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G.M. Bedford

Bio: G.M. Bedford is an academic researcher from University of Portsmouth. The author has contributed to research in topics: Tempering & Carbon steel. The author has an hindex of 4, co-authored 4 publications receiving 194 citations.

Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors describe the events that the matrix and carbides experience as the coating material pass from the coating rod to the substrate, in forming the coating, and the coating is observed to harden automatically within a few seconds of being deposited onto the cold substrate.
Abstract: This paper is concerned with the friction surfacing of high-speed steels, BM2, BT15 and ASP30 onto plain carbon steel plate. The events that the matrix and carbides experience as the coating material pass from the coating rod to the substrate, in forming the coating, is described. The coating is observed to harden automatically within a few seconds of being deposited onto the cold substrate. This autohardening is observed to be an inherent feature of the friction surfacing process and the only post-coating heat treatment required is tempering, as with traditionally hardened high-speed steels. The mechanism of autohardening is discussed in terms of the mechtrode/coating/substrate thermal system.

85 citations

Journal ArticleDOI
TL;DR: In this article, a three-stage process is considered to optimise the process parameters required to cause the friction surfacing process to work smoothly and produce a well-formed coating.

57 citations

Journal ArticleDOI
TL;DR: In this paper, the main friction surfacing parameters are identified and the first stage of the optimisation process is achieved by visually assessing the coatings and introducing the substrate speed vs. force map.
Abstract: This paper discusses the procedures for data collection, management and optimisation of the friction surfacing process. Experimental set-up and characteristics of measuring equipment are found to match the requirements for accurate and unbiased data signals. The main friction surfacing parameters are identified and the first stage of the optimisation process is achieved by visually assessing the coatings and introducing the substrate speed vs. force map. The optimum values from this first stage forms a region around the middle of a trapezium-shaped area whose borders are found experimentally. Data collected for the second stage were analysed using the least squares method which were applied to find the coefficients of a second order regression model. Advantages of applying artificial intelligence methods to friction surfacing modelling are also described and the higher accuracy achieved using neural networks demonstrated.

40 citations

Journal ArticleDOI
TL;DR: In this paper, a new frame of a Neurofuzzy-model based Decision Support System (FricExpert) is proposed to speed up the parameter selection process and to assist in obtaining values for cost effective development.
Abstract: Friction surfacing is an advanced manufacturing process, which has been successfully developed and commercialised over the past decade. The process is used for corrosion and wear resistant coatings and for reclamation of worn engineering components. At present, the selection of process parameters for new coating materials or substrate geometries experimentally requires lengthy development work. The major requirement is for the flexibility to enable rapid changes of process parameters in order to develop new applications, with variations of materials and geometries in a cost effective and reliable manner. Further improvement requires development of appropriate mathematical models of the process, which will facilitate the introduction of optimisation techniques for efficient experimental work as well as the introduction of real time feedback adaptive control. This paper considers the use of combined artificial intelligence and modelling techniques. It includes a new frame of a Neurofuzzy-model based Decision Support System — FricExpert, which is aimed at speeding up the parameter selection process and to assist in obtaining values for cost effective development. Derived models can then be readily used for optimisation techniques, discussed in our earlier work.

31 citations


Cited by
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Journal ArticleDOI
TL;DR: Friction stir welding (FSW) has achieved remarkable success in the joining and processing of aluminium alloys and other softer structural alloys, however, it has not been entirely successful in the manufacturing of different desired materials essential to meet the sophisticated green globe requirements as discussed by the authors.

347 citations

Journal ArticleDOI
TL;DR: Friction surfacing (FS) is a solid state technology with increasing applications in the context of localized surface engineering and has been investigated mainly for producing fine grained coatings, which exhibit superior wear and corrosion properties.

198 citations

Journal ArticleDOI
TL;DR: In this article, the influence of forging force, consumable tilt angle, travel and rotation speeds on interfacial bond properties and process efficiency of mild steel was investigated, and the applied load on the consumable rod was found essential to improve joining efficiency and to increase the deposition rate.

105 citations

Journal ArticleDOI
TL;DR: In this paper, a multi-layer aluminium-SiC composite coatings were produced using a Friction Surfacing multi-layering approach using a median size of 118.8, 37.4 and 12.3 µm.

91 citations

Journal ArticleDOI
TL;DR: In this article, the microstructural evolution during friction surfacing of H13 tool steel is discussed, and the current work shows that friction surfaced tool steel coatings are suitable for use in as-deposited condition.

86 citations