CN117291400B - MES-based production management method and system - Google Patents
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Abstract
The invention belongs to the technical field of production data management, and particularly relates to a production management method and system based on MES. The method and the system can classify the order products into the auxiliary products, the main products and the independent products based on the order information, and meanwhile, the order products can be completed before the product demand date based on the yield in the order product production process, so that the phenomenon that the enterprise breaks the contract due to overtime of the order is reduced, redundant inventory of the auxiliary products can be cleaned, and the inventory turnover rate of the enterprise is improved.
Description
Technical Field
The invention belongs to the technical field of production data management, and particularly relates to a production management method and system based on MES.
Background
The MES is a management system integrating various technologies such as computer technology, communication technology and automation technology, and aims to realize real-time monitoring, data acquisition, analysis and optimization of a production process, in the manufacturing industry, in order to improve production efficiency, reduce cost and improve product quality, enterprises need to adopt a more advanced and intelligent production management system, and the traditional production management mode cannot meet the requirements of modern enterprises, so that the application of the MES-based production management system or method has gradually become a development trend of the industry.
In the prior art, the enterprise production management system can play the functions of scheduling production, monitoring and the like, and is more focused on the control level, the aspect of production management of products is ignored, products corresponding to orders cannot be evaluated according to the production capacity of the enterprise, further reasonable planning of product production is possibly caused, even the phenomenon that the orders cannot be regularly delivered is possibly caused, capacity analysis can be introduced in the current production management, and a scheduling method is designated according to the delivery date, but the mode generally only performs scheduling on a single product, and in fact, for different order products, one order product can be another order product raw material, namely an accessory product can be the other order product, and the products have a mutual matching relation, so compared with the traditional production scheduling method, the accessory product is fully considered, and turnover among the accessory products is flexibly utilized in the actual production process, so that is necessary.
Disclosure of Invention
The invention aims to provide a production management method and system based on MES, which can reasonably plan production and production optimization of products, flexibly call subsidiary products, ensure that order production is more reasonable and avoid the occurrence of default phenomenon caused by overtime of orders by enterprises.
The technical scheme adopted by the invention is as follows:
a MES-based production management method, comprising:
acquiring order information, and generating a production work order according to the product demand and the product demand date, wherein the order information comprises the product demand and the product demand date;
obtaining products corresponding to the order information, and classifying the products into auxiliary products, main products and independent products;
acquiring the production priority of each order information, and arranging production work orders according to the production priority;
making a monitoring period according to the product demand date, acquiring whether order information can be completed normally or not in the monitoring period, and determining risk parameters if the order information cannot be completed normally;
matching an optimization scheme according to the risk parameters, wherein the optimization scheme comprises an accessory product optimization scheme and an independent optimization scheme;
the auxiliary product optimization scheme corresponds to the main product, the independent optimization scheme corresponds to the main product and the independent product, and the execution priority of the auxiliary product optimization scheme is higher than that of the independent optimization scheme;
When the auxiliary optimizing scheme is executed, judging whether auxiliary products of the main product have redundant stock or not;
if so, directly adding the redundant stock into the production of the main product;
if not, executing an independent optimization scheme.
In a preferred embodiment, the step of determining the risk parameter includes:
setting a plurality of parallel time periods in the monitoring period, acquiring the production quantity of products in each parallel time period, calibrating the production quantity as parameters to be evaluated, and summarizing the parameters to be evaluated into a data set to be evaluated;
measuring and calculating the unit yield of the product according to the parameters to be evaluated, and calibrating the unit yield as parameters to be checked, wherein the parameters to be checked comprise a primary parameter to be checked and a secondary parameter to be checked;
judging whether the product yield meets the product demand after the product demand date is finished according to the parameter to be checked;
if yes, indicating that order information corresponding to the parameter to be checked can be normally completed;
if not, the order information corresponding to the parameter to be checked cannot be completed normally, the order information is marked as a risk parameter, and an alarm signal is sent synchronously.
In a preferred embodiment, the step of acquiring the products corresponding to the order information and classifying the products into the subsidiary products, the main product and the independent products includes:
The products corresponding to the order information are calibrated as parameters to be classified, the material details of the parameters to be classified are respectively obtained, the materials are calibrated as parameters to be compared, and the parameters to be classified are compared with the parameters to be compared;
if the parameters to be classified are consistent with the parameters to be compared, the parameters to be classified are marked as auxiliary products, and the products corresponding to the parameters to be compared are marked as main products, wherein the main products at least comprise one auxiliary product;
if the parameters to be classified are inconsistent with the parameters to be compared, the parameters to be classified are directly calibrated into independent products.
In a preferred embodiment, the step of acquiring the production priority of each order information and arranging the production worksheets according to the production priority includes:
classifying the production worksheets of the same class to obtain a plurality of worksheets to be classified;
inputting the product demand date and the product demand quantity corresponding to the worksheets to be classified in the same class into a classification function to obtain classification parameters;
ranking the ranking parameters in order from large to small, and determining ranking results as production priorities of the order information;
and sequencing the production worksheets according to the production priority.
In a preferred scheme, after the parameter to be evaluated is calibrated, the method further comprises the step of judging the effectiveness of the parameter to be evaluated, wherein the judging process is as follows:
acquiring a starting point of product processing and a production stopping interval of the product processing, and judging whether the starting point of the product processing is overlapped with an ending point of the production stopping interval;
if yes, the time interval between the starting point of product processing and the starting point of the production stopping interval is calibrated as a reference time interval, the reference time interval is shifted in a cis-position mode in the monitoring period, and the shifting result is calibrated as a parallel time interval;
if not, the time interval between the starting point of product processing and the starting point of the production stopping interval is marked as a temporary time interval, the time interval between the ending point of the production stopping interval and the starting point of the next production stopping interval is determined as a reference time interval, the reference time interval is shifted in order in the monitoring period, and the shifting result is marked as a parallel time interval;
and comparing the parameter to be evaluated with a screening threshold value, wherein the parameter to be evaluated, which is higher than the screening threshold value, is reserved in the data set to be evaluated, and the parameter to be evaluated, which is lower than or equal to the screening threshold value, is screened out from the data set to be evaluated.
In a preferred embodiment, the step of measuring the unit yield of the product according to the parameter to be evaluated and calibrating the unit yield as the parameter to be verified includes:
Calculating an average value of the product yield in each parallel period, and calibrating the calculation result as a first-level parameter to be checked;
measuring and calculating the distribution density of the product yield in each parallel period, and calibrating the product yield with the maximum distribution density as a secondary parameter to be checked;
if the evaluation score of the first-level parameter to be checked is greater than or equal to the evaluation score of the second-level parameter to be checked, deleting the second-level parameter to be checked, and only reserving the first-level parameter to be checked;
and if the evaluation score of the primary parameter to be checked is smaller than that of the secondary parameter to be checked, deleting the primary parameter to be checked and only retaining the secondary parameter to be checked.
In a preferred embodiment, the step of determining whether the product yield meets the product demand after the product demand date is finished according to the parameter to be checked includes:
according to the parameter to be verified, predicting the product yield under the product demand date through a verification function, and performing difference processing on the product yield and the product demand to obtain the parameter to be approved;
comparing the parameter to be approved with a verification threshold;
if the parameter to be approved is larger than or equal to the verification threshold, judging that the product yield under the predicted product demand date meets the product demand;
And if the parameter to be approved is smaller than the verification threshold, judging that the product yield under the predicted product demand date does not meet the product demand.
The invention also provides a production management system based on the MES, which is applied to the production management method based on the MES, and comprises an order acquisition module, a bill making module, a classification module, a production scheduling module, a monitoring module, an evaluation module, a verification module and an optimization module;
the order acquisition module is used for acquiring order information, wherein the order information comprises product demand and product demand date;
the bill making module is used for generating a production work bill according to the product demand and the product demand date;
the classification module is used for acquiring products corresponding to the order information and classifying the products into auxiliary products, main products and independent products;
the scheduling module is used for acquiring the production priority of each order information and scheduling production work orders according to the production priority of the order information;
the monitoring module is used for making a monitoring period according to a product demand date, setting a plurality of parallel time periods in the monitoring period, acquiring the product production quantity under each parallel time period, calibrating the product production quantity as a parameter to be evaluated, and summarizing the parameter to be evaluated into a data set to be evaluated;
The evaluation module is used for measuring and calculating the unit yield of the product according to the parameters to be evaluated and calibrating the unit yield as the parameters to be checked, wherein the parameters to be checked comprise a first-level parameter to be checked and a second-level parameter to be checked;
the verification module is used for judging whether the product yield meets the product demand after the product demand date is finished according to the parameter to be verified;
if yes, indicating that order information corresponding to the parameter to be checked can be normally completed;
if not, indicating that the order information corresponding to the parameter to be checked cannot be completed normally, calibrating the order information as a risk parameter, and synchronously sending out an alarm signal;
the optimization module is used for matching an optimization scheme according to risk parameters, and the optimization scheme comprises an accessory product optimization scheme and an independent optimization scheme
In a preferred embodiment, the evaluation module includes:
the first-level evaluation unit is used for measuring and calculating the average value of the product yield in each parallel period and calibrating the measuring and calculating result into a first-level parameter to be checked;
the secondary evaluation unit is used for measuring and calculating the distribution density of the product yield in each parallel period, and calibrating the product yield with the maximum distribution density as a secondary parameter to be checked;
The evaluation unit is used for measuring and calculating evaluation scores of the primary parameter to be checked and the secondary parameter to be checked;
if the evaluation score of the first-level parameter to be checked is greater than or equal to the evaluation score of the second-level parameter to be checked, deleting the second-level parameter to be checked, and only reserving the first-level parameter to be checked;
and if the evaluation score of the primary parameter to be checked is smaller than that of the secondary parameter to be checked, deleting the primary parameter to be checked and only retaining the secondary parameter to be checked.
The invention also provides a production management terminal based on MES, which comprises:
at least one processor;
and a memory communicatively coupled to the at least one processor;
wherein the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the MES-based production management method described above.
The invention has the technical effects that:
the invention can classify the order products into the auxiliary products, the main products and the independent products based on the order information, and can also determine parameters to be checked for predicting the product yield based on the yield in the order product production process in combination with the evaluation module, so that the order products can be completed before the product demand date, and the most critical is that the scheduling planning is more reasonable and ordered through flexible calling between the auxiliary products and the main products, thereby not only reducing the occurrence of default caused by overtime of orders of enterprises, but also cleaning redundant stock of the auxiliary products, and further improving the stock turnover rate of the enterprises.
Drawings
FIG. 1 is a flow chart of a method provided by the present invention;
fig. 2 is a block diagram of a system provided by the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one preferred embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
As shown in fig. 1 and 2, the present invention provides a MES-based production management method, which includes:
Acquiring order information, and generating a production work order according to the product demand and the product demand date, wherein the order information comprises the product demand and the product demand date;
obtaining products corresponding to the order information, and classifying the products into auxiliary products, main products and independent products;
acquiring the production priority of each order information, and arranging production work orders according to the production priority;
making a monitoring period according to the product demand date, acquiring whether order information can be completed normally or not in the monitoring period, and determining risk parameters if the order information cannot be completed normally;
matching an optimization scheme according to the risk parameters, wherein the optimization scheme comprises an accessory product optimization scheme and an independent optimization scheme;
the auxiliary product optimization scheme corresponds to the main product, the independent optimization scheme corresponds to the main product and the independent product, and the execution priority of the auxiliary product optimization scheme is higher than that of the independent optimization scheme;
when the auxiliary optimizing scheme is executed, judging whether auxiliary products of the main product have redundant stock or not;
if so, directly adding the redundant stock into the production of the main product;
if not, executing an independent optimization scheme.
In the above embodiment, with the continuous development of the informatization technology, the production management of the manufacturing industry gradually tends to be automatic management, so that orders meeting demands can be obtained according to enterprise productivity information, data support can be provided for enterprise rationalization production, meanwhile, production orders can be reasonably distributed to all production lines, stability in the enterprise production and manufacturing process is guaranteed, production data can be displayed in real time, so that enterprise supervisory personnel can know the production process in real time.
The core of this embodiment is: the optimization scheme comprises an auxiliary product optimization scheme and an independent optimization scheme, wherein the auxiliary product corresponds to the main product only, in this way, under the condition that the raw materials of the main product are insufficient, the auxiliary product can be added into the production of the main product as raw materials, the order product can be completed before the product demand date, the phenomenon that the enterprise breaks due to overtime of the order is effectively reduced, meanwhile, the redundant stock of the auxiliary product can be cleaned, the stock turnover rate is improved, in this way, reasonable production management can be provided for the enterprise, in particular, the main product is not influenced for selling the auxiliary product in the production process, the redundant stock of the auxiliary product is not directly used as raw materials for processing, but in the case that the main product cannot complete the order product before the product demand date, the redundant stock of the auxiliary product is called out of doubt to be the optimal solution, and in the case that the redundant stock is insufficient, or in the case that the auxiliary product is an independent product, the product yield is improved by a proper way, so that the product demand can be completed before the product demand date is ensured.
In one preferred embodiment, the step of acquiring the products corresponding to each order information and classifying the products into the subsidiary products, the main product and the independent products includes:
The products corresponding to the order information are calibrated as parameters to be classified, the material details of the parameters to be classified are respectively obtained, the materials are calibrated as parameters to be compared, and the parameters to be classified are compared with the parameters to be compared;
if the parameters to be classified are consistent with the parameters to be compared, the parameters to be classified are marked as auxiliary products, and the products corresponding to the parameters to be compared are marked as main products, wherein the main products at least comprise one auxiliary product;
if the parameters to be classified are inconsistent with the parameters to be compared, the parameters to be classified are directly calibrated into independent products.
In this embodiment, when sorting products, the products corresponding to the order information are marked as parameters to be sorted, each parameter to be sorted corresponds to a material detail, for different order products, one of the order products may be another order product raw material, for example, the dumpling wrappers, dumpling stuffing and finished dumpling are involved in the processing and making process of the dumplings, for the manufacturing enterprises, the dumpling wrappers, dumpling stuffing and finished dumpling stuffing can be regarded as the order, the dumpling wrappers and dumpling stuffing can be regarded as the raw materials of the finished dumpling, the products are marked as subsidiary products, and the finished dumpling is a main product, but between the dumpling wrappers and the dumpling stuffing, the products are not related to each other, so that the products are independent products.
In a preferred embodiment, the step of determining the risk parameter comprises:
setting a plurality of parallel time periods in the monitoring period, acquiring the production quantity of products in each parallel time period, calibrating the production quantity as parameters to be evaluated, and summarizing the parameters to be evaluated into a data set to be evaluated;
measuring and calculating the unit yield of the product according to the parameters to be evaluated, and calibrating the unit yield as parameters to be checked, wherein the parameters to be checked comprise a primary parameter to be checked and a secondary parameter to be checked;
judging whether the product yield meets the product demand after the product demand date is finished according to the parameter to be checked;
if yes, indicating that order information corresponding to the parameter to be checked can be normally completed;
if not, the order information corresponding to the parameter to be checked cannot be completed normally, the order information is marked as a risk parameter, and an alarm signal is sent synchronously.
In the above embodiment, after the product corresponding to the order is put into production, a monitoring period is set, a plurality of parallel time periods are set in the monitoring period, the product throughput under each parallel time period is used as a parameter to be evaluated, the unit throughput of the product of the order is measured according to the parameter to be evaluated, whether the product throughput meets the product demand is judged based on the unit throughput, an alarm signal is sent out when the product throughput is not met, the alarm signal is calibrated to be a risk parameter after being sent out, and finally, a corresponding optimization scheme is matched according to the risk parameter.
The method is characterized by further comprising the step of judging the effectiveness of the parameter to be evaluated after the parameter to be evaluated is calibrated, wherein the judging process is as follows:
acquiring a starting point of product processing and a production stopping interval of the product processing, and judging whether the starting point of the product processing is overlapped with an ending point of the production stopping interval;
if yes, the time interval between the starting point of product processing and the starting point of the production stopping interval is calibrated as a reference time interval, the reference time interval is shifted in a cis-position mode in the monitoring period, and the shifting result is calibrated as a parallel time interval;
if not, the time interval between the starting point of product processing and the starting point of the production stopping interval is marked as a temporary time interval, the time interval between the ending point of the production stopping interval and the starting point of the next production stopping interval is determined as a reference time interval, the reference time interval is shifted in order in the monitoring period, and the shifting result is marked as a parallel time interval;
and comparing the parameter to be evaluated with a screening threshold value, wherein the parameter to be evaluated, which is higher than the screening threshold value, is reserved in the data set to be evaluated, and the parameter to be evaluated, which is lower than or equal to the screening threshold value, is screened out from the data set to be evaluated.
In the judging process, after the product is put into production, the starting point of the monitoring period is a starting node of the actual production of the product, the ending node of the monitoring period is a time node corresponding to the product demand date, the production progress of the product is monitored in real time, a plurality of parallel time periods connected end to end are defined in the monitoring period, when the parallel time periods are constructed, the starting point of the product processing (the starting node of the monitoring period) and the production stopping interval (for example, the rest time period of a daily worker) are required to be acquired in advance, in the process of constructing the parallel time periods, the time period between the starting point of the product processing and the starting node of the first production interval is checked to judge whether the time period is a temporary time period or not, the time period is taken as the parallel time period, and the phenomenon of counting wrong parameters to be evaluated is avoided, in the production progress of the parallel time periods may be coincident, though the phenomenon of overtime production may exist, the yield of the products is obviously lower than that of the normal production, in order to avoid the integral evaluation process, the corresponding parameters to be evaluated are screened from the data set, the data to be evaluated are required to be high, the actual parameters are required to be set up according to the setting of the parallel time periods, the setting of the screening threshold is required to be high, the data to be required to be limited, and the data to be evaluated is kept to be high, and the data to be evaluated is required to be high to be evaluated.
Further, the step of measuring and calculating the unit yield of the product according to the parameter to be evaluated and calibrating the unit yield as the parameter to be checked comprises the following steps:
calculating an average value of the product yield in each parallel period, and calibrating the calculation result as a first-level parameter to be checked;
measuring and calculating the distribution density of the product yield in each parallel period, and calibrating the product yield with the maximum distribution density as a secondary parameter to be checked;
if the evaluation score of the first-level parameter to be checked is greater than or equal to the evaluation score of the second-level parameter to be checked, deleting the second-level parameter to be checked, and only reserving the first-level parameter to be checked;
and if the evaluation score of the primary parameter to be checked is smaller than that of the secondary parameter to be checked, deleting the primary parameter to be checked and only retaining the secondary parameter to be checked.
In this embodiment, when the parameter to be evaluated is evaluated, the first-level parameter to be checked is obtained by respectively inputting the parameter to be evaluated in the data set to be evaluated into the measuring and calculating function, where the expression of the measuring and calculating function is:wherein->Representing the first-level parameter to be checked, < > and->Representing the number of parameters to be evaluated, +.>The method comprises the steps of representing parameters to be evaluated (product yield in parallel time periods), acquiring secondary parameters to be checked by setting a plurality of evaluation intervals, comparing the evaluation intervals with the parameters to be evaluated, acquiring an average value of the secondary parameters to be evaluated in the same evaluation interval, determining the average value as a reference parameter, taking the reference parameter with the highest occupation ratio as the product yield with the largest distribution density, and determining the average value as the secondary parameters to be checked.
After the primary to-be-checked parameter and the secondary to-be-checked parameter are determined, the corresponding evaluation scores of the primary to-be-checked parameter and the secondary to-be-checked parameter can be calculated respectively, firstly, the weight factors of the primary to-be-checked parameter and the secondary to-be-checked parameter are required to be determined, and are formulated by a supervisor according to historical forward date, wherein the weight factor of the primary to-be-checked parameter is a, the weight factor of the secondary to-be-checked parameter is b, a+b=1, and the weight factors of the primary to-be-checked parameter and the secondary to-be-checked parameter are compared according to a formula k=a-b/>The sizes of the primary parameter to be checked and the secondary parameter to be checked can be judged, wherein k represents the comparison result and +.>And when the value of k is larger than zero, determining that the evaluation score of the first-level parameter to be checked is larger than the evaluation score of the second-level parameter to be checked, otherwise, determining that the evaluation score of the second-level parameter to be checked is larger than the evaluation score of the first-level parameter to be checked.
On the basis of the above steps, the step of judging whether the product yield meets the product demand after the product demand date is finished according to the parameter to be checked comprises the following steps:
according to the parameter to be verified, predicting the product yield under the product demand date through a verification function, and performing difference processing on the product yield and the product demand to obtain the parameter to be approved;
Comparing the parameter to be approved with a verification threshold;
if the parameter to be approved is larger than or equal to the verification threshold, judging that the product yield under the predicted product demand date meets the product demand;
and if the parameter to be approved is smaller than the verification threshold, judging that the product yield under the predicted product demand date does not meet the product demand.
In the step, after the comparison of the primary parameter to be checked and the secondary parameter to be checked, the primary parameter to be checked and the secondary parameter to be checked are used as reference parameters with larger evaluation scores, and the reference parameters are input into a check function, wherein the expression of the check function is as follows:wherein->Indicating predicted product yield,/->Indicating that it has been generatedYield of the product,/->Representing reference parameters->The time interval between the product demand date and the current date is represented, the time interval is then subjected to difference with the product demand, the parameter to be approved can be obtained, the parameter to be approved is then compared with a verification threshold, the verification threshold is set to be larger than zero in order to avoid uncontrollable factors in the production process, the specific value is set according to the actual product and the actual yield, and whether the product yield under the predicted product demand date meets the product demand can be determined according to the comparison result of the parameter to be approved and the verification threshold.
In a preferred embodiment, the step of acquiring the production priority of each order information and arranging the production worksheets according to the production priority comprises:
classifying the production worksheets of the same class to obtain a plurality of worksheets to be classified;
inputting the product demand date and the product demand quantity corresponding to the worksheets to be classified in the same class into a classification function to obtain classification parameters;
ranking the ranking parameters in order from large to small, and determining ranking results as production priorities of the order information;
and sequencing the production worksheets according to the production priority.
In this embodiment, for different production orders, the product demand and the product demand date are different, so that in order to ensure that enough products can be produced before the product date, the products need to be classified and ordered, in this embodiment, the production orders of the same class are classified first, specifically, the product demand date and the product demand corresponding to the work orders of the same class are input into a classification function, so as to calculate classification parameters, where the expression of the classification function is:wherein->Representing grading parameters- >Represents unit standard yield,/->Indicating the required yield of the product, < >>And the interval between the product demand date and the current day period is represented, after the grading parameters are obtained, the grading parameters can be arranged according to the order from large to small, and the arrangement result is used for determining the production priority of the order line, so that the products corresponding to the order information can be completed under the product demand date.
The invention also provides a production management system based on the MES, which comprises an order acquisition module, a bill making module, a classification module, a production scheduling module, a monitoring module, an evaluation module, a verification module and an optimization module;
the order acquisition module is used for acquiring order information, wherein the order information comprises product demand and product demand date;
the bill making module is used for generating a production work bill according to the product demand and the product demand date;
the classification module is used for acquiring products corresponding to the order information and classifying the products into auxiliary products, main products and independent products;
the scheduling module is used for acquiring the production priority of each order information and scheduling production work orders according to the production priority of the order information;
the monitoring module is used for making a monitoring period according to a product demand date, setting a plurality of parallel time periods in the monitoring period, acquiring the product production quantity under each parallel time period, calibrating the product production quantity as a parameter to be evaluated, and summarizing the parameter to be evaluated into a data set to be evaluated;
The evaluation module is used for measuring and calculating the unit yield of the product according to the parameters to be evaluated and calibrating the unit yield as the parameters to be checked, wherein the parameters to be checked comprise a first-level parameter to be checked and a second-level parameter to be checked;
the verification module is used for judging whether the product yield meets the product demand after the product demand is finished according to the parameter to be verified, wherein a verification function is arranged in the verification module and used for predicting the product yield under the product demand according to the parameter to be verified, and then performing difference processing on the product yield and the product demand to obtain the parameter to be approved, and a verification threshold value is also arranged in the verification module and used for comparing the verification threshold value with the parameter to be approved;
if yes, indicating that order information corresponding to the parameter to be checked can be normally completed;
if not, indicating that the order information corresponding to the parameter to be checked cannot be completed normally, calibrating the order information as a risk parameter, and synchronously sending out an alarm signal;
the optimization module is used for matching an optimization scheme according to the risk parameters, and the optimization scheme comprises an accessory product optimization scheme and an independent optimization scheme.
In the scheme, order information is acquired through an order acquisition module, after the order information is acquired, a corresponding production work order can be generated through a making module, subsequent production planning is facilitated, products corresponding to the order information are classified through a classification module, the corresponding products can be classified into auxiliary products, main products and independent products, the production priority of the order information is ordered through a production arrangement module, each production line can be reasonably distributed, after the products corresponding to the order are put into production, a monitoring period is formulated through a monitoring module, a plurality of parallel time periods are set in the monitoring period, the production capacity under each parallel time period is used as a parameter to be evaluated, the unit production capacity of the ordered products is measured and calculated through an evaluation module according to the parameter to be evaluated, whether the product capacity meets the product demand quantity or not is judged based on the unit production capacity, an alarm signal is sent out when the unit production capacity does not meet the product demand quantity, the alarm signal is sent out and is calibrated as a risk parameter, and finally a corresponding optimization scheme is matched through an optimization module;
In this embodiment, the optimization scheme includes an auxiliary product optimization scheme and an independent optimization scheme, where the auxiliary product corresponds to only the main product, in this way, under the condition that the main product is insufficient in raw material, the auxiliary product can be added as a raw material to the production of the main product, so as to ensure that the order product can be completed before the product demand date, effectively avoid the occurrence of default phenomena caused by overtime of the order by an enterprise, and at the same time, can also clear up redundant inventory of the auxiliary product, and improve inventory turnover rate.
Further, the evaluation module includes:
the first-level evaluation unit is used for measuring and calculating the average value of the product yield in each parallel period and calibrating the measuring and calculating result into a first-level parameter to be checked;
the secondary evaluation unit is used for measuring and calculating the distribution density of the product yield in each parallel period, and calibrating the product yield with the maximum distribution density as a secondary parameter to be checked;
the evaluation unit is used for measuring and calculating evaluation scores of the primary parameter to be checked and the secondary parameter to be checked;
If the evaluation score of the first-level parameter to be checked is greater than or equal to the evaluation score of the second-level parameter to be checked, deleting the second-level parameter to be checked, and only reserving the first-level parameter to be checked;
and if the evaluation score of the primary parameter to be checked is smaller than that of the secondary parameter to be checked, deleting the primary parameter to be checked and only retaining the secondary parameter to be checked.
The bill making module comprises an identification unit, wherein the identification unit is used for adding identification information to the production work bill, and the identification information comprises serial number information and product category information.
The scheduling module comprises a grading unit and a sequencing unit, wherein the grading unit is used for defining the production priority of each order information, and the sequencing unit is used for sequencing production work orders according to the production priority of the order information;
when the grading unit executes, the production worksheets of the same category are classified to obtain a plurality of worksheets to be graded, then the product demand date and the product demand quantity corresponding to the worksheets to be graded of the same category are input into a grading function to obtain grading parameters, the grading parameters are arranged according to the order from large to small, and the arrangement result is determined to be the production priority of the order information.
The monitoring module comprises a partition unit and a screening unit, wherein the partition unit is used for defining parallel time periods in a monitoring period, and the screening unit is used for judging the validity of parameters to be evaluated and screening invalid parameters to be evaluated from a data set to be evaluated.
The invention also discloses a production management terminal based on the MES, which comprises:
at least one processor;
and a memory communicatively coupled to the at least one processor;
wherein the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the MES-based production management method described above.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, apparatus, article or method that comprises the element.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention. Structures, devices and methods of operation not specifically described and illustrated herein, unless otherwise indicated and limited, are implemented according to conventional means in the art.
Claims (7)
1. A MES-based production management method, comprising:
acquiring order information, and generating a production work order according to the product demand and the product demand date, wherein the order information comprises the product demand and the product demand date;
obtaining products corresponding to the order information, and classifying the products into auxiliary products, main products and independent products;
acquiring the production priority of each order information, and arranging production work orders according to the production priority;
making a monitoring period according to the product demand date, acquiring whether order information can be completed normally or not in the monitoring period, and determining risk parameters if the order information cannot be completed normally;
matching an optimization scheme according to the risk parameters, wherein the optimization scheme comprises an accessory product optimization scheme and an independent optimization scheme;
The auxiliary product optimization scheme corresponds to the main product, the independent optimization scheme corresponds to the main product and the independent product, and the execution priority of the auxiliary product optimization scheme is higher than that of the independent optimization scheme;
when the auxiliary optimizing scheme is executed, judging whether auxiliary products of the main product have redundant stock or not;
if so, directly adding the redundant stock into the production of the main product;
if not, executing an independent optimization scheme;
wherein the step of determining the risk parameter comprises:
setting a plurality of parallel time periods in the monitoring period, acquiring the production quantity of products in each parallel time period, calibrating the production quantity as parameters to be evaluated, and summarizing the parameters to be evaluated into a data set to be evaluated;
measuring and calculating the unit yield of the product according to the parameters to be evaluated, and calibrating the unit yield as parameters to be checked, wherein the parameters to be checked comprise a primary parameter to be checked and a secondary parameter to be checked;
judging whether the product yield meets the product demand after the product demand date is finished according to the parameter to be checked;
if yes, indicating that order information corresponding to the parameter to be checked can be normally completed;
If not, indicating that the order information corresponding to the parameter to be checked cannot be completed normally, calibrating the order information as a risk parameter, and synchronously sending out an alarm signal;
the step of measuring and calculating the unit yield of the product according to the parameters to be evaluated and calibrating the unit yield as the parameters to be checked comprises the following steps:
calculating an average value of the product yield in each parallel period, and calibrating the calculation result as a first-level parameter to be checked;
measuring and calculating the distribution density of the product yield in each parallel period, and calibrating the product yield with the maximum distribution density as a secondary parameter to be checked;
if the evaluation score of the first-level parameter to be checked is greater than or equal to the evaluation score of the second-level parameter to be checked, deleting the second-level parameter to be checked, and only reserving the first-level parameter to be checked;
if the evaluation score of the primary parameter to be checked is smaller than that of the secondary parameter to be checked, deleting the primary parameter to be checked, and only retaining the secondary parameter to be checked;
and after the first-level parameter to be checked and the second-level parameter to be checked are compared, taking the evaluation score as a reference parameter, and inputting the reference parameter into a checking function, wherein the expression of the checking function is as follows: Wherein->Indicating predicted product yield,/->Indicating the yield of the product produced,/->Representing reference parameters->Representing a time interval between a product demand date and a current date;
after judging that the product demand date is over according to the parameter to be checked, the step of judging whether the product yield meets the product demand comprises the following steps:
according to the parameter to be verified, predicting the product yield under the product demand date through a verification function, and performing difference processing on the product yield and the product demand to obtain the parameter to be approved;
comparing the parameter to be approved with a verification threshold;
if the parameter to be approved is larger than or equal to the verification threshold, judging that the product yield under the predicted product demand date meets the product demand;
and if the parameter to be approved is smaller than the verification threshold, judging that the product yield under the predicted product demand date does not meet the product demand.
2. The MES-based production management method according to claim 1, wherein: the step of obtaining the products corresponding to the order information and classifying the products into the auxiliary products, the main products and the independent products comprises the following steps:
the products corresponding to the order information are calibrated as parameters to be classified, the material details of the parameters to be classified are respectively obtained, the materials are calibrated as parameters to be compared, and the parameters to be classified are compared with the parameters to be compared;
If the parameters to be classified are consistent with the parameters to be compared, the parameters to be classified are marked as auxiliary products, and the products corresponding to the parameters to be compared are marked as main products, wherein the main products at least comprise one auxiliary product;
if the parameters to be classified are inconsistent with the parameters to be compared, the parameters to be classified are directly calibrated into independent products.
3. The MES-based production management method according to claim 1, wherein: the step of obtaining the production priority of each order information and arranging the production worksheets according to the production priority comprises the following steps:
classifying the production worksheets of the same class one by one to obtain a plurality of worksheets to be classified;
inputting the product demand date and the product demand quantity corresponding to the worksheets to be classified in the same class into a classification function to obtain classification parameters, wherein the expression of the classification function is as follows:wherein->Representing grading parameters->Represents unit standard yield,/->Indicating the required yield of the product, < >>Representing an interval between a product demand date and a current day period;
ranking the ranking parameters in order from large to small, and determining ranking results as production priorities of the order information;
And sequencing the production worksheets according to the production priority.
4. The MES-based production management method according to claim 1, wherein: after the parameter to be evaluated is calibrated, the method further comprises the step of judging the effectiveness of the parameter to be evaluated, wherein the judging process is as follows:
acquiring a starting point of product processing and a production stopping interval of the product processing, and judging whether the starting point of the product processing is overlapped with an ending point of the production stopping interval;
if yes, the time interval between the starting point of product processing and the starting point of the production stopping interval is calibrated as a reference time interval, the reference time interval is shifted in a cis-position mode in the monitoring period, and the shifting result is calibrated as a parallel time interval;
if not, the time interval between the starting point of product processing and the starting point of the production stopping interval is marked as a temporary time interval, the time interval between the ending point of the production stopping interval and the starting point of the next production stopping interval is determined as a reference time interval, the reference time interval is shifted in order in the monitoring period, and the shifting result is marked as a parallel time interval;
and comparing the parameter to be evaluated with a screening threshold value, wherein the parameter to be evaluated, which is higher than the screening threshold value, is reserved in the data set to be evaluated, and the parameter to be evaluated, which is lower than or equal to the screening threshold value, is screened out from the data set to be evaluated.
5. The MES-based production management system applied to the MES-based production management method of any one of claims 1 to 4, comprising an order acquisition module, a bill making module, a classification module, a production scheduling module, a monitoring module, an evaluation module, a verification module and an optimization module, and being characterized in that:
the order acquisition module is used for acquiring order information, wherein the order information comprises product demand and product demand date;
the bill making module is used for generating a production work bill according to the product demand and the product demand date;
the classification module is used for acquiring products corresponding to the order information and classifying the products into auxiliary products, main products and independent products;
the scheduling module is used for acquiring the production priority of each order information and scheduling production work orders according to the production priority of the order information;
the monitoring module is used for making a monitoring period according to a product demand date, setting a plurality of parallel time periods in the monitoring period, acquiring the product production quantity under each parallel time period, calibrating the product production quantity as a parameter to be evaluated, and summarizing the parameter to be evaluated into a data set to be evaluated;
The evaluation module is used for measuring and calculating the unit yield of the product according to the parameters to be evaluated and calibrating the unit yield as the parameters to be checked, wherein the parameters to be checked comprise a first-level parameter to be checked and a second-level parameter to be checked;
the verification module is used for judging whether the product yield meets the product demand after the product demand date is finished according to the parameter to be verified;
if yes, indicating that order information corresponding to the parameter to be checked can be normally completed;
if not, indicating that the order information corresponding to the parameter to be checked cannot be completed normally, calibrating the order information as a risk parameter, and synchronously sending out an alarm signal;
the optimization module is used for matching an optimization scheme according to the risk parameters, and the optimization scheme comprises an accessory product optimization scheme and an independent optimization scheme.
6. The MES-based production management system of claim 5, wherein the evaluation module includes:
the first-level evaluation unit is used for measuring and calculating the average value of the product yield in each parallel period and calibrating the measuring and calculating result into a first-level parameter to be checked;
the secondary evaluation unit is used for measuring and calculating the distribution density of the product yield in each parallel period, and calibrating the product yield with the maximum distribution density as a secondary parameter to be checked;
The evaluation unit is used for measuring and calculating evaluation scores of the primary parameter to be checked and the secondary parameter to be checked;
if the evaluation score of the first-level parameter to be checked is greater than or equal to the evaluation score of the second-level parameter to be checked, deleting the second-level parameter to be checked, and only reserving the first-level parameter to be checked;
and if the evaluation score of the primary parameter to be checked is smaller than that of the secondary parameter to be checked, deleting the primary parameter to be checked and only retaining the secondary parameter to be checked.
7. The utility model provides a production management terminal based on MES which characterized in that: comprising the following steps:
at least one processor;
and a memory communicatively coupled to the at least one processor;
wherein the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the MES-based production management method of any one of claims 1 to 4.
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