Industrial manufacturing equipment intelligent control system based on Internet of Things

Abstract

The invention relates to the technical field of industrial automation, in particular to an industrial manufacturing equipment intelligent control system based on the Internet of Things, which comprises a manufacturing data acquisition module used for acquiring equipment parameters of manufacturing equipment and demand parameters of manufactured products, a real-time data acquisition module used for acquiring workshop environment data and equipment operation data in real time, and a processing module used for processing the workshop environment data and the equipment operation data. The product parameter analysis module is used for dividing manufacturing demand levels and constructing a demand standard index according to a division result, the manufacturing environment monitoring module is used for analyzing the environmental abnormality of a workshop, and the equipment monitoring module is used for monitoring the environmental abnormality of the workshop. The monitoring module is used for analyzing the operation state of each piece of manufacturing equipment in a workshop according to the equipment operation data collected in the monitoring period and analyzing the operation state of a production line according to the analysis result, and the equipment control module is used for controlling the manufacturing equipment in the next monitoring period. According to the invention, the equipment control efficiency in the industrial manufacturing process is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial automation, and in particular to an intelligent control system for industrial manufacturing equipment based on the Internet of Things. Background Art

[0002] With the development of information technology, especially the advancement of Internet of Things technology, new development opportunities have been brought to the traditional manufacturing industry. By connecting various sensors, actuators and other devices and using the Internet to achieve information exchange and communication, production efficiency can be greatly improved, operating costs can be reduced, and product quality can be improved. However, in actual applications, due to compatibility issues between devices provided by different manufacturers and the lack of unified data standards, most solutions on the current market are difficult to achieve the expected results.

[0003] Chinese patent publication number CN108508856A discloses an intelligent control system and method for industrial equipment, the system includes: an RT module, an AI module and an APP module; wherein: the RT module is connected to the industrial equipment through an interface, obtains the field data of the industrial equipment, processes the field data, and transmits the processing result data to the AI ​​module and the APP module; the AI ​​module performs intelligent analysis on the received processing result data, and transmits the intelligent analysis result to the APP module connected thereto; the APP module includes a plurality of APPs with multiple functions, and judges and controls the analysis results, sends feedback signals to the RT module to implement a closed-loop control strategy, sends feedback signals to the AI ​​module to implement parameter adjustment of the artificial intelligence model, and the APP module also includes an APP interface for data transmission; it can be seen that the invention only analyzes the operating data of the industrial equipment to obtain the operating status of the equipment, does not analyze the impact of the construction environment on the equipment, cannot achieve efficient control of the equipment in the industrial manufacturing process, and has the problem of low control efficiency of the manufacturing equipment. Summary of the invention

[0004] The object of the present invention is to provide an intelligent control system for industrial manufacturing equipment based on the Internet of Things to solve at least one of the problems existing in the prior art.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] An intelligent control system for industrial manufacturing equipment based on the Internet of Things, characterized by comprising:

[0007] A manufacturing data acquisition module is used to obtain equipment parameters of manufacturing equipment and demand parameters of manufacturing products;

[0008] Real-time data collection module, used to collect workshop environment data and equipment operation data in real time;

[0009] Product parameter analysis module, used to classify manufacturing demand levels according to the demand parameters of manufactured products, and to construct a demand standard index based on the classification results;

[0010] The manufacturing environment monitoring module is used to analyze the abnormality of particle concentration, electromagnetic interference and vibration in the workshop according to the workshop environment data collected during the monitoring period and the demand standard index, and analyze the abnormality of the workshop environment according to the analysis results of the abnormality of particle concentration, electromagnetic interference and vibration;

[0011] The equipment monitoring module is used to analyze the operating status of each manufacturing equipment in the workshop according to the equipment operation data collected during the monitoring period, and analyze the operating status of the production line according to the analysis results;

[0012] The equipment control module is used to control the manufacturing equipment of the next monitoring cycle according to the results of the workshop environment abnormality analysis and the production line operation status analysis.

[0013] Furthermore, the product parameter analysis module is provided with a product demand analysis unit, and the product demand analysis unit is used to analyze the manufacturing demand level of the manufacturing product according to the demand parameters of the manufacturing product, and the manufacturing demand level of the manufacturing product includes level one, level two and level three;

[0014] The product parameter analysis module further includes a manufacturing standard construction unit, which is used to construct a demand standard index according to the manufacturing demand level of the manufactured product.

[0015] Furthermore, the environmental monitoring module includes an electrostatic monitoring unit, which is used to analyze the electromagnetic interference abnormality of the workshop according to the electromagnetic field strength within the monitoring period. The analysis results of the electromagnetic interference abnormality include normal and abnormal, and when the electromagnetic interference abnormality is normal, the electromagnetic influence factor is set to DC1; when the electromagnetic interference is abnormal, the electromagnetic influence factor is set to DC2.

[0016] Furthermore, the environmental monitoring module also includes a particle monitoring unit, which is used to compare the particle concentration ρ within the monitoring period with the preset particle concentration P, and analyze the abnormality of the particle concentration in the workshop based on the comparison result. The analysis results of the abnormality of the particle concentration in the workshop include normal and abnormal, and when the particle concentration in the workshop is normal, the dust impact factor is set to CA1; when the particle concentration in the workshop is abnormal, the dust impact factor is set to CA2.

[0017] Furthermore, the environmental monitoring module also includes a vibration monitoring unit, which is used to analyze the vibration abnormality of the workshop according to the vibration data within the monitoring period. The vibration abnormality analysis results of the workshop include normal vibration and abnormal vibration. When the vibration of the workshop is normal, the vibration influence factor is set to ZD1; when the vibration of the workshop is abnormal, the vibration influence factor is set to ZD2.

[0018] Furthermore, the environmental monitoring unit also includes an abnormality analysis unit, which is used to analyze the environmental abnormalities of the workshop based on the electromagnetic interference abnormality analysis results, the vibration abnormality analysis results and the particle concentration abnormality analysis results within the monitoring period. The environmental abnormalities of the workshop include normal and abnormal.

[0019] Furthermore, the equipment monitoring module also includes an equipment status analysis unit, which is used to analyze the operating status of each manufacturing equipment according to the equipment operation data collected during the monitoring period, and the operating status of each manufacturing equipment includes normal and abnormal.

[0020] Furthermore, the equipment monitoring module also includes an error analysis unit, and the equipment status analysis unit is used to analyze the error status of each manufacturing equipment within the monitoring period according to the calibration current and calibration voltage of each manufacturing equipment within the monitoring period, and the analysis results of the error status of each manufacturing equipment include normal and abnormal, and when the error status of the i-th manufacturing equipment is abnormal, the standard status index of the i-th manufacturing equipment in the workshop is adjusted to R(i)'.

[0021] Furthermore, the equipment monitoring module further includes a workshop operation analysis unit, which is used to analyze the production line operation status according to the operation status analysis results of each manufacturing equipment within the monitoring period and the demand standard index;

[0022] The workshop operation analysis unit counts the number YN of abnormal operation states of manufacturing equipment during the monitoring period, and calculates the abnormality ratio μ;

[0023] The workshop operation analysis unit compares the abnormality ratio μ with the preset abnormality ratio U, and analyzes the production line operation status according to the comparison result, and the production line operation status includes normal and abnormal.

[0024] Furthermore, the equipment control module is used to control the manufacturing equipment of the next monitoring cycle according to the results of the workshop environment abnormality analysis and the production line operation status analysis:

[0025] If the environmental abnormality of the workshop is normal and the production line operation status is normal, the equipment control module does not change the operation process of the manufacturing equipment in the next monitoring cycle;

[0026] If the environmental abnormality of the workshop is abnormal and the production line operation status is normal, the equipment control module sets the production rate of the production line in the workshop in the next monitoring cycle to XV', setting XV' = XV × [1-(b1 × electromagnetic influence factor + b2 × dust influence factor + b3 × vibration influence factor-Y) / Y];

[0027] If the environmental abnormality of the workshop is normal and the production line operation state is abnormal, the equipment control module sets the equipment power of the abnormal operation state of the manufacturing equipment in the next monitoring cycle to P(i)', and sets P(i)'=P(i)×{1-[r(i)-R(i)] / R(i)};

[0028] If the environmental abnormality of the workshop is abnormal and the operation status of the production line is abnormal, the equipment control module suspends the operation of each equipment in the workshop and alerts the user;

[0029] Where P(i) is the rated power of the i-th manufacturing equipment, XV is the production rate of the production line in the workshop during the current monitoring period

[0030] Compared with the prior art, the beneficial effects of the present invention are: by dividing the manufacturing demand levels of manufactured products and setting the demand standard index according to the division results, different judgment standards are set according to the manufacturing difficulty of the manufactured products, and by analyzing the environmental abnormalities and production line operation status in the workshop, a multi-dimensional analysis of the workshop manufacturing conditions and manufacturing process is performed, and finally specific parameter control of each manufacturing equipment is given, thereby improving the efficiency of equipment control in the industrial manufacturing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0032] Figure 1 This is a schematic diagram of the structure of an intelligent control system for industrial manufacturing equipment based on the Internet of Things in this embodiment.

[0033] Figure 2 Schematic diagram of the structure of the product parameter analysis module of this embodiment.

[0034] Figure 3 This is a schematic diagram of the structure of the environment monitoring module manufactured in this embodiment.

[0035] Figure 4 Schematic diagram of the structure of the equipment monitoring module in this embodiment. DETAILED DESCRIPTION

[0036] In order to more clearly illustrate the present invention, the present invention is further described below in conjunction with preferred embodiments and accompanying drawings. Similar components in the accompanying drawings are represented by the same reference numerals. It should be understood by those skilled in the art that the content specifically described below is illustrative rather than restrictive, and should not be used to limit the scope of protection of the present invention.

[0037] It should be noted that, although the terms first, second, third, etc. may be used to describe in the embodiments of the present application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of the present application, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0038] Specifically, the IoT-based intelligent control system for industrial manufacturing equipment described in this embodiment is applied to the control of manufacturing equipment in a dust-free intelligent manufacturing workshop; the dust-free intelligent manufacturing workshop described in this embodiment is specifically an industrial manufacturing workshop that produces products through computer-controlled manufacturing equipment, and the products described in this embodiment are specifically electronic products; the system described in this embodiment is installed in the workshop master control server.

[0039] See also Figure 1 As shown, it is a structural diagram of the industrial equipment intelligent manufacturing control system based on the Internet of Things described in this embodiment, including:

[0040] A manufacturing data acquisition module is used to obtain equipment parameters of manufacturing equipment and required parameters of manufactured products; the equipment parameters of the manufacturing equipment include standard values ​​of workshop magnetic field strength, standard values ​​of workshop electric field strength, standard vibration amplitude of workshop construction level, standard vibration frequency of workshop construction level, set voltage of manufacturing equipment and set current of manufacturing equipment; the required parameters of the product include the number of electronic components of the manufactured product and the number of lines between the electronic components of the manufactured product.

[0041] Specifically, this embodiment does not specifically limit the method for obtaining the equipment parameters of the manufacturing equipment and the required parameters of the manufacturing products. Those skilled in the art can set it freely as long as the requirements for obtaining the equipment parameters of the manufacturing equipment and the required parameters of the manufacturing products are met. This embodiment obtains the standard value of the workshop magnetic field strength, the standard value of the workshop electric field strength, the standard vibration amplitude of the workshop construction level, the standard vibration frequency of the workshop construction level, the set voltage of the manufacturing equipment, and the set current of the manufacturing equipment through the construction indicators of the dust-free workshop; and obtains the required parameters of the manufacturing products through user interactive input.

[0042] Please continue reading Figure 1As shown, the system also includes a real-time data acquisition module for real-time acquisition of workshop environment data and equipment operation data; the workshop environment data includes the electric field strength of the workshop, the magnetic field strength of the workshop, the particle concentration, the vibration amplitude of the workshop and the vibration frequency of the workshop; the equipment operation data includes the number of error products of the manufacturing equipment, the total number of manufactured products of the manufacturing equipment, the calibration current of the manufacturing equipment, the calibration voltage of the manufacturing equipment, the rated power of the manufacturing equipment and the production rate of the production line.

[0043] Specifically, the method for collecting workshop environment data and equipment operation data in this embodiment is to collect them through various sensors (particle concentration sensors, electromagnetic sensors, vibration detection sensors, etc.), and send the collected workshop environment data and equipment operation data to the workshop master control server through the Internet of Things; the specific collection and sending process has been described in detail in the prior art, and will not be repeated in this embodiment.

[0044] Please continue reading Figure 1 As shown, the system also includes a product parameter analysis module, which is connected to the manufacturing data acquisition module. The product parameter analysis module is used to analyze the manufacturing demand level according to the demand parameters of the manufactured products and construct a demand standard index according to the division results.

[0045] See also Figure 2 As shown, the product parameter analysis module is provided with a product demand analysis unit, and the product demand analysis unit is used to analyze the manufacturing demand level of the manufacturing product according to the demand parameters of the manufacturing product, so as to accurately determine the manufacturing difficulty of the manufacturing product;

[0046] The product demand analysis unit calculates the product demand index α according to the demand parameters of the manufactured product, setting α=log 10 n / log 10 xn; where n is the number of electronic components in the manufactured product, and xn is the number of circuits between the electronic components in the manufactured product;

[0047] The product demand analysis unit compares the product demand index α with each preset product demand index, and divides the manufacturing demand level of the manufactured product according to the comparison result: if α<A1, the product demand analysis unit determines that the manufacturing demand level of the manufactured product is level three; if A1≤α<A2, the product demand analysis unit determines that the manufacturing demand level of the manufactured product is level two; if α≥A2, the product demand analysis unit determines that the manufacturing demand level of the manufactured product is level one; wherein A1 is the first preset product demand index, A2 is the second preset product demand index, and A1<A2; by calculating the product demand index of the manufactured product, the manufacturing difficulty of the manufactured product is quantified, and then the manufacturing demand level of the manufactured product is analyzed, so as to achieve accurate judgment of the manufacturing scenario requirements, which is convenient for the subsequent setting of its demand standard index.

[0048] Specifically, this embodiment does not make any specific restrictions on the values ​​of the first preset product demand index A1 and the second preset product demand index A2. Those skilled in the art can set them freely as long as the value requirements of the first preset product demand index A1 and the second preset product demand index A2 are met. In this embodiment, the first preset product demand index A1 is set to 0.7, and the second preset product demand index A2 is set to 0.9; it can be understood that the number of electronic components of the manufactured product described in this embodiment is the total number of electronic components used to produce electronic products. The electronic components described in this embodiment include electronics, capacitors, diodes, semiconductor chips, etc.

[0049] Please continue reading Figure 2 As shown, the product parameter analysis module also includes a manufacturing standard construction unit, which is connected to the product demand analysis unit. The manufacturing standard construction unit is used to construct a demand standard index according to the manufacturing demand level analysis result of the manufactured product: if the manufacturing demand level of the manufactured product is level three, the manufacturing standard construction unit sets the demand standard index to β1, and sets β1=α 2 ; If the manufacturing demand level of the manufactured product is level two, the manufacturing standard construction unit sets the demand standard index to β2, and sets β2=α; If the manufacturing demand level of the manufactured product is level one, the manufacturing standard construction unit sets the demand standard index to β3, and sets β3=ln(1+α); Through different incremental degree curves, the demand standard index is set to fit the needs of the actual demand standard, thereby realizing accurate calculation of the demand standard index.

[0050] Please continue reading Figure 1As shown, the system also includes a manufacturing environment monitoring module, which is connected to the real-time data acquisition module and the product parameter analysis module. The manufacturing environment monitoring module is used to analyze the environmental abnormalities of the workshop based on the workshop environment data collected during the monitoring period and the manufacturing requirement level of the manufactured products.

[0051] Specifically, this embodiment does not impose any specific limitation on the value of the duration of the monitoring period, and those skilled in the art can freely set it as long as the value requirement of the duration of the monitoring period is met. In this embodiment, the duration of the monitoring period is 10 minutes.

[0052] See also Figure 3 As shown, the environmental monitoring module includes an electrostatic monitoring unit, which is used to analyze the abnormality of electromagnetic interference in the workshop according to the electromagnetic field strength during the monitoring period, so as to realize the abnormal judgment of electromagnetic interference in the workshop, and construct an electromagnetic influence factor according to the abnormality analysis result of electromagnetic interference: if e / E×a1+b / B×a2<F×demand standard index, the electrostatic monitoring unit determines that the electromagnetic interference is normal during the monitoring period, and sets the electromagnetic influence factor to DC1, setting DC1=DC; if e / E×a1+b / B×a2≥F×demand standard index, the electrostatic monitoring unit determines that the electromagnetic interference is abnormal during the monitoring period, and sets the electromagnetic influence factor to DC1=DC. The factor is set to DC2, and DC2=DC×[1+(e / E×a1+b / B×a2-F) / F] is set; wherein, a1 is the electric field strength influence factor, a2 is the magnetic field strength influence factor, a1+a2=1 and a1>a2, F is the preset electromagnetic interference index, e is the electric field strength of the workshop during the monitoring period, b is the magnetic field strength of the workshop during the monitoring period, E is the standard value of the electric field strength of the workshop, B is the standard value of the magnetic field strength of the workshop, and DC is the standard electromagnetic influence constant; by comprehensively analyzing the two-way interference of the electric field and the magnetic field to determine whether the interference will affect the manufacturing process of the manufactured product, accurate judgment of the abnormality of the electromagnetic interference is achieved.

[0053] Specifically, this embodiment does not impose any specific limitation on the value of the preset electromagnetic interference index F. Those skilled in the art can set it freely as long as the value requirement of the preset electromagnetic interference index F is met. In this embodiment, the preset electromagnetic interference index F is set to 0.1; at the same time, the value of the standard influence constant DC in this embodiment is 1.

[0054] Please continue reading Figure 3As shown, the environmental monitoring module also includes a particle monitoring unit, which is used to compare the particle concentration ρ within the monitoring period with the preset particle concentration P, and analyze the abnormality of the particle concentration in the workshop according to the comparison result, so as to realize real-time monitoring of the dust-free demand of the workshop, and to construct a dust impact factor according to the analysis result: if ρ<P×demand standard index, the particle monitoring unit determines that the particle concentration in the workshop is normal, and sets the dust impact factor to CA1, and sets CA1=CA; if ρ≥P×demand standard index, the particle monitoring unit determines that the particle concentration in the workshop is abnormal, and sets the dust impact factor to CA2, and sets CA2=CA+(ρ-P) / P; wherein CA is the standard particle impact constant; the requirement of the electronic product of this embodiment for the particle concentration is a necessary requirement in the etching manufacturing process, and through real-time monitoring of the particle concentration, accurate judgment of the particle concentration in the on-site environment can be achieved.

[0055] Specifically, this embodiment does not impose any specific limitation on the value of the preset particle concentration P. Those skilled in the art can set it freely as long as the value requirement of the preset particle concentration P is met. In this embodiment, the preset particle concentration P is set to 1000 particles / cubic meter; at the same time, the value of the standard particle influence constant CA in this implementation is 0.

[0056] Please continue reading Figure 3 As shown, the environment monitoring module also includes a vibration monitoring unit, which is used to analyze the vibration abnormality of the workshop according to the vibration data within the monitoring period, and construct a vibration influence factor according to the analysis result of the vibration abnormality: if k<K×demand standard index, the vibration monitoring unit determines that the vibration of the workshop within the monitoring period is normal, and sets the vibration influence factor to ZD1, and sets ZD1=ZD; if k≥K×demand standard index, the vibration monitoring unit determines that the vibration of the workshop within the monitoring period is abnormal, and sets the vibration influence factor to ZD2, and sets ZD2=exp[(kK) / K]; wherein k is the vibration abnormality index within the monitoring period, K is the preset vibration abnormality index, and k=exp{(gG) / G+(vV) / V} is set, g is the vibration amplitude of the workshop during the monitoring period, v is the vibration frequency of the workshop during the monitoring period, G is the preset vibration amplitude of the workshop, V is the preset vibration frequency of the workshop, and ZD is the standard vibration influence constant; through a comprehensive analysis of the workshop vibration, it is determined whether the vibration in its manufacturing environment meets the manufacturing requirements of the manufactured products, thereby achieving an accurate judgment of the vibration abnormality of the workshop.

[0057] Specifically, this embodiment does not impose any specific limitation on the value of the preset vibration abnormality index K. Those skilled in the art can set it freely as long as the value requirement of the preset vibration abnormality index K is met. In this embodiment, the value of the preset vibration abnormality index K is 1.3; at the same time, the values ​​of the vibration amplitude G of the preset workshop and the vibration frequency V of the preset workshop described in this embodiment are 90% of the standard value of the workshop construction level (including the standard vibration amplitude of the workshop construction level and the standard vibration frequency of the workshop construction level); in this embodiment, the value of the standard vibration influence constant ZD is 0.

[0058] Please continue reading Figure 3 As shown, the environment monitoring unit also includes an abnormality analysis unit, which is connected to the electrostatic monitoring unit, the vibration monitoring unit and the particle monitoring unit, and is used to analyze the environmental abnormality of the workshop according to the electromagnetic interference abnormality analysis result, the vibration abnormality analysis result of the workshop and the particle concentration abnormality analysis result within the monitoring period: if b1×electromagnetic influence factor+b2×dust influence factor+b3×vibration influence factor<Y, the abnormality analysis unit determines that the environment of the workshop within the monitoring period is normal; if b1×electromagnetic influence factor+b2×dust influence factor+b3×vibration influence factor≥Y, the abnormality analysis unit determines that the environment of the workshop within the monitoring period is abnormal;

[0059] Among them, Y is the preset workshop environment judgment constant, b1 is the electromagnetic weight, b2 is the dust weight, b3 is the vibration weight, and b1+b2+b3=1; by setting the weights, the abnormality of the three environmental factors that have a direct impact on the manufacturing process is comprehensively considered, and the abnormality of the environment in the workshop is judged, thereby achieving accurate judgment of environmental abnormalities and improving the accuracy and efficiency of specific control of manufacturing equipment.

[0060] Specifically, the relationship between the electromagnetic weight b1, the dust weight b2 and the vibration weight b3 in this embodiment is as follows: if n is less than 20, then b2≤b3≤b2; if n≥20, then b3≤b1≤b2; this embodiment only sets the relationship, and the specific value is determined according to the actual situation. In this embodiment, b1=0.3, b2=0.5, b3=0.2; at the same time, this embodiment does not make specific limitations on the value of the preset workshop environment judgment constant Y. Those skilled in the art can freely set it as long as the value requirement of the preset workshop environment judgment constant Y is met. In this embodiment, the preset workshop environment judgment constant Y is set to 3.5.

[0061] Please continue reading Figure 1As shown, the system also includes an equipment monitoring module, which is connected to the product parameter analysis module and the real-time data acquisition module. The equipment monitoring module is used to analyze the production line operation status based on the equipment operation data collected during the monitoring period.

[0062] See also Figure 4 As shown, the equipment monitoring module also includes an equipment status analysis unit, which is used to analyze the operating status of each manufacturing equipment according to the equipment operation data collected during the monitoring period, so as to realize real-time monitoring of the operating status of a single manufacturing equipment: if r(i)<R(i)×demand standard index, the equipment status analysis unit determines that the operating status of the i-th manufacturing equipment is normal; if r(i)≥R(i)×demand standard index, the equipment status analysis unit determines that the operating status of the i-th manufacturing equipment is abnormal;

[0063] Among them, r(i) is the state index of the i-th manufacturing equipment in the workshop during the monitoring period, r(i)=η(i) / sv(i), η(i) is the number of error products of the i-th manufacturing equipment during the monitoring period, sv(i) is the total number of manufacturing products passing through the i-th manufacturing equipment during the monitoring period, R(i) is the standard state index of the i-th manufacturing equipment in the workshop, i=1,2...N, N is the number of manufacturing equipment in the workshop; by reflecting the operating status of each manufacturing equipment on the status of the actual manufactured products, accurate judgment of the operating status of the manufacturing equipment is achieved, and then accurate judgment of the operating status of the production line is achieved, and finally the accuracy and efficiency of the specific control of the manufacturing equipment are improved.

[0064] Specifically, this embodiment does not impose any specific restrictions on the value of the standard status index of each manufacturing equipment in the workshop. It only needs to meet the value requirements of the standard status index of each manufacturing equipment in the workshop. In this embodiment, the rated data of each manufacturing equipment is substituted into the calculation formula of the status index of each manufacturing equipment in the workshop during the monitoring period, and the calculation result is used as the standard status index of the manufacturing equipment. As an example, the calculation formula of the standard status index of the first manufacturing equipment is R(1)=BN(1) / BSV(1), BN(1) is the maximum error ratio of the first manufacturing equipment, and BSV(1) is the manufacturing product rate of the first manufacturing equipment.

[0065] Please continue reading Figure 4As shown, the equipment monitoring module also includes an error analysis unit, which is connected to the equipment status analysis unit. The equipment status analysis unit is used to analyze the error status of each manufacturing equipment in the monitoring period according to the calibration current and calibration voltage of each manufacturing equipment in the monitoring period, so as to realize the real-time calculation of the error of a single manufacturing equipment in the manufacturing process, and adjust the analysis process of the operating status of the manufacturing equipment according to the error status analysis results of each manufacturing equipment: if c1×j(i) / JI(i)+c2×ju(i) / JU (i)<γ, the error analysis unit determines that the error state of the i-th manufacturing equipment in the monitoring period is normal and does not make adjustments; if c1×j(i) / JI(i)+c2×ju(i) / JU(i)≥γ, the error analysis unit determines that the error state of the i-th manufacturing equipment in the monitoring period is abnormal, and adjusts the standard state index of the i-th manufacturing equipment in the workshop to R(i)', setting R(i)'=R(i)×ln{2-[c1×j(i) / JI(i)+c2×ju(i) / JU(i)-γ] / Y};

[0066] Among them, γ is the calibration offset error value, j(i) represents the calibration current of the i-th manufacturing equipment in the monitoring period, JI(i) represents the set current of the i-th manufacturing equipment in the monitoring period, ju(i) represents the calibration voltage of the i-th manufacturing equipment in the monitoring period, JU(i) represents the set voltage of the i-th manufacturing equipment in the monitoring period, c1 is the current error weight, c2 is the voltage error weight, c1+c2=1; by making real-time judgment on the error state of a single device and adjusting the analysis process of the operating state of the manufacturing equipment, the accuracy of the operating state analysis of the manufacturing equipment is improved, thereby realizing accurate judgment of the operating state of the production line, and finally improving the accuracy and efficiency of the specific control of the manufacturing equipment.

[0067] Specifically, this embodiment does not impose any specific limitation on the value of the calibration offset error value γ, and those skilled in the art can freely set it as long as the value requirement of the calibration offset error value γ is met. In this embodiment, the value of the calibration offset error value γ is 0.05.

[0068] Please continue reading Figure 4 As shown, the equipment monitoring module also includes a workshop operation analysis unit, which is connected to the equipment monitoring unit, and the workshop operation analysis unit is used to analyze the production line operation status according to the operation status analysis results of each manufacturing equipment within the monitoring period and the demand standard index;

[0069] The workshop operation analysis unit counts the number YN of abnormal operating states of manufacturing equipment during the monitoring period, and calculates the abnormality ratio μ, setting μ=YN / N;

[0070] The workshop operation analysis unit compares the abnormality ratio μ with the preset abnormality ratio U, and analyzes the operation status of the production line according to the comparison result: if μ<U, the workshop operation analysis unit determines that the operation status of the production line within the monitoring period is normal; if μ≥U, the workshop operation analysis unit determines that the operation status of the production line within the monitoring period is abnormal.

[0071] Specifically, this embodiment does not specifically limit the value of the preset abnormality ratio U, and those skilled in the art can freely set it as long as the value requirement of the preset abnormality ratio U is met. In this embodiment, the preset abnormality ratio U is set to 0.1.

[0072] Please continue reading Figure 1 As shown, the system further includes an equipment control module, which is connected to the equipment monitoring module and the environment monitoring module, and is used to control the manufacturing equipment of the next monitoring cycle according to the environmental abnormality analysis results of the workshop and the production line operation status analysis results:

[0073] If the environmental abnormality of the workshop is normal and the production line operation status is normal, the equipment control module does not change the operation process of the manufacturing equipment in the next monitoring cycle;

[0074] If the environmental abnormality of the workshop is abnormal and the production line operation status is normal, the equipment control module sets the production rate of the production line in the workshop in the next monitoring cycle to XV', setting XV' = XV × [1-(b1 × electromagnetic influence factor + b2 × dust influence factor + b3 × vibration influence factor-Y) / Y];

[0075] If the environmental abnormality of the workshop is normal and the production line operation state is abnormal, the equipment control module sets the equipment power of the abnormal operation state of the manufacturing equipment in the next monitoring cycle to P(i)', and sets P(i)'=P(i)×{1-[r(i)-R(i)] / R(i)};

[0076] If the environmental abnormality of the workshop is abnormal and the operation status of the production line is abnormal, the equipment control module suspends the operation of each equipment in the workshop and alerts the user;

[0077] Among them, P(i) is the rated power of the i-th manufacturing equipment, and XV is the production rate of the production line in the workshop during the current monitoring period. By controlling the production rate of the production line and the operating power of each equipment, local fine control based on the overall production line can be achieved to ensure the orderly and normal operation of the manufacturing process of the manufacturing equipment in the workshop, thereby improving the accuracy and efficiency of the specific control of the manufacturing equipment.

[0078] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. An intelligent control system for industrial manufacturing equipment based on the Internet of Things, characterized in that: include: A manufacturing data acquisition module is used to obtain equipment parameters of manufacturing equipment and demand parameters of manufacturing products; Real-time data collection module, used to collect workshop environment data and equipment operation data in real time; Product parameter analysis module, used to classify manufacturing demand levels according to the demand parameters of manufactured products, and to construct a demand standard index based on the classification results; The manufacturing environment monitoring module is used to analyze the abnormality of particle concentration, electromagnetic interference and vibration in the workshop according to the workshop environment data collected during the monitoring period and the demand standard index, and analyze the abnormality of the workshop environment according to the analysis results of the abnormality of particle concentration, electromagnetic interference and vibration; The equipment monitoring module is used to analyze the operating status of each manufacturing equipment in the workshop according to the equipment operation data collected during the monitoring period, and analyze the operating status of the production line according to the analysis results; The equipment control module is used to control the manufacturing equipment of the next monitoring cycle according to the results of the workshop environment abnormality analysis and the production line operation status analysis.

2. The intelligent control system for industrial manufacturing equipment based on the Internet of Things according to claim 1 is characterized in that: The product parameter analysis module is provided with a product demand analysis unit, and the product demand analysis unit is used to analyze the manufacturing demand level of the manufacturing product according to the demand parameters of the manufacturing product, and the manufacturing demand level of the manufacturing product includes level one, level two and level three; The product parameter analysis module further includes a manufacturing standard construction unit, which is used to construct a demand standard index according to the manufacturing demand level of the manufactured product.

3. The intelligent control system for industrial manufacturing equipment based on the Internet of Things according to claim 2 is characterized in that: The environmental monitoring module includes an electrostatic monitoring unit, which is used to analyze the electromagnetic interference abnormality of the workshop according to the electromagnetic field strength within the monitoring period. The analysis results of the electromagnetic interference abnormality include normal and abnormal. When the electromagnetic interference abnormality is normal, the electromagnetic influence factor is set to DC1; when the electromagnetic interference is abnormal, the electromagnetic influence factor is set to DC2.

4. The intelligent control system for industrial manufacturing equipment based on the Internet of Things according to claim 3 is characterized in that: The environmental monitoring module also includes a particle monitoring unit, which is used to compare the particle concentration ρ within the monitoring period with the preset particle concentration P, and analyze the abnormality of the particle concentration in the workshop based on the comparison result. The abnormality analysis results of the particle concentration in the workshop include normal and abnormal. When the particle concentration in the workshop is normal, the dust impact factor is set to CA1; when the particle concentration in the workshop is abnormal, the dust impact factor is set to CA2.

5. The intelligent control system for industrial manufacturing equipment based on the Internet of Things according to claim 4 is characterized in that: The environmental monitoring module also includes a vibration monitoring unit, which is used to analyze the vibration abnormality of the workshop according to the vibration data within the monitoring period. The vibration abnormality analysis results of the workshop include normal vibration and abnormal vibration. When the vibration of the workshop is normal, the vibration influence factor is set to ZD1; when the vibration of the workshop is abnormal, the vibration influence factor is set to ZD2.

6. The intelligent control system for industrial manufacturing equipment based on the Internet of Things according to claim 5 is characterized in that: The environmental monitoring unit also includes an abnormality analysis unit, which is used to analyze the environmental abnormality of the workshop according to the electromagnetic interference abnormality analysis results, the vibration abnormality analysis results and the particle concentration abnormality analysis results within the monitoring period. The environmental abnormality of the workshop includes normal and abnormal.

7. The intelligent control system for industrial manufacturing equipment based on the Internet of Things according to claim 6 is characterized in that: The equipment monitoring module also includes an equipment status analysis unit, which is used to analyze the operating status of each manufacturing equipment according to the equipment operation data collected during the monitoring period. The operating status of each manufacturing equipment includes normal and abnormal.

8. The intelligent control system for industrial manufacturing equipment based on the Internet of Things according to claim 7 is characterized in that: The equipment monitoring module also includes an error analysis unit, which is used to analyze the error state of each manufacturing equipment within the monitoring period according to the calibration current and calibration voltage of each manufacturing equipment within the monitoring period. The analysis results of the error state of each manufacturing equipment include normal and abnormal. When the error state of the i-th manufacturing equipment is abnormal, the standard state index of the i-th manufacturing equipment in the workshop is adjusted to R(i)'.

9. The intelligent control system for industrial manufacturing equipment based on the Internet of Things according to claim 8 is characterized in that: The equipment monitoring module also includes a workshop operation analysis unit, which is used to analyze the production line operation status according to the operation status analysis results of each manufacturing equipment within the monitoring period and the demand standard index; The workshop operation analysis unit counts the number YN of abnormal operation states of manufacturing equipment during the monitoring period, and calculates the abnormality ratio μ; The workshop operation analysis unit compares the abnormality ratio μ with the preset abnormality ratio U, and analyzes the production line operation status according to the comparison result, and the production line operation status includes normal and abnormal.

10. The intelligent control system for industrial manufacturing equipment based on the Internet of Things according to claim 9 is characterized in that: The equipment control module is used to control the manufacturing equipment of the next monitoring cycle according to the results of the workshop environment abnormality analysis and the production line operation status analysis: If the environmental abnormality of the workshop is normal and the production line operation status is normal, the equipment control module does not change the operation process of the manufacturing equipment in the next monitoring cycle; If the environmental abnormality of the workshop is abnormal and the production line operation status is normal, the equipment control module sets the production rate of the production line in the workshop in the next monitoring cycle to XV', setting XV' = XV × [1-(b1 × electromagnetic influence factor + b2 × dust influence factor + b3 × vibration influence factor-Y) / Y]; If the environmental abnormality of the workshop is normal and the production line operation state is abnormal, the equipment control module sets the equipment power of the abnormal operation state of the manufacturing equipment in the next monitoring cycle to P(i)', and sets P(i)'=P(i)×{1-[r(i)-R(i)] / R(i)}; If the environmental abnormality of the workshop is abnormal and the operation status of the production line is abnormal, the equipment control module suspends the operation of each equipment in the workshop and alerts the user; Where P(i) is the rated power of the i-th manufacturing equipment, and XV is the production rate of the production line in the workshop during the current monitoring period.

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