CN116128221A - Digital twin-based dispatching method for remanufacturing production line of aero-hair blade - Google Patents
Digital twin-based dispatching method for remanufacturing production line of aero-hair blade Download PDFInfo
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Abstract
The invention discloses a dispatching method of a digital twin-based aerial hair blade remanufacturing production line, which comprises the following steps: constructing a remanufacturing workshop digital twin model and historical twin data based on physical remanufacturing workshop information, and acquiring a plurality of groups of damaged blade information; based on a plurality of groups of damaged blade information, constructing an optimization model of cross-batch workshop dispatching based on the damaged blade remanufacturing profit rate, and carrying out optimization solution to obtain a cross-batch dispatching scheme based on the damaged blade remanufacturing profit rate; based on a real-time sensor, constructing a workshop dynamic scheduling model based on real-time procedure completion time, and regenerating a workshop dynamic scheduling scheme based on a profit margin model and the real-time procedure completion time; and correcting the machining track digital twin simulation man-hour of a plurality of working procedures based on a workshop dynamic scheduling model of real-time working procedure completion time, performing scheduling planning on the next batch of damaged blade remanufacturing workshops, and completing scheduling of the damaged blade remanufacturing production line.
Description
Technical Field
The invention belongs to the field of digital twin of complex part remanufacturing production lines, and particularly relates to a dispatching method of a digital twin-based aerial hair blade remanufacturing production line.
Background
In remanufacturing workshop scheduling, the processing time of each working procedure is uncertain due to different damage degrees of workpieces, so that algorithms such as fuzzy variables and the like are adopted to expand and solve the production scheduling problem of the traditional manufacturing workshop. In recent years, in order to solve the real-time correction requirement of dispatching caused by fuzzy variables, a digital twin technology is introduced into the production dispatching of a remanufacturing workshop, the processing time, equipment energy consumption, equipment utilization rate and the like of a batch damaged workpiece under the dispatching of the remanufacturing workshop are taken as optimization targets, and a digital space model and a physical space model of the damaged workpiece and the remanufacturing workshop are in real-time interaction through technical means such as virtual-real interaction feedback, data fusion analysis and the like, so that the damaged workpiece and the remanufacturing workshop can timely master the dynamic change of each other and make dispatching response in real time.
Under the remanufacturing system of the aerial hair blade, the damaged areas of the blade are different, and the processing time and the process path have larger uncertainty; the blades in the same damaged area still have different service deformation differences due to the damage degree such as the area, the depth and the like of the damaged area of the blade and the undamaged area of the blade. The scheduling problem in the remanufacturing plant is therefore complex compared to conventional manufacturing, and accurate description and analysis of uncertainty factors in the remanufacturing plant facilitates production management. The general drawbacks of the prior art in this context are as follows:
(1) The damage state, the technological process, the working procedure time and other uncertain factors of each blade in the remanufacturing process cause different profits of each blade, so that the objective function (such as minimum maximum finishing time, minimum maximum machine load, minimum advance/pull period and other indexes) of the scheduling of the existing remanufacturing workshop cannot consider the profit target;
(2) The existing remanufacturing shop scheduling is aimed at a single batch, and for the existence of a single piece or a small number of pieces in the batch of blades caused by the uncertain factors, the reduction of the profit margin serving as an evaluation index is inevitably caused, so that the remanufacturing shop scheduling effect is poor, and a cross-batch scheduling method is urgently needed;
(3) The digital twin in the remanufacturing process mainly solves the problem of determining the time of each working procedure, and for damaged blades, the main working procedures are the additive and subtractive processing procedures, and the highest time proportion of a single working procedure is the track time when the equipment operates to increase and decrease the material processing. Therefore, by means of historical data and real-time data in digital twinning, the processing time of the key working procedure is accurately estimated, and therefore the scheduling scheme is dynamically adjusted.
Disclosure of Invention
The invention aims to provide a dispatching method of a remanufacturing production line of an aerovane based on digital twin, which can accurately evaluate and correct the processing time of each working procedure in the digital twin environment on one hand, so that the generated dispatching scheme can respond to the actual workshop state more quickly; on the other hand, the profit margin of the remanufacturing of the aeronautical blade can be improved, so that technical support is provided for the scheduling of a remanufacturing workshop of the aeronautical blade.
In order to achieve the above purpose, the invention provides a dispatching method of a digital twin-based aerial hair blade remanufacturing production line, comprising the following steps:
s1, acquiring physical remanufacturing workshop information, and constructing a remanufacturing workshop digital twin model and historical twin data based on the physical remanufacturing workshop information;
s2, acquiring a plurality of groups of damaged blade information based on the historical twin data and the remanufacturing workshop digital twin model;
s3, constructing an optimization model of cross-batch workshop scheduling based on the damaged blade remanufacturing profit margin based on a plurality of groups of damaged blade information;
s4, optimizing and solving an optimization model of the cross-batch workshop scheduling based on the damaged blade remanufacturing profit margin to obtain a cross-batch scheduling scheme based on the damaged blade remanufacturing profit margin;
s5, constructing a workshop dynamic scheduling model based on real-time procedure completion time based on the real-time sensor, and returning to S4 to regenerate a workshop dynamic scheduling scheme based on the profit margin model and the real-time procedure completion time;
s6, correcting the machining track digital twin simulation man-hour of a plurality of working procedures based on the workshop dynamic scheduling model based on the real-time working procedure completion time, acquiring correction data, returning to S2 based on the correction data to perform scheduling planning of the next batch of damaged blade remanufacturing workshops, and completing scheduling of the damaged blade remanufacturing production line.
Optionally, the physical remanufacturing plant information includes cleaning equipment, detection equipment, additive machining equipment, subtractive machining equipment, plant transfer equipment, and automation equipment.
Optionally, the historical twinning data includes: damaged blade evaluation index, damage grouping, theoretical model, remanufacturing process route and processing track.
Optionally, based on the historical twin data and the remanufacturing plant digital twin model, obtaining a plurality of sets of damaged blade information includes:
acquiring damaged blade data based on the historical twin data and the remanufacturing workshop digital twin model;
detecting a plurality of damaged blades based on the damaged blade data, and constructing a plurality of actual models of the damaged blades;
comparing the actual model of the damaged blades with the theoretical model, and carrying out evaluation grouping based on the damaged blade evaluation indexes to obtain a plurality of groups of damaged blade information.
Optionally, performing optimization solution on the optimization model of the cross-batch shop scheduling based on the damaged blade remanufacturing profit margin, and obtaining the cross-batch scheduling scheme based on the damaged blade remanufacturing profit margin includes:
constructing an optimization target of the cross-batch workshop scheduling based on the damaged blade remanufacturing profit margin based on an optimization model of the cross-batch workshop scheduling based on the damaged blade remanufacturing profit margin;
and optimizing and solving the optimization target of the cross-batch workshop scheduling based on the damaged blade remanufacturing profit margin to obtain a cross-batch scheduling scheme based on the damaged blade remanufacturing profit margin.
Optionally, constructing the optimization objective for cross-batch shop scheduling based on damaged blade remanufacturing profit margins includes:
acquiring the remanufacturing profit of the single damaged blade based on a plurality of groups of damaged blade information;
a step of acquiring the single damaged blade based on the historical twin data;
remanufacturing and scheduling the procedure of damaging the blade by one piece to obtain a processing starting time point and a processing ending time point after remanufacturing and scheduling;
based on the remanufactured profit of the single damaged blade, the processing start time point and the processing end time point after remanufacturing scheduling, constructing an optimization objective of the cross-batch shop scheduling based on the damaged blade remanufacturing profit margin.
Optionally, the optimizing and solving the optimizing target of the cross-batch workshop dispatching based on the damaged blade remanufacturing profit margin, and the method for obtaining the cross-batch dispatching scheme based on the damaged blade remanufacturing profit margin comprises the following steps:
and based on the historical twin data and a plurality of groups of damaged blade information, obtaining a cross-batch scheduling scheme based on the damaged blade remanufacturing profit rate for the cross-batch workshop scheduling optimization target matching multi-target optimization algorithm based on the damaged blade remanufacturing profit rate.
Optionally, based on the real-time sensor, constructing a workshop dynamic scheduling model based on the real-time process completion time, and returning to S4 to regenerate the workshop dynamic scheduling scheme based on the profit margin model and the real-time process completion time includes:
based on real-time sensors to monitor actual working hours of a plurality of working procedures in the damaged blade remanufacturing process flow, a workshop dynamic scheduling model based on real-time working procedure completion time is constructed;
and returning to execute S4 based on the workshop dynamic scheduling model based on the real-time procedure completion time, and regenerating a profit margin model and a workshop dynamic scheduling scheme of the real-time procedure completion time.
Optionally, based on the workshop dynamic scheduling model based on the real-time process completion time, returning to S4, and regenerating the profit margin model and the workshop dynamic scheduling scheme of the real-time process completion time includes:
based on the workshop dynamic scheduling model based on the real-time working procedure completion time, acquiring actual working hours of a plurality of damaged blade working procedures
Acquiring simulation man-hours of a plurality of damaged blade procedures based on the cross-batch scheduling scheme based on the damaged blade remanufacturing profit margin;
acquiring a plurality of man-hour differences based on the actual man-hours of a plurality of damaged blade procedures and the simulation man-hours of a plurality of damaged blade procedures;
and (4) returning to execute the step (S4) based on a plurality of the man-hour differences, and regenerating a profit margin model and a workshop dynamic scheduling scheme of real-time procedure completion time.
Optionally, correcting the machining track digital twin simulation man-hour of a plurality of processes based on the workshop dynamic scheduling model of the real-time process completion time, and obtaining correction data includes:
acquiring actual working hours of a plurality of blade damaging working procedures based on a workshop dynamic scheduling model of the real-time working procedure completion time;
correcting simulation man-hours of a plurality of damaged blade procedures based on actual man-hours of the plurality of damaged blade procedures to obtain correction data;
the simulation man-hour of the plurality of damaged blade working procedures is the digital twin simulation man-hour of the processing track of the plurality of working procedures.
The invention has the following beneficial effects:
aiming at the difficult scheduling problem of the remanufacturing workshop caused by uncertain factors such as damage state, process flow, working procedure time and the like of each blade in the remanufacturing workshop of the aerial damaged blade, the scheduling of the remanufacturing workshop is carried out by taking the batch profit margin as a target, and the maximization of the remanufacturing economic benefit is realized. Meanwhile, a cross-batch dispatching method is provided for the situation that the total dispatching time is additionally increased due to a small number of parts in single-batch damaged blades, and the remanufacturing efficiency of the damaged blades is improved. In addition, aiming at the problem of working procedure track working hour simulation deviation in the digital twin environment caused by the uncertain factors, the workshop dynamic scheduling and processing track digital twin simulation working hour correction based on real-time working procedure completion time are provided by means of history and real-time data, the working hour simulation accuracy is technically improved, and meanwhile, the dynamic response capability of a remanufacturing workshop is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application, illustrate and explain the application and are not to be construed as limiting the application. In the drawings:
FIG. 1 is a schematic flow chart of a dispatching method for a digital twin-based aerial hair blade remanufacturing line according to an embodiment of the present invention;
FIG. 2 is a diagram of an overall frame of a digital twin based aerial hair blade remanufacturing plant scheduling in accordance with an embodiment of the present invention;
fig. 3 is a processing track of a digital twin lower damaged blade according to an embodiment of the present invention.
Detailed Description
It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
The invention discloses a digital twin-based dispatching method for a remanufacturing workshop of an aerial hair blade, which comprises 4 parts including a physical remanufacturing workshop, a digital twin model of the remanufacturing workshop, remanufacturing twin data and a dispatching method of the remanufacturing workshop. Wherein the remanufactured twin data comprises historical data, real-time data and a scheduling scheme; the remanufacturing workshop scheduling method comprises cross-batch scheduling based on a profit margin model, workshop dynamic scheduling based on real-time working procedure completion time and machining track digital twin simulation working hour correction.
As shown in fig. 1-2, in this embodiment, a dispatching method for a digital twin-based aerial hair blade remanufacturing line is provided, including:
step one, constructing a remanufacturing workshop digital twin model and historical twin data
And digitally mapping the physical remanufacturing workshop through a modeling technology to form a remanufacturing workshop resource element composition virtual model. Meanwhile, the damaged blade evaluation index and damage grouping, the theoretical model V, the remanufacturing process route and the processing track of each procedure which are applicable to the remanufacturing workshop are used as historical data, and the specific implementation modes are as follows:
1) The physical remanufacturing plant for damaged blades generally comprises cleaning equipment, detecting equipment, additive machining equipment, material reduction machining equipment, plant transferring equipment, other automatic equipment and the like, and a digital twin model of each equipment is constructed by adopting a digital modeling method.
2) The damaged blade is evaluated by strict standards, and the damaged blade is divided into small, medium and large types according to the standards, and the different damage types are manufactured by laser additive manufacturing, plasma patch welding, linear friction welding, blade replacement and other methods. The damaged areas under the same damage standard can be subdivided into groups such as a citron board surface, a blade root surface, an air inlet and outlet edge, a blade back and leaf basin and the like, and the corresponding technological routes and the processing tracks of the working procedures of the areas are completely different.
3) And storing the damaged blade evaluation indexes and the damage groups, the corresponding theoretical model V, the remanufacturing process route and the processing track of each working procedure, and the corresponding equipment digital twin model into a twin database as historical data.
Step two, collecting batch damaged blade data and evaluating grouping
Data acquisition and processing of damaged blades of a W (w=1, …, W) lot are performed by detection equipment in a physical remanufacturing workshop, an actual model of each blade is established, and the actual models are grouped by means of damage evaluation indexes after comparison with theoretical models, namely the lot n w The damaged blades are divided into G groups, each group s wg Piece, itWherein W is the batch of damaged blades, W is the total batch number of damaged blades, n w For the number of damaged blades in the w-th batch, G is n w Total group number after damaged blade evaluation grouping, g is group number after damaged blade evaluation grouping, s wg The number of damaged blades for group g is as follows:
cleaning equipment to w lot total n in physical remanufacturing plant w After the damaged blade is subjected to surface cleaning, the damaged blade is subjected to damage detection and profile detection by using detection equipment, a blade actual model is constructed by using a CAD modeling technology, and the model is compared with V and then subjected to damage grouping according to evaluation indexes, namely the batch n w The damaged blades are divided into G groups, each group s wg And (3) a piece.
Step three, constructing an optimization model of cross-batch workshop scheduling based on damaged blade remanufacturing profit margin
1) The remanufacturing profit of a g group of single-piece damaged blades given by a craftsman is Y g Obtaining a corresponding process route for remanufacturing the group of blades from the twin data, wherein the process route comprises K working procedures P g {p g1 ,…p gk ,…,p gK }. Kth procedure p during shop scheduling gk Corresponding processing equipment is M bm Wherein b=1, …, B is the machining equipment category, m=1, …, M is the number of M machining equipment of the B category, wherein K is the total number of steps, P g {p g1 ,…p gK ,…,p gK K steps, K is the number of steps, p gk For the kth procedure, M bm And (5) processing equipment corresponding to the kth procedure in workshop scheduling.
2) For the w lot, group g, i=1, …, s wg Damaged blade, i is the number of damaged blades in group g of the w-th batch, p is gk The working procedure is that the processing starting time point after the remanufacturing and scheduling in the digital twin environment is that
The ending time point is +.>
The worker of the processThe time is->
The nominal total working man-hour of the blade is +.>
The nominal profit margin is thus defined as:
the total working time of the blade after being scheduled in a remanufacturing workshop is
Wherein (1)>
The actual profit margin is defined by the processing start time point of the first process for the ith damaged blade in the g group of the w lot:
establishing a remanufacturing workshop scheduling optimization target based on remanufacturing profit margin is as follows:
when the optimization target performs workshop scheduling under digital twin, the single working procedure time of each damaged blade
The method is obtained by the simulation operation of the processing track under digital twinning. As shown in FIG. 3, since the damaged condition of each blade in the group g is different, inThe actual model of the ith damaged blade in the w-th batch g-th group established by the detection equipment before dispatching is +.>
Then V and +.>
The difference between them is->
It is known that a damaged blade with V as the target is at p gk The corresponding processing track in the working procedure is TL gk Then->
The corresponding processing track is->
Whereby the man-hour for obtaining the procedure by simulation under digital twinning is +.>
The cross-lot dispatch threshold is given by the shop personnel as α, if
And (3) moving the ith damaged blade in the g group of the w lot into the w+1st lot for workshop dispatching, and iteratively executing the fourth production dispatching scheme without considering the blade in the current w lot.
Step four, solving a cross-batch scheduling scheme based on a profit margin model
The method comprises the steps of utilizing historical data, batch damaged blade detection and grouping data in a total framework of digital twin remanufacturing workshop dispatching to obtain a dispatching scheme and issuing workshop execution for a multi-objective optimization algorithm which is most effective in cross-batch dispatching optimization objective and condition matching based on a profit margin model, wherein the specific implementation mode is as follows:
solving cross-batch dispatching optimization targets based on a profit margin model by adopting a multi-target optimization algorithm such as a genetic algorithm, and issuing the constructed workshop dispatching scheme to a physical remanufacturing workshop for execution after simulating in a digital twin environment.
Step five, constructing a workshop dynamic scheduling mechanism based on real-time procedure completion time
1) In the execution process of the workshop scheduling scheme, the operation states of the material adding processing equipment and the material subtracting processing equipment are monitored in real time, and the damaged blade of the ith piece in the g group of the w batch is recorded in M bm Upper completion p gk Actual working time of the working procedure and
comparing to obtain man-hour difference->
2) At the execution time point of the current workshop scheduling scheme, if the accumulated working hour deviation is
And starting a workshop dynamic scheduling mechanism. At this point in time, the damaged blade that has completed all the procedures does not participate in the dynamic scheduling; the blade in the process execution needs to finish the current process, and the rest processes participate in dynamic scheduling; for the blade which is not manufactured yet, all working procedures participate in dynamic scheduling, a workshop dynamic scheduling scheme based on a profit margin model and real-time working procedure completion time is constructed by utilizing a solving algorithm in the fourth step, and the solution is issued to a physical remanufacturing workshop for execution; if the accumulated working time deviation is->
P of the blade gk+1 The process start time is adjusted to
And continuing to execute the current workshop scheduling scheme.
Step six, correcting the machining track digital twin simulation man-hour
Establishment of
Middle->
Time correction factor for the individual knife sites->
The ith damaged blade in the ith working procedure is at the cutter position point of the kth working procedure for the ith lot, and the data is stored in a data twinning database. Then the processing track +.>
The corresponding digital twinning lower simulation man-hour is corrected into
The foregoing is merely a preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the technical scope of the present application should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A dispatching method of a digital twin-based aerial hair blade remanufacturing production line is characterized by comprising the following steps of:
s1, acquiring physical remanufacturing workshop information, and constructing a remanufacturing workshop digital twin model and historical twin data based on the physical remanufacturing workshop information;
s2, acquiring a plurality of groups of damaged blade information based on the historical twin data and the remanufacturing workshop digital twin model;
s3, constructing an optimization model of cross-batch workshop scheduling based on the damaged blade remanufacturing profit margin based on a plurality of groups of damaged blade information;
s4, optimizing and solving an optimization model of the cross-batch workshop scheduling based on the damaged blade remanufacturing profit margin to obtain a cross-batch scheduling scheme based on the damaged blade remanufacturing profit margin;
s5, constructing a workshop dynamic scheduling model based on real-time procedure completion time based on the real-time sensor, and returning to S4 to regenerate a workshop dynamic scheduling scheme based on the profit margin model and the real-time procedure completion time;
s6, correcting the machining track digital twin simulation man-hour of a plurality of working procedures based on the workshop dynamic scheduling model based on the real-time working procedure completion time, acquiring correction data, returning to S2 based on the correction data to perform scheduling planning of the next batch of damaged blade remanufacturing workshops, and completing scheduling of the damaged blade remanufacturing production line.
2. The digital twinning-based aerial hair blade remanufacturing line scheduling method of claim 1, wherein the physical remanufacturing shop information comprises a cleaning tool, a detection tool, an additive manufacturing tool, a subtractive manufacturing tool, a shop transfer tool, and an automation tool.
3. The digital twinning-based aerial hair blade remanufacturing line scheduling method of claim 1, wherein the historical twinning data comprises: damaged blade evaluation index, damage grouping, theoretical model, remanufacturing process route and processing track.
4. The digital twin based aerial hair blade remanufacturing line scheduling method of claim 3, wherein obtaining sets of damaged blade information based on the historical twin data and the remanufacturing plant digital twin model comprises:
acquiring damaged blade data based on the historical twin data and the remanufacturing workshop digital twin model;
detecting a plurality of damaged blades based on the damaged blade data, and constructing a plurality of actual models of the damaged blades;
comparing the actual model of the damaged blades with the theoretical model, and carrying out evaluation grouping based on the damaged blade evaluation indexes to obtain a plurality of groups of damaged blade information.
5. The digital twin-based aerial hair blade remanufacturing production line scheduling method of claim 1, wherein optimizing the optimization model of the cross-batch shop scheduling based on damaged blade remanufacturing profit margin to obtain a cross-batch scheduling scheme based on the damaged blade remanufacturing profit margin comprises:
constructing an optimization target of the cross-batch workshop scheduling based on the damaged blade remanufacturing profit margin based on an optimization model of the cross-batch workshop scheduling based on the damaged blade remanufacturing profit margin;
and optimizing and solving the optimization target of the cross-batch workshop scheduling based on the damaged blade remanufacturing profit margin to obtain a cross-batch scheduling scheme based on the damaged blade remanufacturing profit margin.
6. The digital twin based aerial hair blade remanufacturing line scheduling method of claim 5, wherein constructing the optimization objective for cross-batch shop scheduling based on damaged blade remanufacturing profit margins comprises:
acquiring the remanufacturing profit of the single damaged blade based on a plurality of groups of damaged blade information;
a step of acquiring the single damaged blade based on the historical twin data;
remanufacturing and scheduling the procedure of damaging the blade by one piece to obtain a processing starting time point and a processing ending time point after remanufacturing and scheduling;
based on the remanufactured profit of the single damaged blade, the processing start time point and the processing end time point after remanufacturing scheduling, constructing an optimization objective of the cross-batch shop scheduling based on the damaged blade remanufacturing profit margin.
7. The digital twin based aerial hair blade remanufacturing line scheduling method of claim 6, wherein optimizing the optimization objective of the cross-batch shop scheduling based on damaged blade remanufacturing profit margin, the method for obtaining the cross-batch scheduling scheme based on damaged blade remanufacturing profit margin comprises:
and based on the historical twin data and a plurality of groups of damaged blade information, obtaining a cross-batch scheduling scheme based on the damaged blade remanufacturing profit rate for the cross-batch workshop scheduling optimization target matching multi-target optimization algorithm based on the damaged blade remanufacturing profit rate.
8. The digital twin based dispatching method for aerial hair blade remanufacturing production line of claim 1, wherein constructing a shop dynamic dispatching model based on real time process completion time based on real time sensors, returning to S4 to regenerate a shop dynamic dispatching scheme based on profit margin model and real time process completion time comprises:
based on real-time sensors to monitor actual working hours of a plurality of working procedures in the damaged blade remanufacturing process flow, a workshop dynamic scheduling model based on real-time working procedure completion time is constructed;
and returning to execute S4 based on the workshop dynamic scheduling model based on the real-time procedure completion time, and regenerating a profit margin model and a workshop dynamic scheduling scheme of the real-time procedure completion time.
9. The digital twin based aerial hair blade remanufacturing line scheduling method of claim 8, wherein returning to execute S4 based on the real-time process completion time based shop dynamic scheduling model, regenerating a profitability model and a real-time process completion time based shop dynamic scheduling scheme comprises:
based on the workshop dynamic scheduling model based on the real-time working procedure completion time, acquiring actual working hours of a plurality of damaged blade working procedures
Acquiring simulation man-hours of a plurality of damaged blade procedures based on the cross-batch scheduling scheme based on the damaged blade remanufacturing profit margin;
acquiring a plurality of man-hour differences based on the actual man-hours of a plurality of damaged blade procedures and the simulation man-hours of a plurality of damaged blade procedures;
and (4) returning to execute the step (S4) based on a plurality of the man-hour differences, and regenerating a profit margin model and a workshop dynamic scheduling scheme of real-time procedure completion time.
10. The digital twin-based aerial hair blade remanufacturing line scheduling method of claim 9, wherein correcting the machining trajectory digital twin simulation man-hours of the plurality of processes based on the shop dynamic scheduling model of the real-time process completion time comprises:
acquiring actual working hours of a plurality of blade damaging working procedures based on a workshop dynamic scheduling model of the real-time working procedure completion time;
correcting simulation man-hours of a plurality of damaged blade procedures based on actual man-hours of the plurality of damaged blade procedures to obtain correction data;
the simulation man-hour of the plurality of damaged blade working procedures is the digital twin simulation man-hour of the processing track of the plurality of working procedures.
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