CN118333580A - Intelligent factory data intelligent analysis management system - Google Patents

Abstract

The invention discloses an intelligent analysis management system for intelligent factory data, which relates to the technical field of intelligent factories. According to the intelligent factory data intelligent analysis management system, through intelligent analysis of the data of the to-be-ordered, production managers can quickly identify orders which can be completed in a current target period, the recommendation coefficient is used for helping to avoid default risks possibly caused by blind subscription, enterprise reputation and customer satisfaction are ensured, the reasonable screening and recommendation of the orders can ensure that the factory production flow is more stable, production interruption or confusion caused by emergency order insertion is reduced, and the recommendation analysis unit provides data-driven decision support, so that the production managers can make decisions according to objective data analysis results instead of experience only.

Description

Intelligent factory data intelligent analysis management system

Technical Field

The invention relates to the technical field of intelligent factories, in particular to an intelligent analysis management system for intelligent factory data.

Background

As industrialization progresses, the scale and complexity of plant production increases. In modern industrial production, how to effectively manage production data, predict production time of products, reasonably arrange production tasks, ensure order completion on time, improve customer satisfaction is a challenge facing each factory. The traditional production management mode often depends on manual experience, lacks scientific data support, and cannot meet the requirements of accuracy and instantaneity of modern production.

To solve this problem, an intelligent factory data intelligent analysis management system has emerged. The system collects factory production data and order data through the data collecting unit, processes and analyzes the data through the data processing unit, and finally further analyzes the processed and analyzed data through the data analysis unit so as to facilitate the establishment of a more scientific and reasonable production plan.

However, when the existing intelligent factory data intelligent analysis management system processes and analyzes data, various factors in the production process, such as relevance among products, are not considered, so that the accuracy of analysis results is not high. In addition, the existing system often lacks intuitiveness when displaying analysis results, and is inconvenient for production management staff to quickly know various conditions in the production process.

Therefore, there is a need for a new intelligent factory data intelligent analysis management system that can more accurately analyze and predict the production time of a product and the completion of an order, while displaying the analysis results in a more intuitive manner so that production managers can make more informed decisions.

Disclosure of Invention

Aiming at the defects of the prior art, the invention provides an intelligent analysis management system for intelligent factory data, which solves the problems in the background art.

In order to achieve the above purpose, the invention is realized by the following technical scheme: an intelligent plant data intelligent analysis management system, comprising:

The data acquisition unit is used for acquiring factory production data in a plurality of historical target periods and order data in a current target period in a target factory;

the factory production data comprises operation man-hour in a target period, production quantity of different specified products and corresponding effective production man-hour, the order data comprises required production quantity of different specified products, and the order data is divided into order-taken data and order-to-be-taken data;

The data processing unit is used for carrying out data calculation processing on the factory production data in the previous period and obtaining single product time analysis values of different appointed products:

The single product time analysis value is an average value of corresponding production time obtained by performing discrete value analysis corresponding to the production time according to the production quantity of the specified product in factory production data and the multiple production time of the specified product calculated by effective production work;

the data analysis unit is used for carrying out the determination analysis of the order to be taken according to the respective required production amount of the order to be taken data and the data calculation processing result of the data processing unit, judging whether the order to be taken data can be completed in the current target period according to the determination analysis result of the order to be taken, and then sending the judgment result to the data display unit;

The data display unit is used for displaying the analysis result obtained by the data analysis unit to production management personnel.

Preferably, the start-stop time nodes corresponding to the historical target periods and the current target periods are different, and the period interval duration is the same, namely the operation time is the same.

Preferably, the data calculation processing mode is as follows:

StepR1, selecting a specified product, acquiring the production quantity of the specified product and the corresponding effective production man-hour in a plurality of history periods, respectively marking the production quantity of the specified product as Li and Si, wherein i=1, 2 and … … m, m represents the number of the history periods, li represents the production quantity of the specified product in the history period, and Si represents the effective production man-hour of the specified product in the history period;

StepR2, followed by calculation formula one: calculating to obtain a discrete value L1 corresponding to the single product of the appointed product;

In the first calculation formula: DSi represents the time when the appointed product is produced in one history period, the time when the appointed product is recorded as single product time, and DSp represents the average value of the appointed product corresponding to all single product time in a plurality of history periods;

StepR3, comparing L1 with a preset discrete threshold Ly:

if L1 is more than Ly, the discrete degree value of the appointed product corresponding to each single product is larger, and then the corresponding DSi values are deleted in sequence from large to small according to the |DSi-DSp|;

StepR4, according to StepR3, through calculation formula two, Correspondingly calculating a deviation value L1 of undeleted DSi until L1 is less than or equal to Ly;

In the second calculation formula, the corresponding DSi is an undeleted value, and DSp is an average value of undeleted DSi;

StepR5, if L1 is less than or equal to Ly, extracting all DSi used for correspondingly calculating L1, then obtaining the average value of all DSi, and recording the average value as a single product time analysis value DF.

Preferably, the order determination analysis is as follows:

StepE1, obtaining the required production quantity of each specified product from the order-taken data;

meanwhile, according to each appointed product in the received order data, acquiring a single product time analysis value of the corresponding product from a data calculation processing result of the data processing unit;

StepE2, marking the operation man-hour in the target period as YG;

Marking the required production quantity of each specified product in StepE <1 > as XLj, marking the time analysis value of each specified product as DFj, j=1, 2 and … … m, wherein m represents the category number of all different specified products in the order-taken data;

StepE3, by calculation formula three: Calculating the used processing working hours JY for the production of the order-taken data, and recording the JY as JY0 when the processing is consumed;

StepE4, obtaining the required production quantity of each specified product from the data of the order to be taken;

meanwhile, according to each appointed product in the data of the order to be taken, acquiring a single product time analysis value of the corresponding product from a data calculation processing result of the data processing unit;

marking the data according to StepE and simultaneously calculating according to a calculation formula III in StepE3, calculating the used processing working hours JY for producing the data of the order to be taken, and marking the working hours JY as the analysis time JY1 to be processed;

StepE5, then comparing JY1 with YG-JY 0:

the result value obtained by YG-JY0 is expressed as the working hours which can be continued after the order taking data are produced;

If JY1 is less than or equal to YG-JY0, the data of the to-be-taken order can be completed in the current target period;

if JY1 > YG-JY0, it indicates that the data to be taken cannot be completed in the current target period.

Preferably, the resulting value of YG-JY0 is expressed as a continued working time after the order taking data is produced.

Preferably, the number of corresponding production equipment and the number of workers used by the data analysis unit are consistent with the number of corresponding production equipment and the number of workers used by the data acquisition unit for acquiring corresponding production capacity and corresponding effective production man-hour;

And the related production equipment and workers used by different specified products have relevance, namely the operation time consumed by the different specified products is not in parallel relation, wherein the parallel relation of time means that a plurality of events or processes can be overlapped and executed in the same time period.

Preferably, the data acquisition unit is further configured to acquire a predetermined manufacturing cost and manufacturing unit price corresponding to each specified product.

Preferably, the method further comprises:

And the recommendation analysis unit is used for selecting the data to be ordered which can be completed in the current target period from the plurality of data to be ordered, generating corresponding recommendation coefficients, and then transmitting the data to be ordered which can be completed in the current target period and the recommendation coefficients thereof to the data display unit.

Preferably, the recommended analysis unit analyzes the following manner:

StepW1, respectively importing a plurality of to-be-taken order data into a data analysis unit to carry out to-be-taken order determination analysis, screening out to-be-taken order data which cannot be completed in the current target period according to an analysis result, and reserving to-be-taken order data which can be completed in the current target period;

Meanwhile, when the production is finished and the analysis to be processed corresponding to each to-be-processed order data which can be completed in the current target period is used, the to-be-processed analysis is marked as JY1t, t=1, 2 and … … v, v represents the order batch of the to-be-processed order data which can be completed in the current target period, JY0 when the processing is consumed and the operation time YG in the target period are also obtained;

StepW2, selecting corresponding designated products from the data of each to-be-taken order which can be completed in the current target period, calculating profit values of the corresponding single products of each designated products according to the preset manufacturing cost and manufacturing unit price of each designated product, and marking the profit values as YZt;

StepW3, extracting corresponding required production quantity from each to-be-taken order data which can be completed in the current target period, and marking the corresponding required production quantity as XLt;

StepW4, by calculation formula four: calculating recommendation coefficients TXt of the data of each to-be-taken order;

in the calculation formula IV, alpha 1 and alpha 2 are preset scale factors.

Preferably, the data display unit is further configured to display the recommendation coefficient of each to-be-taken order data to a production manager, so that the production manager obtains the to-be-taken order data that can be signed according to the maximum recommendation coefficient.

The invention provides an intelligent factory data intelligent analysis management system. Compared with the prior art, the method has the following beneficial effects:

the decision efficiency is improved: by intelligent analysis of the to-be-taken order data, the production manager can quickly identify those orders that can be completed within the current target period.

Optimizing resource allocation: scientific recommendation can be provided for production managers based on the completability of orders and profit values, so that the production managers can be helped to optimize resource allocation and ensure efficient utilization of resources.

Increase the economic benefits of enterprises: by calculating the individual profit value for each given product, and combining the volume to be made, the system is able to recommend the order combination with the highest total profit.

Ensuring enterprise reputation and customer satisfaction: the recommendation coefficient is used for helping to avoid the default risk possibly caused by blind subscription and ensuring enterprise reputation and customer satisfaction.

Ensure that the production flow of the factory is more stable: through reasonable screening and recommendation of orders, the production flow of a factory can be ensured to be more stable, and production interruption or confusion caused by emergency order insertion is reduced.

Variability in adaptation to market demand: the method can process orders of a plurality of batches corresponding to a plurality of demanding parties and adapt to the variability of market demands.

Flexible adjustment: the system can be flexibly adjusted according to different product and order demands.

Providing data driven decision support: the recommendation analysis unit provides data-driven decision support so that production managers can make decisions based on objective data analysis results, rather than just empirically.

Drawings

Fig. 1 is a system block diagram of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made more apparent and fully hereinafter with reference to the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

As an embodiment of the invention

Referring to fig. 1, the present invention provides a technical solution: an intelligent plant data intelligent analysis management system, comprising:

The data acquisition unit is used for acquiring factory production data in a plurality of historical target periods and order data in a current target period in a target factory;

the factory production data comprises operation man-hour in a target period, production quantity of different specified products and corresponding effective production man-hour;

The operation man-hour is expressed as the normal start-up time of a designated factory except overtime, and the effective production man-hour is expressed as the production time of the corresponding production capacity of the designated product;

The system comprises a plurality of historical target periods and current target periods, wherein the corresponding start-stop time nodes between the historical target periods and the current target periods are different, and the period interval duration is the same, namely the operation time is the same;

The order data comprises the required production quantity of different appointed products, and is divided into order data and order data to be taken;

The data processing unit is used for carrying out data calculation processing on the factory production data in the previous period:

The method comprises the following steps:

StepR1, take a specific product as an example;

in a plurality of history periods, the production quantity of the appointed product and the corresponding effective production man-hour are obtained and marked as Li and Si respectively, i=1, 2 and … … m, wherein m represents the number of the history periods, li represents the production quantity of the appointed product in the history period, and Si represents the effective production man-hour of the appointed product in the history period;

StepR2, followed by calculation formula one: calculating to obtain a discrete value L1 corresponding to the single product of the appointed product;

in the first calculation formula:

DSi indicates that the time of the specified product is recorded as the time of the single product in a history period when the specified product is produced;

DSp is expressed as an average value of the appointed products corresponding to all single product use times in a plurality of history periods;

StepR3, comparing L1 with a preset discrete threshold Ly:

if L1 is more than Ly, the discrete degree value of the appointed product corresponding to each single product is larger, and then the corresponding DSi values are deleted in sequence from large to small according to the |DSi-DSp|;

StepR4, according to StepR3, through calculation formula two, Correspondingly calculating a deviation value L1 of undeleted DSi until L1 is less than or equal to Ly;

In the second calculation formula, the corresponding DSi is an undeleted value, and DSp is an average value of undeleted DSi;

StepR5, if L1 is less than or equal to Ly, extracting all DSi used for correspondingly calculating L1, then solving the average value of all DSi, and recording the average value as a single-product time analysis value DF;

StepR6, calculating single product time analysis values of other different specified products according to the modes StepR to StepR;

the data analysis unit is used for carrying out determination analysis on the order to be taken according to the respective required production amounts of the order to be taken and the data calculation processing result of the data processing unit;

The method comprises the following steps:

StepE1, obtaining the required production quantity of each specified product from the order-taken data;

meanwhile, according to each appointed product in the received order data, acquiring a single product time analysis value of the corresponding product from a data calculation processing result of the data processing unit;

StepE2, marking the operation man-hour in the target period as YG;

marking the required production quantity of each specified product in StepE as XLj, and marking the single-product time analysis value of each specified product as DFj;

Where j=1, 2, … … m, m represents the number of categories for all different specified products in the order taken data;

StepE3, by calculation formula three: Calculating the used processing working hours JY for the production of the order-taken data, and recording the JY as JY0 when the processing is consumed;

StepE4, obtaining the required production quantity of each specified product from the data of the order to be taken;

In this embodiment, the order batch value corresponding to the to-be-taken order data is 1, that is, one batch of orders expressed as a single customer or a demander;

meanwhile, according to each appointed product in the data of the order to be taken, acquiring a single product time analysis value of the corresponding product from a data calculation processing result of the data processing unit;

marking the data according to StepE and simultaneously calculating according to a calculation formula III in StepE3, calculating the used processing working hours JY for producing the data of the order to be taken, and marking the working hours JY as the analysis time JY1 to be processed;

StepE5, then comparing JY1 with YG-JY 0:

the result value obtained by YG-JY0 is expressed as the working hours which can be continued after the order taking data are produced;

If JY1 is less than or equal to YG-JY0, the data of the to-be-taken order can be completed in the current target period;

if JY1 > YG-JY0, it indicates that the data to be taken cannot be completed in the current target period;

The data analysis unit is used for determining and analyzing the number of corresponding production equipment and the number of workers, and the corresponding production quantity is acquired by the data acquisition unit and is consistent with the number of corresponding production equipment and the number of workers used in the corresponding effective production man-hour; the related production equipment and workers used by different specified products have relevance, namely the operation time consumed by the different specified products is not in parallel relation, wherein the parallel relation of time means that a plurality of events or processes can be overlapped and executed in the same time period;

According to the method, the production time of different products can be predicted through analysis of historical production data, basis is provided for production planning, reasonable arrangement of production tasks is facilitated, order completion is guaranteed on time, production period can be predicted through analysis of order data, order completion is guaranteed on time, customer satisfaction is improved, analysis results are displayed to production management staff in an intuitive mode by a data display unit, various conditions in the production process can be conveniently and rapidly known by the production management staff, accordingly, intelligent decision making is made, and the system can be flexibly adjusted according to different products and order requirements, and is suitable for diversified production environments.

Example two

Referring to fig. 1, as a second embodiment of the present application, in comparison with the first embodiment, the technical solution of the present embodiment is only different from the first embodiment in that:

In this embodiment, the order batch value corresponding to the to-be-taken order data is greater than 1, that is, the orders of a plurality of batches corresponding to a plurality of requesters are expressed;

the data acquisition unit is also used for acquiring the preset manufacturing cost and manufacturing unit price corresponding to each specified product;

and this embodiment further includes:

The recommendation analysis unit is used for selecting the data to be ordered which can be completed in the current target period from the plurality of data to be ordered, generating corresponding recommendation coefficients, and then transmitting the data to be ordered which can be completed in the current target period and the recommendation coefficients thereof to the data display unit;

The specific selection mode is as follows:

StepW1, respectively importing a plurality of to-be-taken order data into a data analysis unit to carry out to-be-taken order determination analysis, screening out to-be-taken order data which cannot be completed in the current target period according to an analysis result, and reserving to-be-taken order data which can be completed in the current target period;

Meanwhile, when the production is finished and the analysis to be processed corresponding to each to-be-processed order data which can be completed in the current target period is used, the to-be-processed analysis is marked as JY1t, t=1, 2 and … … v, v represents the order batch of the to-be-processed order data which can be completed in the current target period, JY0 when the processing is consumed and the operation time YG in the target period are also obtained;

StepW2, selecting corresponding designated products from the data of each to-be-taken order which can be completed in the current target period, calculating profit values of the corresponding single products of each designated products according to the preset manufacturing cost and manufacturing unit price of each designated product, and marking the profit values as YZt;

StepW3, extracting corresponding required production quantity from each to-be-taken order data which can be completed in the current target period, and marking the corresponding required production quantity as XLt;

StepW4, by calculation formula four: calculating recommendation coefficients TXt of the data of each to-be-taken order;

in the calculation formula IV, alpha 1 and alpha 2 are preset scale factors;

The data display unit is also used for displaying the recommendation coefficient of each to-be-taken order data to production management staff, so that the production management staff can acquire the to-be-taken order data which can be signed according to the maximum recommendation coefficient, and the problem that the to-be-taken order data after being signed cannot be produced in a specified time and generate default risks due to blind signing is avoided.

Example III

As an embodiment three of the present application, in the implementation of the present application, compared with the first embodiment and the second embodiment, the technical solution of the present embodiment is that the solutions of the first embodiment and the second embodiment are implemented in combination, and the difference between the technical solution of the present embodiment and the first embodiment and the second embodiment is only in the present embodiment, before the calculation is performed by the calculation formula four in the second embodiment;

The two or more than two to-be-processed analysis time slots corresponding to the to-be-processed order data are added to obtain a plurality of corresponding to-be-processed analysis time slots;

then comparing the sum of the corresponding analysis time to be processed with the value obtained by YG-JY0, obtaining the data of the order to be taken corresponding to the sum of the corresponding analysis time to be processed which is less than or equal to YG-JY0, and forming a plurality of packages to be recommended;

and then, calculating recommendation coefficients of the plurality of packages to be recommended, wherein the recommendation coefficients are calculated in the following specific modes:

The sum of the to-be-processed analysis time in each to-be-recommended package is marked as JY2g, g=1, 2 and … … f, and f represents the number of to-be-recommended packages;

Meanwhile, according to the single product profit value of each appointed product in the package to be recommended and the corresponding production quantity to be produced, calculating the total profit of each appointed product in the package to be recommended, and obtaining the sum ZLZg of the total profit of all appointed products in the package to be recommended;

then the transformation formula of the fourth calculation formula is: Calculating recommendation coefficients TXt of each package to be recommended;

The data display unit is also used for displaying the recommendation coefficient of each package to be recommended to production management staff, so that the production management staff can acquire a plurality of pieces of order to be taken data in the package to be recommended which can be signed according to the maximum recommendation coefficient, and the problem that the signed pieces of order to be taken data cannot be produced in a specified time to generate default risks due to blind signing is avoided;

By implementing the intelligent analysis of the data of the to-be-taken orders, production management personnel can quickly identify the orders which can be completed in the current target period, so that the decision efficiency is improved; scientific recommendation can be provided for production management staff based on the completability of orders and profit values, so that the production management staff can be helped to optimize resource allocation, and efficient utilization of resources is ensured; by calculating the profit value of each single product of each specified product and combining the required production quantity, the system can recommend the order combination with the highest total profit, thereby increasing the economic benefit of enterprises; the recommendation coefficient is used for helping to avoid the default risk possibly caused by blind subscription, and the enterprise reputation and the customer satisfaction are ensured; through reasonable screening and recommendation of orders, the production flow of a factory can be ensured to be more stable, and production interruption or confusion caused by emergency order insertion is reduced; the method can process orders of a plurality of batches corresponding to a plurality of demand parties, adapt to the variability of market demands, and can flexibly adjust according to different products and order demands; the recommendation analysis unit provides data-driven decision support so that production managers can make decisions based on objective data analysis results, rather than just empirically.

Example IV

As an embodiment four of the present application, in the implementation of the present application, compared with the first, second and third embodiments, the technical solution of the present embodiment is to combine the solutions of the first, second and third embodiments.

The above formulas are all formulas with dimensionality removed and numerical calculation, the formulas are formulas with the latest real situation obtained by software simulation through collecting a large amount of data, and preset parameters and threshold selection in the formulas are set by those skilled in the art according to the actual situation.

And all that is not described in detail in this specification is well known to those skilled in the art.

The embodiments of the present invention have been described in detail, but the present invention is merely the preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.

Claims (10)

1. An intelligent analysis management system for intelligent factory data, comprising:

The data acquisition unit is used for acquiring factory production data in a plurality of historical target periods and order data in a current target period in a target factory;

the factory production data comprises operation man-hour in a target period, production quantity of different specified products and corresponding effective production man-hour, the order data comprises required production quantity of different specified products, and the order data is divided into order-taken data and order-to-be-taken data;

The data processing unit is used for carrying out data calculation processing on the factory production data in the previous period and obtaining single product time analysis values of different appointed products:

The single product time analysis value is an average value of corresponding production time obtained by performing discrete value analysis corresponding to the production time according to the production quantity of the specified product in factory production data and the multiple production time of the specified product calculated by effective production work;

the data analysis unit is used for carrying out the determination analysis of the order to be taken according to the respective required production amount of the order to be taken data and the data calculation processing result of the data processing unit, judging whether the order to be taken data can be completed in the current target period according to the determination analysis result of the order to be taken, and then sending the judgment result to the data display unit;

The data display unit is used for displaying the analysis result obtained by the data analysis unit to production management personnel.

2. The intelligent plant data intelligent analysis management system according to claim 1, wherein: the corresponding start-stop time nodes between the historical target periods and the current target periods are different, and the period interval duration is the same, namely the operation time is the same.

3. The intelligent plant data intelligent analysis management system according to claim 1, wherein: the data calculation processing mode is as follows:

StepR1, selecting a specified product, acquiring the production quantity of the specified product and the corresponding effective production man-hour in a plurality of history periods, respectively marking the production quantity of the specified product as Li and Si, wherein i=1, 2 and … … m, m represents the number of the history periods, li represents the production quantity of the specified product in the history period, and Si represents the effective production man-hour of the specified product in the history period;

StepR2, followed by calculation formula one: calculating to obtain a discrete value L1 corresponding to the single product of the appointed product;

In the first calculation formula: DSi represents the time when the appointed product is produced in one history period, the time when the appointed product is recorded as single product time, and DSp represents the average value of the appointed product corresponding to all single product time in a plurality of history periods;

StepR3, comparing L1 with a preset discrete threshold Ly:

if L1 is more than Ly, the discrete degree value of the appointed product corresponding to each single product is larger, and then the corresponding DSi values are deleted in sequence from large to small according to the |DSi-DSp|;

StepR4, according to StepR3, through calculation formula two, Correspondingly calculating a deviation value L1 of undeleted DSi until L1 is less than or equal to Ly;

In the second calculation formula, the corresponding DSi is an undeleted value, and DSp is an average value of undeleted DSi;

StepR5, if L1 is less than or equal to Ly, extracting all DSi used for correspondingly calculating L1, then obtaining the average value of all DSi, and recording the average value as a single product time analysis value DF.

4. The intelligent plant data intelligent analysis management system according to claim 1, wherein: the order determination and analysis mode is as follows:

StepE1, obtaining the required production quantity of each specified product from the order-taken data;

meanwhile, according to each appointed product in the received order data, acquiring a single product time analysis value of the corresponding product from a data calculation processing result of the data processing unit;

StepE2, marking the operation man-hour in the target period as YG;

Marking the required production quantity of each specified product in StepE <1 > as XLj, marking the time analysis value of each specified product as DFj, j=1, 2 and … … m, wherein m represents the category number of all different specified products in the order-taken data;

StepE3, by calculation formula three: Calculating the used processing working hours JY for the production of the order-taken data, and recording the JY as JY0 when the processing is consumed;

StepE4, obtaining the required production quantity of each specified product from the data of the order to be taken;

meanwhile, according to each appointed product in the data of the order to be taken, acquiring a single product time analysis value of the corresponding product from a data calculation processing result of the data processing unit;

marking the data according to StepE and simultaneously calculating according to a calculation formula III in StepE3, calculating the used processing working hours JY for producing the data of the order to be taken, and marking the working hours JY as the analysis time JY1 to be processed;

StepE5, then comparing JY1 with YG-JY 0:

the result value obtained by YG-JY0 is expressed as the working hours which can be continued after the order taking data are produced;

If JY1 is less than or equal to YG-JY0, the data of the to-be-taken order can be completed in the current target period;

if JY1 > YG-JY0, it indicates that the data to be taken cannot be completed in the current target period.

5. The intelligent plant data intelligent analysis management system according to claim 4, wherein: the resulting value obtained by YG-JY0 is indicated as the working time for continued processing after the order taking data is produced.

6. The intelligent plant data intelligent analysis management system according to claim 4, wherein: the data analysis unit is used for determining and analyzing the number of corresponding production equipment and the number of workers, and the corresponding production quantity is acquired by the data acquisition unit and is consistent with the number of corresponding production equipment and the number of workers used in the corresponding effective production man-hour;

And the related production equipment and workers used by different specified products have relevance, namely the operation time consumed by the different specified products is not in parallel relation, wherein the parallel relation of time means that a plurality of events or processes can be overlapped and executed in the same time period.

7. The intelligent plant data intelligent analysis management system according to claim 1, wherein: the data acquisition unit is also used for acquiring the corresponding preset manufacturing cost and manufacturing unit price of each specified product.

8. The intelligent plant data intelligent analysis management system according to claim 7, wherein: further comprises:

And the recommendation analysis unit is used for selecting the data to be ordered which can be completed in the current target period from the plurality of data to be ordered, generating corresponding recommendation coefficients, and then transmitting the data to be ordered which can be completed in the current target period and the recommendation coefficients thereof to the data display unit.

9. The intelligent plant data intelligent analysis management system according to claim 8, wherein: the recommended analysis unit analyzes the following manner:

StepW1, respectively importing a plurality of to-be-taken order data into a data analysis unit to carry out to-be-taken order determination analysis, screening out to-be-taken order data which cannot be completed in the current target period according to an analysis result, and reserving to-be-taken order data which can be completed in the current target period;

Meanwhile, when the production is finished and the analysis to be processed corresponding to each to-be-processed order data which can be completed in the current target period is used, the to-be-processed analysis is marked as JY1t, t=1, 2 and … … v, v represents the order batch of the to-be-processed order data which can be completed in the current target period, JY0 when the processing is consumed and the operation time YG in the target period are also obtained;

StepW2, selecting corresponding designated products from the data of each to-be-taken order which can be completed in the current target period, calculating profit values of the corresponding single products of each designated products according to the preset manufacturing cost and manufacturing unit price of each designated product, and marking the profit values as YZt;

StepW3, extracting corresponding required production quantity from each to-be-taken order data which can be completed in the current target period, and marking the corresponding required production quantity as XLt;

StepW4, by calculation formula four: calculating recommendation coefficients TXt of the data of each to-be-taken order;

in the calculation formula IV, alpha 1 and alpha 2 are preset scale factors.

10. The intelligent plant data intelligent analysis management system according to claim 8, wherein: the data display unit is also used for displaying the recommendation coefficient of each to-be-taken order data to production management personnel, so that the production management personnel can acquire the to-be-taken order data which can be contracted according to the maximum recommendation coefficient.