An intelligent data analysis system and method based on intelligent Internet of Things platform

Abstract

The present invention discloses an intelligent data analysis system and method based on an intelligent Internet of Things platform, which relates to the technical field of industrial data analysis, including analyzing the influence of a product to be processed on the product production of an industrial production line to obtain a target product to be processed; obtaining production data of the target product to be processed, obtaining equipment processing data in the industrial production line, and analyzing the equipment adaptability of the industrial equipment in the industrial production line and the target product to be processed; obtaining location information of the target industrial equipment, obtaining product processing data of the target industrial equipment on the target product to be processed, analyzing different equipment processing routes between the target industrial equipment, the influence on the production of the target product to be processed, and generating target processing data of the target product to be processed; obtaining the target processing data of the target product to be processed in the current cycle, adjusting the industrial production line of the industrial enterprise in the current cycle, and intelligently managing the industrial production data.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial data analysis, and in particular to an intelligent data analysis system and method based on an intelligent Internet of Things platform. Background Art

[0002] Nowadays, many data analyses are done with the help of the Internet of Things platform, especially in the industrial field. The Internet of Things platform can be used to obtain data in real time. Smart Internet of Things devices can collect and transmit data in real time, allowing companies to randomly monitor production and operation status. The acquisition of real-time data can also help regions respond quickly to market changes and adjust corporate strategies in a timely manner. On the other hand, the use of the Internet of Things platform can integrate data from different devices, sensors and systems, which is conducive to data analysis. Through the Internet of Things platform, the data of various departments within the enterprise can be seamlessly connected, which is more conducive to information sharing and collaborative work.

[0003] In the actual production and processing process of products by industrial enterprises, the quantity and types of products produced by industrial enterprises are not single and fixed. Enterprises need to produce and process different types of products according to actual orders and market demand. Different products have different process requirements. Therefore, the industrial equipment and production processes required in the production process are different. This requires adjustments to the company's industrial production lines. However, in actual practice, most industrial enterprises rarely adjust industrial production intelligently based on actual needs and corresponding data in the industrial production process. This will not only cause the production line to stop and efficiency to decline during the adjustment process, but may also lead to the failure to deliver orders in time, affecting the company's operating efficiency and long-term development. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent data analysis system and method based on an intelligent Internet of Things platform to solve the problems raised in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solution: an intelligent data analysis method based on an intelligent Internet of Things platform, the method comprising:

[0006] Step S100: construct a data analysis cloud platform, obtain the production orders of industrial enterprises in the current cycle, obtain product data of the products to be processed from the production orders, obtain the industrial production data of the industrial production lines of the industrial enterprises, analyze the influence of the products to be processed on the product production of the industrial production lines, and obtain the target products to be processed;

[0007] Step S200: Acquire production data of the target product to be processed, acquire equipment processing data in the industrial production line, analyze the compatibility of industrial equipment in the industrial production line with the equipment of the target product to be processed, and obtain the target industrial equipment;

[0008] Step S300: Acquire the location information of the target industrial equipment, acquire the product processing data of the target industrial equipment on the target product to be processed, analyze the different equipment processing routes between the target industrial equipment, the degree of influence on the production of the target product to be processed, and generate the target processing data of the target product to be processed;

[0009] Step S400: Acquire target processing data of target products to be processed in the current cycle, adjust the industrial production lines of industrial enterprises in the current cycle, and intelligently manage industrial production data.

[0010] Furthermore, step S100 includes:

[0011] Step S101: obtaining products to be processed by the industrial enterprise in the current cycle, and obtaining product data of the products to be processed, wherein the product data includes the total amount of the products to be processed planned to be produced in the current cycle;

[0012] Step S102: obtaining the historical cycle closest to the current cycle from each historical cycle and recording it as a characteristic historical cycle, obtaining the industrial production line of the industrial enterprise and the industrial production data within the characteristic historical cycle, the industrial production data including the product models of the historical processed products produced and processed by the industrial production line within the characteristic historical cycle;

[0013] Step S103: Setting the unit time length T △ , obtain the product model of each product to be processed in the current cycle of the industrial enterprise. When a product to be processed has the same product model as a historical processed product, obtain the maximum value U of the product quantity of a historical processed product produced by the industrial production line in each unit time of the characteristic historical cycle max , and the minimum value P of the product qualification rate of a certain historical processing product min ;

[0014] Step S104: Calculate the characteristic production volume K of the product to be processed in the current cycle = (U max ×P min )×(T sum / T △ ), where T sum Represented as the total duration of the current cycle;

[0015] Step S105: When the characteristic production volume of a certain product to be processed in the current cycle is less than the total volume of the product to be processed that the industrial enterprise plans to produce, the certain product to be processed is recorded as a target product to be processed;

[0016] Step S106: When a product to be processed is different from a product model of a historically processed product, the product to be processed is recorded as a target product to be processed.

[0017] Further, step S200 includes:

[0018] Step S201: Acquire production data of a target product to be processed in a current cycle of an industrial production line, wherein the production data includes demand data corresponding to a plurality of processes for processing the target product to be processed;

[0019] Step S202: obtaining equipment types of industrial equipment in the industrial production line, obtaining industrial equipment that meets the demand data corresponding to several processes of the target product to be processed, and recording them as the industrial equipment to be selected for the several processes;

[0020] Step S203: Analyze the bth candidate industrial equipment of the ath process of the target product to be processed, and the specific process of the compatibility with the equipment of the ath process of the target product to be processed is to obtain the reference industrial equipment for processing the ath process from the cloud platform;

[0021] Step S204: respectively obtaining equipment processing data of the reference industrial equipment and the bth industrial equipment to be selected, wherein the equipment processing data includes data corresponding to various equipment performance indicators of the industrial equipment;

[0022] Step S205: Obtain the maximum value E of a certain equipment performance index of the reference industrial equipment and the selected industrial equipment of the a-th process max and the minimum value E min , calculate the characteristic value D of a certain equipment performance index in the reference industrial equipment = (E´-E min ) / (E max -E min ), where E´ is the average value of a certain equipment performance index in the control industrial equipment;

[0023] Step S206: Obtain the characteristic values ​​of various equipment performance indicators of the reference industrial equipment and the bth industrial equipment to be selected, and calculate the characteristic equipment adaptation value R of the bth industrial equipment to be selected and the ath process of the target product to be processed a,b :

[0024] ,

[0025] Wherein, j represents the total number of equipment performance indicators of the control industrial equipment; f a b,i It is expressed as the characteristic value of the i-th equipment performance index in the b-th selected industrial equipment; f a i It is expressed as the characteristic value of the i-th equipment performance indicator in the reference industrial equipment;

[0026] Step S207: Obtain the characteristic equipment adaptation values ​​of the reference industrial equipment and the several industrial equipment to be selected in the process item a, and prioritize the several industrial equipment to be selected based on the characteristic equipment adaptation values ​​and the values;

[0027] Step S208: Obtain the total planned production volume γ of the target product to be processed in the current cycle SUM , get the characteristic equipment screening condition γ of the a-th process SUM z,a ×m, where Q z,a It is represented as the industrial equipment to be selected with the priority of the zth order, and the expected total amount of products processed by the ath process in the target product to be processed in the current cycle. When the characteristic equipment screening condition is met, the minimum value of m in the characteristic equipment screening condition is obtained;

[0028] Step S209: based on the priority order, obtain the number of industrial equipment to be selected corresponding to the minimum value, and record them as the target industrial equipment of the a-th process, and obtain the target industrial equipment of several processes of the target product to be processed;

[0029] The above steps calculate the characteristic equipment adaptation values ​​of the selected industrial equipment and several processes of the target product to be processed based on the obtained reference industrial equipment and the characteristic values ​​of various equipment performance indicators of the selected industrial equipment. This is because the process requirements of different processes of the target product to be processed are different. If the various equipment performance indicators of an industrial equipment are more similar to those of the reference industrial equipment of a certain process, then it means that the industrial equipment is more adapted to the certain process. This not only makes it possible to quickly find suitable industrial equipment, but also greatly improves the production and processing efficiency of the target product to be processed.

[0030] Furthermore, step S300 includes:

[0031] Step S301: obtaining the location information of each target industrial equipment corresponding to several processes of the target product to be processed, the location information including the equipment coordinates of the target industrial equipment;

[0032] Step S302: obtaining a target industrial equipment corresponding to the first process among a plurality of processes, and recording it as the starting target industrial equipment of the target product to be processed;

[0033] Step S303: Analyze the different equipment processing routes between target industrial equipment and the degree of influence on the production of target products to be processed, and plan several target processing routes of target products to be processed, wherein the specific planning process of the g-th target processing route is to obtain the equipment coordinates of several target industrial equipment of different processes;

[0034] ​Step S304: Calculate the characteristic distance W between the starting target industrial equipment of the g-th target processing route and the β-th target industrial equipment corresponding to the second process. β :

[0035] ,

[0036] Among them, x g ,y g They are respectively represented as the horizontal coordinate and vertical coordinate of the starting target industrial equipment of the g-th target processing route; β ,y β They are respectively represented as the horizontal and vertical coordinates of the β-th target industrial equipment;

[0037] Step S305: construct an equipment route array Hg of the g-th target processing route, take the starting target industrial equipment of the g-th target processing route as the first element of the equipment route array Hg, obtain the minimum value of the characteristic distance between the starting target industrial equipment of the g-th target processing route and a plurality of target industrial equipment corresponding to the second process of the target product to be processed, and record the target industrial equipment corresponding to the minimum value as the second element of the equipment route array Hg;

[0038] Step S306: Accumulate the characteristic distances between adjacent elements of the equipment route array Hg to obtain the total distance L[Hg] of the marked equipment route, and match the equipment route array with several target industrial equipment of different processes of the target product to be processed. The specific matching process is to obtain the total number of elements v in the equipment route array Hg, and obtain the characteristic matching formula: min{L[Hg]+W v β |β∈(1, 2, ..., δ)}, where W v β It is represented as the characteristic distance between the target industrial equipment corresponding to the vth element in the equipment route array Hg and the βth target industrial equipment in the v+1th process of the target product to be processed, and δ is represented as the total number of target industrial equipment corresponding to the v+1th process;

[0039] Step S307: Obtain the target industrial equipment of the v+1th process in the gth target processing route through the feature matching formula, and collect them into the equipment route array Hg, update the equipment route array Hg, and update the equipment route array Hg in sequence according to the feature matching formula to obtain the equipment coordinates of the target industrial equipment corresponding to several processes in the gth target processing route, and generate the product production route information of the gth target processing route;

[0040] Step S308: Acquire product production route information in a plurality of target processing routes, and generate target processing data of target products to be processed.

[0041] Furthermore, step S400 includes:

[0042] Step S401: acquiring target processing data of each target product to be processed in the industrial production line within the current cycle;

[0043] Step S402: Based on the target processing data and the target industrial equipment for processing each target product to be processed, the target products to be processed in the industrial production line within the current cycle are processed and the industrial production data are intelligently managed.

[0044] In order to better implement the above method, an intelligent data analysis system based on an intelligent Internet of Things platform is also proposed. The system includes a target product module to be processed, a target industrial equipment module, a target processing data module, and an intelligent management module;

[0045] The target product to be processed module is used to analyze the impact of the product to be processed on the product production of the industrial production line and obtain the target product to be processed;

[0046] The target industrial equipment module is used to analyze the compatibility of the industrial equipment in the industrial production line with the target product to be processed, and obtain the target industrial equipment;

[0047] The target processing data module is used to analyze the different equipment processing routes between target industrial equipment, the degree of influence on the production of target products to be processed, and generate target processing data for target products to be processed;

[0048] The intelligent management module is used to adjust the industrial production lines of industrial enterprises in the current cycle and to intelligently manage industrial production data.

[0049] Further, the target product to be processed module includes a characteristic production volume unit and a target product to be processed unit;

[0050] Characteristic production volume unit, used to calculate the characteristic production volume of the product to be processed in the current cycle;

[0051] The target product unit to be processed is used to obtain the target product to be processed of the industrial production line in the current cycle according to the characteristic production volume.

[0052] Further, the target industrial equipment module includes a characteristic equipment adaptation value unit and a target industrial equipment unit;

[0053] A characteristic equipment adaptation value unit is used to calculate characteristic equipment adaptation values ​​of several processes of the selected industrial equipment and the target product to be processed;

[0054] The target industrial equipment unit is used to obtain target industrial equipment for several processes of the target product to be processed according to the characteristic equipment adaptation value.

[0055] Further, the target processing data module includes a target processing route unit and a target processing data unit;

[0056] The target processing route unit is used to analyze the different equipment processing routes between target industrial equipment, the degree of influence on the production of target products to be processed, and plan several target processing routes for target products to be processed;

[0057] The target processing data unit is used to obtain product production route information in a number of target processing routes and generate target processing data of target products to be processed.

[0058] Further, the intelligent management module includes an intelligent management unit;

[0059] The intelligent management unit is used to produce and process the target products to be processed in the industrial production line within the current cycle, and to intelligently manage the industrial production data.

[0060] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention realizes intelligent adjustment of the industrial production line of an industrial enterprise according to the real-time order of the enterprise, obtains the products to be processed that the industrial enterprise needs to process in the current cycle from the production orders of the industrial enterprise in the current cycle, selects the products to be processed that need to adjust the industrial production line from them, and obtains the target industrial equipment for processing the products to be processed according to the process requirements of the products to be processed, and also intelligently plans the route for processing the target products to be processed according to the equipment coordinates of the target industrial equipment, thereby maximizing the processing efficiency of the industrial production line for the target products to be processed, and further improving the output of the industrial enterprise. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a method flow chart of an intelligent data analysis system and method based on an intelligent Internet of Things platform of the present invention;

[0062] Figure 2 It is a module schematic diagram of an intelligent data analysis system and method based on an intelligent Internet of Things platform of the present invention. DETAILED DESCRIPTION

[0063] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] Example: Figure 1-Figure 2 As shown, the present invention provides a technical solution, an intelligent data analysis method based on an intelligent Internet of Things platform, the method comprising:

[0065] Step S100: construct a data analysis cloud platform, obtain the production orders of industrial enterprises in the current cycle, obtain product data of the products to be processed from the production orders, obtain the industrial production data of the industrial production lines of the industrial enterprises, analyze the influence of the products to be processed on the product production of the industrial production lines, and obtain the target products to be processed;

[0066] Wherein, step S100 includes:

[0067] Step S101: obtaining products to be processed by the industrial enterprise in the current cycle, and obtaining product data of the products to be processed, wherein the product data includes the total amount of the products to be processed planned to be produced in the current cycle;

[0068] Step S102: obtaining the historical cycle closest to the current cycle from each historical cycle and recording it as a characteristic historical cycle, obtaining the industrial production line of the industrial enterprise and the industrial production data within the characteristic historical cycle, the industrial production data including the product models of the historical processed products produced and processed by the industrial production line within the characteristic historical cycle;

[0069] Step S103: Setting the unit time length T △ , obtain the product model of each product to be processed in the current cycle of the industrial enterprise. When a product to be processed has the same product model as a historical processed product, obtain the maximum value U of the product quantity of a historical processed product produced by the industrial production line in each unit time of the characteristic historical cycle max , and the minimum value P of the product qualification rate of a certain historical processing product min ;

[0070] Step S104: Calculate the characteristic production volume K of the product to be processed in the current cycle = (U max ×P min )×(T sum / T △ ), where T sum Represented as the total duration of the current cycle;

[0071] Step S105: When the characteristic production volume of a certain product to be processed in the current cycle is less than the total volume of the product to be processed that the industrial enterprise plans to produce, the certain product to be processed is recorded as a target product to be processed;

[0072] Step S106: When a product to be processed is different from a product model of a historically processed product, the product to be processed is recorded as a target product to be processed;

[0073] Step S200: Acquire production data of the target product to be processed, acquire equipment processing data in the industrial production line, analyze the compatibility of industrial equipment in the industrial production line with the equipment of the target product to be processed, and obtain the target industrial equipment;

[0074] Wherein, step S200 includes:

[0075] Step S201: Acquire production data of a target product to be processed in a current cycle of an industrial production line, wherein the production data includes demand data corresponding to a plurality of processes for processing the target product to be processed;

[0076] For example, the demand data includes the welding strength and grinding accuracy of the target product to be processed;

[0077] Step S202: obtaining equipment types of industrial equipment in the industrial production line, obtaining industrial equipment that meets the demand data corresponding to several processes of the target product to be processed, and recording them as the industrial equipment to be selected for the several processes;

[0078] Step S203: Analyze the bth candidate industrial equipment of the ath process of the target product to be processed, and the specific process of the compatibility with the equipment of the ath process of the target product to be processed is to obtain the reference industrial equipment for processing the ath process from the cloud platform;

[0079] Step S204: respectively obtaining equipment processing data of the reference industrial equipment and the bth industrial equipment to be selected, wherein the equipment processing data includes data corresponding to various equipment performance indicators of the industrial equipment;

[0080] For example, various equipment performance indicators include maximum processing accuracy, maximum processing speed, etc.;

[0081] Step S205: Obtain the maximum value E of a certain equipment performance index of the reference industrial equipment and the selected industrial equipment of the a-th process max and the minimum value E min , calculate the characteristic value D of a certain equipment performance index in the reference industrial equipment = (E´-E min ) / (E max -E min ), where E´ is the average value of a certain equipment performance index in the control industrial equipment;

[0082] Step S206: Obtain the characteristic values ​​of various equipment performance indicators of the reference industrial equipment and the bth industrial equipment to be selected, and calculate the characteristic equipment adaptation value R of the bth industrial equipment to be selected and the ath process of the target product to be processed a,b :

[0083] ,

[0084] Wherein, j represents the total number of equipment performance indicators of the control industrial equipment; f a b,i It is expressed as the characteristic value of the i-th equipment performance index in the b-th selected industrial equipment; f a i It is expressed as the characteristic value of the i-th equipment performance indicator in the reference industrial equipment;

[0085] For example, the total number j of equipment performance indicators of the control industrial equipment of the first process is 3; the characteristic value f of the first equipment performance indicator of the first candidate industrial equipment of the first process is 1 1,1 It is expressed as 0.6; the characteristic value f of the second equipment performance index in the first candidate industrial equipment of the first process 1 1,2 It is expressed as 0.7; the characteristic value f of the third equipment performance index in the first candidate industrial equipment of the first process 1 1,2 It is expressed as 0.8;

[0086] The characteristic value f of the first equipment performance index in the reference industrial equipment of the first process 1 1 is expressed as 0.65; the characteristic value f of the performance index of the second equipment in the reference industrial equipment of the first process 1 2 is expressed as 0.85; the characteristic value f of the third equipment performance index in the reference industrial equipment of the first process 1 3 is expressed as 0.75;

[0087] Calculate the first industrial equipment to be selected and the characteristic equipment adaptation value R of the first process of the target product to be processed 1,1 :

[0088] ,

[0089] Step S207: Obtain the characteristic equipment adaptation values ​​of the reference industrial equipment and the several industrial equipment to be selected in the process item a, and prioritize the several industrial equipment to be selected based on the characteristic equipment adaptation values ​​and the values;

[0090] Step S208: Obtain the total planned production volume γ of the target product to be processed in the current cycle SUM , get the characteristic equipment screening condition γ of the a-th process SUM z,a ×m, where Q z,a It is represented as the industrial equipment to be selected with the priority of the zth order, and the expected total amount of products processed by the ath process in the target product to be processed in the current cycle. When the characteristic equipment screening condition is met, the minimum value of m in the characteristic equipment screening condition is obtained;

[0091] Step S209: based on the priority order, obtain the number of industrial equipment to be selected corresponding to the minimum value, and record them as the target industrial equipment of the a-th process, and obtain the target industrial equipment of several processes of the target product to be processed;

[0092] Step S300: Acquire the location information of the target industrial equipment, acquire the product processing data of the target industrial equipment on the target product to be processed, analyze the different equipment processing routes between the target industrial equipment, the degree of influence on the production of the target product to be processed, and generate the target processing data of the target product to be processed;

[0093] Wherein, step S300 includes:

[0094] Step S301: obtaining the location information of each target industrial equipment corresponding to several processes of the target product to be processed, the location information including the equipment coordinates of the target industrial equipment;

[0095] Step S302: obtaining a target industrial equipment corresponding to the first process among a plurality of processes, and recording it as the starting target industrial equipment of the target product to be processed;

[0096] Step S303: Analyze the different equipment processing routes between target industrial equipment and the degree of influence on the production of target products to be processed, and plan several target processing routes of target products to be processed, wherein the specific planning process of the g-th target processing route is to obtain the equipment coordinates of several target industrial equipment of different processes;

[0097] Step S304: Calculate the characteristic distance W between the starting target industrial equipment of the g-th target processing route and the β-th target industrial equipment corresponding to the second process. β :

[0098] ,

[0099] Among them, x g ,y g They are respectively represented as the horizontal coordinate and vertical coordinate of the starting target industrial equipment of the g-th target processing route; β ,y β ​They are respectively represented as the horizontal and vertical coordinates of the β-th target industrial equipment;

[0100] Step S305: construct an equipment route array Hg of the g-th target processing route, take the starting target industrial equipment of the g-th target processing route as the first element of the equipment route array Hg, obtain the minimum value of the characteristic distance between the starting target industrial equipment of the g-th target processing route and a plurality of target industrial equipment corresponding to the second process of the target product to be processed, and record the target industrial equipment corresponding to the minimum value as the second element of the equipment route array Hg;

[0101] Step S306: Accumulate the characteristic distances between adjacent elements of the equipment route array Hg to obtain the total distance L[Hg] of the marked equipment route, and match the equipment route array with several target industrial equipment of different processes of the target product to be processed. The specific matching process is to obtain the total number of elements v in the equipment route array Hg, and obtain the characteristic matching formula: min{L[Hg]+W v β |β∈(1, 2, ..., δ)}, where W v β It is represented as the characteristic distance between the target industrial equipment corresponding to the vth element in the equipment route array Hg and the βth target industrial equipment in the v+1th process of the target product to be processed, and δ is represented as the total number of target industrial equipment corresponding to the v+1th process;

[0102] Step S307: Obtain the target industrial equipment of the v+1th process in the gth target processing route through the feature matching formula, and collect them into the equipment route array Hg, update the equipment route array Hg, and update the equipment route array Hg in sequence according to the feature matching formula to obtain the equipment coordinates of the target industrial equipment corresponding to several processes in the gth target processing route, and generate the product production route information of the gth target processing route;

[0103] Step S308: obtaining product production route information in a plurality of target processing routes, and generating target processing data of target products to be processed;

[0104] Step S400: acquiring target processing data of target products to be processed in the current cycle, adjusting the industrial production line of the industrial enterprise in the current cycle, and intelligently managing the industrial production data;

[0105] Wherein, step S400 includes:

[0106] Step S401: acquiring target processing data of each target product to be processed in the industrial production line within the current cycle;

[0107] Step S402: Based on the target processing data and the target industrial equipment for processing each target product to be processed, the target product to be processed in the industrial production line within the current cycle is processed, and the industrial production data is intelligently managed;

[0108] In order to better implement the above method, an intelligent data analysis system based on an intelligent Internet of Things platform is also proposed. The system includes a target product module to be processed, a target industrial equipment module, a target processing data module, and an intelligent management module;

[0109] The target product to be processed module is used to analyze the impact of the product to be processed on the product production of the industrial production line and obtain the target product to be processed;

[0110] The target industrial equipment module is used to analyze the compatibility of the industrial equipment in the industrial production line with the target product to be processed, and obtain the target industrial equipment;

[0111] The target processing data module is used to analyze the different equipment processing routes between target industrial equipment, the degree of influence on the production of target products to be processed, and generate target processing data for target products to be processed;

[0112] Intelligent management module, used to adjust the industrial production lines of industrial enterprises in the current cycle and intelligently manage industrial production data;

[0113] Among them, the target product to be processed module includes a characteristic production volume unit and a target product to be processed unit;

[0114] Characteristic production volume unit, used to calculate the characteristic production volume of the product to be processed in the current cycle;

[0115] The target product unit to be processed is used to obtain the target product to be processed of the industrial production line in the current cycle according to the characteristic production volume.

[0116] Among them, the target industrial equipment module includes a characteristic equipment adaptation value unit and a target industrial equipment unit;

[0117] A characteristic equipment adaptation value unit is used to calculate characteristic equipment adaptation values ​​of several processes of the selected industrial equipment and the target product to be processed;

[0118] A target industrial equipment unit is used to obtain target industrial equipment for several processes of a target product to be processed according to a characteristic equipment adaptation value;

[0119] Among them, the target processing data module includes a target processing route unit and a target processing data unit;

[0120] The target processing route unit is used to analyze the different equipment processing routes between target industrial equipment, the degree of influence on the production of target products to be processed, and plan several target processing routes for target products to be processed;

[0121] A target processing data unit is used to obtain product production route information in a plurality of target processing routes and generate target processing data of target products to be processed;

[0122] Wherein, the intelligent management module includes an intelligent management unit;

[0123] The intelligent management unit is used to produce and process the target products to be processed in the industrial production line within the current cycle, and to intelligently manage the industrial production data.

[0124] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. An intelligent data analysis method based on an intelligent Internet of Things platform, characterized in that: The method comprises: Step S100: construct a data analysis cloud platform, obtain production orders of industrial enterprises in the current cycle, obtain product data of the products to be processed from the production orders, obtain industrial production data of the industrial production lines of the industrial enterprises, analyze the influence of the products to be processed on the product production of the industrial production lines, and obtain the target products to be processed; The step S100 includes: Step S101: obtaining products to be processed by an industrial enterprise in a current cycle, and obtaining product data of the products to be processed, wherein the product data includes the total amount of the products to be processed planned to be produced in the current cycle; Step S102: obtaining the historical cycle closest to the current cycle from each historical cycle and recording it as a characteristic historical cycle, obtaining the industrial production line of the industrial enterprise and the industrial production data within the characteristic historical cycle, wherein the industrial production data includes the product models of the historical processed products produced and processed by the industrial production line within the characteristic historical cycle; Step S103: Setting the unit time length T △ , obtain the product model of each product to be processed in the current cycle of the industrial enterprise. When a product to be processed has the same product model as a historical processed product, obtain the maximum value U of the product quantity of the historical processed product produced by the industrial production line in each unit time of the characteristic historical cycle. max , and the minimum value P of the product qualification rate of a certain historical processed product min ; Step S104: Calculate the characteristic production volume K of the product to be processed in the current cycle = (U max ×P min )×(T sum / T △ ), where T sum Represented as the total duration of the current cycle; Step S105: When the characteristic production volume of the product to be processed in the current cycle is less than the total volume of the product to be processed that the industrial enterprise plans to produce, the product to be processed is recorded as a target product to be processed; Step S106: When the product model of the certain product to be processed is different from that of a certain historically processed product, the certain product to be processed is recorded as a target product to be processed; Step S200: Acquire production data of the target product to be processed, acquire equipment processing data in the industrial production line, analyze the compatibility of industrial equipment in the industrial production line with the equipment of the target product to be processed, and obtain target industrial equipment; The step S200 includes: Step S201: Acquiring production data of a target product to be processed in a current cycle of an industrial production line, wherein the production data includes demand data corresponding to a plurality of processes for processing the target product to be processed; Step S202: obtaining equipment types of industrial equipment in the industrial production line, obtaining industrial equipment that meets the demand data corresponding to the several processes of the target product to be processed, and recording them as the industrial equipment to be selected for the several processes; Step S203: Analyze the bth candidate industrial equipment of the ath process of the target product to be processed, and the specific process of the compatibility with the equipment of the ath process of the target product to be processed is to obtain the reference industrial equipment for processing the ath process from the cloud platform; Step S204: respectively obtaining equipment processing data of the reference industrial equipment and the bth industrial equipment to be selected, wherein the equipment processing data includes data corresponding to various equipment performance indicators of the industrial equipment; Step S205: Obtain the maximum value E of a certain equipment performance index of the reference industrial equipment and the several selected industrial equipment of the a-th process max and the minimum value E min , calculate the characteristic value D of a certain equipment performance index in the reference industrial equipment = (E´-E min ) / (E max -E min ), wherein E´ is represented by the average value of the equipment performance index of the control industrial equipment; Step S206: Obtain the characteristic values ​​of various equipment performance indicators of the reference industrial equipment and the bth selected industrial equipment, and calculate the characteristic equipment adaptation value R of the bth selected industrial equipment and the ath process of the target product to be processed a,b : ， Wherein, j represents the total number of various equipment performance indicators of the reference industrial equipment; f a b,i f is represented by the characteristic value of the i-th equipment performance indicator in the b-th industrial equipment to be selected; a i is represented as the characteristic value of the i-th equipment performance indicator in the reference industrial equipment; Step S207: Obtain the characteristic equipment adaptation values ​​of the reference industrial equipment and the several industrial equipment to be selected in the process item a, and prioritize the several industrial equipment to be selected based on the characteristic equipment adaptation values ​​and according to the values; Step S208: Obtain the total planned production volume γ of the target product to be processed in the current cycle SUM , obtain the characteristic equipment screening condition γ of the process item a SUM z,a ×m, where Q z,a It is represented as the industrial equipment to be selected with the priority of the zth order, and the expected total amount of products processed by the ath process in the target product to be processed in the current cycle, and the minimum value of m in the characteristic equipment screening condition is obtained when the characteristic equipment screening condition is met;​ Step S209: based on the priority order, obtaining the number of to-be-selected industrial equipment corresponding to the minimum value, and recording them as the target industrial equipment of the a-th process, and obtaining the target industrial equipment of the several processes of the target product to be processed; Step S300: Acquire the location information of the target industrial equipment, acquire the product processing data of the target industrial equipment on the target product to be processed, analyze the different equipment processing routes between the target industrial equipment, the degree of influence on the production of the target product to be processed, and generate the target processing data of the target product to be processed; The step S300 includes: Step S301: obtaining the position information of each target industrial equipment corresponding to the plurality of processes of the target product to be processed, wherein the position information includes the equipment coordinates of the target industrial equipment; Step S302: obtaining a target industrial equipment corresponding to the first process among the plurality of processes, and recording it as the starting target industrial equipment of the target product to be processed; Step S303: Analyze the different equipment processing routes between target industrial equipment, the degree of influence on the production of the target product to be processed, and plan several target processing routes of the target product to be processed, wherein the specific planning process of the g-th target processing route is to obtain the equipment coordinates of several target industrial equipment of different processes; Step S304: Calculate the characteristic distance W between the starting target industrial equipment of the g-th target processing route and the β-th target industrial equipment corresponding to the second process. β : ， Among them, x g ,y g They are respectively represented as the horizontal coordinate and the vertical coordinate of the starting target industrial equipment of the g-th target processing route; β ,y β are respectively represented as the abscissa and ordinate of the β-th target industrial equipment; Step S305: constructing an equipment route array Hg of the g-th target processing route, taking the starting target industrial equipment of the g-th target processing route as the first element of the equipment route array Hg, obtaining the minimum value of the characteristic distance between the starting target industrial equipment of the g-th target processing route and a plurality of target industrial equipment corresponding to the second process of the target product to be processed, and recording the target industrial equipment corresponding to the minimum value as the second element of the equipment route array Hg; Step S306: Obtain each adjacent element in the equipment route array Hg, accumulate the characteristic distances between the adjacent elements, obtain the total distance L[Hg] of the marked equipment route, and match the equipment route array with several target industrial equipment of different processes of the target product to be processed. The specific matching process is to obtain the total number of elements v in the equipment route array Hg, and obtain the characteristic matching formula: min{L[Hg]+W v β |β∈(1, 2, ..., δ)}, where W v β It is represented as the characteristic distance between the target industrial equipment corresponding to the vth element in the equipment route array Hg and the βth target industrial equipment in the v+1th process of the target product to be processed, and δ is represented as the total number of target industrial equipment corresponding to the v+1th process; Step S307: Obtain the target industrial equipment of the v+1th process in the gth target processing route through the feature matching formula, and collect them into the equipment route array Hg, update the equipment route array Hg, and update the equipment route array Hg in sequence according to the feature matching formula to obtain the equipment coordinates of the target industrial equipment corresponding to the several processes in the gth target processing route, and generate the product production route information of the gth target processing route; Step S308: obtaining product production route information in the plurality of target processing routes, and generating target processing data of the target product to be processed; Step S400: Acquire target processing data of the target product to be processed in the current cycle, adjust the industrial production line of the industrial enterprise in the current cycle, and intelligently manage the industrial production data.

2. According to claim 1, an intelligent data analysis method based on an intelligent Internet of Things platform is characterized in that: The step S400 includes: Step S401: acquiring target processing data of each target product to be processed in the industrial production line in the current cycle; Step S402: Based on the target processing data and the target industrial equipment for processing the target products to be processed, the target products to be processed in the industrial production line within the current cycle are processed and the industrial production data are intelligently managed.

3. An intelligent data analysis system based on an intelligent Internet of Things platform, used to execute an intelligent data analysis method based on an intelligent Internet of Things platform as described in any one of claims 1-2, characterized in that: The system includes a target product to be processed module, a target industrial equipment module, a target processing data module, and an intelligent management module; The target product to be processed module is used to analyze the influence of the product to be processed on the product production of the industrial production line to obtain the target product to be processed; The target industrial equipment module is used to analyze the compatibility of industrial equipment in the industrial production line with the equipment of the target product to be processed to obtain the target industrial equipment; The target processing data module is used to analyze the different equipment processing routes between target industrial equipment, the degree of influence on the production of the target product to be processed, and generate target processing data of the target product to be processed; The intelligent management module is used to adjust the industrial production lines of industrial enterprises in the current cycle and to intelligently manage industrial production data.

4. The intelligent data analysis system based on the intelligent Internet of Things platform according to claim 3 is characterized in that: The target product to be processed module includes a characteristic production volume unit and a target product to be processed unit; The characteristic production volume unit is used to calculate the characteristic production volume of the product to be processed in the current cycle; The target product to be processed unit is used to obtain the target product to be processed of the industrial production line in the current cycle according to the characteristic production volume.

5. The intelligent data analysis system based on the intelligent Internet of Things platform according to claim 3 is characterized in that: The target industrial equipment module includes a characteristic equipment adaptation value unit and a target industrial equipment unit; The characteristic equipment adaptation value unit is used to calculate the characteristic equipment adaptation values ​​of several processes of the selected industrial equipment and the target product to be processed; The target industrial equipment unit is used to acquire the target industrial equipment of the several processes of the target product to be processed according to the characteristic equipment adaptation value.

6. The intelligent data analysis system based on the intelligent Internet of Things platform according to claim 3 is characterized in that: The target processing data module includes a target processing route unit and a target processing data unit; The target processing route unit is used to analyze the different equipment processing routes between target industrial equipment, the degree of influence on the production of the target product to be processed, and plan several target processing routes of the target product to be processed; The target processing data unit is used to obtain product production route information in the plurality of target processing routes to generate target processing data of the target product to be processed.

7. The intelligent data analysis system based on the intelligent Internet of Things platform according to claim 3 is characterized in that: The intelligent management module includes an intelligent management unit; The intelligent management unit is used to produce and process the target products to be processed in the industrial production line within the current cycle, and to intelligently manage the industrial production data.

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