Research On Intelligent Nesting Technology Of Leather

Engineering description of the optimization nesting problem is a set of cuttings or stampings put on a certain shape master sheet, doing not overlap each sample, within the effective area of the master sheet, meetting certain cutting technology and industry requirements, to achieve the goals of maximum utilization of raw materials and reduce the production of waste. Optimization nesting problem exists widely in all kinds of sheet metal processing and manufacturing sectors in the aerospace, shipbuilding, automobile and other industries. Such as, sheet metal, leather and glass cutting. Intelligent optimization nesting is an important part of intelligent manufacturing.In this paper, the object of intelligent optimization nesting material is leather. China is the largest leather consuming country. Manufacturing leather not only covers footwear, leather clothing, fur and its products, but also close to relationship with the airplane, automobile, furniture and other industries. How to achieve automation and intelligence of leather production technology and improving production efficiency is the problem of existence that China’s leather enterprises need to solve, especially in the face of increasingly scarce resources.In this paper, leather products for industrial background, to improve material utilization and production efficiency in the leather enterprises production process for the purpose carrying out scientific research. Focus on how to achieve high utilization of raw materials, while ensuring a reasonable search nesting time, achieve optimal layout.Optimization nesting problem is NP-hard problem. With the increasing size of the nesting objects, computational complexity sharp increase. The most effective way to solve NP-complete problems had yet to be found. This paper mainly from the following several aspects to study the problem of leather intelligent optimization:Firstly, using the improved adaptive genetic algorithm search the optimal order of the row of rectangular sample group, then the remaining rectangle algorithm as the decoding algorithm for automatic layout of rectangular sample.Secondly, firefly algorithm do discrete processing, which extension applies to continuous space optimization to combinatorial optimization rectangular sample. Simulated annealing algorithm do corresponding improvement and proposed discrete fireflies simulated annealing algorithm, combined with the remaining rectangle algorithm to achieve automatic layout of rectangular sample.Thirdly, extraction of the outer contour information of leather fabric master, outer contour of leather sample curve discrete, Matlab read DXF format graphics data and so pretreatment, do simple study. This paper proposes an improved algorithm of based on the scan line BL strategies for irregular polygon sample positioning and overlap detection.Fourthly, using simulated annealing algorithm to achieve the think of "shake the bottle policy" and using parallel search strategy separately search into the sample order and rotation angle. Combining the discrete fireflies simulated annealing algorithm and "shake the bottle policy" solve layout problems of irregular pieces.The simulation experiment proved that effect of the two-dimensional sample nesting by using the intelligent algorithm proposed is significant and substantial increase in utilization. Smart leather optimization nesting problem of this paper providing a theoretical basis for companies to achieve intelligent production and also can be applied to the sheet metal cutting and other industries. It has a certain theoretical value and practical significance.