A data analysis system and method for intelligent manufacturing platform

Abstract

The invention relates to the field of intelligent manufacturing technology, and discloses a data analysis system and method for an intelligent manufacturing platform, which solves the technical problem in the prior art that the design composition adaptability analysis cannot be performed according to the type of intelligent manufacturing scene. Specifically, a scene analysis unit performs ship use scene analysis on a design front end, marks the designed ship as a stand-by object, obtains use scene requirement information of the stand-by object, substitutes the use scene requirement information into a formula to obtain a use scene requirement analysis coefficient, and divides the use scene by comparing the obtained use scene requirement analysis coefficient threshold; a composition adaptation analysis unit performs adaptability analysis on the design composition of the stand-by object, collects the composition adaptation information of the stand-by object, substitutes the composition adaptation information into a formula to obtain the composition adaptation analysis coefficient of the stand-by object, and judges whether the composition adaptation analysis is normal according to the comparison of the composition adaptation analysis coefficient threshold of the stand-by object.

Description

Technical Field

[0001] The present invention relates to the field of intelligent manufacturing technology, and in particular to a data analysis system and method for an intelligent manufacturing platform. Background Art

[0002] The data analysis system of the intelligent manufacturing platform is built based on advanced technologies such as big data, cloud computing, the Internet of Things and artificial intelligence. It aims to provide support for the company's intelligent decision-making by deeply mining and analyzing the massive data generated in the manufacturing process. The system can collect, process, analyze and display various types of data in real time, helping companies to achieve precise control, predictive optimization and decision support.

[0003] Intelligent manufacturing is a new manufacturing method. In the process of intelligent manufacturing, "digitalization, networking, and intelligence" have become important trends in technological change. Shipbuilding is developing towards intelligent design, intelligent products, refined management, and information integration. However, there are still some shortcomings in the use of intelligent manufacturing systems for ship design. Hull production design plays a very important role in the entire ship design process, and the accuracy of its data directly affects the accuracy of subsequent outfitting modeling and shipbuilding.

[0004] However, in the existing technology, it is impossible to analyze the use of intelligent manufacturing scenarios during ship design, and it is impossible to perform design component adaptability analysis based on the type of intelligent manufacturing scenario used, which reduces the efficiency of ship design and cannot ensure the feasibility of ship design.

[0005] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0006] The purpose of the present invention is to solve the above-mentioned problems and to propose a data analysis system and method for an intelligent manufacturing platform.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A data analysis system for an intelligent manufacturing platform includes a design management platform, wherein the design management platform is communicatively connected with a design front end and a design back end;

[0009] After the design management platform generates the design front-end instruction and sends it to the design front-end, the scenario analysis unit is used to analyze the ship usage scenario of the design front-end, the designed ship is marked as a stand-by object, the usage scenario requirement information of the stand-by object is obtained, and the usage scenario requirement information is substituted into the formula to obtain the usage scenario requirement sub-item coefficient, and the usage scenario requirement analysis coefficient is compared with the usage scenario requirement analysis coefficient threshold to complete the usage scenario division;

[0010] The component adaptation analysis unit performs adaptability analysis on the design components of the object to be used, marks the pipe fittings, valves and accessories of the object to be used as components, collects the component adaptation information of the object to be used, substitutes the component adaptation information into the formula to obtain the component adaptation analysis coefficient of the object to be used, and judges whether the component adaptation analysis is normal according to the comparison of the component adaptation analysis coefficient threshold of the object to be used;

[0011] The design progress supervision unit monitors and controls the implementation of the design of the objects to be used, obtains the stacking growth rate data and conveying error frequency data of the objects to be used, and determines whether the monitoring is normal based on the data threshold comparison. At the same time, the risk trend assessment unit assesses the design risk trend of the objects to be used, obtains the deformation data and usage data of the objects to be used, and determines whether the risk trend assessment is normal through data analysis.

[0012] As a preferred embodiment of the present invention, the usage scenario requirement information includes the reciprocating maximum interval value of the water depth in the water scene used by the stand-by object, the reciprocating floating span value of the wading depth of the hull when the stand-by object is stagnant in the water scene, and the maximum floating height value of the hull moving trajectory when the stand-by object moves in the water scene.

[0013] As a preferred implementation of the present invention, the usage scenario requirement analysis coefficient is compared with the usage scenario requirement analysis coefficient threshold range:

[0014] If the usage scenario demand analysis coefficient is lower than the minimum value of the usage scenario demand analysis coefficient threshold range, the usage scenario of the current standby object is set as a low demand scenario;

[0015] If the usage scenario demand analysis coefficient is higher than the minimum value of the usage scenario demand analysis coefficient threshold range, the usage scenario of the current standby object is set as a high demand scenario;

[0016] If the usage scenario demand analysis coefficient is at the minimum value of the usage scenario demand analysis coefficient threshold range, the usage scenario of the current standby object is set as a medium demand scenario.

[0017] As a preferred embodiment of the present invention, the composition adaptation information includes the maximum reduction in moving speed, the update speed of the floating height peak value, and the floating frequency of the actual power supply value; the composition adaptation analysis coefficient of the object to be used is compared with the composition adaptation analysis coefficient threshold:

[0018] If the composition adaptation analysis coefficient of the object to be used exceeds the composition adaptation analysis coefficient threshold, a composition adaptation analysis abnormal signal is generated and the composition adaptation analysis abnormal signal is sent to the design front end;

[0019] If the composition adaptation analysis coefficient of the object to be used does not exceed the composition adaptation analysis coefficient threshold, a composition adaptation analysis normal signal is generated and sent to the design front end.

[0020] As a preferred embodiment of the present invention, the stacking growth rate data and the conveying error frequency data are respectively the growth rate of the unused stacking amount of existing components corresponding to the component distribution time during the design and implementation of the stand-by object, and the error frequency of the conveying position of components of different sizes when assembling components of the same type during the design and implementation of the stand-by object.

[0021] As a preferred embodiment of the present invention, if the accumulation growth rate data exceeds the accumulation amount growth rate threshold, or the delivery error frequency data exceeds the delivery position error frequency threshold, a progress monitoring abnormality signal is generated and sent to the design backend;

[0022] If the accumulation growth rate data does not exceed the accumulation amount growth rate threshold, and the conveying error frequency data does not exceed the conveying position error frequency threshold, a normal progress monitoring signal is generated and sent to the design backend.

[0023] As a preferred embodiment of the present invention, the deformation data and usage data are respectively the percentage of the deformation amount of the components in the period between the time when the components are installed and the time when the manufacturing of the stand-by object is completed during the design and implementation stage of the stand-by object, and the floating amount of the speed difference between the installation consumption speed of the same type of components and the component supply speed during the design and implementation stage of the stand-by object.

[0024] As a preferred embodiment of the present invention, if the deformation data exceeds the deformation amount ratio threshold, or the usage data exceeds the speed difference floating amount threshold, an abnormal trend signal is generated and sent to the design backend;

[0025] If the deformation data does not exceed the deformation quantity ratio threshold, and the usage data does not exceed the speed difference floating amount threshold, a normal trend signal is generated and sent to the design backend.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. In the present invention, a ship usage scenario analysis is performed on the design front end, and combined with the current ship usage scenario analysis, the rationality of the current design model data management is improved to ensure that the design conforms to the actual usage scenario and avoid the incompatibility of the ship design affecting the design efficiency; the design composition of the object to be used is analyzed for adaptability to determine whether the adaptability of the design composition of the current object to be used meets the requirements, thereby ensuring that the design adaptability meets the design of the usage scenario and ensuring the ship design efficiency.

[0028] 2. In the present invention, the design implementation of the object to be used is monitored and controlled to ensure that the implementation efficiency is qualified during the ship design process, thereby improving the efficiency of ship design; the design risk trend of the object to be used is evaluated to improve the efficiency of the design implementation of the object to be used, ensure the real-time manufacturing progress of the object to be used, and avoid the abnormal progress of the object to be used causing a decrease in manufacturing feasibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0030] Figure 1 It is a principle block diagram of the present invention as a whole;

[0031] Figure 2 This is a principle block diagram of Embodiment 1 of the present invention;

[0032] Figure 3 This is a principle block diagram of the second embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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.

[0034] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0035] See also Figure 1 As shown, a data analysis system for an intelligent manufacturing platform includes a design management platform, wherein the design management platform is communicatively connected with a design front end and a design back end, wherein, in the actual ship design process, the design front end is used for comprehensive planning and design of ship component design and usage scenario analysis, and the design back end is used for implementing and processing the ship planning and design; Embodiment 1

[0036] Please refer to 2. At the design front end, after the design management platform generates a design front end instruction and sends it to the design front end, the design front end generates a usage scenario analysis signal and sends the usage scenario analysis signal to the usage scenario analysis unit. After the usage scenario analysis unit receives the usage scenario analysis signal, it performs a ship usage scenario analysis on the design front end, and combines the current ship usage scenario analysis to improve the rationality of the current design model data management, ensure that the design conforms to the actual usage scenario, and avoid the incompatibility of the ship design affecting the design efficiency;

[0037] Mark the designed ship as a standby object, obtain the maximum reciprocating interval value of the water depth in the water scene used by the standby object, and mark the maximum reciprocating interval value of the water depth in the water scene used by the standby object as JG, and at the same time obtain the reciprocating floating span value of the wading depth of the hull when the standby object is stagnant in the water scene and the maximum floating height value of the hull movement trajectory when the standby object moves in the water scene, and mark the reciprocating floating span value of the wading depth of the hull when the standby object is stagnant in the water scene and the maximum floating height value of the hull movement trajectory when the standby object moves in the water scene as SD and GD respectively;

[0038] The above collected data are uniformly marked as usage scenario demand information, and substituted into the formula to obtain the usage scenario demand analysis coefficient G, where the formula is , fa1, fa2 and fa3 are preset proportional coefficients of the maximum reciprocating interval value, the reciprocating floating span value and the maximum floating height value respectively, and e is a natural constant, and β is an error correction factor, which is set to 1.24;

[0039] Compare the usage scenario requirement analysis coefficient G with the usage scenario requirement analysis coefficient threshold range:

[0040] If the usage scenario demand analysis coefficient G is lower than the minimum value of the usage scenario demand analysis coefficient threshold range, the usage scenario of the current standby object is set as a low demand scenario;

[0041] If the usage scenario demand analysis coefficient G is higher than the minimum value of the usage scenario demand analysis coefficient threshold range, the usage scenario of the current standby object is set as a high demand scenario;

[0042] If the usage scenario demand analysis coefficient G is at the minimum value of the usage scenario demand analysis coefficient threshold range, the usage scenario of the current standby object is set as a medium demand scenario;

[0043] It can be understood that the scenario demand analysis coefficient used in this system is matched with the coefficient threshold range to be set, the demand analysis coefficient is obtained according to data collection and analysis, and the threshold comparison is performed according to the existing technology, that is, the scenario demand analysis coefficient that meets the design requirements in the design stage of the same type of ship in the historical design process, and the analysis coefficient threshold is obtained by averaging after the large volume coefficient value is collected and invalid data is processed; when used in actual use scenarios, the parameters such as the maximum reciprocating interval value of the water depth, the reciprocating floating span value of the wading depth, and the maximum floating height value of the moving trajectory, in real scenarios, their numerical influence is not limited to a fixed data, such as the water depth. According to the analysis of the ship's adaptive depth data, the ship's adaptive depth is also an interval value, and the numerical fluctuation of adjacent units has no effect on the use of the ship. Therefore, the threshold range is set in the threshold comparison process of the scenario demand analysis coefficient, and the threshold range is also updated in real time according to the real-time use of the analysis coefficient threshold to divide the range interval;

[0044] Invalid data processing means that after the design of the ship is completed in the historical period and the time threshold for the use scenario is reached, if there is a continuous failure, the corresponding analysis coefficient will be invalidated;

[0045] At the same time, a composition adaptation analysis signal is generated and sent to the composition adaptation analysis unit. After receiving the composition adaptation analysis signal, the composition adaptation analysis unit performs adaptability analysis on the design composition of the object to be used, and determines whether the adaptability of the design composition of the current object to be used meets the requirements, thereby ensuring that the design adaptability meets the design of the use scenario and ensuring the efficiency of ship design;

[0046] The pipe fittings, valves and accessories of the objects to be used are collected and marked as components. The components of the objects to be used are connected according to the corresponding connection methods to construct a virtual model diagram, and force is applied to the virtual model diagram according to the 3D simulation technology to simulate the force exerted on the hull by the water area in the use water scene; the maximum reduction in the moving speed of the current peak power of the object to be used when the lateral force is applied in the simulated use water scene is obtained, and the update speed of the peak floating height of the traveling trajectory of the object to be used under the current hull load when the longitudinal force is applied in the simulated use water scene is obtained, and the maximum reduction in the moving speed of the current peak power of the object to be used when the lateral force is applied in the simulated use water scene and the update speed of the peak floating height of the traveling trajectory of the object to be used under the current hull load when the longitudinal force is applied in the simulated use water scene are marked as ZDJD and GXSD respectively, wherein the technical solution of the present application performs speed simulation calculation according to the physical relationship between the moving speed and the friction force in the prior art, and the floating height is also simulated and calculated according to the physical mechanics in the prior art;

[0047] At the same time, the actual power supply value floating frequency of the moving direction of the standby object when the multi-directional force is applied in the simulated water scene is obtained, and the actual power supply value floating frequency of the moving direction of the standby object when the multi-directional force is applied in the simulated water scene is marked as DLSZ;

[0048] By formula The composition adaptation analysis coefficient GF of the standby object is obtained, wherein vb1, vb2 and vb3 are respectively the preset proportional coefficients of the maximum reduction in moving speed, the update speed of the floating height peak value and the floating frequency of the actual power supply value, and the maximum reduction in moving speed, the update speed of the floating height peak value and the floating frequency of the actual power supply value are uniformly marked as composition adaptation information, wherein α is an error factor, and when the water scene is a high-demand scene, the value is 1.2; when the water scene is a medium-demand scene, the value is 1.1; when the water scene is a low-demand scene, the value is 0.9;

[0049] Compare the composition adaptation analysis coefficient GF of the object to be used with the composition adaptation analysis coefficient threshold:

[0050] If the composition adaptation analysis coefficient GF of the object to be used exceeds the composition adaptation analysis coefficient threshold, the composition adaptation analysis of the object to be used is determined to be unqualified, a composition adaptation analysis abnormality signal is generated and sent to the design front end, and after the design front end receives it, the component of the object to be used is reselected or the use scenario of the object to be used is changed;

[0051] If the composition adaptation analysis coefficient GF of the standby object does not exceed the composition adaptation analysis coefficient threshold, the composition adaptation analysis of the standby object is determined to be qualified, a composition adaptation analysis normal signal is generated and sent to the design front end, and the design front end generates a front end normal signal after receiving it and sends the front end normal signal to the design management platform; Embodiment 2

[0052] After the design front end sends a normal signal, this embodiment is used to design the back end, and manage the ship design through the design back end to improve the design efficiency;

[0053] See also Figure 3 As shown, after the design management platform sends the design backend instruction to the design backend, the design backend generates a design progress supervision signal and sends the design progress supervision signal to the design progress supervision unit. After receiving the design progress supervision signal, the design progress supervision unit monitors and controls the design implementation of the object to be used, ensuring that the implementation efficiency in the ship design process is qualified, thereby improving the efficiency of ship design;

[0054] The growth rate of the unused accumulation amount of existing components corresponding to the distribution time of components in the process of design and implementation of the standby object is obtained, and the error frequency of the conveying position of components of different sizes when assembling components of the same type in the process of design and implementation of the standby object is obtained, and the growth rate of the unused accumulation amount of existing components corresponding to the distribution time of components in the process of design and implementation of the standby object and the error frequency of the conveying position of components of different sizes when assembling components of the same type in the process of design and implementation of the standby object are marked as accumulation growth rate data and conveying error frequency data, respectively, and compared with the accumulation growth rate threshold and the conveying position error frequency threshold, respectively:

[0055] If the growth rate of the unused accumulation amount of existing components corresponding to the distribution time of the components during the design and implementation of the standby object exceeds the accumulation growth rate threshold, or the delivery position error frequency of components of different sizes when assembling components of the same type during the design and implementation of the standby object exceeds the delivery position error frequency threshold, it is determined that there is an abnormality in the progress of the implementation of the standby object, and a progress monitoring abnormality signal is generated and sent to the design backend. After receiving the progress monitoring abnormality signal, the design backend controls the design process of the standby object;

[0056] If the growth rate of the unused accumulation amount of existing components corresponding to the distribution time of the components during the implementation of the design of the standby object does not exceed the accumulation growth rate threshold, and the delivery position error frequency of components of different sizes when assembling components of the same type during the implementation of the design of the standby object does not exceed the delivery position error frequency threshold, then it is determined that the progress of the implementation of the standby object is normal, a progress monitoring normal signal is generated and sent to the design backend;

[0057] At the same time, a risk trend assessment signal is generated and sent to a risk trend assessment unit. After receiving the risk trend assessment signal, the risk trend assessment unit assesses the design risk trend of the object to be used, thereby improving the efficiency of the design implementation of the object to be used, ensuring the real-time manufacturing progress of the object to be used, and avoiding the decrease in manufacturing feasibility due to abnormal progress of the object to be used;

[0058] The proportion of deformation variables of components in the period between the moment when the components are installed and the moment when the manufacturing of the standby object is finished in the design and implementation stage of the standby object is obtained, and at the same time, the floating amount of the speed difference between the installation consumption speed of the same type of components and the component supply speed in the design and implementation stage of the standby object is obtained, and the proportion of deformation variables of components in the period between the moment when the components are installed and the moment when the manufacturing of the standby object is finished in the design and implementation stage of the standby object and the floating amount of the speed difference between the installation consumption speed of the same type of components and the component supply speed in the design and implementation stage of the standby object are set as deformation data and usage data, respectively, and compared with the deformation variable quantity proportion threshold and the speed difference floating amount threshold, respectively:

[0059] If the proportion of deformation variables of components in the period between the moment when the installation of components is completed and the moment when the manufacturing of the standby object is finished during the design implementation stage of the standby object exceeds the threshold value of the proportion of deformation variables, or the floating amount of the speed difference between the installation consumption speed and the component supply speed of the same type of components during the design implementation stage of the standby object exceeds the threshold value of the speed difference floating amount, then it is determined that the risk trend assessment during the design implementation stage of the standby object is abnormal, an abnormal trend signal is generated and sent to the design backend, and after the design backend receives the abnormal trend signal, the design implementation of the standby object is suspended and the implementation is rectified to ensure the balance of component consumption and supply, and at the same time ensure the qualified rate of component installation;

[0060] If the proportion of deformation variables of components in the period between the moment when the components are installed and the moment when the manufacturing of the standby object is finished during the design and implementation stage of the standby object does not exceed the threshold value of the proportion of deformation variables, and the floating amount of the speed difference between the installation consumption speed and the supply speed of components of the same type during the design and implementation stage of the standby object does not exceed the threshold value of the speed difference floating amount, then it is determined that the risk trend assessment during the design and implementation stage of the standby object is normal, a normal trend signal is generated and sent to the design backend, and after the design backend receives the normal trend signal, a backend normal signal is generated and sent to the design management platform;

[0061] A data analysis method for an intelligent manufacturing platform, the specific steps are as follows:

[0062] Step 1: Perform ship usage scenario analysis on the design front end, mark the designed ship as a stand-by object, obtain the usage scenario requirement information of the stand-by object, substitute the usage scenario requirement information into the formula to obtain the usage scenario requirement analysis coefficient, and compare the usage scenario requirement analysis coefficient with the usage scenario requirement analysis coefficient threshold to complete the usage scenario division;

[0063] Step 2: Perform adaptability analysis on the design composition of the object to be used, mark the pipe fittings, valves and accessories of the object to be used as components, collect the composition adaptation information of the object to be used, substitute the composition adaptation information into the formula to obtain the composition adaptation analysis coefficient of the object to be used, and judge whether the composition adaptation analysis is normal based on the comparison of the composition adaptation analysis coefficient threshold of the object to be used.

[0064] Step 3: Monitor and control the design and implementation of the objects to be used, obtain the accumulation growth rate data and transmission error frequency data of the objects to be used, and judge whether the monitoring is normal based on the data threshold comparison;

[0065] Step 4: Evaluate the design risk trend of the object to be used, obtain the deformation data and usage data of the object to be used, and determine whether the risk trend evaluation is normal through data analysis.

[0066] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The coefficients in the formula are set by technicians in this field according to actual conditions;

[0067] When the present invention is in use, after the design management platform generates a design front-end instruction and sends it to the design front-end, the design front-end performs a ship usage scenario analysis, marks the designed ship as a stand-by object, obtains the usage scenario requirement information of the stand-by object, substitutes the usage scenario requirement information into a formula to obtain a usage scenario requirement analysis coefficient, and compares the usage scenario requirement analysis coefficient with a usage scenario requirement analysis coefficient threshold to complete the division of the usage scenario; the composition adaptation analysis unit performs adaptability analysis on the design composition of the stand-by object, marks the pipe fittings, valves and accessories of the stand-by object as components, collects the composition adaptation information of the stand-by object, substitutes the composition adaptation information into a formula to obtain the composition adaptation analysis coefficient of the stand-by object, and judges whether the composition adaptation analysis is normal based on the comparison of the composition adaptation analysis coefficient threshold of the stand-by object; the design progress supervision unit monitors and controls the design implementation of the stand-by object, and at the same time the risk trend assessment unit assesses the design risk trend of the stand-by object.

[0068] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A data analysis system for an intelligent manufacturing platform, characterized in that: It includes a design management platform, which is connected to a design front end and a design back end; After the design management platform generates the design front-end instruction and sends it to the design front-end, the scenario analysis unit is used to analyze the ship usage scenario of the design front-end, the designed ship is marked as a stand-by object, the usage scenario requirement information of the stand-by object is obtained, and the usage scenario requirement information is substituted into the formula to obtain the usage scenario requirement analysis coefficient, and the usage scenario requirement analysis coefficient is compared with the usage scenario requirement analysis coefficient threshold to complete the usage scenario division; The component adaptation analysis unit performs adaptability analysis on the design components of the object to be used, marks the pipe fittings, valves and accessories of the object to be used as components, collects the component adaptation information of the object to be used, substitutes the component adaptation information into the formula to obtain the component adaptation analysis coefficient of the object to be used, and judges whether the component adaptation analysis is normal according to the comparison of the component adaptation analysis coefficient threshold of the object to be used; The design progress supervision unit monitors and controls the design implementation of the objects to be used, obtains the accumulation growth rate data and the transmission error frequency data of the objects to be used, and determines whether the monitoring is normal based on the data threshold comparison. At the same time, the risk trend assessment unit assesses the design risk trend of the objects to be used, obtains the deformation data and usage data of the objects to be used, and determines whether the risk trend assessment is normal through data analysis; The accumulation growth rate data and the conveying error frequency data are respectively the growth rate of the unused accumulation amount of existing components corresponding to the distribution time of the components during the design and implementation of the standby object, and the conveying position error frequency of components of different sizes when assembling components of the same type during the design and implementation of the standby object; The deformation data and usage data are respectively the proportion of the deformation quantities of components in the period between the time when the components are installed and the time when the manufacturing of the stand-by object is completed during the design and implementation stage of the stand-by object, and the floating amount of the speed difference between the installation consumption speed of the same type of components and the component supply speed during the design and implementation stage of the stand-by object.

2. A data analysis system for an intelligent manufacturing platform according to claim 1, characterized in that: The usage scenario requirement information includes the maximum reciprocating interval value of the water depth in the water scene used by the standby object, the reciprocating floating span value of the wading depth of the hull when the standby object is stagnant in the water scene, and the maximum floating height value of the hull movement trajectory when the standby object moves in the water scene.

3. A data analysis system for an intelligent manufacturing platform according to claim 2, characterized in that: Compare the usage scenario demand analysis factor with the usage scenario demand analysis factor threshold range: If the usage scenario demand analysis coefficient is lower than the minimum value of the usage scenario demand analysis coefficient threshold range, the usage scenario of the current standby object is set as a low demand scenario; If the usage scenario demand analysis coefficient is higher than the minimum value of the usage scenario demand analysis coefficient threshold range, the usage scenario of the current standby object is set as a high demand scenario; If the usage scenario demand analysis coefficient is at the minimum value of the usage scenario demand analysis coefficient threshold range, the usage scenario of the current standby object is set as a medium demand scenario.

4. The data analysis system for an intelligent manufacturing platform according to claim 1, characterized in that: The composition adaptation information includes the maximum reduction in moving speed, the update speed of the floating height peak value, and the floating frequency of the actual power supply value; the composition adaptation analysis coefficient of the object to be used is compared with the composition adaptation analysis coefficient threshold: If the composition adaptation analysis coefficient of the object to be used exceeds the composition adaptation analysis coefficient threshold, a composition adaptation analysis abnormal signal is generated and the composition adaptation analysis abnormal signal is sent to the design front end; If the composition adaptation analysis coefficient of the object to be used does not exceed the composition adaptation analysis coefficient threshold, a composition adaptation analysis normal signal is generated and sent to the design front end.

5. The data analysis system for an intelligent manufacturing platform according to claim 1, characterized in that: If the accumulation growth rate data exceeds the accumulation amount growth rate threshold, or the conveying error frequency data exceeds the conveying position error frequency threshold, a progress monitoring abnormality signal is generated and sent to the design backend; If the accumulation growth rate data does not exceed the accumulation amount growth rate threshold, and the conveying error frequency data does not exceed the conveying position error frequency threshold, a normal progress monitoring signal is generated and sent to the design backend.

6. The data analysis system for an intelligent manufacturing platform according to claim 1, characterized in that: If the deformation data exceeds the deformation quantity ratio threshold, or the usage data exceeds the speed difference floating amount threshold, an abnormal trend signal is generated and sent to the design backend.

7. A data analysis system for an intelligent manufacturing platform according to claim 6, characterized in that: If the deformation data does not exceed the deformation quantity ratio threshold, and the usage data does not exceed the speed difference floating amount threshold, a normal trend signal is generated and sent to the design backend.

8. A data analysis method for an intelligent manufacturing platform, characterized in that: A data analysis system for an intelligent manufacturing platform based on any one of claims 1-7.

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