Characterization of surface layer development on duplex stainless steel resulting from thermochemical hybrid treatment / Mohd Shahriman Adenan

The application of duplex stainless steels in various applications such as in petrochemical, water desalination and paper milling industries has rapidly increased in recent years, taking advantage of the combination of high strength and good corrosion resistance from the dual phase stainless steels. However, having low wear resistance and low surface hardness limits the applicability of the steels for wider applications; thus, improvement of the features is essential. A thermochemical hybrid treatment process has been developed to improve the wear resistance and surface hardness of duplex stainless steels without compromising its corrosion resistance. The process was performed by using a Faculty of Mechanical Engineering 8 mixture of methane (CH4), ammonia(NH3) and nitrogen (N2) at low temperature of below 500°C

Delaminating control on drilling the medium density fiber board with robust optimization

Drilling the medium density fiber (MDF) board always emerge the occurrence of delaminating, as the unwanted result of the process. The defect will moderate the aesthetical value of the finished products particularly if the product is a furniture product. This work optimizes the control factor of delamination using robust engineering technique founded by Genichi Taguchi, father of robust engineering. The optimum drilling parameter which based on smallest the better is optimized and it is confirmed by the confirmation experiment that the imperfections is minimized. Three control factors are investigated in the study: feed rate, cutting speed, and drill bits diameter. The response plot of the control factor shows a drill bit diameter is the highest contributing control factor that influences delaminating as the different of the robustness is 2.047 dB. The optimum parameter shows that the variability of the noise factor is improved as compared to the initial parameter by means of the dB gain of 1.308 dB and 1.451 dB for the prediction and confirmation respectively. The robust assessment of the optimization has indicates that the drilling parameter is less sensitive to the noise factor

Integrated approach to Wire Arc Additive Manufacturing (WAAM) optimization: Harnessing the synergy of process parameters and deposition strategies

The flexibility of Additive Manufacturing (AM) technologies in the metal 3D printing process has gained significant attention in research and industry, which allows for fabricating complicated and intricate Near-Net-Shape (NNS) geometry designs. The achievement of desired characteristics in Wire-Arc Additive Manufactured (WAAM) components is primarily contingent upon the careful selection and precise control of significant processing variables, including bead deposition strategy, wire materials, type of heat source, wire feed speed, and the application of shielding gas. As a result, optimizing these most significant process parameters has improved, producing higher-quality WAAM-manufactured components. Consequently, this has contributed to the overall rise in the method's popularity and many applications. This article aims to provide an overview of the wire deposition strategy and the optimization of process parameters in WAAM. The optimization of numerous wire deposition techniques and process parameters in the WAAM method, which is required to manufacture high-quality additively manufactured metal parts, is summarised. The WAAM optimization algorithm, in addition to anticipate technological developments, has been proposed. Subsequently, a discussion ensues regarding the potential for WAAM optimization within the swiftly growing domain of WAAM. In the end, conclusions have been derived from the reviewed research work

Research challenges, quality control and monitoring strategy for Wire Arc Additive Manufacturing

Metal additive manufacturing is a high-growth process owing to the capability of producing parts with complicated geometries and custom facets for various applications. The low material input ratio to final part output, in which minimum raw materials are needed to produce complex parts and thin-walled components with a large volume envelop-to-volume ratio, is advantageous compared to the conventional method. The Wire Arc Additive Manufacturing (WAAM) method has undergone significant research and advancement because it can be utilised to produce large metal components at high deposition rates as well as low cost and with better mechanical and microstructural properties than other AM techniques. Because of the significant amounts of processing temperature, various issues and defects arise during the process, hampering high-quality component manufacturing in WAAM. In addition, these components often have an insufficient and poor surface, affecting the metal components' quality. This article reviews common defects and research challenges associated with manufacturing different metal and alloy components using the WAAM process. Various control strategies in WAAM methods, which are essential to reduce or minimise defects to form high-quality metal parts, are summarised. Recent research on implementing artificial intelligence (AI) in quality improvement is discussed. The strategy for quality control using the multi-sensor-based closed-loop system is proposed in conclusion. This strategy could serve as a roadmap for ensuring the deposit efficiency and quality of WAAM components under complex, high-volume manufacturing circumstances

Distortion analysis of generatively designed hinge bracket using meso-scaled thermomechanical simulation with experimental validation

The accuracy of meso-scaled thermomechanical method (TMM) in analysing distortion of hinge bracket additively manufactured using selective laser melting (SLM) is investigated with SS316L as material and optimised design using Generative Design (GD) approach in which loads, boundaries, and constraints are considered as parametric inputs and stress goal as output. Prior to 3D printing, process simulation for predicting distortion was conducted including a geometrical model with hexahedral mesh type, temperature dependent material and flow curve referred from specialised software. To reduce computational time, a lumping approach with volume fraction was implemented considering heat flux parameters. For validation purposes, a series of experiments was accomplished using SLM, manual support structure removal, and surface finishing process by sandblasting. Furthermore, the finished bracket was measured using an optical scanner and compared with the simulation result. In conclusion, TMM can predict the distortion accurately with percentage point-by-point and mean error of less than 3% and 1.5%, respectively