjustment request is valid includes: Obtaining a degree of deviation between the range adjustment information and the parameter adjustment request based on the first adjustment information; Determining whether the parameter of the parameter adjustment request has the association rule with the parameter of the parameter adjustment record of the copper wire lamp based on the first adjustment information; If the parameter of the parameter adjustment request and the parameter of the parameter adjustment record of the copper wire lamp have the association rule, adjusting the first probability based on the deviation and the association rule to obtain the second probability; If the parameter of the parameter adjustment request does not have the association rule with the parameter of the parameter adjustment record of the copper wire lamp, the first probability is adjusted based on the deviation to obtain the second probability.

7. The copper wire lamp production process optimization method according to claim 6, characterized in that: After obtaining the deviation between the range adjustment information and the parameter adjustment request based on the first adjustment information, the method further includes: If the deviation exceeds the deviation threshold, a secondary confirmation message is sent; Whether the parameter adjustment request is valid is determined according to the return value of the secondary confirmation information.

8. The copper wire lamp production process optimization method according to claim 4, characterized in that: In the case where it is determined that the parameter adjustment request is valid based on the parameter adjustment record and the second probability, before adjusting the parameters of the production equipment of the current production link according to the parameter adjustment request, the method further includes: Determine, based on the parameter adjustment record, a first time interval and a first similarity between the parameter adjustment request and the valid adjustment record having the shortest time interval with the parameter adjustment request; determining, based on the parameter adjustment record, a second time interval and a second similarity between the parameter adjustment request and the invalid adjustment record having the shortest time interval with the parameter adjustment request; Obtaining a time interval weight according to the first time interval and the second time interval; Obtaining a similarity weight according to the first similarity and the second similarity; Determine a comprehensive evaluation value based on the second probability, the time interval weight and the similarity weight; If the comprehensive evaluation value exceeds the evaluation threshold, it is determined that the parameter adjustment request is valid.

9. The copper wire lamp production process optimization method according to claim 8, characterized in that: The obtaining a time interval weight according to the first time interval and the second time interval includes: Obtaining an adjustment factor according to the first time interval and the second time interval; Adjust the initial weight of the time interval according to the adjustment factor to obtain the time interval weight; And / or, obtaining a similarity weight according to the first similarity and the second similarity includes: Determining whether the first similarity and the second similarity exceed a similarity threshold; If both the first similarity and the second similarity exceed the similarity threshold or do not exceed the similarity threshold, determining the initial similarity weight as the similarity weight; If the first similarity exceeds the similarity threshold and the second similarity does not exceed the similarity threshold, increasing the initial similarity weight and obtaining the similarity weight; If the first similarity does not exceed the similarity threshold and the second similarity exceeds the similarity threshold, the initial similarity weight is reduced to obtain the similarity weight.

10. A copper wire lamp production process optimization device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 9 is implemented.

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