Manual teaching of robot paths and welding parameters for multi-pass robotic welding is a cumbersome and time-consuming task, which decreases the flexibility, adaptability, and potential of such systems. This paper introduces and presents a new automated weld parameter and pass deposition sequencing framework, which builds on the current state of the art developments and enables automatic planning of multi-pass welding for single-sided V-groove geometries. By integrating a novel cost-function concept that permutates and identifies the welding parameters for each layer through a user-driven weighting, the framework delivers the minimum number of passes, filler material and welding arc time based on application requirements. A mathematical model relating the cross-section area of beads with the pose of the torch and weaving width was built upon to allow full-process automated welding parameter generation and adaption for different geometric characteristics of the groove. The concept methodology and framework were then developed and verified experimentally, through robotically deployed Metal Active Gas (MAG) welding. For a given representative joint, the arc welding time and amount of filler wire were found to be 32.9 % and 26.18 % lower respectively, than the worst-case available welding parameter combination, delivering a corresponding decrease in direct automated welding manufacturing costs. Lastly, an ultrasonic inspection was undertaken to verify the consistent quality of the weldments validating the framework outcome and enabling welding pass automation through robotic systems.

手动教授多道机器人焊接的机器人路径和焊接参数是一项繁琐且耗时的任务，这降低了此类系统的灵活性，适应性和潜力。本文介绍并介绍了一种新的自动焊接参数和焊道沉积排序框架，该框架建立在当前的最新技术基础上，并能够自动规划单面V形槽几何形状的多焊道焊接。通过集成新颖的成本函数概念，该结构通过用户驱动的权重来排列和标识每一层的焊接参数，该框架根据应用要求提供了最少的焊道数量，填充材料和焊接电弧时间。建立了将焊珠横截面面积与焊炬的姿势和编织宽度相关联的数学模型，以允许全过程自动生成焊接参数，并适应凹槽的不同几何特征。然后，通过机器人部署的金属活性气体（MAG）焊接，开发并通过实验验证了概念方法和框架。对于给定的代表性接头，发现电弧焊接时间和填充焊丝数量分别比最坏情况下可用的焊接参数组合降低了32.9％和26.18％，从而相应地降低了直接自动化焊接的制造成本。最后，