Method of optimization of cutting of flat products made of natural material, mainly of wood, and system for its realization

Abstract

When cutting the flat products (3) a set of the desired shapes and dimension of the products (3) is defined. Firstly at least one surface of the material (1) is scanned; scanning sets the boundaries of the available surface of the material (1). Optical scanning can be supplied by radiological scanning, preferably by a CT scanner (8). Defects (2) are identified in the scanned image and a position is assigned to them. A weight coefficient is assigned to each element from a set of the desired shapes and dimensions of the products (3). A cutting plan (4) is created; this plan (4) defines the boundaries of individual flat products (3), whereby the places with the identified defects (2) of the material (1). Optimalization of the distribution of the desired products (3) is realized with the goal of achieving the highest sum of the number of the products (3) multiplied by the weight coefficient of a given product (3) without the need to cut all the elements from a set of the desired products (3). Subsequently a cutting machine (6) is used to cut the products (3); this machine (6) cuts the material (1) without any limitation with regard to the mutual position of the cut lines of the neighboring products (3).

Claims

1. A method for cutting flat products from wood, the method comprising the steps of: providing a database on a computer, including storage information about a pre-set set of shapes and dimensions of flat products (3) to be cut, wherein the pre-set set includes a predetermined group of elements; running the flat material on a working table having an optical scanner located on a first side of the working table and a CT scanner located on a second side of the working table, wherein the first side of the working table is opposite to the second side of the table; simultaneously scanning an image of a first visible side of the flat material (1) by using the optical scanner and scanning a second image of a second visible side of the material by using the CT scanner; identifying defects (2) of the scanned image of the material (1) by using a controlling unit located on the scanner; setting boundaries of the individual flat products (3); sending information obtained in the identification step to the database; assigning a position to each one of the identified defects by using a computer program on the computer; creating a cutting plan (4) by using linear programming without the need to cut all flat products (3) from the group of desired products, wherein during the creation of the cutting plan (4), locations of the identified defects (2) of the material (1) are taken into account; using a numerical algorithm to determine a distribution of the flat products (3) on the available surface of the material (1); assigning a weight coefficient to each one of the elements from the pre-set set of the shapes and the dimensions of the flat products (3); wherein the optimalization of the distribution of the flat products (3) is realized with a goal of achieving a highest sum of a number of the flat products (3) multiplied by a weight coefficient of a given product (3); immediately cutting the material (1) by using a cutting machine (6) by following the cutting plan.

2. The method according to claim 1, wherein the weight coefficient expresses an economic value of the flat product (3).

3. The method according to claim 1, wherein the material (1) is selected from a group of hardwood consisting of an oak, a beech, an elm, an ash, a black locust, and a walnut tree.

4. The method according to claim 1, wherein the scanner is an optical scanner (5) working in a visible spectrum and a contrast of neighboring points of the image is analyzed for the purpose of recognition of the defects, wherein the identified defects delimits the boundaries of a selected zone which is subsequently compared to pre-set criteria of the defects (2).

5. The method according to claim 1, wherein the material (1) is cut by a laser cutting ray whose position with regard to the material can be set in at least two planes.

6. The method according to claim 1, wherein the detected defects (2) are categorized into multiple sets, wherein at least one set contains the defects (2) which are acceptable in the flat product (3), whereby a localization of at least one acceptable defect (2) enters into the process of the cutting plan (4) as a boundary condition.

7. The method according to claim 1, wherein the weight coefficient is directly proportional to a size of the given flat product (3) and indirectly proportional to a number of the acceptable defects (2).

8. A system for cutting flat products from wood, the system comprising: a working table having a first side and a second side, the first side is opposite to the second side; an optical scanner (5) adapted to scan a first side of a material and located on the first side of the working table; a CT scanner adapted to scan a second side of the material and located on the second side of the working table; a cutting machine (6) located on the working table; and a controlling computer (7) connected to the scanner (5) and the cutting machine (6), wherein a database with at least one set of desired shapes and dimensions of flat products (3) is stored in the controlling computer (7), and the controlling computer (7) has an output for a control of a cutting line of the cutting machine (6), according to a cutting plan (4); wherein the optical scanner and the CT scanner simultaneously scan both sides of the material when the material runs though the working table; wherein a weight value stored in the database is assigned to each flat product (3) from the at least one set; a program for producing the cutting plan (4) by using a linear programming, whereas a maximum sum of weight values of the flat products (3) is in the controlling computer (7); wherein the cutting machine (6) is designed for jump changes in a direction of the cutting line and that the cutting machine (6) is a machine acting on a point.

9. The system according to claim 8, wherein the cutting machine (6) is a laser cutting machine.

10. The system according to claim 8, wherein the scanner (5) is placed between two suppliers that move the material (1).

Description

BRIEF DESCRIPTION OF DRAWINGS

(1) The invention is further disclosed by means of drawings 1 to 7. The used scale and shapes of the products, their mutual size ratio as well as the distribution of the defects are not binding, they are informative or directly adjusted for the purposes of clarity. The chosen ratios and shapes cannot be interpreted as limiting the scope of protection.

(2) FIG. 1 depicts a cutting plan pursuant to the prior state of the art in case of the optimalization for the circular saw where it can be seen that the cut lines of the neighboring products are intertwined and defined by the common longitudinal cut which forms the basic plates.

(3) FIG. 2 depicts a cutting plan with the products during weight optimalization according to this invention where the independence of the cut lines of the neighboring products can be seen, whereby all recognized defects are avoided and bypassed.

(4) FIG. 3 on the left there are cut products from the FIG. 2; on the right there is a set of the desired shapes and dimensions of the products.

(5) FIG. 4 depicts a cutting plan where during the optimalization a classification of defects is used. Optimalization is realized on the same basis as in case of the FIG. 2. The allowed defects are part of the product.

(6) FIG. 5 on the left there are cut products from the FIG. 4 and on the right there is a set of the desired shapes and dimensions of the products with the acceptable defects. Even though the number of the cut products according to FIG. 5 is smaller than the number on FIG. 3, its value is higher with regard to the products with larger surface and therefore the weight coefficient is higher.

(7) FIG. 6 is a simplified scheme of the connection of the elements in the system according to this invention.

(8) FIG. 7 depicts a system with use of the CT scanner where the plank moves between two suppliers whereby the material is optically scanned from all sides.

EXAMPLES OF REALIZATION

Example 1

(9) In this example according to FIGS. 2 and 3 is a method and system used at wood processing enterprise. The debranched trunks of the hardwood trees are cut to planks with the width which corresponds to the width of the products of one set of the desired shapes and dimensions of the products 3.

(10) In this example the debranched trunk of the tree is after the basic peeling off of the bark cut by a set of the circular saws to the width 25 mm. This creates the plates on the surface of which there are defects 2 such as knots, cracks or zones with mechanical or biological damage. These defects 2 can be recognized on the basis of the optical analysis.

(11) The scanner 5 is placed above the working table of the cutting machine 6. The working table moves in two directions; during scanning the working table moves in one direction and the plank placed on the working table runs under the scanner 5.

(12) When scanning the surface of the visible side of the plank the gathered image is analyzed in such a way that the color of the pixels and contrast of the neighboring pixels—or contrast of groups of pixels—is analyzed. This analysis is realized in the controlling unit of the scanner 5. At its output there is a file which discloses the outer boundaries of the scanned surface and it also discloses the boundaries of the recognized defects 2. Polygon S defines a shape of the available surface of the scanned plank. Defects 2 are described by the list of polygons E, which delimit the defect 2.

(13) The output from the scanner 5 is connected to the controlling computer 7 where there is a database with the products 3. The product 3 is defined by width W and length L. A weight coefficient C is assigned to each product 3 in the database.

(14) In this example the absence of the defects 2 of any category is required for all products 3. The conditions from the database of the desired products 3, the definition of polygon S of an available surface and polygon E of the defects 2 are re-written into the matrix of the linear programming. The result of the iterative method of the optimalization is a cutting plan 4 according to FIG. 2.

(15) The plank is cut by the laser cutting machine 6 according to the calculated cutting plan 4. As can be seen on the FIG. 3, not all elements from the database of the desired products 3 are contained in the result of the cutting; however, maximal economical yield from the available material 1 is achieved.

Example 2

(16) System in this example according to FIGS. 4 and 5 is concerned by the classification of the defects 2 in such a way that the acceptable defects 2 can appear on the resulting final products 3. On the scanner's 5 output there is a file which describes the outer boundaries of the scanned surface S and it discloses the boundaries of the recognized defects 2 alongside their classification into sets. Each defect is marked by category E_C[i] except for polygon E_P[i]; the number of categories is chosen pursuant to the nature of the material 1 and the clients' demands.

(17) One of the sets contains unacceptable defects 2 such as cracks running through a whole width of the plank.

(18) In this example the value of the residual material Crest is taken into account during optimalization, too.

(19) The list of the desired products 3 has a structure with the parameters W[j], L[j], C[j] (width, length, weight coefficient) and A_E[j, x], which denotes the acceptability of the defect 2 defined as E. If j-th product 3 can contain a defect 2 indexed x, it holds that A_E[j, x]=1, therefore it can overlap with all defects 2 defined as E_P[k] for which E_C[k]=x holds.

(20) Firstly, the choice of the products 3 sel[j]=1 takes place during the optimalization. The position of the lower left corner of the j-th product 3 is posX[j], posY[j]−X, Y. The positions are valid only for the products 3 selected to the choice of the cutting plan 4.

(21) An allowed surface S_P[j] is defined for the placement of the j-th product 3 as Σ E_P[i] for all i for which A_E[j, E_C[i]]< >0 holds. For the j-th product 3 it also holds that its definition by the polygon P[j] in form of a laid rhomboid with dimensions W[j] x L[j] which has a lower left corner defined by the position posX[j], posY[j].

(22) The correct solution of the task for the selected products 3 is written down as S_P[j] ΠP[j]=P[j] under the condition sel[j]=1. The mutual non-collision is defined by the condition P[j1]ΠP[j2]=0 for all j1, j2, for which sel[j]=1 holds.

(23) Through optimalization a maximum value of Pplaced=Σ C[j] is sought for all j where sel[j]=1. In case of counting of the value of the residual material, the maximum value of the sum Pplaced+Prest is sought.

(24) Optimalization can contain a learning step. The planks following one another from one and the same trunk have a mutually following or intertwined shape of the boundary polygon. Comparison of the just scanned surface of the material 1 with the surface of the previous scan can be used, and it can be assessed whether this is a cut from the same source—for example, from the same trunk. If it is, the recognition of the defects and their classification will be simple because we can expect them in the same or slightly moved or tilted positions as in the previous scan. The move or tilt is usually given by the width of the material 1 and the angle of cut relative to the direction of the spreading of the defect 2.

(25) Linear optimalization used in this example can be substituted by other ways of seeking of the maximal value of the function. The method according to this invention is not tied to a single algorithm; the crucial aspect of this invention is the interconnectedness of the optimalization with the freedom of the cutting line, whereby during the optimalization a maximal weight count is sought, without the need for all elements from the set of the desired products 3 to be present at the same time.

Example 3

(26) The system in this example according to FIGS. 2 to 5 and 7 uses a CT scanner 8, too, by which the inside of the material 1 is radiologically investigated.

(27) The material 1 runs between two suppliers which secure the regular movement of the material 1 and they produce a free space between them for the placement of the optical scanner 5 and CT scanner 8.

(28) The scanner 5 allows for scanning of the surface from all sides; it has scanning strip with a given optics and it has cameras placed from above, from below and from sides. The complete surface of the material 1 is scanned within a single drag of the material 1. A CT scanner 8 with a shielding cover is placed behind the optical scanner 5. The X-ray runs through the material under various angles; the detectors analyze the impacting radiation and the computer creates an image in the scanned cross-section. The output from the CT scanner 8 is connected to the controlling computer 7, where the data from the optical scanning arrive, too. When assessing the defects 2 the mutual relationship between the data from the scanner 5 and CT scanner 8 is assessed, too.

(29) The in-depth defects 2 inside the material 1, recognized by CT scanner 8, which do not manifest themselves on the surface, can be a subject to the independent category of the defects 2. After the creation of the cutting plan 4 the excerpts from the data of the scanning which correspond to the given position of the product 3 are assigned to individual products 3. The data are stored for the purposes of eventual complaint. It is possible to determine both inner and outer state of the product 3 during the expedition for each product 3.

INDUSTRIAL APPLICABILITY

(30) Industrial applicability is obvious. According to this invention it is possible to repeatedly optimalize the cutting plan of the distribution of the flat products on the surface of the natural material, whereby the high effectiveness of the use of the material is achieved.

LIST OF RELATED ELEMENTS

(31) 1—material 2—defect 3—product 4—cutting plan 5—scanner 6—cutting machine 7—controlling computer 8—CT scanner CT—Computed Tomography