An approach to reduce stress and defects: a hybrid process of laser cladding deposition and shot peening

Purpose Laser cladding deposition is limited in industrial application by the micro-defects and residual tensile stress for the thermal forming process, leading to lower fatigue strength compared with that of the forging. The purpose of this paper is to develop an approach to reduce stress and defects. Design/methodology/approach A hybrid process of laser cladding deposition and shot peening is presented to transform surface strengthening technology to the overall strengthening technology through layer-by-layer forming and achieve enhancement. Findings The results show that the surface stress of the sample formed by the hybrid process changed from tensile stress to compressive stress, and the surface compressive stress introduced could reach more than four times the surface tensile stress of the laser cladding sample. At the same time, internal micro-defects such as pores were reduced. The porosity of the sample formed by the hybrid process was reduced by 90.12% than that of the laser cladding sample, and the surface roughness was reduced by 43.16%. Originality/value The authors believe that the hybrid process proposed in this paper can significantly expand the potential application of laser cladding deposition by solving its limitations, promoting its efficiency and applicability in practical cases.

Selected bending properties of mineral-acrylic solid surface material for furniture construction purposes

Selected bending properties of mineral-acrylic solid surface material for furniture construction purposes. The aim of this work was to characterize the bending properties of selected, commercially available panels made with the use of mineral acrylic fillers and thermoplastic matrix (trade names Corian and Staron), with regard to thermal forming. The research showed that when the temperature of the tested materials rises from 20 to 160°C, there is a significant reduction in the value of bending strength (by over 90% for Corian and about 80% for Staron) and the modulus of elasticity (by almost 99% for Corian and by 97% for Staron), which should definitely improve the thermoformability of these materials. Among the two tested materials, Staron is a material that is more susceptible to shape modification at elevated temperatures.

Curved Hull Plate Classification for Determining Forming Method using Deep Learning

Curved hull plate forming, the process of forming a flat plate into a curved surface that can fit into the outer shell of a ship’s hull, can be achieved through either cold or thermal forming processes, with the latter processes further subcategorizable into line or triangle heating. The appropriate forming process is determined from the plate shape and surface classification, which must be determined in advance to establish a precise production plan. In this study, an algorithm to extract two-dimensional features of constant size from three-dimensional design information was developed to enable the application of machine and deep learning technologies to hull plates with arbitrary polygonal shapes. Several candidate classifiers were implemented by applying learning algorithms to datasets comprising calculated features and labels corresponding to various hull plate types, with the performance of each classifier evaluated using cross-validation. A classifier applying a convolution neural network as a deep learning technology was found to have the highest prediction accuracy, which exceeded the accuracies obtained in previous hull plate classification studies. The results of this study demonstrate that it is possible to automatically classify hull plates with high accuracy using deep learning technologies and that a perfect level of classification accuracy can be approached by obtaining further plate data.