Mobile terminal disassembly strategy optimization method considering tool interference influence

Abstract

The invention relates to the technical field of mobile terminal recovery, and discloses a mobile terminal disassembly strategy optimization method considering tool interference influence, and the method comprises the steps: obtaining a standard three-dimensional model and a disassembly tool model library of a mobile terminal; and a part disassembly priority graph model of the mobile terminal is constructed, so that a structure constraint matrix in the standard three-dimensional model is extracted and is used for representing the disassembly priority sequence of the parts. Obtaining a disassembly gap point location in the standard three-dimensional model; the method comprises the following steps: constructing a disassembling tool point vector model, combining a tool-assembly-part three-coordinate system dynamic conversion mechanism to realize automatic positioning matching of a disassembling tool and a disassembling gap point position, and meanwhile, detecting the interference volume quantity between the disassembling tool and a part in the part disassembling process. And constructing a fitness function with tool influence, optimizing a disassembly strategy by adopting an intelligent optimization algorithm in combination with a structure constraint matrix and an interference volume, and generating an optimal disassembly sequence, disassembly time and maintenance benefits. The disassembly efficiency of the mobile terminal is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of mobile terminal recycling, and in particular to a method for optimizing mobile terminal disassembly strategies taking into account tool interference effects. Background Art

[0002] With the rapid development of electronic products, the recycling and reuse of mobile terminal devices (such as mobile phones, tablets, laptops, POS terminals, and in-vehicle computers) are receiving increasing attention. To improve the disassembly efficiency and component recovery rate of such devices, researchers have proposed a variety of disassembly strategies to enhance overall disassembly performance. However, these mobile terminals generally have multi-part stacking structures, with densely packed internal components and high assembly precision requirements. This leads to geometric interference between tools and surrounding parts during the actual disassembly process, thus affecting the feasibility and operational safety of the disassembly plan.

[0003] Current disassembly sequence planning methods primarily focus on optimizing path selection and cost control, with limited consideration of the impact of tool interference on disassembly feasibility. However, in products with multi-part stacks, failure to adequately identify and address tool-part interference can lead to disassembly failure and even component damage. Therefore, incorporating tool interference into disassembly strategies has significant engineering application value.

[0004] Existing tool interference detection methods generally use 3D modeling software to simulate the disassembly process manually in virtual space. This involves relying on the engineer's experience to manually adjust the tool's position (e.g., moving and rotating the tool model), then observing the geometric matching relationship between the tool and the part and locally verifying the interference using collision detection algorithms. However, these methods have significant shortcomings. On the one hand, manual intervention relies on operator experience, which can easily distort detection results due to tool positioning deviations. On the other hand, the matching relationship between the disassembly tool and the part has not been quantitatively defined, making it difficult to efficiently determine whether the tool strictly meets the disassembly geometric conditions. Furthermore, traditional interference detection requires frame-by-frame analysis of the entire tool path, resulting in high computational redundancy and low efficiency. This makes it particularly difficult to apply to large-scale, complex assemblies, and therefore urgently needs to be addressed. Summary of the Invention

[0005] In order to solve the technical problems existing in the prior art, the present invention provides a mobile terminal disassembly strategy optimization method that takes into account the influence of tool interference. While improving the accuracy and efficiency of tool interference detection, it reduces or eliminates tool interference during mobile phone disassembly sequence planning and structural optimization, thereby minimizing the influence of disassembly tools and improving the disassembly efficiency of the mobile phone structure.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The present invention discloses a mobile terminal disassembly strategy optimization method considering the influence of tool interference, which includes the following steps, namely S1 to S4.

[0008] S1. Obtain a standard three-dimensional model of a mobile terminal and a disassembly tool model library.

[0009] S2. Construct a parts disassembly priority graph model of the mobile terminal, thereby extracting a structural constraint matrix in the standard three-dimensional model; wherein the structural constraint matrix is used to represent the disassembly priority order of the parts.

[0010] S3. Obtain the disassembly clearance points in the standard three-dimensional model; construct a disassembly tool point vector model, and combine it with the dynamic conversion mechanism of the tool-assembly-part three-coordinate system to realize the automatic positioning and matching of the disassembly tool and the disassembly clearance points, while detecting the interference volume between the disassembly tool and the part during the part disassembly process.

[0011] S4. Construct a tool-influenced fitness function, combine the structural constraint matrix and the interference volume, and use an intelligent optimization algorithm to optimize the disassembly strategy; the disassembly strategy includes the optimal disassembly sequence of parts, disassembly time, and maintenance efficiency.

[0012] As a further improvement to the above solution, the optimization method further includes the following steps:

[0013] S5. Calculate the optimized data of the part size or part gap based on the interference volume, adjust the specific part size or gap distance of the mobile terminal accordingly, and use the improved new structure to return to step S4 to optimize the disassembly strategy again.

[0014] As a further improvement to the above solution, in step S5, the calculation formula for the part size or part gap optimization data is as follows:

[0015]

[0016] Where ΔG represents the optimized part size or optimized gap distance; V inf Indicates the interference volume between the disassembly tool and the parts during the disassembly process; A tool_contact Represents the tool contact projection area, which is the plane projection area with the modified width as the normal within the part gap volume.

[0017] As a further improvement of the above solution, step S2 includes the following specific steps, namely S21 to S22.

[0018] S21. Construct a priority graph model for disassembling n parts of a mobile terminal, with disassembly parts as nodes and directed arrows to indicate the order of disassembly. The part pointed to by the end of the arrow is disassembled first, and the part pointed to by the tip of the arrow is disassembled later.

[0019] S22. Quantify the priority graph model into a priority matrix P, i.e., the structural constraint matrix; wherein P is an n×n matrix, n is the total number of parts in the mobile terminal, i and j correspond to part numbers, i, j = 1, 2, ..., n; if there is a directed edge from any node i to node j in the priority graph model, then the corresponding element p in the matrix P is ij The value is 1, otherwise p ij The value is 0.

[0020] As a further improvement to the above solution, in step S4, the optimization goal of the intelligent optimization algorithm is to minimize the disassembly time and maximize the maintenance benefit; the tool-influenced fitness function consists of two parts: the disassembly time function and the maintenance benefit function. The expression formula of the disassembly time function is as follows:

[0021]

[0022] T i v =k2V inf

[0023] Where, T represents the disassembly time; T i m represents the basic time for disassembling part i; T i v It indicates the increased disassembly time caused by the volume interference between the disassembly tool and part i; represents the disassembly tool change time from part i to part j; represents the time it takes for the disassembly tool to change direction from part i to part j; k2 represents the proportional coefficient between the interference volume and the increased disassembly time caused by the volume interference; V inf It indicates the interference volume between the disassembly tool and the part during the disassembly process.

[0024] The maintenance benefit function is expressed as follows:

[0025]

[0026] Where, V represents the maintenance benefit; c i represents the disassembly and repair value of part i; represents the cost of disassembling part i itself; c r Indicates labor-hour costs; represents the depreciation cost of the tools used to disassemble part i; c z represents the depreciation expense of disassembly tools; represents the disassembly cost caused by the volume interference between the disassembly tool and part i; k1 represents the proportional coefficient between the interference volume and the disassembly cost caused by the volume interference.

[0027] The algorithm fitness f of the intelligent optimization algorithm is expressed as:

[0028] f=ω1·V+ω2·T

[0029] Where ω1 is the maintenance benefit weight factor; ω2 is the disassembly time weight factor.

[0030] As a further improvement of the above solution, in step S3, the expression formula of the disassembly tool point vector model is:

[0031] M=[p i' ,v i' ]

[0032] Where M represents the disassembly tool point vector model; p i' v represents the action point of the i'th disassembly tool, i'=1,2,3,…,n', n' is the total number of disassembly tools; i' Represents the i'th tool vector, which is along the disassembly tool positioning constraint line or the moving axis and points to the crank, and its magnitude is a unit vector.

[0033] The interference volume detection process includes the following specific steps, namely S31 to S34.

[0034] S31. Change the posture state of the disassembly tool in the tool coordinate system, and the change of the posture state is achieved by controlling the tool point vector model M to move an adaptation distance in the part matching direction, and the part matching direction is along the connection line between the disassembly tool and the part to be disassembled, and is close to the part.

[0035] S32. Convert the tool coordinate system into the assembly coordinate system, and perform automatic positioning and matching between the tool point vector and the disassembly clearance point.

[0036] S33. Detect the interference volume between the disassembly tool and the part to be tested using the entity intersection interference detection method.

[0037] S34. Convert the assembly coordinate system to the part coordinate system and remove the parts that have been inspected.

[0038] As a further improvement of the above solution, in step S32, the automated positioning matching means that: at the disassembly gap point, the action point of the disassembly tool is included in the disassembly action edge line or disassembly action plane of the part to be disassembled, and the tool vector is perpendicular to the disassembly action edge line or disassembly action plane of the part to be disassembled, and the following conditional expression is satisfied:

[0039] p i' ∈x part ,v i' ⊥x part

[0040] pi' ∈m part ,v i' ⊥m part

[0041] Where x part is the disassembly edge line of the part to be disassembled; m part It is the disassembly plane of the parts to be disassembled.

[0042] As a further improvement to the above solution, in step S3, the coordinate conversion formula in the three-coordinate system dynamic conversion mechanism is as follows:

[0043] A V=R' B V

[0044] Where, the point vector coordinates of the disassembly tool in the assembly coordinate system are: A V=[x 1A ,x 2A ,x 3A ] T , the superscript T is the transposition symbol; the point vector coordinates of the disassembly tool in the tool coordinate system are B V=[x 1B ,x 2B ,x 3B ] T ; R' is the transformation matrix of the tool point vector between the tool coordinate system and the assembly coordinate system, which is expressed as follows:

[0045]

[0046] In the formula, (x a ,y a ,z a ) T Indicates the three-dimensional coordinates of any point on the part to be measured in the assembly coordinate system; (x b ,y b ,z b ) T Indicates the three-dimensional coordinates of any point on the part to be measured in the part coordinate system; represents the basis vectors of the assembly coordinate system, Represents the basis vectors of the part coordinate system.

[0047] As a further improvement of the above solution, in step S3, the disassembly clearance points in the standard three-dimensional model are obtained through the three-dimensional modeling application program interface.

[0048] As a further improvement of the above solution, in step S1, the standard three-dimensional model includes functional parts and connection parts of the mobile terminal.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] 1. This invention automates the interference detection process by constructing a point vector model for disassembly tools and a dynamic three-coordinate conversion mechanism. This quantifies the tool-part matching relationship as mathematical constraints between vectors. This, combined with the precise calculation of local interference volumes using API functions of the 3D model, reduces tool pose transformation and matching time, improving detection efficiency while maintaining a controllable error range for interference calculation.

[0051] 2. The present invention optimizes and improves the mobile phone disassembly operation process and product design structure by using tool interference information as the objective function variable of mobile phone disassembly sequence planning and the size or gap modification formula factor of mobile phone structure interference optimization, reducing the impact of tool interference in both the disassembly process and the design process, and improving the efficiency of mobile phone parts disassembly. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a flowchart of a method for optimizing a mobile terminal disassembly strategy taking into account the influence of tool interference in Example 1 of the present invention.

[0053] Figure 2 This is a schematic diagram of the structure of a three-dimensional CAD model of a mobile phone in Example 1 of the present invention.

[0054] Figure 3 It is the structural constraint matrix of the mobile phone CAD model in Example 1 of the present invention.

[0055] Figure 4 The following are the disassembly steps and disassembly point diagrams for the key components of the mobile phone CAD model in Example 1 of the present invention.

[0056] Figure 5 This is a diagram of the interference detection process of disassembly tools in the mobile phone CAD model in Example 1 of the present invention.

[0057] Figure 6 This is a diagram annotating the structural parameters of the mobile phone CAD model in Example 1 of the present invention.

[0058] Figure 7 This is a schematic diagram of the structure of a computer terminal in Example 2 of the present invention. DETAILED DESCRIPTION

[0059] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0060] Example 1

[0061] See also Figure 1 This embodiment provides a method for optimizing a disassembly strategy of a mobile terminal taking into account the influence of tool interference, which includes the following steps, namely S1 to S5. In this embodiment, a mobile phone is used as the object of disassembly strategy optimization.

[0062] S1. Obtain a standard 3D CAD model of a mobile terminal and a library of disassembly tool models. In some embodiments, the standard 3D CAD model includes functional components and connection parts of the mobile terminal. In this embodiment, the connection parts include screws, clips, BTB connectors, and RF connectors.

[0063] In this embodiment, the mobile phone 3D CAD model and the disassembly tool model are constructed using Creo Parametric software. The detailed structure of the mobile phone 3D CAD model can be found in Figure 2 .

[0064] S2. Construct a parts disassembly priority graph model of the mobile terminal, thereby extracting a structural constraint matrix in the standard three-dimensional model; wherein the structural constraint matrix is used to represent the disassembly priority order of the parts.

[0065] Step S2 includes the following specific steps, namely S21 to S22.

[0066] S21. Construct a priority graph model for disassembling n parts of a mobile terminal, with disassembly parts as nodes and directed arrows to indicate the order of disassembly. The part pointed to by the end of the arrow is disassembled first, and the part pointed to by the tip of the arrow is disassembled later.

[0067] S22. Quantify the priority graph model into a priority matrix P, i.e., the structural constraint matrix; wherein P is an n×n matrix, n is the total number of parts in the mobile terminal, i and j correspond to part numbers, i, j = 1, 2, ..., n; if there is a directed edge from any node i to node j in the priority graph model, then the corresponding element p in the matrix P is ij The value is 1, otherwise p ij The value is 0.

[0068] In this embodiment, step S2 is implemented to construct a parts disassembly priority graph model based on the mobile phone 3D CAD model, and the graph model is converted into a structural constraint matrix P (i, j = 1, 2, ..., 51) that can express the priority order of parts disassembly. Figure 3 Due to structural design limitations, some parts have a specific disassembly order, such as p in the structural constraint matrix 21 A value of "1" means that part No. 2 is disassembled before part No. 1, and the same applies to the other "1" values.

[0069] S3. The disassembly clearance points in the standard three-dimensional model can be obtained through the three-dimensional modeling application program interface (API); a disassembly tool point vector model is constructed, and combined with the dynamic conversion mechanism of the tool-assembly-part three-coordinate system, the automatic positioning and matching of the disassembly tool and the disassembly clearance points is realized, and the interference volume between the disassembly tool and the part during the part disassembly process is detected.

[0070] In step S3, the expression formula of the disassembly tool point vector model is:

[0071] M=[p i' ,v i' ]

[0072] Where M represents the disassembly tool point vector model; p i' v represents the action point of the i'th disassembly tool, i'=1,2,3,…,n', n' is the total number of disassembly tools; i' Represents the i'th tool vector, which is along the disassembly tool positioning constraint line or the moving axis and points to the crank, and its magnitude is a unit vector.

[0073] The interference volume detection process includes the following specific steps, namely S31 to S34.

[0074] S31. Change the posture state of the disassembly tool in the tool coordinate system, and the change of the posture state is achieved by controlling the tool point vector model M to move an adaptation distance in the part matching direction, and the part matching direction is along the connection line between the disassembly tool and the part to be disassembled, and is close to the part.

[0075] In this embodiment, first determine the disassembly points of the mobile phone 3D CAD model based on the key components and disassembly steps of the mobile phone. The key components include the back cover, screen, battery, main board cover, sub-board cover, main board, sub-board, rear camera, front camera, and sub-board parts (vibration motor, charging port, etc.). For the disassembly steps and disassembly points of the key components, please refer to Figure 4 The disassembly steps are: whole machine model → remove back cover → remove battery → remove main and sub-board covers → remove BTB connector → remove main and sub-boards → remove small parts on the main board (front camera, rear camera) and small parts on the sub-board (vibration motor, charging port) → remove screen. The disassembly order of battery and main and sub-board covers can be adjusted at the same level. Please refer to Figure 4The 28 disassembly points are marked in red circles, including: the gaps between the two vertices of the upper battery and the mainboard cover; the gaps between the two vertices of the lower battery and the subboard cover; the BTB connectors connecting the mainboard and subboard; the BTB connectors connecting the screen and the mainboard; the BTB connectors between the rear camera and the mainboard; the BTB connectors between the front camera and the mainboard; the gap between the vibration motor and the subboard; the gap between the charging port and the subboard; and the screws on the main and subboard covers. A 3D modeling API was used to obtain the paths to these disassembly points.

[0076] Furthermore, the position state of the disassembly tool point vector M is changed based on the tool coordinate system, and M is rotated and moved to simulate the movement of the tool during the disassembly process. This operation is achieved in the API by changing the coordinates of the selected tool point vector. Assume that the initial coordinates of the part in the assembly coordinate system are (x0, y0, z0), and the components of the tool movement distance in the X, Y, and Z axis directions of the assembly coordinate system are (x trans ,y trans ,z trans ), the coordinates after the tool moves are (x, y, z). The movement formula entered in the Creo API control program is:

[0077]

[0078] Assume that the initial coordinates of the tool in the tool coordinate system are (x0, y0, z0), and rotate around the X', Y', and Z' axes of the coordinate system respectively Angle, then the coordinates after the state change are (x', y', z'). The rotation formula entered in the Creo API control program is:

[0079]

[0080] The direction of rotation or movement of the tool point vector is along the connection line between the tool and the part to be disassembled, and is close to the part.

[0081] S32. Convert the tool coordinate system to the assembly coordinate system and automatically position and match the tool point vector with the disassembly clearance point. The coordinate conversion formula is as follows:

[0082] A V=R' B V

[0083] Where, the point vector coordinates of the disassembly tool in the assembly coordinate system are: A V=[x 1A ,x 2A ,x 3A ] T , the superscript T is the transposition symbol; the point vector coordinates of the disassembly tool in the tool coordinate system areB V=[x 1B ,x 2B ,x 3B ] T ; R' is the transformation matrix of the tool point vector between the tool coordinate system and the assembly coordinate system.

[0084] Automated positioning and matching means that at the disassembly clearance point, the disassembly tool's action point is included in the disassembly action edge line or disassembly action plane of the part to be disassembled, and the tool vector is perpendicular to the disassembly action edge line or disassembly action plane of the part to be disassembled. The formula that must be satisfied in the Creo API program is as follows:

[0085] p i' ∈x part ,v i' ⊥x part

[0086] p i' ∈m part ,v i' ⊥m part

[0087] Where x part is the disassembly edge line of the part to be disassembled; m part It is the disassembly plane of the parts to be disassembled.

[0088] S33. Detect the interference volume between the disassembly tool and the part to be tested using the entity intersection interference detection method.

[0089] In this embodiment, the Creo API function pro_compute_volume() is used to detect the interference between the parts and the disassembly tool around the disassembly gap point, and the tool interference volume V is obtained. inf Please refer to Table 1 for tool interference V inf Calculation results.

[0090] Table 1: Interference volume V inf Calculation results

[0091]

[0092]

[0093] Note: See the detection position. Figure 4 Logo.

[0094] See also Figure 5 During the disassembly tool interference detection process in the mobile phone CAD model, all disassembly clearance points are traversed, the assembly coordinate system is converted to the part coordinate system, and the relevant parts that have been detected are removed. The coordinate system conversion formula entered in the Creo API is as follows:

[0095]

[0096] In the formula, (x a ,y a ,z a ) T Indicates the three-dimensional coordinates of any point on the part to be measured in the assembly coordinate system; (x b ,y b ,z b ) T Indicates the three-dimensional coordinates of any point on the part to be measured in the part coordinate system; represents the basis vectors of the assembly coordinate system, Represents the basis vectors of the part coordinate system.

[0097] S34. Convert the assembly coordinate system to the part coordinate system and remove the parts that have been inspected.

[0098] S4. Construct a tool-influenced fitness function, combine the structural constraint matrix and the interference volume, and use an intelligent optimization algorithm to optimize the disassembly strategy; the disassembly strategy includes the optimal disassembly sequence of parts, disassembly time, and maintenance efficiency.

[0099] In step S4, the optimization goal of the intelligent optimization algorithm is to minimize the disassembly time and maximize the maintenance benefit; the tool-influenced fitness function consists of two parts: the disassembly time function and the maintenance benefit function. The expression formula of the disassembly time function is as follows:

[0100]

[0101] T i v =k2V inf

[0102] Where, T represents the disassembly time; T i m represents the basic time for disassembling part i; T i v It indicates the increased disassembly time caused by the volume interference between the disassembly tool and part i; represents the disassembly tool change time from part i to part j; represents the time it takes for the disassembly tool to change direction from part i to part j; k2 represents the proportional coefficient between the interference volume and the increased disassembly time caused by the volume interference; V inf It indicates the interference volume between the disassembly tool and the part during the disassembly process.

[0103] The maintenance benefit function is expressed as follows:

[0104]

[0105] In the formula, V represents the maintenance benefit; c i represents the disassembly and maintenance value of part i; represents the cost of disassembling part i itself; c r represents the labor cost; represents the depreciation cost of the tool used to disassemble part i; c z represents the depreciation cost of the disassembly tool; represents the disassembly cost caused by the volume interference between the disassembly tool and part i; k1 represents the proportionality coefficient between the interference volume and the disassembly cost caused by the volume interference.

[0106] The algorithm fitness f of the intelligent optimization algorithm is expressed as:

[0107] f = ω1·V + ω2·T

[0108] In the formula, ω1 is the maintenance benefit weight factor; ω2 is the disassembly time weight factor.

[0109] In this embodiment, the intelligent optimization algorithm adopts the butterfly-genetic optimization algorithm. Of course, in other embodiments, other types of intelligent optimization algorithms can also be adopted.

[0110] Specifically, the steps of the butterfly-genetic optimization algorithm for implementing the disassembly sequence planning are as follows:

[0111] (1) Initialize parameters such as the population size pop_size and the conversion probability p, and store the detachable parts in the array down_array;

[0112] (2) Calculate the fitness f of each butterfly, and record the optimal fitness value f min and the optimal disassembly sequence;

[0113] (3) For each butterfly, calculate its fragrance perception amount. If r < p, perform the global search of the butterfly; otherwise, perform the local search of the butterfly;

[0114] The formula for calculating the fragrance perception amount is as follows:

[0115] f i = cI a

[0116] Among them, f i represents the fragrance perception amount of the i-th butterfly; c represents the sensory form; I represents the stimulus intensity, which is related to the fitness; a represents the fragrance.

[0117] The global search formula is as follows:

[0118]

[0119] Among them, x i t+1 , x i t represents the position of the i-th butterfly iterating to (t+1) and t generation; r is a random number between 0 and 1; g best Represents the optimal solution found by the butterfly in the current iteration.

[0120] The local search formula is as follows:

[0121]

[0122] Among them, x j t , Indicates the position of the j-th, k-th butterfly iterating to the t-th generation.

[0123] (4) Check the boundary conditions, recalculate the butterfly's fitness, and record the new optimal fitness value F min , if F min <f min , then update the optimal fitness value and optimal disassembly sequence;

[0124] (5) Using roulette wheel method to perform genetic selection operation, as well as crossover and mutation operations;

[0125] (6) Recalculate the fitness, if F min <f min , then update the optimal fitness value and optimal disassembly sequence;

[0126] (7) updating the aroma perception amount;

[0127] The formula for updating the fragrance perception amount is as follows:

[0128] c t+1 =c t +(b / c t ×Ngen)

[0129] Where c represents the sensory form, b is a constant, and Ngen is the maximum number of iterations.

[0130] (8) Determine whether the maximum number of iterations has been reached. If so, output the optimal fitness and optimal disassembly sequence. Otherwise, jump to step (3).

[0131] Please refer to Table 2. The results of disassembly sequence planning for mobile phone parts show that tool interference has a negative impact on the results of disassembly sequence planning, that is, disassembly time increases and maintenance benefits decrease. Therefore, it is necessary to reduce or eliminate tool interference by improving the optimization method of the structure.

[0132] Table 2: Disassembly sequence planning results for mobile phone parts

[0133]

[0134] S5. Calculate the optimized data of the part size or part gap based on the interference volume, adjust the specific part size or gap distance of the mobile terminal accordingly, and use the improved new structure to return to step S4 to optimize the disassembly strategy again.

[0135] In step S5, the calculation formula for the part size or part gap optimization data is as follows:

[0136]

[0137] Where ΔG represents the optimized part size or optimized gap distance; V inf Indicates the interference volume between the disassembly tool and the parts during the disassembly process; A tool_contact Represents the tool contact projection area, which is the plane projection area with the modified width as the normal within the part gap volume.

[0138] Refer to Table 3, mobile phone structure interference optimization data, to modify the part size and part clearance distance of the corresponding tool operating position.

[0139] Table 3: Mobile phone structure interference optimization data

[0140]

[0141] Note: The “*” in the upper right corner of the data indicates that the data is the part size or clearance data that needs to be modified or adjusted.

[0142] See also Figure 6 ,exist Figure 6 The parts size or gap of the structure shown are modified based on the actual structure, and finally the optimization suggestions for the mobile phone model are given: please refer to Figure 4 , the points for optimizing the gap distance between parts include: 1, 3, 4, 23-(1). In order to improve the disassembly efficiency, when the tool is performing the disassembly operation, it will cause interference with the adjacent parts at the gap, so it is necessary to increase the distance of the gap in the tool interference direction. Figure 5As shown, when the pry bar is inserted and removed at position 1, it interferes with the left middle frame. Therefore, the interference direction is the length direction of the gap. The original gap length in this direction is 3.02628mm. After calculation and optimization, it increases by 0.149050mm, and the revised gap length is 3.17533mm. When the pry bar is inserted and removed at positions 3 and 4, it interferes with the lower sub-plate cover. Therefore, the interference direction is the height direction of the gap. The original gap heights in this direction were 0.51mm and 0.510068mm, respectively. After calculation and optimization, they increase by 0.695700mm and 0.002037mm, respectively, and the revised gap heights are 6.262634mm and 0.037983mm. When the tweezers at position 23-(1) are placed and disassembled, the right end of the right lobe of the tweezers interferes with the power BTB connector interface on the right side. Therefore, the interference direction is the length direction of the gap. The original gap length in this direction is 0.5mm. After calculation and optimization, it is increased by 0.003849mm, and the modified gap length is 0.503849mm.

[0143] See also Figure 6 ,Part size optimization mainly refers to the length dimension of the BTB connector interface, and its points include: 21, 22, 23-(2), and 24. In order to improve the disassembly efficiency, when the tool is disassembling, interference occurs at the BTB interface, and the size of the part in the interference direction needs to be reduced. When the tweezers are inserted and the disassembly operation is performed at positions 21, 22, 23-(2), and 24, interference occurs in the length direction of the interface, so the dimensions in this direction are modified respectively. The original length dimensions are 9.5mm, 9mm, and 4.5mm respectively. After calculation and optimization, they are reduced by 0.032528mm, 0.003024mm, and 0.109759mm respectively. The modified interface length dimensions are 9.17472mm, 8.996976mm, and 4.390241mm. When the tweezers at position 23-(2) are placed and disassembled, the left end of the right flap of the tweezers or the left flap of the tweezers interferes with the BTB connector interface on the sub-board. Therefore, the interference direction is the direction of the interface length. The original length of the interface in this direction is 9.3mm. After calculation and optimization, it is reduced by 0.064738mm, and the modified interface length is 9.235262mm.

[0144] With the goal of reducing or eliminating tool interference, the part size and gap distance of the mobile phone model are optimized, and the disassembly sequence planning is re-implemented on the optimized new structure. The fitness function changes, and there are no variables affected by tool interference, including the increased disassembly time T caused by the volume interference between the tool and the part. i v and the disassembly cost c caused by volume interference between tool and part i kTherefore, the disassembly time function expression for disassembly sequence planning of the new structure is:

[0145]

[0146] Among them, T' represents the disassembly time, T i m Indicates the basic time for disassembling parts, T ij t T represents the time of disassembly tool change from part i to j, ij d It represents the time of direction change of the disassembly tool from part i to j.

[0147] The maintenance benefit function expression of the new structure disassembly sequence planning is:

[0148]

[0149] Among them, V' represents the maintenance benefit, c i Indicates the value of parts disassembly and repair, Indicates the cost of disassembling the parts themselves (labor cost), c r Indicates labor cost, c i t represents the depreciation cost of the tools used to disassemble the parts, c z Represents the depreciation expense of disassembly tools.

[0150] The fitness function expression of the new structure for disassembly sequence planning is:

[0151] f′=ω1·V′+ω2·T′

[0152] Among them, f' represents the algorithm fitness, ω1 represents the maintenance benefit weight factor, and ω2 represents the disassembly time weight factor.

[0153] Using the fitness function f', repeat step S2 to obtain the structural constraint matrix. With the goal of minimizing disassembly time and maximizing repair efficiency, the butterfly-genetic optimization algorithm is used to optimize the mobile phone parts disassembly sequence. See Table 4 for the disassembly sequence planning results for the new and old mobile phone structures.

[0154] Table 4: Results of disassembly sequence planning for the new and old structures of mobile phones

[0155]

[0156]

[0157] The new structure modified some part dimensions and clearances, eliminating tool interference during disassembly, resulting in zero tool interference. The original structure, however, did not consider tool interference in disassembly sequence planning, similar to eliminating tool interference. Therefore, the disassembly sequence planning results for the new structure with tool interference eliminated were compared with those for the original structure without. Both structures used the same method to generate the structural constraint matrix and optimize the disassembly sequence using the butterfly-genetic algorithm. The experimental results revealed different optimal sequences, with the new structure improving maintenance efficiency by 0.38% and reducing disassembly time by 0.41%. This result is due to the elimination of tool interference in the new structure, which reduces the increased disassembly time and cost caused by tool-part interference. While the part value and base disassembly time remain constant, the calculated value of the fitness function is reduced, resulting in improved disassembly time efficiency and maintenance efficiency for the new structure.

[0158] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. If other mobile terminals, three-dimensional modeling software, or CAD drawing software are used to replace the state transformation features or interference detection methods, the essence of the corresponding technical solutions will not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

[0159] Example 2

[0160] This embodiment provides a computer terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for optimizing the disassembly strategy of a mobile terminal considering the influence of tool interference as described in Example 1 are implemented.

[0161] like Figure 7 As shown, the computer terminal provided in this embodiment includes: at least one processor 101, and a memory 102 connected to the at least one processor 101. The specific connection medium between the processor 101 and the memory 102 is not limited in this embodiment. Figure 7 In the example, the processor 101 and the memory 102 are connected via the bus 100. Figure 7 The bus 100 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 7 The bus is represented by only one thick line, but it does not mean that there is only one bus or one type of bus. Alternatively, the processor 101 can also be called a controller, and there is no limitation on the name.

[0162] In this embodiment, the memory 102 stores instructions that can be executed by at least one processor 101 , and the at least one processor 101 can perform the aforementioned method by executing the instructions stored in the memory 102 .

[0163] Among them, the processor 101 is the control center of the device, which can use various interfaces and lines to connect the various parts of the entire control device, and monitor the device as a whole by running or executing instructions stored in the memory 102 and calling data stored in the memory 102, the various functions of the device and processing data.

[0164] In one possible design, processor 101 may include one or more processing units. Processor 101 may integrate an application processor and a modem processor. The application processor primarily processes the operating system, user interface, and application programs, while the modem processor primarily handles wireless communications. It is understood that the modem processor may not be integrated into processor 101. In some embodiments, processor 101 and memory 102 may be implemented on the same chip. In some embodiments, they may also be implemented on separate chips.

[0165] The processor 101 can be a general-purpose processor, such as a central processing unit (CPU), a digital signal processor, an application-specific integrated circuit, a field-programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the mobile terminal disassembly strategy optimization method considering tool interference effects disclosed in Example 1 can be directly implemented as a hardware processor, or can be implemented using a combination of hardware and software modules in the processor 101.

[0166] The memory 102 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The memory 102 may include at least one type of storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (RAM), a static random access memory (SRAM), a programmable read-only memory (PROM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 102 is any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 102 in this embodiment can also be a circuit or any other device that can implement a storage function, for storing program instructions and / or data.

[0167] By designing and programming the processor 101, the code corresponding to the security verification method described in the above embodiment can be fixed into the chip, so that the chip can execute the security verification method when it is running. Figure 1 The steps of the mobile terminal disassembly strategy optimization method considering the influence of tool interference are shown. How to design and program the processor 101 is a technology well known to those skilled in the art and will not be described in detail here.

[0168] Example 3

[0169] This embodiment provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the steps of the method for optimizing a mobile terminal disassembly strategy considering tool interference effects as described in Example 1 are implemented.

[0170] The computer-readable storage medium may include flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the storage medium may be an internal storage unit of a computer device, such as the hard disk or memory of the computer device. In other embodiments, the storage medium may also be an external storage device of the computer device, such as a plug-in hard disk equipped on the computer device, a smart media card (SMC), a secure digital (SD) card, a flash memory card, etc. Of course, the storage medium may also include both the internal storage unit of the computer device and its external storage device. In this embodiment, the memory is generally used to store the operating system and various application software installed on the computer device. In addition, the memory may also be used to temporarily store various types of data that have been output or are about to be output.

[0171] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A mobile terminal disassembly strategy optimization method considering the influence of tool interference, characterized in that: The following steps are involved: S1. Obtain a standard three-dimensional model of the mobile terminal and a disassembly tool model library; S2. Constructing a parts disassembly priority graph model of a mobile terminal to extract a structural constraint matrix from a standard three-dimensional model; wherein the structural constraint matrix is used to characterize the disassembly priority of the parts; S3. Obtain disassembly clearance points in the standard 3D model; construct a disassembly tool point vector model, and combine it with the dynamic conversion mechanism of the tool-assembly-part three-coordinate system to achieve automated positioning and matching of the disassembly tool and the disassembly clearance points, while also detecting the interference volume between the disassembly tool and the part during the part disassembly process; S4. Construct a tool-influenced fitness function, combine the structural constraint matrix and the interference volume, and use an intelligent optimization algorithm to optimize the disassembly strategy; the disassembly strategy includes the optimal disassembly sequence of parts, disassembly time, and maintenance efficiency.

2. The method for optimizing disassembly strategies of a mobile terminal considering the influence of tool interference according to claim 1, characterized in that: The following steps are also included: S5. Calculate the optimized data of the part size or part gap based on the interference volume, adjust the specific part size or gap distance of the mobile terminal accordingly, and use the improved new structure to return to step S4 to optimize the disassembly strategy again.

3. The method for optimizing disassembly strategies of a mobile terminal considering the influence of tool interference according to claim 2, characterized in that: In step S5, the calculation formula for the part size or part gap optimization data is as follows: Where ΔG represents the optimized part size or optimized gap distance; V inf Indicates the interference volume between the disassembly tool and the parts during the disassembly process; A tool_contact Represents the tool contact projection area, which is the plane projection area with the modified width as the normal within the part gap volume.

4. The method for optimizing disassembly strategies of a mobile terminal considering the influence of tool interference according to claim 1, characterized in that: Step S2 includes the following specific steps: S21. Construct a priority graph model for disassembling n parts of a mobile terminal, with disassembly parts as nodes and directed arrows to indicate the order of disassembly. The parts pointed to by the end of the arrow are disassembled first, and the parts pointed to by the tip of the arrow are disassembled later. S22. Quantify the priority graph model into a priority matrix P, i.e., the structural constraint matrix; wherein P is an n×n matrix, n is the total number of parts in the mobile terminal, i and j correspond to part numbers, i, j = 1, 2, ..., n; if there is a directed edge from any node i to node j in the priority graph model, then the corresponding element p in the matrix P is ij The value is 1, otherwise p ij The value is 0.

5. The method for optimizing disassembly strategies of a mobile terminal considering the influence of tool interference according to claim 4, characterized in that: In step S4, the optimization goal of the intelligent optimization algorithm is to minimize the disassembly time and maximize the maintenance benefit; the tool-influenced fitness function consists of two parts: the disassembly time function and the maintenance benefit function. The expression formula of the disassembly time function is as follows: T i v =k2V inf Where, T represents the disassembly time; T i m represents the basic time for disassembling part i; T i v It indicates the increased disassembly time caused by the volume interference between the disassembly tool and part i; represents the disassembly tool change time from part i to part j; represents the time it takes for the disassembly tool to change direction from part i to part j; k2 represents the proportional coefficient between the interference volume and the increased disassembly time caused by the volume interference; V inf Indicates the interference volume between the disassembly tool and the part during the disassembly process; The maintenance benefit function is expressed as follows: Where, V represents the maintenance benefit; c i represents the disassembly and repair value of part i; represents the cost of disassembling part i itself; c r Indicates labor-hour costs; represents the depreciation cost of the tools used to disassemble part i; c z represents the depreciation expense of disassembly tools; represents the disassembly cost caused by the volume interference between the disassembly tool and part i; k1 represents the proportional coefficient between the interference volume and the disassembly cost caused by the volume interference; The algorithm fitness f of the intelligent optimization algorithm is expressed as: f=ω1·V+ω2·T Where ω1 is the maintenance benefit weight factor; ω2 is the disassembly time weight factor.

6. The method for optimizing disassembly strategies of a mobile terminal considering the influence of tool interference according to claim 1, characterized in that: In step S3, the expression formula of the disassembly tool point vector model is: M=[p i' ,v i' ] Where M represents the disassembly tool point vector model; p i' v represents the action point of the i'th disassembly tool, i'=1,2,3,…,n', n' is the total number of disassembly tools; i' It represents the i'th tool vector, which is along the positioning constraint line or the moving axis of the disassembly tool and points to the crank, and its magnitude is a unit vector; The detection process of the interference volume includes the following specific steps: S31. Changing the position of the disassembly tool in the tool coordinate system by controlling the tool point vector model M to move an adaptation distance in the part matching direction, wherein the part matching direction is along the connection line between the disassembly tool and the part to be disassembled and close to the part; S32. Convert the tool coordinate system to the assembly coordinate system, and perform automated positioning and matching between the tool point vector and the disassembly clearance point; S33. By means of entity intersection interference detection method, the interference volume between the disassembly tool and the part to be tested is detected; S34. Convert the assembly coordinate system to the part coordinate system and remove the parts that have been inspected.

7. The method for optimizing disassembly strategies of a mobile terminal considering the influence of tool interference according to claim 6, characterized in that: In step S32, the automated positioning matching means that at the disassembly gap point, the action point of the disassembly tool is included in the disassembly action edge line or disassembly action plane of the part to be disassembled, and the tool vector is perpendicular to the disassembly action edge line or disassembly action plane of the part to be disassembled, and the following conditional expression is satisfied: p i' ∈x part ,in i' ⊥x part p i' ∈m part ,in i' ⊥m part Where x part is the disassembly edge line of the part to be disassembled; m part It is the disassembly plane of the parts to be disassembled.

8. The method for optimizing disassembly strategies of a mobile terminal considering the influence of tool interference according to claim 1, characterized in that: In step S3, the coordinate conversion formula in the three-coordinate system dynamic conversion mechanism is as follows: A V=R' B V Where, the point vector coordinates of the disassembly tool in the assembly coordinate system are: A V=[x 1A ,x 2A ,x 3A ] T , the superscript T is the transposition symbol; the point vector coordinates of the disassembly tool in the tool coordinate system are B V=[x 1B ,x 2B ,x 3B ] T ; R' is the transformation matrix of the tool point vector between the tool coordinate system and the assembly coordinate system, which is expressed as follows: In the formula, (x a ,y a ,z a ) T Indicates the three-dimensional coordinates of any point on the part to be measured in the assembly coordinate system; (x b ,y b ,z b ) T Indicates the three-dimensional coordinates of any point on the part to be measured in the part coordinate system; represents the basis vectors of the assembly coordinate system, Represents the basis vectors of the part coordinate system.

9. The method for optimizing disassembly strategies of a mobile terminal considering the influence of tool interference according to claim 1, characterized in that: In step S3, the disassembly clearance points in the standard three-dimensional model are obtained through the three-dimensional modeling application program interface.

10. The method for optimizing disassembly strategies of a mobile terminal considering tool interference according to claim 1, characterized in that: In step S1, the standard three-dimensional model includes functional parts and connection parts of the mobile terminal.

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