Energy saving and consumption reduction is one of the current important research in the field of green and sustainable manufacturing. Products or components containing variable curvature contouring are widely used in the automotive, medical, aerospace, and mold industries, while there is a lack of methods to model the energy consumption ratio for variable curvature contouring and improve its energy efficiency. A method for modeling the specific energy consumption of variable curvature contouring and energy consumption optimization is proposed for this problem. Firstly, the components of energy consumption in processing of the CNC machine tool machining are analyzed, and the relationship between curvature characteristics and material removal rate is investigated from the geometric perspective. Secondly, orthogonal experiments with different curvatures of straight lines, convex arcs, and concave arcs are designed to collect energy consumption data. Based on the experimental data, the Dueling Deep Q-Network optimization support vector regression (Dueling DQN-SVR) was used to establish the specific energy consumption model considering the curvature. Finally, a multi-objective optimization model is constructed when considering specific energy consumption, efficiency, and quality, and the Pareto solution set is solved using a multi-objective Gray Wolf optimization algorithm (MOGWO). The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was used to select the optimal combination of machining parameters. The experimental results show that the accuracy of the established model is more than 95%. The method improved energy efficiency by more than 7.82% and efficiency by more than 1.128%. These research results are of great theoretical and practical significance for achieving energy-efficient variable curvature contour machining.

The machining trajectory of the irregular contour is usually discretized into straight lines and arcs, and process parameters selection affects the quality and efficiency of irregular sheet metal parts machining. To guide parameters selection of irregular sheet metal parts milling, a multi-objective optimization framework for efficiency and side machining quality is constructed. In the framework, to improve the modeling accuracy and reduce modeling cost, the theory-data coupled models of side roughness for straight line, convex arc and concave arc constructed, respectively. Aiming at the problems of single search method and susceptibility to local optima in the standard multi-objective seagull optimization algorithm (MOSOA), an improved MOSOA (MOSOAimprove) is proposed to solved the multi-objective optimization model of side quality and efficiency developed by the coupled model of side roughness and the empirical formula of the material removal rate. The effectiveness of coupled models and MOSOAimprove in multi-objective optimization of irregular sheet metal parts milling are verified by the actual machining.

The continuous short line segment processing method in CNC machining has the defect of frequent fluctuation of feedrate, which affects the quality and efficiency. For this problem, the local and global methods are common solutions. The local method is to insert transition curves at the corners to obtain a smooth toolpath, but this method does not essentially reduce the number of accelerations and decelerations, and it is difficult to insert transition curves between tiny straight sections. Although the global method can obtain smooth tool trajectories, the parametric interpolation method is not suitable for middle- and low-end CNC machine tools. The article proposes an adaptive tool path generation method with the original part contour as the research object and discretizes the NURBS curves into smooth trajectories consisting of large segments of straight lines and circular arcs. The article mimics the crawling characteristics of snakes and designs a double-headed snake algorithm based on the least squares method to implement this process. First, given the start and end points of the curve, two snakeheads search for the maximum linear and circular segments that satisfy the error constraint in the curve direction. The winner will then be selected as the candidate track segment through a competition mechanism. Finally, all trajectory segments are connected to obtain a smooth tool path. Experiments show that the toolpath data of the method in this paper are reduced by 75.56% compared with commercial CAM software when the contour error threshold is the same, and the contour error is reduced by more than one order of magnitude when the number of toolpath segments is equal. In addition, the method in this paper can obtain a smoother machining surface and more stable cutting force, thus achieving a win‒win situation of quality and efficiency.

This study introduces a developed method to a smart computer-aided design/manufacturing (CAD/CAM) system, where layout design, process planning, and comprehensive computerized numerical control (CNC) code generation can be implemented to satisfy laser cutting holes, tapping, irregular and complicated profile processing, engraving, and burr back-scraping. The smart CAD/CAM(SCAM) system is developed as a commercial software product or application and firstly applied to flexible sheet metal machining center (BGL 130R). In this study, a formal modeling method involving Petri nets and first-order predicate logic is proposed to develop the smart manufacturing system. High-level Petri nets are employed to achieve the formal application architecture design of data flow for various functions, and the first-order logic used to represent the process plan is defined and deduced according to the machining methods. The developed system possesses the following characteristics: (1) a sound and complete deductive system to implement various types of trajectory planning, automatic generation, and validation of the CNC code; (2) a convenient design input environment and readiness for re-design and modification by adding specific design functions and using standard design procedures on a widely used CAD/CAM package; (3) helpful for designers in sheet metal layout designing, layout interference detection, process planning validation, preprocess manufacturing operation of CNC code generation, and autodefinition of storable file names; and (4) formal and simple in human–computer interaction, automatic and intelligent in process operations, and satisfactory in terms of the requirements of the flexible sheet metal machining center (BGL 130R).

Optimal nesting is one effective method to reduce manufacturing cost by improving material utilization.To settle the nesting problem of circular blanks,a quick physical nesting algorithm based on rubber band potential energy descending (RPED) was proposed.Firstly,the mathematical optimal model of circular blanks nesting was constructed.Basic procedure of RPED strategy based on some ideal conditions was presented here.Secondly,force analysis and motion analysis were described in detail And the nesting simulation method in discrete time step was proposea.Finally,genetic algorithm was merged with RPED strategy to enable this hybrid version to get the best global solution.Several typical computer instances were carried out.And consequences showed that the average material utilization increased by 1.1％ in engineering practice and by 0.68％/0.19％ in other five international standard examples compared with other algorithms.The nesting algorithm proposed in this paper performs more effectively with a high average material utilization.

This thesis put forward a physical force-driven packing optimization design method for solving the Strip Packing Problems (SPP). This thesis researched on the following aspects: The mathematical optimization model of SPP is proposed firstly. Based on the convex hull plus rubber band compact layout method, the method of physical analysis of the layout process and the time-based layout simulation process are presented definitely. An enhanced version of the mate algorithm of surplus rectangle for rectangle packing is proposed. This method use the minimal rectangle to replacing polygon objects and choose the next packing object by a series of score decision rules. Different forces are applied to the packing objects in corresponding stages which would drive them to move compactly and the optimal packing result can be obtained in the end. The comparison of computational experiment results shows that the proposed packing method have a better performance.

This article deals with the packing problem of irregular items allocated into a rectangular sheet to minimize the waste. Conventional solution is not visual during the packing process. It obtains a reasonable and relatively satisfactory solution between the nesting time and nesting solution. This article adopts a physical method that uses rubber band packing algorithm to simulate a rubber band wrapping those packing irregular items. The simulation shows a visual and fast packing process. The resultant rubber band force is applied in the packing items to translate, rotate, and slide them to make the area decrease and obtain a high packing density. An improved analogy QuickHull algorithm is presented to obtain extreme points of rubber band convex hull. An adaptive module could set a variable rubber band force and a variable time step to make a proper convergence and no intersection. A quick convex decomposition method is used to solve the problem of concave polygon. A plural vector expression approach is adopted to calculate the resultant vector of the rubber band force. Several cases are compared with the benchmark problems to prove rubber band packing algorithm performance.

Strip packing problems is one important sub-problem of the Cutting stock problems. Its application domains include sheet metal, ship making, wood, furniture, garment, shoes and glass. In this paper, a hierarchical layout design method based on rubber band potential-energy descending was proposed. The basic concept of the rubber band enclosing model was described in detail. We divided the layout process into three different stages: initial layout stage, rubber band enclosing stage and local adjustment stage. In different stages, the most efficient strategies were employed for further improving the layout solution. Computational results show that the proposed method performed better than the GLSHA algorithm for three out of nine instances in utilization.

At present, layout problem is still a NP hard problem, which does not have a recognized method. This paper discusses a compact layout problem with multi-object. In order to solve the problem efficiently, we present a CPR (convex hull plus rubber band) compact layout method using annulus-centre heuristic algorithm. In the proposed algorithm, firstly, we divided the layout procedure into three stages-only outers, outer-inner and more objects involved. In addition, rules of multi-object response are built to guide the movement of objects. Finally, we also express the procedure of compact layout as predicate logic that provides detail design of programming. The simulation on a example indicates the proposed algorithm is effective and feasible.

Computing the convex hull of any given point set is a fundamental problem in computational geometry. In this paper, a new algorithm is proposed to improve the efficiency of the creation of convex hull. The algorithm employed a rectangular segmentation method to divide the initial convex hull with some rectangular windows, then most of non-convex points could be easily removed out by comparing their coordinate values in order to reduce the computation time of the creation procedure. To validate the efficiency, three computer experiments were conducted and the results showed that the proposed algorithm has better performance than some other present convex hull algorithms such as Quickhull algorithm when dealing with the large scale two dimension scattered point set.