A cluster-based pick-and-place path optimization method for LED placement machines
A LED placement machine and path optimization technology, applied in printed circuit, printed circuit manufacturing, computer components, etc., can solve problems such as long search time, low efficiency of LED chip production, unsatisfactory optimization results, etc., to achieve improvement The effect of production efficiency
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specific Embodiment approach 1
[0023] Specific implementation mode 1: The specific process of a cluster-based pick-and-place path optimization method for LED placement machines in this implementation mode is as follows:
[0024] Step 1: Convert the coordinates of the placement point to the coordinates of the leftmost suction rod when the placement head mounts components, calculate the chebyshev distance of the placement head when mounting components with different suction rods, and construct the corresponding distance matrix;
[0025] Step 2: Use the clustering method to select a group of elements with the smallest distance sum from the distance matrix in step 1, as the component serial number for each pick-and-place cycle;
[0026] Step 3: According to the serial numbers of the components picked and placed in each pick-and-place cycle in step 2, use the method of dynamic programming to determine the sequence of mounting components in each pick-and-place cycle.
specific Embodiment approach 2
[0027] Specific embodiment 2: The difference between this embodiment and specific embodiment 1 is that in the step 1, the coordinates of the mounting point are converted into the coordinates of the leftmost suction rod when the chip head mounts the component, and when the components are mounted by different suction rods The chebyshev distance of the patch head is used to construct the corresponding distance matrix; the specific process is:
[0028] Step 11: define the distance matrix Dist of S numCp rows and S numCp columns, initialize the row index r=1, and record the column index as c;
[0029] Among them, numCp is the total number of components, and S is the total number of suction rods;
[0030] For the element Dist(r,c) in the distance matrix, Dist(r,c) means that the element r%numCp is determined by the suction rod When picking up, the position of the placement head is compared with the component c%numCp by the suction rod Chebyshev distance between picks;
[0031] ...
specific Embodiment approach 3
[0045] Specific embodiment three: the difference between this embodiment and specific embodiment one or two is that in the step two, a clustering method is used to select a group of distance and minimum elements from the distance matrix in step one, as each pick The serial number of the component picked and pasted in the pasting cycle; the specific process is:
[0046] Step 21: Initialize the number of pick-and-stick cycles cntCycle=1, the total number of pick-and-stick cycles
[0047] Step two and two: determine the number of suction rods usedS used by the current pick-and-stick cycle cntCycle, when cntCycle
[0048] Step two and three: define RD as an array containing usedS elements whose initial values are all 0, and RD(s) represents the minimum distance that the placement head moves within a pick-and-place cycle on the premise that the suction rod s absorbs the compone...
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