A tool-path generation strategy for wire and arc additive manufacturing

This paper presents an algorithm to automatically generate optimal tool-paths for the wire and arc additive manufacturing (WAAM) process for a large class of geometries. The algorithm firstly decomposes 2D geometries into a set of convex polygons based on a divide-and-conquer strategy. Then, for each convex polygon, an optimal scan direction is identified and a continuous tool-path is generated using a combination of zigzag and contour pattern strategies. Finally, all individual sub-paths are connected to form a closed curve. This tool-path generation strategy fulfils the design requirements of WAAM, including simple implementation, a minimized number of starting-stopping points, and high surface accuracy. Compared with the existing hybrid method, the proposed path planning strategy shows better surface accuracy through experiments on a general 3D component

Fabricating superior NiAl bronze components through wire arc additive manufacturing

Cast nickel aluminum bronze (NAB) alloy is widely used for large engineering components in marine applications due to its excellent mechanical properties and corrosion resistance. Casting porosity, as well as coarse microstructure, however, are accompanied by a decrease in mechanical properties of cast NAB components. Although heat treatment, friction stir processing, and fusion welding were implemented to eliminate porosity, improve mechanical properties, and refine the microstructure of as-cast metal, their applications are limited to either surface modification or component repair. Instead of traditional casting techniques, this study focuses on developing NAB components using recently expanded wire arc additive manufacturing (WAAM). Consumable welding wire is melted and deposited layer-by-layer on substrates producing near-net shaped NAB components. Additively-manufactured NAB components without post-processing are fully dense, and exhibit fine microstructure, as well as comparable mechanical properties, to as-cast NAB alloy. The effects of heat input from the welding process and post-weld-heat-treatment (PWHT) are shown to give uniform NAB alloys with superior mechanical properties revealing potential marine applications of the WAAM technique in NAB production

Advanced Design for Additive Manufacturing: 3D Slicing and 2D Path Planning

Commercial 3D printers have been increasingly implemented in a variety of fields due to their quick production, simplicity of use, and cheap manufacturing. Software installed in these machines allows automatic production of components from computer-aided design (CAD) models with minimal human intervention. However, there are fewer options provided, with a limited range of materials, limited path patterns, and layer thicknesses. For fabricating metal functional parts, such as laser-based, electron beam-based, and arc-welding-based additive manufacturing (AM) machines, usually more careful process design requires in order to obtain components with the desired mechanical and material properties. Therefore, advanced design for additive manufacturing, particularly slicing and path planning, is necessary for AM experts. This chapter introduces recent achievements in slicing and path planning for AM process

Effect of chemical composition on microstructure, strength and wear resistance of wire deposited Ni-Cu alloys

Two Ni-Cu alloys (Monel K500 and FM 60) having various Mn, Fe, Al, Ti and C contents were deposited on a Monel K500 plate at three different speeds using wire arc additive manufacturing technique. Microstructure characterisation, in particular a detailed study of precipitates, was carried out using optical and scanning electron microscopy. Mechanical properties were assessed using hardness, tensile and wear testing. For similar deposition conditions, Monel K500 has exhibited smaller secondary dendrite arm spacing and higher number density of Ti-rich particles, although the Ti concentration in FM 60 was higher. Finer microstructure and Ti precipitation led to superior hardness, tensile and wear resistance of Monel K500 compared to FM 60. The variation in microstructure-properties relationship with alloy composition is discussed

Model-free adaptive iterative learning control of melt pool width in wire arc additive manufacturing

© 2020, Springer-Verlag London Ltd., part of Springer Nature. Wire arc additive manufacturing (WAAM) is a Direct Energy Deposition (DED) technology, which utilize electrical arc as heat source to deposit metal material bead by bead to make up the final component. However, issues like the lack of assurance in accuracy, repeatability and stability hinder the further application in industry. Therefore, a Model Free Adaptive Iterative Learning Control (MFAILC) algorithm was developed to be applied in WAAM process in this study. The dynamic process of WAAM is modelled by adaptive neuro fuzzy inference system (ANFIS). Based on this ANFIS model, simulations are performed to demonstrate the effectiveness of MFAILC algorithm. Furthermore, experiments are conducted to investigate the tracking performance and robustness of the MFAILC controller. This work will help to improve the forming accuracy and automatic level of WAAM

Path Planning with a Lazy Significant Edge Algorithm (LSEA)

Probabilistic methods have been proven to be effective for robotic path planning in a geometrically complex environment. In this paper, we propose a novel approach, which utilizes a specialized roadmap expansion phase, to improve lazy probabilistic path planning. This expansion phase analyses roadmap connectivity information to bias sampling towards objects in the workspace that have not yet been navigated by the robot. A new method to reduce the number of samples required to navigate narrow passages is also proposed and tested. Experimental results show that the new algorithm is more efficient than the traditional path planning methodologies. It was able to generate solutions for a variety of path planning problems faster, using fewer samples to arrive at a valid solution

Recent progress on sampling based dynamic motion planning algorithms

This paper reviews recent developments extending sampling based motion planning algorithms to operate in dynamic environments. Sampling based planners provide an effective approach for solving high degree of freedom robot motion planning problems. The two most common algorithms are the Probabilistic Roadmap Method and Rapidly Exploring Random Trees. These standard techniques are well established, however they assume a fully known environment and generate paths ahead of time. For realistic applications a robot may be required to update its path in real-time as information is gained or obstacles change position. Variants of these standard algorithms designed for dynamic environments are categorically presented and common implementation strategies are explored

Development of safe optimized welding procedures for high strength Q&T steel welded with austenitic consumables

High strength quenched and tempered (Q&T) steels offer obvious economic benefits originating from their advantageous strength to price and weight ratios. These steels are usually welded using ferritic consumables and for this combination the risk of hydrogen assisted cold cracking (HACC) is high. The use of austenitic stainless steel (ASS) consumables has great potential to significantly improve this issue. Yet, there are no guidelines for determination of safe level of preheat for welding ferritic steels with ASS consumables. For this reason manufacturers adopt this parameter from procedures developed for conventional ferritic consumables thus significantly limiting the benefits ASS consumables are capable to deliver. Productivity could be further enhanced by identifying the upper interpass temperature threshold, thus reducing the stand-off times. Aim of this work is to develop safe highly optimised procedures for welding of high strength Q&T steel with ASS consumable