Additive layer manufacturing is emerging as the next generation in part manufacture. It is being adopted by aerospace, tool making, dental and medical industries to produce and develop new conceptual designs and products due to its speed and flexibility. It has been noted that parts produced using additive layer manufacturing are not to a consistent quality. Variations have been recorded showing inadequate control over dimensional tolerances, surface roughness, porosity, and other defects in built parts. It is, however, possible to control these variables using real-time processes that currently lack adequate process measurement methods. This paper identifies process variation and lists parameters currently being recorded during a commercial additive manufacture (AM) machine build process. Furthermore, it examines correlations between manufactured parts and real time build variations.
(accessed July 10, 2009).The capabilities of a high average power picosecond laser are assessed for micromachining yttria-stabilized tetragonal zirconia polycrystal (Y-TZP) in its hard state. Laser machining of this material presents an attractive alternative to conventional machining techniques when precision customized parts are required due to the difficulty in machining Y-TZP in its hard state. Compared with previous nanosecond work the picosecond laser enables similar micromachining to be carried out at the same rate but with a superior surface finish and with no evidence of surface cracking. Strength measurements have been carried out using a four-point bend test rig and confirm that the improvement in surface quality translates to higher strength in machined components.
In this paper we have used laser powder bed fusion (PBF) to manufacture and characterize metal microwave components. Here we focus on a 2.5 GHz microwave cavity resonator, manufactured by PBF from the alloy AlSi10Mg. Of particular interest is its thermal expansion coefficient, especially since many microwave applications for PBF produced components will be in satellite systems where extreme ranges of temperature are experienced. We exploit the inherent resonant frequency dependence on cavity geometry, using a number of TM cavity modes, to determine the thermal expansion coefficient over the temperature range 6–450 K. Our results compare well with literature values and show that the material under test exhibits lower thermal expansion when compared with a bulk aluminium alloy alternative (6063).
The implementation of in-situ sensing solutions to monitor additive manufacturing processes has seen a significant surge in recent years, notably in processes where localised heating is used. These technologies, however, have not always yielded accurate information about final part quality, due to differences between the irregularities observed in-process and the anomalies present in the finished part. One way of investigating such differences is to establish correlations between in-process layer properties and the final condition of the part. In this work, we put forward a solution based on a bespoke fringe projection system designed to monitor layers within the build chamber of a PBF-LB machine. Through the computation of quantitative indicators on fringe projection data and the use of statistical control charts for their monitoring and analysis, we are able to predict local reductions in part density, detrimental to the quality of the final build, which are typically only visible after part manufacture. Principally, this article describes the developed fringe projection system utilised for data collection and the custom indicators used to examine layer topographical characteristics and which are correlated with local final densities. We design an experimental campaign to produce parts with different local densities and show how the proposed indicators, combined with statistical control charts, can predict in-process drops in density. The monitoring performance is validated via X-ray computed tomography (XCT) measurements performed on the as-built samples.
Millisecond‐pulsed Nd:YAG laser systems can be used for high‐speed cutting of ceramics, due to the high average power available. However, due to the relatively long pulse duration (0.3–5 ms), millisecond laser‐machining is predominantly a thermal, melt‐eject process. The quality of the finished surface is limited by a redeposited melt and a heat‐affected zone, in particular surface cracking. Shorter pulse duration lasers can provide a better surface finish but with a significantly longer processing time. This paper presents a method of improving the finish of millisecond‐machined yttria‐stabilized tetragonal zirconia polycrystal surfaces by postprocessing with a nanosecond‐pulsed laser. Nanosecond machining was carried out directly onto the as‐cut surface produced after millisecond processing, yielding a dramatic improvement of the surface finish in a relatively short time.
Abstract Recent studies in additive manufacturing (AM) monitoring techniques have focussed on the identification of defects using in situ monitoring sensor systems, with the aim of improving overall AM part quality. Much work has focussed on the use of of camera-based monitoring systems; however, limitations such as the slow response rates of the sensors (1-10kHz) and the post-processing requirements of the collected images make it difficult to apply these developmental monitoring methods on production systems in real-time. Furthermore, the replication of results from camera-based monitoring systems (often obtained using deep learning models) in a production environment is limited by the need for specialised hardware with high computational capacity (e.g GPUs). Focussing specifically on laser powder bed fusion ( PBF-L/M ), photodiodes, with fast data collection rates (50–100kHz) and providing data that is relatively easy to process are potentially better suited to real-time monitoring systems. The current study, therefore, focuses on using data collected from photodiodes to identify defects in PBF-L/M builds. A predictive model with real-time potential is proposed that, having been validated on data from computer tomography (CT) images, can be used to locate porosity within layers of PBF-L/M builds.
Yttria-Stabilized Tetragonal Zirconia Polycrystal (Y-TZP) as a high toughness, high strength and biocompatible material can be found in many medical applications where customized part manufacturing is required. Current machining techniques, including mechanical grinding [1] and (developed within our group) laser processing [2–4], may introduce cracking, resulting in reduced strength. Uncertainty of the exact shape, size and distribution of flaws introduced during manufacturing or machining require a reliable testing technique. In this paper we present a novel mid-infrared transmission technique for flaw detection in zirconia.
'%3e%3cpath fill='%23012169' d='M0 0v30h60V0z'/%3e%3cpath stroke='%23fff' stroke-width='6' d='m0 0 60 30m0-30L0 30'/%3e%3cpath stroke='%23C8102E' stroke-width='4' d='m0 0 60 30m0-30L0 30' clip-path='url(%23b)'/%3e%3cpath stroke='%23fff' stroke-width='10' d='M30 0v30M0 15h60'/%3e%3cpath stroke='%23C8102E' stroke-width='6' d='M30 0v30M0 15h60'/%3e%3c/g%3e%3c/svg%3e)
