Intelligent matching method for cutter remanufacturing

Abstract

The invention discloses an intelligent matching method for cutter remanufacturing, and the method comprises the steps: S1, data preparation and evaluation index construction: collecting cutter parameters, and constructing a hardness index, an elasticity index and a selectivity index; s2, generating a cutter matching scheme graph, judging remanufacturing feasibility between any two cutters by using a hard index, if the remanufacturing feasibility is feasible, calculating a utility value of the remanufacturing by using an elastic index, regarding all the cutters as vertexes and regarding a feasible remanufacturing relationship as a directed edge, and forming a weighted directed graph, namely the cutter matching scheme graph; step S3, obtaining an optimal remanufacturing path; comprising three process solving algorithms, namely searching for connected components, solving the longest path through topological sorting and determining the optimal path.

Description

Technical Field

[0001] This invention relates to the field of cutting tool manufacturing, and more particularly to an intelligent matching method for cutting tool remanufacturing. Background Technology

[0002] Existing methods for remanufacturing and matching cutting tools (such as patent CN116663420A) have the following main shortcomings:

[0003] First, the evaluation indicators are singular, mainly relying on the geometric features of the tool's outer contour (intersection of wireframes, cutting amount) to judge feasibility and economy, without comprehensively considering key factors such as tool type matching, cost, durability, and demand relationship. Therefore, the evaluation results deviate to some extent from the actual economic benefits.

[0004] Second, it only considers the local optimum of the matching strategy, which is not comprehensive; it adopts the idea of ​​"greedy algorithm", which selects only the target tool with the smallest cutting amount in a single remanufacturing for each scrap tool, ignoring the global optimum path (i.e., maximizing the total benefit of the whole life cycle) that the tool may undergo multi-level remanufacturing.

[0005] Third, the matching information was not used to optimize the design: the matching results were not fed back to optimize the design parameters of the new tool, thus failing to improve the remanufacturability and economy of future tools from the source.

[0006] Fourth, efficiency and completeness cannot be achieved simultaneously; manual matching is insufficient to exhaust all possible combinations of a massive number of non-standard customized cutting tools; although existing intelligent methods improve efficiency, they lack evaluation dimensions and the results are not globally optimal.

[0007] In addition, existing solutions used by various parties in the public domain have the following drawbacks:

[0008] In current production practices, tool remanufacturing matching solutions are mainly provided by technicians through manual comparison. This method can ensure that remanufacturing matching is feasible through the experience and actual observation of technicians. However, due to the wide variety of tools, especially in the group of tools for machining automotive engines which are basically non-standard customized parts, comparing all tools would bring an enormous workload that is difficult for humans to bear. Therefore, it is difficult for technicians to find the most suitable remanufacturing target tool for each tool under a certain evaluation system, such as cutting volume or the benefits obtained from remanufacturing.

[0009] Although current intelligent matching methods can effectively address the problem of massive matching workload, there are still areas for improvement in intelligent matching methods for remanufacturing carbide drill bits. When determining the matching scheme for tool remanufacturing, it only considers the cutting amount as an indicator. Given the complexity of the remanufacturing process itself, a more comprehensive remanufacturing evaluation index system is still needed to more accurately and realistically assess the feasibility and economy of remanufacturing matching.

[0010] Meanwhile, the current method selects the tool with the smallest cutting amount during the remanufacturing process as the optimal target tool for each tool. This approach has a drawback similar to the "greedy algorithm". Since the outer contour of the tool is a complex polygon, the matching scheme with the smallest cutting amount may not be as good as some matching schemes with a larger cutting amount at the current stage, but which can guarantee more remanufacturing in the future.

[0011] By designing an algorithm that allows programs to replace technicians in determining whether tools can be remanufactured, the comparison speed can be greatly improved, enabling detailed comparisons covering all tools and overcoming the problem of the enormous workload of manual comparison. Specifically, the comparison of tool outlines is achieved by extracting key data from the tool design drawings and inputting it into a tool outline reconstruction algorithm, transforming the tool outline in the design drawings into polygons that the program can analyze. Other data related to the feasibility and economy of remanufacturing, such as category and cost, can be directly input into the database and processed according to corresponding constraints or functions, ultimately generating a tool matching scheme diagram. This approach considers more relevant factors, making the output results closer to actual production. After obtaining this scheme diagram, a depth-first search algorithm can be used to distinguish different connected components, and then topological sorting can be used to find the optimal remanufacturing path for each tool. This method avoids the drawback of "greedy algorithms," which may only output feasible solutions without finding the optimal solution.

[0012] Based on real tool data from enterprises, this invention proposes a remanufacturing path optimization algorithm and a tool design optimization algorithm that considers the tool remanufacturing matching results. It proves that the intelligent tool remanufacturing matching algorithm can replace manual one-by-one comparison, perform large-scale tool remanufacturing matching, and output the optimal remanufacturing path. It also confirms that the tool remanufacturing matching results can indeed be applied to the optimization of tool design schemes, increase the overall utility of the optimal remanufacturing path for some tools, and improve the overall economy of tool design schemes.

[0013] All of the above findings can be applied to actual production practices, helping enterprises reduce costs, increase efficiency, and improve environmental friendliness. Summary of the Invention

[0014] The purpose of this invention is to provide an intelligent matching method for tool remanufacturing, aiming to solve the problems existing in the prior art. Its core task is:

[0015] Construct a multi-dimensional evaluation index system that comprehensively considers technical feasibility (such as outer contour inclusion and type consistency) and economic efficiency (such as cost, durability, and demand relationship) to make the algorithm evaluation more closely reflect actual production experience.

[0016] Design an intelligent matching algorithm that can find the globally optimal remanufacturing path for a tool: that is, starting from the initial tool, going through possible multi-stage remanufacturing, and finally obtaining the path with the greatest total utility, to overcome the local optima defect of greedy algorithms.

[0017] Automating and intelligentizing the above processes significantly improves matching efficiency and overall economic efficiency of the solution.

[0018] To achieve the above objectives, this invention proposes an intelligent matching method for tool remanufacturing, comprising: step S1, data preparation and evaluation index construction, collecting tool parameters, and constructing hard indices, flexible indices, and selective indices;

[0019] Step S2: The tool matching scheme diagram is generated by judging the feasibility of remanufacturing between any two tools based on hard indicators. If it is feasible, the utility value of this remanufacturing is calculated based on the elastic indicators. All tools are regarded as vertices and feasible remanufacturing relationships are regarded as directed edges to form a weighted directed graph, which is the tool matching scheme diagram.

[0020] Step S3, obtaining the optimal remanufacturing path; includes a solution algorithm with three processes: finding connected components, topological sorting to find the longest path, and determining the optimal path.

[0021] Furthermore, hard indicators include the tool's outer profile, regrinding rules, and consistency of tool type.

[0022] Furthermore, the outer contour of the tool is the starting outer contour of the tool that has reached the regrinding limit, which can wrap around the outer contour of the target tool.

[0023] The grinding rules are as follows: if the step length is less than 3mm, it cannot be ground; if the step length is between 3mm and 10mm, the grinding amount is equal to the step length minus 3mm; if the step length is greater than or equal to 10mm, the grinding amount is equal to 10mm.

[0024] Tool type consistency means that the starting tool and the target tool are of the same type.

[0025] Furthermore, the elasticity indicators include the ratio of tool cost, remanufacturing cost, and theoretical tool durability. These three indicators are used to quantify the economic benefits of a single remanufacturing operation.

[0026] Furthermore, the ratio of theoretical tool durability is P, P = D2 / D1; when D2 / D1 < 1, P = D2 / D1; when D2 / D1 >= 1, P = 1; where D1 is the initial tool durability and D2 is the target tool durability; when P < 1, it indicates that the initial tool is excessive.

[0027] Furthermore, the economic benefits of a single remanufacturing operation are quantified by a utility function U, U = (C drill -(C re ))*P, where C drill For tooling costs, C re For remanufacturing costs.

[0028] Furthermore, the generation of the tool matching scheme diagram in step S2 also includes setting any two tools as the starting point and the target point, the starting point is transformed into the target point through remanufacturing, and the machining path is a directed edge.

[0029] Furthermore, finding connected components involves treating the directed graph as an undirected graph and applying a depth-first search algorithm to identify all connected components.

[0030] Furthermore, topological sorting for the longest path involves applying topological sorting to each connected component to calculate the longest path between any two vertices.

[0031] Furthermore, determining the optimal path involves, for the starting point, traversing other target points within the connected components, finding the target point with the longest path length, and the longest machining path between the starting point and the target point is the globally optimal remanufacturing path for the tool.

[0032] The main beneficial effects of this invention are:

[0033] Based on real tool data from enterprises, the proposed remanufacturing path optimization algorithm and tool design optimization algorithm considering tool remanufacturing matching results demonstrate the ability of the intelligent tool remanufacturing matching algorithm to replace manual one-by-one comparison, perform large-scale tool remanufacturing matching, and output the optimal remanufacturing path. It also confirms that the tool remanufacturing matching results can indeed be applied to the optimization of tool design schemes, increase the overall utility of the optimal remanufacturing path for some tools, and improve the overall economy of tool design schemes.

[0034] Both of these achievements can be applied to actual production practices, helping enterprises reduce costs, increase efficiency, and improve environmental friendliness. Attached Figure Description

[0035] Figure 1 This is a flowchart illustrating an intelligent matching method for tool remanufacturing according to an embodiment of the present invention.

[0036] Figure 2This is a schematic diagram of a matching scheme for tool remanufacturing in one embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram of the outline of a flat-end tool and a second-order tool in one embodiment of the present invention;

[0038] Figure 4 This is a schematic diagram of the tool machining path in one embodiment of the present invention. Detailed Implementation

[0039] The blade manufacturing system of the present invention will be further explained and described below with reference to the accompanying drawings and specific embodiments. However, such explanation and description do not constitute an undue limitation on the technical solution of the present invention.

[0040] Figure 1 This is a flowchart illustrating an intelligent matching method for tool remanufacturing according to an embodiment of the present invention.

[0041] Step S1: Data preparation and evaluation index construction. Collect tool parameters and construct hard indexes, flexible indexes, and selective indexes.

[0042] Step S2: Tool matching scheme diagram is generated. Based on hard indicators, the feasibility of remanufacturing between any two tools is judged. If it is feasible, the utility value of this remanufacturing is calculated based on the elastic indicators. All tools are regarded as vertices, and feasible remanufacturing relationships are regarded as directed edges, forming a weighted directed graph, which is the tool matching scheme diagram.

[0043] Step S3, obtaining the optimal remanufacturing path; includes a solution algorithm with three processes: finding connected components, topological sorting to find the longest path, and determining the optimal path.

[0044] As Figure 1 In the preferred embodiments, the hard indicators include the tool outline, grinding rules, and consistency of tool type.

[0045] As Figure 1 In a preferred embodiment, the outer contour of the tool is such that the initial outer contour of the tool, having reached its grinding limit, can encompass the outer contour of the target tool.

[0046] The grinding rules are as follows: if the step length is less than 3mm, it cannot be ground; if the step length is less than 10mm and the grinding amount is equal to the step length minus 3mm; if the step length is greater than or equal to 10mm, the grinding amount is equal to 10mm.

[0047] Tool type consistency means that the starting tool and the target tool are of the same type. For example, the type of drill bit, such as a straight flute drill or a twist drill, must be consistent.

[0048] As Figure 1In a preferred embodiment, the flexibility indicators include the ratio of tool cost, remanufacturing cost, and theoretical tool durability. These three indicators are used to quantify the economic benefits of a single remanufacturing operation.

[0049] As Figure 1 In a preferred embodiment, the ratio of theoretical tool durability is P, where P = D2 / D1; when D2 / D1 < 1, P = D2 / D1; when D2 / D1 >= 1, P = 1; where D1 is the initial tool durability and D2 is the target tool durability; when P < 1, it indicates that the initial tool is excessive.

[0050] As Figure 1 In a preferred embodiment, the economic benefits of a single remanufacturing operation are represented by a utility function U, where U = (C drill -(C re ))*P, where C drill For tooling costs, C re The utility function U represents remanufacturing costs. It integrates the effects of tooling cost savings, remanufacturing costs, and demand dynamics.

[0051] Remanufacturing cost C re The cost of the grinding process. It is related to the grinding area on the sides and the grinding area on the front, with the former costing more.

[0052] The ratio P of the theoretical durability of cutting tools reflects the demand relationship.

[0053] D1 represents the initial tool life, which is the number of holes that can be machined, and D2 represents the target tool life. P<1 indicates that the initial tool is redundant, and remanufacturing is only beneficial within the range of the target tool requirements.

[0054] As Figure 1 In a preferred embodiment, the generation of the tool matching scheme diagram in step S2 further includes defining any two tools as a starting point and a target point, the starting point being transformed into a target point through remanufacturing, and the machining path being a directed edge.

[0055] As Figure 1 In a preferred embodiment, finding connected components involves treating the directed graph as an undirected graph and applying a depth-first search algorithm to identify all connected components. This step forms the basis for subsequent processing.

[0056] As Figure 1 In a preferred embodiment, topological sorting for finding the longest path involves applying topological sorting to each connected component to calculate the longest path between any two vertices.

[0057] As Figure 1In a preferred embodiment, determining the optimal path includes, for the starting point, traversing other target points within the connected components, finding the target point with the longest path length, and the longest machining path between the starting point and the target point is the globally optimal remanufacturing path for the tool. The globally optimal remanufacturing path generates the greatest economic benefits.

[0058] refer to Figure 2 , Figure 2 This is a schematic diagram of a matching scheme for tool remanufacturing in one embodiment of the present invention. Each tool corresponds to a vertex, that is, each vertex can be a type of tool (the tool type is represented by a combination of T and numbers).

[0059] refer to Figure 3 , Figure 3 This is a schematic diagram of the outline of a flat-end tool and a second-order tool in one embodiment of the present invention;

[0060] Automated detection can be achieved using the `contains` method of the Python library Shapely, or using other programming languages. Figure 3 This example shows a set of tool outlines with an inclusion relationship, where the outer outline of a rectangular tool encloses the outer outline of a second-order tool. Reconstructing the tool outline requires extracting parameters (tool name, type, order, total length, diameters of each order, length, spacing, rake angle, etc.) and drawing the corresponding polygons.

[0061] Figure 3 The second-order tool 1 is a tool with two steps, and the outer contour of the flat-end tool 2 can cover the second-order tool 1.

[0062] refer to Figure 4 , Figure 4 This is a schematic diagram of a tool machining path in one embodiment of the present invention; the tool is set as a vertex, including a starting point r and a target point s, wherein the starting point r reaches the target point S through a machining path with directed edges;

[0063] Understandable, Figure 4 The examples listed are processing paths for straight line vectors, but they can also be processing paths for other curves or other forms with arrow directions.

[0064] Each type of tool corresponds to a vertex, meaning each vertex can be a specific type of tool.

[0065] It should be noted that the prior art portion of the protection scope of this invention is not limited to the embodiments given in this invention document. All prior art that does not contradict the solution of this invention, including but not limited to prior patent documents, prior publications, prior public uses, etc., can be included in the protection scope of this invention.

[0066] Furthermore, the combination of the technical features in this case is not limited to the combination methods described in the claims of this case or the combination methods described in the specific embodiments. All technical features described in this case can be freely combined or combined in any way, unless they contradict each other.

[0067] It should also be noted that the embodiments listed above are merely specific embodiments of the present invention. Obviously, the present invention is not limited to the above embodiments, and similar changes or modifications made thereto are those that can be directly derived or easily conceived by those skilled in the art from the content disclosed in the present invention, and should all fall within the protection scope of the present invention.

Claims

1. A smart matching method for tool remanufacturing, characterized in that, include: Step S1: Data preparation and evaluation index construction, collect tool parameters, and construct hard indexes, flexible indexes, and selective indexes; Step S2: The tool matching scheme diagram is generated by judging the feasibility of remanufacturing between any two tools based on hard indicators. If it is feasible, the utility value of remanufacturing is calculated based on elastic indicators. All tools are regarded as vertices and feasible remanufacturing relationships are regarded as directed edges to form a weighted directed graph, which is the tool matching scheme diagram. Step S3: Obtaining the optimal remanufacturing path; The solution algorithm includes three processes: finding connected components, topological sorting to find the longest path, and determining the optimal path.

2. The intelligent matching method for tool remanufacturing as described in claim 1, characterized in that, The hard indicators include the consistency of the tool's outer contour, grinding rules, and tool type.

3. The intelligent matching method for tool remanufacturing as described in claim 2, characterized in that, The outer contour of the tool is the starting outer contour of the tool that has reached the regrinding limit and can wrap around the outer contour of the target tool. The grinding rules are as follows: if the step length is less than 3mm, it cannot be ground; if the step length is between 3mm and 10mm, the grinding amount is equal to the step length minus 3mm; if the step length is ≥ 10mm, the grinding amount is equal to 10mm. The consistency of tool type means that the starting tool and the target tool are of the same type.

4. The intelligent matching method for tool remanufacturing as described in claim 1, characterized in that, The elasticity indicators include the ratio of tool cost, remanufacturing cost, and theoretical tool durability. These three indicators are used to quantify the economic benefits of a single remanufacturing operation.

5. The intelligent matching method for tool remanufacturing as described in claim 4, characterized in that, The ratio of the theoretical tool durability is P, where P = D2 / D1; when D2 / D1 < 1, P = D2 / D1; when D2 / D1 >= 1, P = 1; where D1 is the initial tool durability and D2 is the target tool durability; when P < 1, it indicates that the initial tool is excessive.

6. The intelligent matching method for tool remanufacturing as described in claim 5, characterized in that, The economic benefits of a single remanufacturing operation are represented by a utility function U, where U = (C drill -(C re ))*P, where C drill For tooling costs, C re For remanufacturing costs.

7. The intelligent matching method for tool remanufacturing as described in claim 6, characterized in that, The generation of the tool matching scheme diagram in step S2 also includes setting any two tools as the starting point and the target point, the starting point is transformed into the target point through remanufacturing, and the machining path is a directed edge.

8. The intelligent matching method for tool remanufacturing as described in claim 7, characterized in that, The process of finding connected components involves treating the directed graph as an undirected graph and applying a depth-first search algorithm to identify all connected components.

9. The intelligent matching method for tool remanufacturing as described in claim 8, characterized in that, The topological sorting for finding the longest path in step S3 involves applying topological sorting to each connected component to calculate the longest path between any two vertices.

10. The intelligent matching method for tool remanufacturing as described in claim 8, characterized in that, The determination of the optimal path includes, for the starting point, traversing other target points within the connected components, finding the target point with the longest path length, and the longest machining path between the starting point and the target point is the globally optimal remanufacturing path of the tool.

Images