Optimization Research On Sheet Cutting Problem

The optimization of rectangular parts under the Guillotine Cutting mode has broad application prospects in stone cutting,wood industry,glass processing,etc.The research on the optimization algorithm of rectangular parts cutting can effectively improve the economic benefits of the enterprises in the process of cutting,and optimize the resource allocation,improve the processing mode and promote production.Because the material characteristics of wood containing defects will cause more interference to the blanking work of wood board(plate),many optimization algorithms can not be directly applied in the processing of sheet blanking.Therefore,this paper proposes a consideration of defects.The blanking optimization method can effectively solve the problem of the optimization of the blanks of the defect-free and defective plates.Because the wooden plate may contain defects,this paper proposes the following methods to optimize the cutting of the plates:First,computer vision technology is used to detect wood defects,reject unqualified materials,and locate defect locations.For the defects that are not allowed in the wood processing process such as blue stain,this paper proposes to use Hue-RGB recognition technology to detect whether the wood has blue stain.For other types of wood defects(sections,cracks,etc.),the Otsu’s method is used for threshold processing,threshold segmentation,mor:phological methods,and region descriptors to identify defects in the wood surface and extract the wood defect position coordinates.On the basis of the previous step,this paper designs a heuristic algorithm to optimize the blanking of wood without defects,and then considers the defect location information obtained by computer vision into the process of optimizing the layout.This method can effectively solve the problem of cutting optimization of defective wood.Finally,a graphical user interface(GUI)is designed for the blanking optimization algorithm.The GUI can be used to directly obtain the raw material size,the size of the part to be stocked,the optimization result layout,the sheet utilization rate,etc.The position information of the sheet defects can be manually set,so that it has good practicability and maintainability.Using the above method to deal with related problems,the following results were obtained:(1)Using the Hue-RGB method to detect blue-containing wood,the detection accuracy,recall rate,false detection rate and average detection time were 85.37%,97.22%,3.66%and 0.79 seconds respectively.(2)Combined with Otsu’s method,threshold segmentation,morphological method and region descriptor,the defects such as knots and cracks were detected.The accuracy,recall and average detection time were 93.7%,99.72%and 0.48 seconds respectively.(3)Using the cutting stock optimization algorithm to optimize the blanking of the defective parts of the wooden plate can achieve a plate utilization rate of 91.33%.The above results prove that this paper uses MATLAB software to realize the original design of optimizing the blanking of defective wood through computer vision technology,digital image processing technology,heuristic algorithm and simple human-computer interaction technology.The example analysis proves that the design can basically meet the "one size fits all" cutting requirements.At the same time,it can effectively solve the problem of blanking of rectangular parts with defective wood.