Cutting Path Optimization Research Articles

Optimizing Cutting Sequences and Paths for Common-Edge Nested Parts

Different from the normal nesting algorithm, common-edge nesting reduces the spacing between parts, improves the utilization rate of the sheet, and shortens the processing time. Although common-edge nested parts may be useful in theory, they are not practical for large-scale production due to their cutting limitations. Existing research either did not consider all common cutting constraints or used graph theory methods for global common cutting path planning. However, due to cutting thermal effects and sheet deformation, it is difficult to use global common cutting path planning in actual processing. Therefore, this paper proposes a cutting sequence optimization algorithm for common-edge nested parts that consider all cutting constraints and proposes an algorithm for generating and optimizing common cutting paths. Experiments show that the common cutting path optimization algorithm proposed in this paper can reduce about 70% of the air path compared with commercial software. Furthermore, comparison by optical microscopy shows that the quality of the actual machined part is not inferior to that of the part machined according to the cut path generated by the commercial software.

An Improved Method for Optimizing CNC Laser Cutting Paths for Ship Hull Components with Thicknesses up to 24 mm

In this paper, the essence and optimization objectives of the hull parts path optimization problem of CNC laser cutting are described, and the shortcomings of the existing optimization methods are pointed out. Based on the optimization problem of the hull parts CNC laser cutting path, a new part-cutting constraint rule based on partial cutting is proposed, which aims to overcome the drawbacks of the traditional algorithms with serial cutting constraint rules. This paper addresses the problem of optimizing the path for CNC laser cutting of hull parts, including an empty path and the order and directions used for the provided cut contours. Based on the discretization of the part contour segments, a novel toolpath model for hull parts called hull parts cutting path optimization problems based on partial cutting rules (HPCPO) is proposed in this paper. To solve the HPCPO problem, a segmented genetic algorithm based on reinforcement learning (RLSGA) is proposed. In RLSGA, the population is viewed as an intelligent agent, and the agent’s state is the population’s diversity coefficient. Three different segmented crossover operators are considered as the agent’s actions, and the agent’s reward is related to the changes in the population’s fitness and diversity coefficients. Two benchmark problems for HPCPO were constructed to evaluate the performance of RLSGA and compared with four other algorithms. The results showed that RLSGA outperformed the other algorithms and effectively solved the HPCPO problem.

A discrete cuckoo search algorithm for traveling salesman problem and its application in cutting path optimization

The Traveling Salesman Problem (TSP) is a classic combinatorial optimization problem with various industrial applications. This paper proposes a discrete cuckoo search algorithm based on random walk and cluster analysis to solve the traveling salesman problem (TSP). Although the original cuckoo search algorithm is not suitable to solve the TSP, this algorithm is modified to solve the TSP. Lévy flights and random preference walk in the original cuckoo search algorithm are replaced with novel tools, including the local adjustment operator and discrete random walk. The former is utilized to preserve superior solutions found by the algorithm, while the latter is employed to maintain the diversity of the population. For large-scale TSP problems, the k-means algorithm is first utilized to divide cities into k categories for optimization, while random algorithms are adopted to combine them. A simple 2-opt operator is utilized as the local optimization operator to accelerate the algorithm's convergence rate. Multiple groups of standard TSPLIB datasets are chosen to compare the proposed method with state-of-the-art optimization algorithms that also use the 2-opt/k-opt optimization operator. According to the experimental results, the stability and accuracy of the proposed algorithm are superior to the state-of-the-art optimization algorithms. Regarding the solution accuracy, the algorithm improves 0.39%, 0.29%, 0.84%, 0.4%, 0.07% and 2.22% in the optimal solution over discrete cuckoo search (DCS), discrete bat algorithm (DBA), discrete sine–cosine algorithm (DSCA), random-key cuckoo search (RKCS) and discrete spider monkey optimization (DSMO) on the standard test cases, and 0.58%, 0.19%, 0.85%, 0.43%, 0.36% and 5.83% in the average optimal solution. Regarding stability, the variance of the optimal solutions of RKCS, DSMO, and novel discrete differential evolution (NDEE) for 30 independent runs is 38.5, 52.6, and 59.4 times higher than that of the algorithm in this paper. Finally, the proposed algorithm optimizes air knife migration during glass cutting. Accordingly, the path for air knife migration is reduced by 8556 mm.

Cutting path optimization for an automatic cutter in polynomial time using a 3/2 approximation algorithm

The optimal path to be followed by an automatic cutter to cut a set of shapes arranged on a material is termed as the cutting path determination problem. The shapes are often considered as polygons. Each polygon can be either cut entirely (complete cutting approach) or partially (partial cutting approach) before cutting the next polygon. This work solves the cutting path determination problem using the partial cutting approach. The proposed approximation algorithm uses the concepts of ma tching, s panning tree, and tri angulation, and is hence termed as MASTRI. The MASTRI algorithm has a time complexity of O(n logn) where n is the total number of vertices of all the polygons. The cutting path computed by the MASTRI algorithm is guaranteed to be within a factor of 3/2 of optimum travel distance of the cutter. No other algorithm has been developed for the partial cutting approach which runs in polynomial time. The MASTRI algorithm is evaluated on 285 input problems, of which 192 problems are randomly generated, and 93 problems are taken from literature. The experimental analysis shows that the MASTRI algorithm computes the cutting path in a very short amount of time. The comparison of MASTRI algorithm with existing works in the literature shows that the MASTRI algorithm gives a shorter cutting path in less time. The MASTRI algorithm can be used for computing cutting path in industries like sheet metal cutting.

Research on Cutting Path Optimization of Trimming Process

For a stamped part, excess material on the edge need to be cut to get the final part. To explore the impact of different laser-cutting paths on the accuracy of part formed by multi-point forming with blank-holder, three different cutting paths are designed in this paper, and the process of laser-cutting is simulated by finite element method. By comparing the springback of the parts under different cutting paths, it is found that the part cut by path 3 has the highest accuracy. Finally, the experiment is performed with path 3 and compare the shape of the formed part with the target part, it is verified that cutting with path 3 can obtain higher precision parts.

Correction to: Laser cutting path optimization with minimum heat accumulation

Due to an unfortunate error on importing the problem dataset, there were mistakes in some of data listed in Table 2

Laser cutting path optimization with minimum heat accumulation

A new approach for minimizing both cutting path and heat accumulation in laser cutting process is presented in this paper. The proposed algorithm was based on a memetic algorithm combining a powerful genetic algorithm with an adaptive large neighborhood search. The cutting path problem was modeled and solved in accordance with generalized traveling salesman problem. A heat conduction model was incorporated into the cutting path optimization by assigning a critical radius of heat-affected zone as a constraint. A penalty was given to the cutting paths overlapping the heat-affected zone to minimize the heat accumulation in workpiece. A heat map indicating thermal gradient around the laser piercing points was also presented together with the optimum cutting path to visualize the level of heat accumulation. By comparing to the approach without the heat constraint, the algorithm incorporating with the heat effect was capable of determining the laser cutting path with minimum travel distance and heat accumulation in workpiece. The presented method could further be applied for other thermal-related processes such as surface hardening, welding, and additive manufacturing, whose processing distance and heat issue need to be optimized for gaining their productivity and final product quality.

Laser cutting path optimization using simulated annealing with an adaptive large neighborhood search

A simulated annealing algorithm combined with an adaptive large neighborhood search (ALNS) has been proposed in this paper to minimize the laser cutting path in a two-dimensional cutting process. The proposed algorithm was capable of finding a near-optimum cutting path from a given layout of cut profiles. In this study, the layout was taken from an image, in which image processing algorithms were employed to extract cut profiles from the input image and to assign coordinates to the contours’ pixels. The optimization algorithm was based on generalized traveling salesman problem (GTSP), where all pixels of the input image were considered as the potential piercing locations. A laser beam made a single visit and then did a complete cut of each profile consecutively. The simulation results revealed that the proposed algorithm can successfully solve several datasets from GTSP-Lib database with a good solution quality. A compromise between the path distance and computing time was achievable by considering only 30% of the total pixels of the input image examined in this study. In addition, the cutting path generated by the proposed method was shorter than that recommended by the commercial CAM software and other previous works in terms of path distance with the same profile sample.

Research on cutting path optimization of sheet metal parts based on ant colony algorithm

In view of the disadvantages of the current cutting path optimization methods of sheet metal parts, a new method based on ant colony algorithm was proposed in this paper. The cutting path optimization problem of sheet metal parts was taken as the research object. The essence and optimization goal of the optimization problem were presented. The traditional serial cutting constraint rule was improved. The cutting constraint rule with cross cutting was proposed. The contour lines of parts were discretized and the mathematical model of cutting path optimization was established. Thus the problem was converted into the selection problem of contour lines of parts. Ant colony algorithm was used to solve the problem. The principle and steps of the algorithm were analyzed.

Research on NC laser combined cutting optimization model of sheet metal parts

The optimization problem for NC laser combined cutting of sheet metal parts was taken as the research object in this paper. The problem included two contents: combined packing optimization and combined cutting path optimization. In the problem of combined packing optimization, the method of “genetic algorithm + gravity center NFP + geometric transformation” was used to optimize the packing of sheet metal parts. In the problem of combined cutting path optimization, the mathematical model of cutting path optimization was established based on the parts cutting constraint rules of internal contour priority and cross cutting. The model played an important role in the optimization calculation of NC laser combined cutting.

Modeling and Cutting Path Optimization of Shallow Shell Considering its Varying Dynamics During Machining

During the milling process of shell structures, such as blades and engine casing, the change of thickness varies the dynamics of the workpiece considerably, which may induce unstable cutting conditions and thus influences the quality of the machined surface. In this paper, common shell structures are firstly simplified as doubly curved shallow shells to notably minimize the computation amounts, and then an analytical model was presented to predict the dynamic changes in the material removal process. The Ritz method and the thin shallow shell theory are combined to solve the dynamic characteristics of the shallow shell structures.Furthermore, based on the simulation results of the above analytical model and the stability lobes theory, the workpiece is divided into several subregions according to the variation of dynamics stiffness. In each subregion, the dynamic characteristics are assumed to be constant to simplify the analysis. Afterwards, trial cuts are performed respectively in each subregion to select the best cutting parameters. The optimized tool paths are generated according to the trial cuts which will guarantee a stable cutting operation during the entire machining process with high efficiency and good surface quality. Finally, experiments are performed to verify the proposed method.

Ball-End Milling Force Modeling and Simulation Based on Cutting Path Optimization Experiments

Modeling and simulation of ball-end milling cutter has an important means in studying milling process characteristics. Most scholars ignore practicability analysis before modeling, according to this, modeling and simulation of optimization path is proposed based on cutting path optimization experiment in this paper, which simplifies modeling and simulation and makes model development and practical application have more pertinence and practicality.

Cutting Path Optimization of Pattern Pieces in Garment Automatic Cutter

In view of the defect and shortage in cutting path automatic optimization of 2D pattern pieces in current garment automatic cutter, a new optimization method of computer is explored. If there is no cutting path optimization implemented by garment automatic cutter before cutting, some problems will be caused, such as too much unless travel and too long processing time. At present, both at home and abroad, the studies on automatic optimization in cutting preprocessing are relatively weak. According to the “segment cutting from left to right” feature of automatic cutter in cutting process, an algorithm which can be summarized as “segment and reducing point” was proposed. This algorithm combined with the solution of shortest path problem, its purpose is to seek for the approximate optimal solution of cutting path. The algorithm implemented through Visual C++ 6.0 programming. Used in production by enterprise shows that the program is simple to operate, and has a high compute speed. Averagely, unless travel in cutting process reduced more than 10%. It proves that the algorithm is feasible and efficient. Using this algorithm achieved the purpose of reducing unless travel, improving cutting efficiency and lowering the cost.

Cutting path optimization in CNC cutting processes using a two-step genetic algorithm

This paper deals with the problem of generating 2D cutting paths for a stock plate nested with a set of regular and/or irregular parts. The objective of the problem is to minimize the total non-productive traveling distance of a cutter starting from a known depot, then cutting all the given parts, and returning back to the depot. A cutting path consists of the depot and piercing points, each of which is to be specified for cutting a part. The cutting path optimization problem is shown to be formulated as a generalized version of the standard traveling salesman problem. To solve the problem, a two-step genetic algorithm combining global search for piercing point optimization and local search for part sequencing is proposed. Traditional genetic operators developed for continuous optimization problems are modified to effectively deal with the continuous nature of piercing-point positions. A series of computational results are provided to illustrate the validity of the proposed algorithm.

An Approach to Efficient Nesting and Cutting Path Optimization of Irregular Shapes

A new nesting and cutting path generation algorithm is proposed and a PC-based GUI system is established for user convenience. The proposed algorithm can reduce the calculation time by updating the boundary of raw material after each part is placed and by selecting the vertices of the boundary as initial allocation points. Grouping the parts by their areas and applying the column nesting can improve the nesting efficiency, e.g., waste ratio. Also, optimal cutting paths are found based on an algorithm by allowing all the convex vertices of the parts to be piercing points compared with existing work that used only fixed piercing points.

A study on torch path planning in laser cutting processes part 2: Cutting path optimization using simulated annealing

In Part 1 of this paper [beginning on page 54], the heat flow in contour laser beam cutting was calculated by using the finite difference model, and a modified analytic model was developed based on the numerical experiments. Part 2 addresses the problem of optimal torch path planning for the 2D laser cutting of a stock plate nested with irregular parts. Under the constraint of the relative positions of parts enforced by nesting, the optimization algorithm generates a feasible cutting path. The simulated annealing technique is adopted for solving the torch path optimization problem to minimize a specified cost function. The objective is to traverse the cutting contours with a minimum path length and, at the same time, to minimize the effect of heat on the cutting path sequence. To minimize the heat effect and avoid overheating, the critical temperature that should be avoided during the whole cutting sequence is considered. In this way, a global solution can be obtained in a reasonable time. Several examples are presented to illustrate the effectiveness of the proposed method.

A Study on Torch Path Planning in Laser Cutting Processes. Part 2: Cutting Path Optimization Using Simulated Annealing

In Part 1 of this paper [beginning on page 54], the heat flow in contour laser beam cutting was calculated by using the finite difference model, and a modified analytic model was developed based on the numerical experiments Part 2 addresses the problem of optimal torch path planning for the 2D laser cutting of a stock plate nested with irregular parts. Under the constraint of the relative positions of parts enforced by nesting, the optimization algorithm generates a feasible cutting path. The simulated annealing technique is adopted for solving the torch path optimization problem to minimize a specified cost function. The objective is to traverse the cutting contours with a minimum path length and, at the same time, to minimize the effect of heat on the cutting path sequence. To minimize the heat effect and avoid overheating, the critical temperature that should be avoided during the whole cutting sequence is considered in this way, a global solution can be obtained in a reasonable time. Several examples are presented to illustrate the effectiveness of the proposed method.