New approach for automatic tool selection in computer numerically controlled lathe by applying image processing

Abstract

Tool selection is a very important step in manufacturing processes so as to improve productivity with high quality. The contribution of this work is the development of a new method for automatic tool selection in computer numerical control lathe machines, based on image processing techniques and information of the boundary of the piece, provided by either a .DXF file (drawing exchange format) or from an image taken with other devices. The proposed method detects the preferential direction in the boundary of the piece and creates a directional field through a directional gradient aiming at selecting the correct tool. Results from experiments show that the method makes it possible to work with a resolution of 1.1 micrometers, and to obtain good performance in automatic tool selection when several types of twodimensional parts in the image are processed.

Triangulation intersection approach from Poisson’s equation applied to automatic tool selection in computer numerical control mill-lathe

“…27,28 The normal vector at a point (x 0 , y 0 , z 0 ) on a surface S = f(x, y, z) is given by equation (26) S = rf = f x (x 0 , y 0 , z 0 ) f y (x 0 , y 0 , z 0 ) f z (x 0 , y 0 , z 0 ) gradient in the edge of the triangles for 3D, for CNC mill-lathe, and the algorithm is shown in Table 1.…”

“…Determination of gradient of the piece in the triangles is obtained by applying the normal vector at a point of the triangulation obtained from the discretization; the gradient gives the position and direction of the piece in the workspace. 27,28 The normal vector at a point ( x 0 , y 0 , z 0 ) on a surface S = f ( x , y , z ) is given by equation (26)…”

Directional morphological approaches from image processing applied to automatic tool selection in computer numerical control milling machine

“…Perimeter of the piece. The perimeter (P(r x0 , r v0 )) can be found by applying an edge (e(x,y)) in the point of edge (e(i,j) into the image (f(i, j) j m n ) to provide information about the shape of the object, 24,25 and the labeled perimeter S p can be defined as the position vector for the edge; 25,26 point (h), obtained by the evaluation of significant discontinuities in pixel intensity 27 (s) the gradient, gives position (x), orientation (u) and direction of the piece (a) (machining workspace), the contour of a figure can be symmetric and periodic with respect to a line (x 2 B) for a pulse of the Dirac (d x (B)) (equation ( 3)), used for image processing and otherwise more complex contour or boundary functions…”

“…Figure 5(a) illustrates the vector direction of the edge of first piece example; Figure 5(b) shows the directional angles according to the trajectory of the edge, applying gradient in the piece. 25 The magnitude ( rf j j(i, j)) and direction (\rf(i, j)) of the labeling and perimeter (\rf(i, j)) of the edge are saved in the variable Des(i, j) to generate the dimension of structural element 25 8 S p (i, j) 2 f(x, y) :…”

“…The first machining is presented in Figure 9; the strategy is lineal zig where the label ''1'' represents an area with a tool of diameter of 0.2000 mm. The tool path is obtained by an algorithm 25 (zig) according to; a structural element with the shape of the cutting tool with diameter d is displaced through the entire image from right to left (first only in the x-axis) and from bottom to top (y-axis) creating roughing paths for m total of pixels if this is approaching to the boundary of the piece or there is an intersection between the cutting tools with the piece or pixel residue exists; then, another cutting tool is changed. If there is no intersection between the structural element and the edge of the piece, then it is considered as piece of the path.…”