CN117631627A - Digital transformation method based on industrial Internet - Google Patents
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Abstract
The invention relates to the technical field of digital transformation, and discloses a digital transformation method based on industrial Internet, which comprises the following steps: collecting production data of a target product; pretreating and marking; calculating a process stability coefficient; calculating a device stability coefficient; calculating a production quality stability coefficient; calculating a production line stability coefficient; calculating a comprehensive production index; judging the comprehensive production index; the step S07 is arranged, so that the comprehensive production index is calculated based on production process data, production equipment data, production quality data and production state data, the actual condition of production in a processing field is combined with the data condition of the real-time state, the processing technology and the product quality of the equipment, the comprehensive operation condition of a production workshop is analyzed, the comprehensiveness of analysis of the industrial production condition is increased, and therefore, workers can pertinently test and optimize the data, and the production efficiency of the production workshop is improved.
Description
Technical Field
The invention relates to the technical field of digital transformation, in particular to a digital transformation method based on an industrial Internet.
Background
The industrial Internet is a novel infrastructure, an application mode and industrial ecology of deep integration of a new generation of information communication technology and industrial economy, a brand-new manufacturing and service system which covers the whole industry and a complete value chain is constructed through comprehensive connection of people, machines, objects, systems and the like, an implementation way is provided for industrial and even industrial digitization, networking and intelligent development, the digitization transformation is to make up production, marketing, storage and customer management of each plate by technical means, the transformation of business mode and organization mode is completed, the digitization transformation is realized through application of the digitization technology and artificial intelligence technology, the online and offline integration can be realized, the operation efficiency and the service quality of merchants are improved, the information management and the intelligent management can be realized, and the labor cost and the management cost are reduced.
The existing digital transformation method based on the industrial Internet is applied to industrial production, but the existing digital transformation method only carries out digital analysis and adjustment on a production line, does not combine the actual condition of production on a processing site, does not combine the real-time state data of equipment, processing technology data and product quality data to analyze the comprehensive operation efficiency of a production workshop, and does not lead to incomplete analysis on the condition of industrial production, so that the production efficiency of the production workshop cannot be effectively improved.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a digital transformation method based on the industrial Internet, which aims to solve the problems in the prior art.
The invention provides the following technical scheme: a digital transformation method based on industrial Internet comprises the following steps:
step S01: collecting production data of a target product: collecting production process data, production equipment data, production quality data and production line production state data in the production process of a target product;
step S02: preprocessing and marking the data in the step S01: preprocessing the industrial product production data acquired in the step S01 to obtain production process data, production equipment data, production quality data and production line production state data which can be directly used, and marking the production process data and the production equipment data;
step S03: based on the production process data in step S02, a process stability factor is calculated: calculating independent process stability coefficients of each procedure and overall process stability coefficients of target product production based on the production process data preprocessed in the step S02, and counting abnormal rates of the production process data;
step S04: based on the production equipment data in step S02, an equipment stability factor is calculated: calculating independent equipment stability coefficients of each procedure and integral equipment stability coefficients of standard product production based on the production equipment data preprocessed in the step S02, and counting abnormal rate of the production equipment data;
step S05: calculating a production quality stability coefficient and a production quality data anomaly rate based on the production quality data preprocessed in the step S02;
step S06: calculating a production line stability coefficient and a production state data anomaly rate based on the production state data of the production line after the pretreatment in the step S02;
step S07: based on the data of the steps S03, S04, S05 and S06, comprehensive analysis and calculation are carried out to obtain a comprehensive production index, and the production process data anomaly rate, the production equipment data anomaly rate, the production quality data anomaly rate and the production state data anomaly rate are ordered;
step S08: and (3) judging the comprehensive production index in the step S07, if the judging result is that the optimization is needed, transmitting the judging result and the ordering condition of the data abnormal rate in the step S07 to the terminal, and if the judging result is that the optimization is not needed, transmitting the judging result and the maximum value of the data abnormal rate to the terminal.
Preferably, the method for marking the production process data and the production equipment data in step S02 is as follows: if the target product has G processes, marking the process temperature corresponding to the G process as W g The process speed corresponding to the g-th procedure is marked as S g The working current of the production equipment corresponding to the g-th procedure is marked as I g The working voltage of the production equipment corresponding to the g-th procedure is marked as V g The equipment working pressure of the production equipment corresponding to the g-th procedure is marked as P g Wherein g=1, 2, 3 … … G.
Preferably, the calculating of the independent process stability factor comprises the steps of:
step S11: marking the total yield of the target product as n, and marking the process temperature of the ith product in the g-th process as W gi The process speed of the ith product in the g-th procedure is recorded as S gi Wherein i=1, 2, 3 … … n;
step S12: calculating a process temperature deviation coefficient and a process speed deviation coefficient of the process in the step g:wherein W is g ' is the mean value of the process temperature in the g-th procedure, ">Process temperature deviation coefficient>Wherein S is g ' is the average value of the process speed of the g-th procedure, < + >>A Sg The process speed deviation coefficient is the process speed deviation coefficient of the g-th procedure;
step S13: calculating independent process stability coefficients of the g-th procedure: a is that dg ＝k 1 (1-A Wg )+k 2 (1-A Sg ) Wherein A is dg Is the independent process stability coefficient, k of the g-th procedure 1 Is the process temperature scale factor, k 2 Is a process speed scaling factor.
Preferably, the calculation formula of the overall process stability coefficient is as follows:wherein A is d ' is the mean value of the stability coefficients of the independent process, < >>A z The stability coefficient of the whole process for the production of the target product.
Preferably, the calculating of the stability coefficient of the independent device includes the following steps:
step S21: marking the total yield of the target product as n, and recording the working current of the ith product when the ith product passes through production equipment corresponding to the g process as I gi The working voltage of the ith product when passing through the production equipment corresponding to the g process is recorded as V gi The equipment working pressure when the ith product passes through the production equipment corresponding to the g process is recorded as P gi Wherein i=1, 2, 3 … … n;
step S22: calculating the device current deviation coefficient, the device voltage deviation coefficient and the device pressure deviation coefficient of the process of the g step:wherein I is g ' is the working current mean value of the production equipment corresponding to the g-th procedure, ">B Ig For the device current deviation coefficient of the g-th procedure, is->Wherein V is g ' is the working voltage average value of the production equipment corresponding to the g-th procedure, ">B Vg For the device voltage deviation coefficient of the g-th procedure, is->Wherein P is g ' is the mean value of the working pressure of the production equipment corresponding to the g-th procedure, ">B Pg The pressure deviation coefficient of the equipment in the g-th procedure;
step S23: calculating the independent equipment stability coefficient of the g-th procedure: b (B) dg ＝λ 1 (1-B Ig )+λ 2 (1-B Vg )+λ 3 (1-B Pg ) Wherein B is dg Is the independent equipment stability coefficient of the g-th procedure, lambda 1 Lambda is the scale factor of the operating current of the device 2 Lambda is the scale factor of the operating voltage of the device 3 Is a scale factor for the operating pressure of the device.
Preferably, the calculation formula of the stability coefficient of the whole device is as follows:wherein B is d ' is the mean value of the stability coefficients of the independent device, +.>B z Stability coefficient of the whole equipment for the production of the target product.
Preferably, the calculation formula of the production quality stability coefficient is as follows:wherein h is the qualified total quantity of target products, t i For the time of production of the ith product, t' is the time average for production of the target product,/->n is the total yield of the target product.
Preferably, the calculation formula of the stability factor of the production line is as follows:wherein m is the total number of production lines, j=1, 2, 3 … … m, r j For the daily production of the product of the jth production line, x j The qualified quantity of products in the jth production line is h is the qualified total quantity of target products,D z is the stability coefficient of the production line.
Preferably, the calculation formula of the comprehensive production index is as follows:wherein n is the total yield of the target product, h is the qualified total quantity of the target product, eta is the characteristic parameter influence factor of the target product, and U is the comprehensive production index.
Preferably, the standard for discriminating the comprehensive production index is: when U is more than or equal to phi, the judgment result is that optimization is not needed, and when U is less than phi, the judgment result is that optimization is needed, and the value of phi meets phi more than or equal to 90%.
The invention has the technical effects and advantages that:
(1) The invention is beneficial to calculating the independent process stability coefficient of each procedure and the integral process stability coefficient of target product production through production process data, counting the abnormal rate of the production process data, calculating the independent equipment stability coefficient of each procedure and the integral equipment stability coefficient of target product production through production equipment data, counting the abnormal rate of the production equipment data, calculating the stable coefficient of production quality and the abnormal rate of the production quality data through production quality data, calculating the stable coefficient of production line and the abnormal rate of the production state data through production line production state data, laying a foundation for the subsequent calculation of comprehensive production indexes, and analyzing the industrial production condition from four aspects of the production process data, the production equipment data, the production quality data and the production state data, and the result is more comprehensive.
(2) The invention is beneficial to calculating the comprehensive production index based on the production process data, the production equipment data, the production quality data and the production state data, analyzing the comprehensive operation condition of a production workshop by combining the actual condition of the production on the processing site with the real-time state of the equipment, the processing technology and the data condition of the product quality, increasing the comprehensiveness of the analysis of the industrial production condition and sequencing the abnormal data rate, thereby leading staff to be capable of checking and optimizing the data in a targeted manner and improving the production efficiency of the production workshop.
Drawings
FIG. 1 is a flow chart of a digital transformation method based on the industrial Internet.
Detailed Description
The embodiments of the present invention will be clearly and completely described below with reference to the drawings in the present invention, and the configurations of the structures described in the following embodiments are merely examples, and the digital modification method based on the industrial internet according to the present invention is not limited to the structures described in the following embodiments, and all other embodiments obtained by a person having ordinary skill in the art without making any inventive effort are within the scope of the present invention.
The invention provides a digital transformation method based on industrial Internet, which comprises the following steps:
step S01: collecting production data of a target product: acquiring production process data, production equipment data, production quality data and production line production state data in a production process of a target product, wherein the target product is an industrial product to be produced, the production process data comprises but is not limited to process temperature and process speed, the process temperature comprises but is not limited to welding temperature and mold temperature, the process speed comprises but is not limited to spraying speed, the production equipment data comprises but is limited to current of production equipment, voltage of production equipment and pressure of production equipment, the production quality data comprises but is not limited to product qualified number and single product production time, the production line production state data comprises but is not limited to production line number, daily product yield of a single production line, product qualified number of a single production line and total target product yield, the production process data and the production equipment data have different data types according to different products, the corresponding data can be selected according to actual conditions, the embodiment only enumerates the main data types, if a blade is required to be used in the production process of the product, the speed of production in the production equipment data can be selected as acquisition data, if the temperature is required to be used as acquisition data in the production process, and the welding process data can be carried out in the production process data if the welding process data is required in the production process data acquisition process of the production speed is required;
step S02: preprocessing and marking the data in the step S01: preprocessing the industrial product production data acquired in the step S01 to obtain directly usable production process data, production equipment data, production quality data and production line production state data, marking the production process data and the production equipment data, and marking the process temperature corresponding to the G-th process as W if the target product has the G-th process g The process speed corresponding to the g-th procedure is marked as S g The working current of the production equipment corresponding to the g-th procedure is marked as I g The working voltage of the production equipment corresponding to the g-th procedure is marked as V g The equipment working pressure of the production equipment corresponding to the g-th procedure is marked as P g Wherein g=1, 2, 3 … … G;
step S03: based on the production process data in step S02, a process stability factor is calculated: calculating independent process stability coefficients of each procedure and overall process stability coefficients of target product production based on the production process data preprocessed in the step S02, and counting abnormal rates of the production process data;
step S04: based on the production equipment data in step S02, an equipment stability factor is calculated: calculating independent equipment stability coefficients of each procedure and integral equipment stability coefficients of standard product production based on the production equipment data preprocessed in the step S02, and counting abnormal rate of the production equipment data;
step S05: calculating a production quality stability coefficient and a production quality data anomaly rate based on the production quality data preprocessed in the step S02;
step S06: calculating a production line stability coefficient and a production state data anomaly rate based on the production state data of the production line after the pretreatment in the step S02;
step S07: based on the data of the steps S03, S04, S05 and S06, comprehensive analysis and calculation are carried out to obtain a comprehensive production index, and the production process data anomaly rate, the production equipment data anomaly rate, the production quality data anomaly rate and the production state data anomaly rate are sequenced, wherein the sequencing criteria are sequencing from the maximum value to the minimum value in sequence;
step S08: the comprehensive production index in the step S07 is judged, if the judging result is that optimization is needed, the judging result and the sorting condition of the data abnormality rate in the step S07 are transmitted to the terminal, the worker can sequentially check and optimize the corresponding production condition according to the sorting condition of the data abnormality rate in the step S07, if the judging result is that optimization is not needed, the judging result and the maximum value of the data abnormality rate are transmitted to the terminal, the worker can check and optimize the production condition corresponding to the maximum value of the data abnormality rate, if the maximum value of the data abnormality rate is the abnormal rate of production process data, the worker can check and optimize the process temperature, the process speed and the like in the production process, if the maximum value of the data abnormality rate is the abnormal rate of production equipment data, the worker can check and optimize the current of production equipment in the production process, the voltage of the production equipment, the pressure of the production equipment and the like, and the like in the production process, if the maximum value of the data abnormality rate is the abnormal rate of the production quality data abnormality rate, the worker can check and optimize the product qualification number and the single product production time and the like in the production process, and the total yield and the production line of the production line and the daily quality of the production process can be optimized.
In this embodiment, it should be specifically described that the calculation of the independent process stability factor includes the following steps:
step S11: marking the total yield of the target product as n, and marking the process temperature of the ith product in the g-th process as W gi The process speed of the ith product in the g-th procedure is recorded as S gi Wherein i=1, 2, 3 … … n;
step S12: calculating the process temperature deviation coefficient of the g-th procedureProcess speed deviation coefficient:wherein W is g ' is the mean value of the process temperature in the g-th procedure, ">Process temperature deviation coefficient>Wherein S is g ' is the average value of the process speed of the g-th procedure, < + >>A Sg The process speed deviation coefficient is the process speed deviation coefficient of the g-th procedure;
step S13: calculating independent process stability coefficients of the g-th procedure: a is that dg ＝k 1 (1-A Wg )+k 2 (1-A Sg ) Wherein A is dg Is the independent process stability coefficient, k of the g-th procedure 1 Is the process temperature scale factor, k 2 As a process speed scale factor, k 1 And k is equal to 2 Satisfy k 1 +k 2 ＝1，k 1 And k is equal to 2 The specific numerical values of (a) can be set according to different target products, and the specific numerical values are not specifically limited in this embodiment.
In this embodiment, it should be specifically described that the calculation formula of the overall process stability coefficient is:wherein A is d ' is the mean value of the stability coefficients of the independent process, < >>A z The stability coefficient of the whole process for the production of the target product.
In this embodiment, it should be specifically described that the calculating of the stability coefficient of the independent device includes the following steps:
step S21: marking the total yield of the target product as n, and recording the working current of the ith product when the ith product passes through production equipment corresponding to the g process as I gi The working voltage of the ith product when passing through the production equipment corresponding to the g process is recorded as V gi The equipment working pressure when the ith product passes through the production equipment corresponding to the g process is recorded as P gi Wherein i=1, 2, 3 … … n, and the working current of the production equipment, the working voltage of the production equipment and the equipment working pressure of the production equipment are instantaneous current, instantaneous voltage and instantaneous pressure;
step S22: calculating the device current deviation coefficient, the device voltage deviation coefficient and the device pressure deviation coefficient of the process of the g step:wherein I is g ' is the working current mean value of the production equipment corresponding to the g-th procedure, ">B Ig For the device current deviation coefficient of the g-th procedure, is->Wherein V is g ' is the working voltage average value of the production equipment corresponding to the g-th procedure, ">B Vg For the device voltage deviation coefficient of the g-th procedure, is->Wherein P is g ' is the mean value of the working pressure of the production equipment corresponding to the g-th procedure, ">B Pg The pressure deviation coefficient of the equipment in the g-th procedure;
step S23: independent equipment stabilization system for calculating g-th procedureThe number: b (B) dg ＝λ 1 (1-B Ig )+λ 2 (1-B Vg )+λ 3 (1-B Pg ) Wherein B is dg Is the independent equipment stability coefficient of the g-th procedure, lambda 1 Lambda is the scale factor of the operating current of the device 2 Lambda is the scale factor of the operating voltage of the device 3 Lambda is the scale factor of the working pressure of the equipment 1 、λ 2 Lambda of 3 Satisfy lambda 1 +λ 2 +λ 3 =1, where λ 3 ＜λ 1 And lambda is 2 ，λ 1 、λ 2 Lambda of 3 The specific numerical values of (a) can be set according to different target products, and the specific numerical values are not specifically limited in this embodiment.
In this embodiment, it should be specifically described that the calculation formula of the stability coefficient of the whole device is:wherein B is d ' is the mean value of the stability coefficients of the independent device, +.>B z Stability coefficient of the whole equipment for the production of the target product.
In this embodiment, it should be specifically described that the calculation formula of the production quality stability coefficient is:wherein h is the qualified total quantity of target products, t i For the time of production of the ith product, t' is the time average for production of the target product,/->n is the total yield of the target product.
In this embodiment, it should be specifically described that the calculation formula of the stability factor of the production line is:wherein,m is the total number of production lines, j=1, 2, 3 … … m, r j For the daily production of the product of the jth production line, x j The qualified quantity of products in the jth production line is h is the qualified total quantity of target products, D z Is the stability coefficient of the production line.
In this embodiment, it should be specifically described that the calculation formula of the integrated production index is:wherein n is the total yield of the target product, h is the qualified total quantity of the target product, eta is the characteristic parameter influence factor of the target product, U is the comprehensive production index, and +.>Wherein y is the hardness of the target product, ρ is the density of the target product, f is the surface finish of the target product, and M is the size of the target product.
In this embodiment, it should be specifically described that the calculation formula of the production process data anomaly rate is:wherein delta A For the abnormal rate of the production process data, q W For the number of data which does not accord with the standard range value of the process temperature, q S For the number of data which does not meet the process speed standard range value, if only one data W exists gi If the value does not meet the process temperature standard range value, W is determined gi Recorded as data which do not meet the process temperature standard range value, q W 1, if there is only one data S gi If the standard range value of the process speed is not met, S is gi Recorded as data which does not meet the process speed standard range value, q S 1, the standard range value of the process temperature and the standard range value of the process speed have different standard range values according to different production processes of target products, wherein the standard range values are allowed by the production of the target products and do not affect the production quality of the target products.
In this embodiment, it should be specifically explained that,the calculation formula of the production equipment data anomaly rate is as follows:wherein delta B To produce equipment data anomaly rate, q I For the number of data which does not accord with the standard range value of the working current of the equipment, q V For the number of data which does not accord with the standard range value of the working voltage of the equipment, q P For the number of data which does not meet the standard range value of the working pressure of the equipment, if only one data I exists gi If the operating current standard range value of the equipment is not met, I is as follows gi Recorded as data which do not meet the standard range of the working current of the equipment, q I 1, if there is only one data V gi If the voltage does not accord with the standard range value of the working voltage of the equipment, V is calculated gi Recorded as data which do not meet the standard range of the operating voltage of the equipment, q V 1 if there is only one data P gi If the pressure does not meet the standard range value of the working pressure of the equipment, P is added gi Recorded as data which do not meet the standard range of operating pressure of the device, q P 1, the standard range value of the working current of the equipment, the standard range value of the working voltage of the equipment and the standard range value of the working pressure of the equipment are different standard range values according to different production equipment of a target product, wherein the standard range values are the range values allowed by the production of the target product and do not affect the production quality of the target product and the production equipment.
In this embodiment, it should be specifically described that the calculation formula of the production quality data anomaly rate is:wherein delta C To produce quality data anomaly rate, q t For the number of products with the single product production time exceeding the allowable longest production time, n is the total yield of the target products, h is the qualified total number of the target products, the allowable longest production time is set by a worker according to the production plan of the target products and cannot be smaller than the time average value used for the production of the target products, and the specific numerical value of the allowable longest production time is not specifically limited in the embodiment.
In this embodiment, it should be specifically described that the calculation formula of the production status data anomaly rate is:wherein delta D To produce abnormal rate of state data, q j For the number of production lines which do not meet the production line qualification standard, m is the total number of production lines, and the judgment formula which does not meet the production line qualification standard is as follows: />Wherein H is j For the production line judgment index, if H exists j And (5) the j-th production line is a production line which does not meet the qualified standard of the production line.
In this embodiment, it should be specifically described that the standard for discriminating the integrated production index is: when U is larger than or equal to phi, the judgment result is that optimization is not needed, when U is smaller than phi, the judgment result is that optimization is needed, the value of phi satisfies phi is larger than or equal to 90%, and the specific numerical value of the value is not specifically limited in the embodiment.
In this embodiment, it needs to be specifically explained that the difference between the implementation and the prior art is mainly that the implementation includes steps S03, S04, S05 and S06, which are beneficial to calculating the independent process stability coefficient of each process and the overall process stability coefficient of the target product production through the production process data, and counting the abnormal rate of the production process data, calculating the independent equipment stability coefficient of each process and the overall equipment stability coefficient of the standard product production through the production equipment data, and counting the abnormal rate of the production equipment data, calculating the production quality stability coefficient and the abnormal rate of the production quality data through the production line production state data, calculating the production line stability coefficient and the abnormal rate of the production state data, laying a foundation for the subsequent calculation of the comprehensive production index, analyzing the industrial production condition from four aspects of the production process data, the production equipment data, the production quality data and the production state data, and calculating the comprehensive production index based on the production process data, calculating the production equipment stability coefficient of each process and the production state data, combining the actual condition of the production on-site production with the real-time state, the quality of the production equipment and the quality data and the production state data, optimizing the overall analysis of the data of the production workshop, and optimizing the overall operation performance of the data of the production workshop, and optimizing the data of the overall operation of the production workshop, and improving the production performance.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A digital transformation method based on industrial Internet is characterized in that: the method comprises the following steps:
step S01: collecting production data of a target product: collecting production process data, production equipment data, production quality data and production line production state data in the production process of a target product;
step S02: preprocessing and marking the data in the step S01: preprocessing the industrial product production data acquired in the step S01 to obtain production process data, production equipment data, production quality data and production line production state data which can be directly used, and marking the production process data and the production equipment data;
step S03: based on the production process data in step S02, a process stability factor is calculated: calculating independent process stability coefficients of each procedure and overall process stability coefficients of target product production based on the production process data preprocessed in the step S02, and counting abnormal rates of the production process data;
step S04: based on the production equipment data in step S02, an equipment stability factor is calculated: calculating independent equipment stability coefficients of each procedure and integral equipment stability coefficients of standard product production based on the production equipment data preprocessed in the step S02, and counting abnormal rate of the production equipment data;
step S05: calculating a production quality stability coefficient and a production quality data anomaly rate based on the production quality data preprocessed in the step S02;
step S06: calculating a production line stability coefficient and a production state data anomaly rate based on the production state data of the production line after the pretreatment in the step S02;
step S07: based on the data of the steps S03, S04, S05 and S06, comprehensive analysis and calculation are carried out to obtain a comprehensive production index, and the production process data anomaly rate, the production equipment data anomaly rate, the production quality data anomaly rate and the production state data anomaly rate are ordered;
step S08: and (3) judging the comprehensive production index in the step S07, if the judging result is that the optimization is needed, transmitting the judging result and the ordering condition of the data abnormal rate in the step S07 to the terminal, and if the judging result is that the optimization is not needed, transmitting the judging result and the maximum value of the data abnormal rate to the terminal.
2. The method for digitally modifying the internet according to claim 1, wherein the method comprises the steps of: the method for marking the production process data and the production equipment data in the step S02 is as follows: if the target product has G processes, marking the process temperature corresponding to the G process as W g The process speed corresponding to the g-th procedure is marked as S g The working current of the production equipment corresponding to the g-th procedure is marked as I g The working voltage of the production equipment corresponding to the g-th procedure is marked as V g The equipment working pressure of the production equipment corresponding to the g-th procedure is marked as P g Wherein g=1, 2, 3 … … G。
3. The method for digitally modifying the internet according to claim 1, wherein the method comprises the steps of: the calculation of the independent process stability factor comprises the following steps:
step S11: marking the total yield of the target product as n, and marking the process temperature of the ith product in the g-th process as W gi The process speed of the ith product in the g-th procedure is recorded as S gi Wherein i=1, 2, 3 … … n;
step S12: calculating a process temperature deviation coefficient and a process speed deviation coefficient of the process in the step g:wherein W is g ' is the mean value of the process temperature in the g-th procedure, ">Process temperature deviation coefficient>Wherein S is g ' is the average value of the process speed of the g-th procedure, < + >>A Sg The process speed deviation coefficient is the process speed deviation coefficient of the g-th procedure;
step S13: calculating independent process stability coefficients of the g-th procedure: a is that dg ＝k 1 (1-A Wg )+k 2 (1-A Sg ) Wherein A is dg Is the independent process stability coefficient, k of the g-th procedure 1 Is the process temperature scale factor, k 2 Is a process speed scaling factor.
4. The method for digitally modifying the internet according to claim 1, wherein the method comprises the steps of: the calculation formula of the integral process stability coefficient is as follows:wherein A is d ' is the mean value of the stability coefficients of the independent process, < >>A z The stability coefficient of the whole process for the production of the target product.
5. The method for digitally modifying the internet according to claim 1, wherein the method comprises the steps of: the calculation of the independent device stability factor comprises the following steps:
step S21: marking the total yield of the target product as n, and recording the working current of the ith product when the ith product passes through production equipment corresponding to the g process as I gi The working voltage of the ith product when passing through the production equipment corresponding to the g process is recorded as V gi The equipment working pressure when the ith product passes through the production equipment corresponding to the g process is recorded as P gi Wherein i=1, 2, 3 … … n;
step S22: calculating the device current deviation coefficient, the device voltage deviation coefficient and the device pressure deviation coefficient of the process of the g step:wherein I is g ' is the working current average value of the production equipment corresponding to the g-th procedure,B Ig for the device current deviation coefficient of the g-th procedure, is->Wherein V is g ' is the working voltage average value of the production equipment corresponding to the g-th procedure, ">B Vg For the device voltage deviation coefficient of the g-th procedure, is->Wherein P is g ' is the equipment working pressure average value of the production equipment corresponding to the g-th procedure,B Pg the pressure deviation coefficient of the equipment in the g-th procedure;
step S23: calculating the independent equipment stability coefficient of the g-th procedure: b (B) dg ＝λ 1 (1-B Ig )+λ 2 (1-B Vg )+λ 3 (1-B Pg ) Wherein B is dg Is the independent equipment stability coefficient of the g-th procedure, lambda 1 Lambda is the scale factor of the operating current of the device 2 Lambda is the scale factor of the operating voltage of the device 3 Is a scale factor for the operating pressure of the device.
6. The method for digitally modifying the internet according to claim 1, wherein the method comprises the steps of: the calculation formula of the stability coefficient of the whole equipment is as follows:wherein B is d ' is the mean value of the stability coefficients of the independent device, +.>B z Stability coefficient of the whole equipment for the production of the target product.
7. The method for digitally modifying the internet according to claim 1, wherein the method comprises the steps of: the calculation formula of the production quality stability coefficient is as follows:wherein h is the qualified total quantity of target products, t i For the ith productTime for production of the product, t' is the time average for production of the target product,/->n is the total yield of the target product.
8. The method for digitally modifying the internet according to claim 1, wherein the method comprises the steps of: the calculation formula of the production line stability coefficient is as follows:wherein m is the total number of production lines, j=1, 2, 3 … … m, r j For the daily production of the product of the jth production line, x j The qualified quantity of products in the jth production line is h is the qualified total quantity of target products, D z Is the stability coefficient of the production line.
9. The method for digitally modifying the internet according to claim 1, wherein the method comprises the steps of: the calculation formula of the comprehensive production index is as follows:wherein n is the total yield of the target product, h is the qualified total quantity of the target product, eta is the characteristic parameter influence factor of the target product, and U is the comprehensive production index.
10. The method for digitally modifying the internet according to claim 1, wherein the method comprises the steps of: the standard for discriminating the comprehensive production index is as follows: when U is more than or equal to phi, the judgment result is that optimization is not needed, and when U is less than phi, the judgment result is that optimization is needed, and the value of phi meets phi more than or equal to 90%.
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