Blister tray production material utilization optimal path planning method

Abstract

The present application relates to the technical field of production material utilization, in particular to a blister tray production material utilization optimal path planning method, comprising: obtaining raw material specification data and blister tray model data, establishing an initial utilization evaluation function based on area proportion and a residual material recyclability scoring function, constructing an initial layout target function, and obtaining initial layout data according to the initial layout target function; generating a residual area binary image matrix based on the initial layout data, identifying the residual material area and extracting a geometric feature vector, and establishing a residual material feature database; establishing a blister tray feature database according to the blister tray model data, constructing a matching degree function in combination with the residual material feature database, constructing a recycling target function, and obtaining recycling layout data according to the recycling target function; and constructing optimal path data by considering the initial layout data and the recycling layout data. The present application improves the production material utilization by considering residual material recycling.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of material utilization rate, in particular to a blister tray production material utilization rate optimal path planning method. BACKGROUND

[0002] The optimization problems in the production process of blister trays include layout optimization and cutting path optimization, which need to be processed with the help of computing technology. Specifically, for blister tray products of different shapes and sizes, a reasonable layout scheme needs to be designed, and an optimal path needs to be planned in the cutting process to minimize the waste of raw materials. Due to the diversity of product shapes and the limitations of production processes, various shapes and sizes of excess materials are inevitably produced in actual production.

[0003] Although these excess materials are difficult to be directly used in the production of large blister trays due to their irregular shapes, part of the areas still have utilization value for the production of small blister trays. This requires analyzing the excess material area, identifying the effective area that can be used to produce small blister trays, and reasonably arranging and planning the path.

[0004] Therefore, a blister tray production material utilization rate optimal path planning method is proposed. SUMMARY

[0005] The purpose of the present application is to provide a blister tray production material utilization rate optimal path planning method, which improves the production material utilization rate by considering the reuse of excess materials. It includes: obtaining raw material specification data and blister tray model data, establishing an initial utilization rate evaluation function based on area ratio and an excess material reusability scoring function, constructing an initial layout objective function, and obtaining initial layout data according to the initial layout objective function; generating a residual area binary image matrix based on the initial layout data, identifying the excess material area and extracting the geometric feature vector, and establishing an excess material feature database; establishing a blister tray feature database according to the blister tray model data, constructing a matching degree function combining the excess material feature database, constructing a reuse objective function, and obtaining reuse layout data according to the reuse objective function; considering the initial layout data and the reuse layout data, constructing an optimal path data.

[0006] To achieve the above purpose, the present application provides the following technical scheme:

[0007] A blister tray production material utilization rate optimal path planning method, comprising:

[0008] Obtaining raw material specification data and blister tray model data, establishing an initial utilization rate evaluation function based on area ratio and an excess material reusability scoring function;

[0009] constructing an initial layout target function based on the initial utilization evaluation function and the recyclability scoring function, and obtaining initial layout data according to the initial layout target function;

[0010] generating a remaining area binary image matrix based on the initial layout data, identifying a remaining material area and extracting a geometric feature vector through a connected region marking algorithm, and establishing a remaining material feature database;

[0011] establishing a blister tray feature database according to the blister tray model data, constructing a matching degree function in combination with the remaining material feature database, constructing a recycling target function based on the matching degree function, and obtaining recycling layout data according to the recycling target function;

[0012] constructing a final target function considering the initial layout data and the recycling layout data, and generating optimal path data according to the final target function.

[0013] Preferably, the initial utilization evaluation function based on the area ratio is established by obtaining the length and width of the raw material, simultaneously obtaining the three-dimensional model data of the blister tray to be produced, projecting the three-dimensional model of the blister tray onto a two-dimensional plane, obtaining the two-dimensional contour of each blister tray, and calculating the area of each blister tray; the initial utilization evaluation function is defined as the ratio of the total area of all successfully arranged blister trays to the area of the original material.

[0014] Preferably, the recyclability scoring function of the remaining material is established by:

[0015] The recyclability scoring function of the remaining material is constructed by considering the area, connectivity index and shape complexity of the remaining material area, and is expressed as:

[0016]

[0017] wherein RE represents the recyclability scoring function of the remaining material, m represents the number of remaining material areas, A k represents the area of the kth remaining material area, C k represents the connectivity index of the kth remaining material area, F k represents the shape complexity of the kth remaining material area, and a, β and γ represent the influence coefficients of the area, connectivity index and shape complexity, respectively.

[0018] Preferably, obtaining initial layout data according to the initial layout objective function comprises: combining the initial utilization evaluation function and the scrap recyclability scoring function to obtain the initial layout objective function; establishing initial layout constraints, including: all blister trays are completely located within the raw material range; any two blister trays cannot overlap; the distance between adjacent blister trays is greater than or equal to the corresponding minimum distance; the arrangement direction rotation angle of the blister tray belongs to the preset rotation angle set; solving the initial layout objective function based on the initial layout constraints; generating an initial layout scheme using a genetic algorithm, including the position coordinates and rotation angle of each blister tray; defining a first fitness function as the value of the initial layout objective function; generating a new population through selection, crossover and mutation operations; using an elite reservation strategy to reserve the optimal solution; stopping iteration when the iteration reaches a preset stop condition; and outputting the initial layout objective function.

[0019] Preferably, establishing the scrap feature database specifically comprises: marking the area where the blister trays are arranged as 0 and the remaining area as 1 based on the initial layout data to obtain a residual area binary image matrix; processing the residual area binary image matrix through a connected region marking algorithm to obtain all scrap areas; performing edge detection on each scrap area to obtain a scrap area contour point set; extracting geometric features of each scrap area to obtain the geometric feature vector; and storing the scrap area contour point set and the geometric feature vector in the scrap feature database.

[0020] Preferably, obtaining the recycling layout data according to the recycling objective function specifically comprises: obtaining a blister tray contour point set and a geometric feature vector of a blister tray based on the blister tray model data to obtain a blister tray feature database; defining a matching degree function to evaluate the adaptation degree of a scrap area to a blister tray, the matching degree function considering area utilization, contour matching degree and feature vector similarity; constructing the recycling objective function according to the matching degrees of all types of blister trays and all scrap areas in the blister tray feature database and the scrap feature database; establishing recycling constraints, including: each scrap area selects at most one arrangement scheme of one type of blister tray; the blister tray is completely located within the scrap area; the distance between adjacent blister trays is greater than or equal to the corresponding minimum distance; the arrangement direction rotation angle of the blister tray belongs to the preset rotation angle set; solving the recycling objective function based on the recycling constraints; for each scrap area, screening out a set of potential matching blister trays based on the matching degree function to form a candidate match; generating multiple arrangement schemes for each candidate match; calculating the matching degree of each arrangement scheme; using a branch and bound algorithm to solve the integer programming problem to find the globally optimal candidate match and arrangement scheme; and outputting the recycling layout data.

[0021] Preferably, generating optimal path data based on the final objective function specifically includes: extracting the outline point set of each blister tray from the initial layout data and the reuse layout data respectively; constructing the final objective function based on the total cutting path length, the number of cuts, and the turning penalty of the cutting path; constructing final constraints, including: each point in each blister tray outline point set appears once in the cutting path; the cutting start point and end point are the same point; the turning radius of the cutting path is greater than or equal to the minimum turning radius; solving the final objective function based on the final constraints: using path encoding to represent the cutting order and the corresponding direction; initializing the population and generating a set of cutting paths; defining the second fitness function as the reciprocal of the final objective function value; generating a new population using roulette wheel selection, sequential crossover, and random mutation operations; performing local optimization on the newly generated individuals; stopping iteration when the preset stopping condition is reached; and outputting the optimal path data.

[0022] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0023] 1. A two-stage optimization layout strategy is proposed, combining initial and secondary layout methods. The first-stage optimization considers not only the current material utilization rate but also the reuse potential of leftover materials. This is achieved by constructing an initial utilization rate evaluation function and a leftover material reusability scoring function, which are then weighted and combined to form the initial layout objective function. This method overcomes the limitation of traditional layout methods that only focus on current utilization rates, introducing forward-looking thinking. This gives the leftover materials after the initial layout higher reuse value, laying a solid foundation for subsequent reuse. This two-stage optimization layout strategy provides a solution to the technical problem of irregularly shaped and difficult-to-reuse leftover materials in blister tray production, significantly improving the overall utilization efficiency of production materials.

[0024] 2. A connected component labeling algorithm is used to intelligently identify the remaining material areas after the initial sorting, and an edge detection algorithm is used to extract contour features, constructing a multi-dimensional geometric feature vector to comprehensively characterize the geometric properties of the remaining material areas. By establishing a remaining material feature database, a data foundation is provided for subsequent matching optimization. Feature extraction can accurately capture the shape characteristics of various irregular remaining material areas, effectively identifying and extracting features from various remaining material areas of different sizes and complex shapes, providing key technical support for the efficient secondary utilization of remaining materials.

[0025] 3. The excess material recycling optimization model based on the matching degree function, by constructing the matching degree function of the excess material area and the small blister tray, comprehensively considering the area utilization rate, the contour matching degree and the feature vector similarity in three dimensions, the intelligent matching of the excess material and the blister tray is realized. The branch and bound algorithm combined with the heuristic search method is used to solve the recycling objective function, which can find the globally optimal matching scheme under complex constraint conditions, can intelligently select the appropriate blister tray product according to the characteristics of the excess material, and determine the best arrangement position and direction, and improve the utilization rate of the excess material. For the excess material area with different geometric characteristics, the algorithm can adaptively generate differentiated matching schemes, greatly improving the matching efficiency and the utilization rate of the excess material. The excess material recycling optimization model based on the matching degree function provides a solution to the problem that the excess material is difficult to be recycled in the production of the blister tray, and realizes the efficient recycling of material resources. BRIEF DESCRIPTION OF DRAWINGS

[0026] Fig. 1 It is a blister tray production material utilization rate optimal path planning method flow chart of the application;

[0027] Fig. 2 It is a blister tray production material utilization rate optimal path planning method data flow chart of the application. DETAILED DESCRIPTION

[0028] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the application.

[0029] Please refer to Figs. 1-2 , the application provides a blister tray production material utilization rate optimal path planning method, and the technical scheme is as follows:

[0030] Embodiment one:

[0031] A blister tray production material utilization rate optimal path planning method, as shown in Fig. 1 , comprising:

[0032] Obtaining raw material specification data and blister tray model data, establishing an initial utilization rate evaluation function based on area ratio and an excess material recyclability scoring function;

[0033] Based on the initial utilization rate evaluation function and the recyclability scoring function, an initial layout objective function is constructed, and initial layout data is obtained according to the initial layout objective function;

[0034] Based on the initial layout data, a binary image matrix of the remaining area is generated. The remaining material area is identified and geometric feature vectors are extracted by the connected component labeling algorithm to establish a remaining material feature database.

[0035] A blister tray feature database is established based on the blister tray model data. A matching degree function is constructed in combination with the waste material feature database. A reuse target function is constructed based on the matching function. Reuse layout data is obtained based on the reuse target function.

[0036] Considering the initial layout data and the reused layout data, construct a final objective function, and generate optimal path data based on the final objective function.

[0037] Furthermore, establishing the initial utilization rate evaluation function based on area ratio includes: obtaining the length and width of the raw materials, and simultaneously obtaining the three-dimensional model data of the blister tray to be produced; projecting the three-dimensional model of the blister tray onto a two-dimensional plane; obtaining the two-dimensional outline of each blister tray; and calculating the area of ​​each blister tray. The initial utilization rate evaluation function is established as the ratio of the total area of ​​all successfully arranged blister trays to the area of ​​the original material.

[0038] By projecting a 3D model onto a 2D plane and calculating the area ratio, the material utilization efficiency can be accurately quantified. This area-ratio-based evaluation method is simple, intuitive, and easy to implement, providing clear optimization objectives and evaluation criteria for optimization algorithms. It effectively improves the accuracy and reliability of nesting optimization, maximizing material utilization.

[0039] Furthermore, establishing the reusability scoring function for the waste material includes:

[0040] The reusability scoring function for the scrap material is constructed by considering the area, connectivity index, and shape complexity of the scrap material region, and is expressed as:

[0041]

[0042] Where RE represents the reusability scoring function of the scrap material, m represents the number of scrap material areas, and A k C represents the area of ​​the k-th residual material region. k The connectivity index for the k-th residual material region is represented by the ratio of the residual material region area to its convex hull area, F. k The shape complexity of the k-th residual material area is represented by the ratio of the square of the perimeter to the area. The smaller the value, the more regular the shape. α, β and γ represent the influence coefficients of area, connectivity index and shape complexity, respectively. They are determined based on the company's actual production experience and multiple test results, and satisfy α+β+γ=1.

[0043] The scrap reusability scoring function comprehensively considers the area, connectivity and shape complexity of the scrap area, and obtains the reusing potential of the scrap area through weighted calculation, so as to accurately evaluate the reusing value of the scrap area of different shapes, guide the first time layout to form more valuable scrap shapes, improve the reusability of the scrap, and increase the feasibility of the second time layout.

[0044] Further, obtaining the initial layout data according to the initial layout objective function includes: weighting and combining the initial utilization evaluation function and the scrap reusability scoring function to obtain the initial layout objective function; establishing initial layout constraint conditions, including: all blister trays are completely located within the raw material range; any two blister trays cannot overlap; the distance between adjacent blister trays is greater than or equal to the corresponding minimum distance; the arrangement direction rotation angle of the blister tray belongs to a preset rotation angle set; solving the initial layout objective function based on the initial layout constraint conditions; generating an initial layout scheme using a genetic algorithm, including the position coordinates and rotation angle of each blister tray; defining a first fitness function as the value of the initial layout objective function; generating a new population through selection, crossover and mutation operations; using an elite reservation strategy to reserve the optimal solution; stopping iteration when a preset stop condition is reached; and outputting the initial layout objective function.

[0045] The minimum distance between adjacent blister trays takes into account the cutter width, cutting accuracy and safety margin of the cutting equipment, and the preset rotation angle set takes into account the anisotropy of the material and the operation requirements of the equipment; to ensure the cutting tool operation space and product quality, the minimum distance in this embodiment is 15 mm, and the preset rotation angle set is {0°, 90°, 180°, 270°}; the preset stop condition for iteration is to reach a preset maximum iteration number of 200 or no improvement for 30 consecutive generations.

[0046] The initial layout optimization method based on the genetic algorithm can efficiently solve complex layout problems under various constraint conditions. The layout result not only meets the production process requirements, but also realizes the comprehensive optimization of material utilization and scrap reusability, creating favorable conditions for subsequent scrap reuse.

[0047] Further, establishing the scrap feature database specifically includes: marking the area where the blister trays are arranged as 0 based on the initial layout data, and marking the remaining areas as 1 to obtain a residual area binary image matrix; processing the residual area binary image matrix through a connected region marking algorithm to obtain all scrap areas; performing edge detection on each scrap area to obtain a scrap area contour point set; extracting geometric features of each scrap area to obtain a geometric feature vector; and storing the scrap area contour point set and the geometric feature vector in the scrap feature database.

[0048] The specific components of the geometric eigenvector include: area, perimeter, shape complexity, minimum bounding matrix, convex hull, convexity defect, and principal axis direction. The convexity defect refers to the difference between the area of ​​the convex hull of the region and the actual area of ​​the region. The principal axis direction is the angle between the major axis of the region and the horizontal direction, obtained by calculating the eigenvector of the region's covariance matrix.

[0049] By using connected component labeling and edge detection technology, we can accurately identify and extract features from irregular scrap areas. This allows us to fully capture the geometric characteristics of scrap areas, providing rich feature information for subsequent matching and optimization. We can accurately identify scrap areas of various shapes and sizes, providing a reliable data foundation for the efficient reuse of scrap materials.

[0050] Furthermore, obtaining the reuse layout data according to the reuse objective function specifically includes: obtaining the blister tray feature database by acquiring the blister tray outline point set and the geometric feature vector of the blister tray based on the blister tray model data; defining a matching degree function to evaluate the fit of the scrap area to the blister tray, the matching degree function considering area utilization rate, outline matching degree, and feature vector similarity; constructing the reuse objective function based on the matching degree of all types of blister trays and all scrap areas in the blister tray feature database and the scrap area feature database; and establishing reuse constraints, including: each scrap area can select at most one A layout scheme for blister packs is provided; the blister packs are entirely located within the waste material area; the distance between adjacent blister packs is greater than or equal to the corresponding minimum distance; the rotation angle of the blister pack layout direction belongs to a preset set of rotation angles; the reuse objective function is solved based on the reuse constraints: for each waste material area, a set of potentially matching blister packs is selected based on the matching degree function to form a candidate match; multiple layout schemes are generated for each candidate match; the matching degree of each layout scheme is calculated, and the branch and bound algorithm is used to solve the integer programming problem to find the globally optimal candidate match and layout scheme, and the reuse layout data is output.

[0051] The matching degree function is expressed as:

[0052] M(R k ,S j )=ω1×(A j / A k )+ω2×φ(O k O j )+ω3×ψ(G k G j );

[0053] Among them, M(R) k ,S j ) represents the k-th residual material area R k With the j-th blister tray S jThe degree of matching, A k and A j R respectively k and S j The area, O k and O j R respectively k and S j The set of contour points, φ(O) k O j ) represents R k With S j The contour matching accuracy is measured using the reciprocal of the Hausdorff distance, G. k and G j R respectively k and S j The geometric feature vectors of the blister tray and the scrap area have the same structure, ψ(G k G j ) represents the similarity of feature vectors, calculated using Euclidean distance. ω1, ω2, and ω3 represent weight coefficients, satisfying ω1+ω2+ω3=1. These coefficients are dynamically adjusted according to specific production needs. For example, when the shape of the scrap material is particularly irregular, the value of ω2 can be appropriately increased to emphasize the importance of shape matching.

[0054] The objective function can then be expressed as:

[0055]

[0056] Where maxZ represents maximizing the reuse objective function, m and s represent the number of waste material areas and the number of blister tray types, respectively, and T max V represents the maximum number of sorting attempts for each remaining material area. j Indicates blister tray S j The value coefficient of X is related to market demand and production costs. k,j,t It is a decision variable, when in the surplus material region R k Successfully arranged small blister trays S j The t-th scheme is X k,j,t =1, otherwise X k,j,t =0, M(R) k ,S j ,t) represents R under the t-th arrangement scheme k With S j The degree of matching.

[0057] By defining a matching degree function to establish the matching relationship between scrap material and blister trays, and using a branch and bound algorithm to solve the reuse objective function, the system can intelligently select the most suitable blister tray type and layout scheme for each scrap material area, thereby maximizing the utilization of scrap material, improving the average utilization rate of scrap material areas, effectively solving the problem of scrap material reuse, and reducing material waste.

[0058] Further, generating optimal path data based on the final objective function specifically includes: extracting the outline point set of each blister pack from the initial layout data and the reuse layout data respectively; constructing the final objective function based on the total cutting path length, the number of cuts, and the turning penalty of the cutting path; constructing final constraints, including: each point in each blister pack outline point set appears once in the cutting path; the cutting start point and end point are the same point; the turning radius of the cutting path is greater than or equal to the minimum turning radius; solving the final objective function based on the final constraints: using path encoding to represent the cutting order and the corresponding direction; initializing the population and generating a set of cutting paths; defining the second fitness function as the reciprocal of the final objective function value; generating a new population using roulette wheel selection, sequential crossover, and random mutation operations; performing local optimization on the newly generated individuals; stopping iteration when the preset stopping condition is reached; and outputting the optimal path data.

[0059] Specifically, the cutting path steering penalty is defined as the sum of the steering penalty function values ​​at each point on the path, and the steering penalty function is proportional to the steering angle; the path optimization process is divided into two stages: the first stage is to optimize the cutting order and path of all blister packs in the initial layout data; the second stage is to optimize the cutting order and path of all blister packs in the reuse layout data.

[0060] Taking into account cutting path length, number of cuts, and turning penalty, a globally optimal cutting path planning was achieved through genetic algorithm and local optimization strategy. This significantly reduced the total cutting distance and the number of tool lifts and drops, improved production efficiency, reduced equipment wear, and lowered production costs.

[0061] This invention solves the problems of low material utilization and serious waste of leftover materials in the production of blister trays by using a collaborative technology of two-stage optimized layout, intelligent matching of leftover materials, and cutting path planning. First, the initial layout objective function considers both immediate utilization and the potential of leftover materials, reducing raw material waste. Second, intelligent matching based on a feature database transforms leftover materials into usable resources. Finally, path optimization reduces equipment wear and energy consumption, improving production efficiency. Through the synergistic effect of these three technologies, the entire process from layout design to cutting execution is optimized, improving the overall utilization rate of materials while reducing production costs.

[0062] Example 2:

[0063] A manufacturing enterprise producing blister trays for medical device packaging mainly produces blister tray products for packaging different specifications of medical devices. The cost of medical-grade plastic materials is relatively high. In order to improve material utilization and reduce production cost, an optimal path planning method for blister tray production material utilization is applied, and the data flow diagram is shown in Fig. 2 The specific steps include:

[0064] Obtain raw material specification data and blister tray model data, and establish an initial utilization evaluation function based on area ratio and a residual material recyclability scoring function;

[0065] Construct an initial layout target function based on the initial utilization evaluation function and the recyclability scoring function, and obtain initial layout data according to the initial layout target function;

[0066] Generate a residual area binary image matrix based on the initial layout data, identify residual material areas and extract geometric feature vectors through a connected region labeling algorithm, and establish a residual material feature database;

[0067] Establish a blister tray feature database according to the blister tray model data, construct a matching degree function combining the residual material feature database, construct a recycling target function based on the matching degree function, and obtain recycling layout data according to the recycling target function;

[0068] Construct a final target function considering the initial layout data and the recycling layout data, and generate optimal path data according to the final target function.

[0069] Further, establishing the initial utilization evaluation function based on area ratio includes: obtaining the length and width of the raw material, and simultaneously obtaining the three-dimensional model data of the blister tray to be produced, projecting the three-dimensional model of the blister tray onto a two-dimensional plane, obtaining the two-dimensional contour of each blister tray, and calculating the area of each blister tray; the initial utilization evaluation function is established, which is defined as the ratio of the total area of all successfully arranged blister trays to the original material area.

[0070] Further, establishing the residual material recyclability scoring function includes:

[0071] The residual material recyclability scoring function is constructed considering the area, connectivity index and shape complexity of the residual material area, and is represented as:

[0072]

[0073] Wherein, RE represents the residual material recyclability scoring function, m represents the number of residual material areas, A k represents the area of the kth residual material area, C k represents the connectivity index of the kth residual material area, F krepresents the shape complexity of the kth excess material area, and a, β and γ respectively represent the influence coefficients of area, connectivity index and shape complexity.

[0074] Further, obtaining initial layout data according to the initial layout objective function comprises: weighting and combining the initial utilization evaluation function and the excess material recyclability scoring function to obtain the initial layout objective function; establishing initial layout constraint conditions, including: all blister trays are completely located within the raw material range; any two blister trays cannot overlap; the distance between adjacent blister trays is greater than or equal to the corresponding minimum distance; the arrangement direction rotation angle of the blister tray belongs to a preset rotation angle set; solving the initial layout objective function based on the initial layout constraint conditions; generating an initial layout scheme using a genetic algorithm, including the position coordinates and rotation angle of each blister tray; defining a first fitness function as the value of the initial layout objective function; generating a new population through selection, crossover and mutation operations; using an elite reservation strategy to reserve the optimal solution; stopping iteration when a preset stopping condition is reached; and outputting the initial layout objective function.

[0075] Further, establishing the excess material feature database specifically comprises: marking the area where the blister tray is arranged as 0 and the remaining area as 1 based on the initial layout data to obtain a remaining area binary image matrix; processing the remaining area binary image matrix through a connected region marking algorithm to obtain all excess material areas; performing edge detection on each excess material area to obtain an excess material area contour point set; extracting geometric features of each excess material area to obtain the geometric feature vector; and storing the excess material area contour point set and the geometric feature vector in the excess material feature database.

[0076] Further, the obtaining the reusing layout data according to the reusing target function specifically comprises: obtaining a blister tray contour point set and a geometric feature vector of the blister tray according to the blister tray model data to obtain the blister tray feature database; defining a matching degree function to evaluate the adaptation degree of the excess material region to the blister tray, the matching degree function considering area utilization, contour matching degree and feature vector similarity; constructing the reusing target function according to the matching degrees of all types of blister trays and all excess material regions in the blister tray feature database and the excess material feature database; establishing a reusing constraint condition, including: each excess material region selects at most one arrangement scheme of one blister tray; the blister tray is completely located in the excess material region; the distance between adjacent blister trays is greater than or equal to the corresponding minimum distance; the arrangement direction rotation angle of the blister tray belongs to a preset rotation angle set; solving the reusing target function based on the reusing constraint condition: for each excess material region, screening out a set of potential matching blister trays based on the matching degree function to form a candidate match; generating a plurality of arrangement schemes for each candidate match; calculating the matching degree of each arrangement scheme, using a branch and bound algorithm to solve an integer programming problem, finding a globally optimal candidate match and arrangement scheme, and outputting the reusing layout data.

[0077] The embodiment is aimed at the standard production requirement of a batch of medical instrument packaging, including 450 large pallets, and the initial layout optimization is performed by using the method of the application, and 32 excess material regions are obtained, and part of the geometric feature data of the excess material regions is shown in Table 1.

[0078] Table 1: Typical excess material region feature data

[0079]

[0080] Based on the excess material feature database and the blister tray feature database, the reusing layout data optimization is performed, and the matching results are shown in Table 2. The excess material regions with larger area and regular shape (such as R01 and R08) can match more small blister trays B001 and B002, and a higher excess material utilization rate is achieved; and the excess material regions with small area and complex shape (such as R29) cannot effectively match any blister tray.

[0081] Table 2: Matching results of excess material regions and blister trays

[0082]

[0083] Further, the generating the optimal path data according to the final target function specifically comprises: extracting each blister tray contour point set in the initial layout data and the recycling layout data respectively; constructing a final target function according to a total cutting path length, a cutting frequency and a cutting path turning penalty; constructing a final constraint condition, including: each point in each blister tray contour point set appears once in the cutting path; a cutting start point and a cutting end point are the same point; a turning curvature radius of the cutting path is greater than or equal to a minimum turning radius; solving the final target function based on the final constraint condition; adopting path coding to represent a cutting sequence and a corresponding direction; initializing a population to generate a cutting path set; defining a second fitness function as an inverse of a final target function value; generating a new population by adopting a roulette wheel selection, a sequential crossover and a random mutation operation; performing local optimization on the newly generated individuals; stopping iteration when an iteration reaches a preset stop condition; and outputting the optimal path data.

[0084] While the embodiments of the application have been illustrated and described, it will be understood by those skilled in the art that various changes, modifications, substitutions, and alterations can be made therein without departing from the spirit and scope of the application, which is defined by the appended claims and their equivalents.

Claims

1. A method for optimal path planning in blister tray production to maximize material utilization, characterized in that, include: Obtain raw material specification data and blister tray model data, and establish an initial utilization rate evaluation function and a scrap material reusability scoring function based on area ratio; The initial utilization rate evaluation function based on area ratio includes: obtaining the length and width of the raw materials, and simultaneously obtaining the three-dimensional model data of the blister tray to be produced; projecting the three-dimensional model of the blister tray onto a two-dimensional plane; obtaining the two-dimensional outline of each blister tray; and calculating the area of ​​each blister tray. The initial utilization rate evaluation function is defined as the ratio of the total area of ​​all successfully arranged blister trays to the area of ​​the original material. Establishing the reusability scoring function for the aforementioned waste materials includes: The reusability scoring function for the scrap material is constructed by considering the area, connectivity index, and shape complexity of the scrap material region, and is expressed as: ; in, This represents the scoring function for the reusability of the waste material. Indicates the quantity of surplus material in the area. Indicates the first The area of ​​the surplus material area Indicates the first Connectivity index of each surplus material area Indicates the first The shape complexity of each surplus material area , and These represent the influence coefficients of area, connectivity index, and shape complexity, respectively. An initial layout objective function is constructed based on the initial utilization rate evaluation function and the reusability scoring function. Initial layout data is obtained according to the initial layout objective function. Obtaining initial layout data according to the initial layout objective function includes: weighting and combining the initial utilization rate evaluation function and the waste material reusability scoring function to obtain the initial layout objective function; establishing initial layout constraints, including: all blister packs are completely within the raw material area; no two blister packs can overlap; the distance between adjacent blister packs is greater than or equal to the corresponding minimum distance; the rotation angle of the blister pack arrangement direction belongs to a preset rotation angle set; solving the initial layout objective function based on the initial layout constraints: generating an initial layout scheme using a genetic algorithm, including the position coordinates and rotation angle of each blister pack; defining a first fitness function as the value of the initial layout objective function; generating a new population through selection, crossover, and mutation operations; using an elite retention strategy to retain the optimal solution; stopping iteration when a preset stopping condition is reached; and outputting the initial layout objective function. Based on the initial layout data, a binary image matrix of the remaining area is generated. The remaining material area is identified and geometric feature vectors are extracted by the connected component labeling algorithm to establish a remaining material feature database. A blister tray feature database is established based on the blister tray model data. A matching degree function is constructed in combination with the waste material feature database. A reuse target function is constructed based on the matching function. Reuse layout data is obtained based on the reuse target function. Considering the initial layout data and the reused layout data, construct a final objective function, and generate optimal path data based on the final objective function.

2. The optimal path planning method for material utilization in blister tray production according to claim 1, characterized in that, Establishing the surplus material feature database specifically includes: marking the area where the blister packs are arranged as 0 and the remaining areas as 1 based on the initial layout data to obtain the binary image matrix of the remaining areas; processing the binary image matrix of the remaining areas through a connected component labeling algorithm to obtain all surplus material areas; performing edge detection on each surplus material area to obtain a set of surplus material area contour points; extracting geometric features from each surplus material area to obtain the geometric feature vector; and storing the surplus material area contour point set and the geometric feature vector into the surplus material feature database.

3. The optimal path planning method for material utilization in blister tray production according to claim 1, characterized in that, Obtaining the reuse layout data according to the reuse objective function specifically includes: obtaining the blister tray feature database by acquiring the blister tray outline point set and the blister tray geometric feature vector based on the blister tray model data; defining a matching degree function to evaluate the fit of the scrap area to the blister tray, the matching degree function considering area utilization rate, outline matching degree, and feature vector similarity; constructing the reuse objective function based on the matching degree of all types of blister trays and all scrap areas in the blister tray feature database and the scrap area feature database; and establishing reuse constraints, including: each scrap area can select at most one type of blister tray. A tray arrangement scheme; the blister trays are completely located within the waste material area; the distance between adjacent blister trays is greater than or equal to the corresponding minimum distance; the rotation angle of the arrangement direction of the blister trays belongs to a preset set of rotation angles; the reuse objective function is solved based on the reuse constraints: for each waste material area, a set of potentially matching blister trays is selected based on the matching degree function to form a candidate match; multiple arrangement schemes are generated for each candidate match; the matching degree of each arrangement scheme is calculated, and the branch and bound algorithm is used to solve the integer programming problem to find the globally optimal candidate match and arrangement scheme, and the reuse layout data is output.

4. The optimal path planning method for material utilization in blister tray production according to claim 1, characterized in that, The specific steps for generating optimal path data based on the final objective function include: extracting the outline point set of each blister pack from the initial layout data and the reuse layout data; constructing the final objective function based on the total cutting path length, the number of cuts, and the turning penalty of the cutting path; constructing final constraints, including: each point in each blister pack outline point set appears once in the cutting path; the starting point and ending point of the cut are the same point; the turning radius of the cutting path is greater than or equal to the minimum turning radius; solving the final objective function based on the final constraints: using path encoding to represent the cutting order and corresponding direction; initializing the population and generating a set of cutting paths; defining the second fitness function as the reciprocal of the final objective function value; generating a new population using roulette wheel selection, sequential crossover, and random mutation operations; performing local optimization on the newly generated individuals; stopping the iteration when the preset stopping condition is reached; and outputting the optimal path data.

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