International Journal of Materials and Product Technology (6 papers in press)

Special Issue on: OA The Application of Advanced Materials for Smart and Sustainable Manufacturing

• Open Access

  Adaptability of welding process parameters and defect control in ship cabin based on low-carbon steel-based materials ( Free Full-text Access )

  by Zhifeng Zhao, Shan Zhou 
  Abstract: Due to the mismatch between current welding process parameters for ship compartments and the metallurgical response of low-carbon steel-based materials, defects such as hot cracking and porosity are easily generated, leading to insufficient joint reliability. To address this issue, this paper first uses Gleeble thermal simulation software to calibrate the phase transformation kinetics and critical strain threshold for hot cracking of the material. Second, the aforementioned metallurgical response characteristics are embedded as constraints into a thermo-mechanical coupled finite element model to extract local thermal cycles and strain rate fields. Then, a Gaussian process surrogate model is constructed with the dual objectives of minimising the HTI (hot cracking tendency index) and maximising the equivalent strength. Finally, the optimal combination of process parameters is searched sequentially using the expected improvement criteria in Bayesian optimisation. Experimental verification shows that this method can achieve a median HTI of 0.18 for the weld, a tensile strength of 512 MPa at the weld centre, and effectively suppress inherent defects.
  Keywords: low-carbon steel; ship cabin welding; adaptive parameter optimisation; thermo-metallurgical-mechanical coupling; welding defect control.
  DOI: 10.1504/IJMPT.2026.10079471
   
  

• Open Access

  Intelligent prediction of geometric morphology of missing parts in Clarke ceramic tile based on 3D-GAE image autoencoder and precise completion in 3D printing ( Free Full-text Access )

  by Yibing Yang, Qiang Zhao 
  Abstract: In the restoration of Clark porcelain, in order to solve the problem of insufficient completion accuracy caused by incomplete geometric information and highly complex fragment shapes, this paper adopts an intelligent prediction method based on 3D graphic autoencoder (3D-GAE). This paper first constructs a point cloud structure of Clark porcelain fragments, integrating local adjacency and global symmetry constraints; then, designs a three-layer graph convolutional encoder to extract 128 dimensional latent vectors; and adopts a mask guided training strategy, combined with L2 loss and chamfer distance, to optimise the reconstruction of missing areas; finally, generates a watertight mesh model suitable for FDM printing through Poisson reconstruction, curvature smoothing, and wall thickness detection. The experiment showed that the proposed method achieved a CD of only 0.62 millimetres and an HD of only 2.87 millimetres in areas with high missed detection rates (70%), demonstrating high geometric fidelity.
  Keywords: Clark ceramics; 3D graph autoencoder; 3D-GAE; intelligent prediction; geometric completion; 3D printing; symmetry constraints.
  DOI: 10.1504/IJMPT.2026.10079715
   
  

• Open Access

  Visual communication morphology generation and algorithm control of photosensitive resins in UV curing process ( Free Full-text Access )

  by Boying Qie 
  Abstract: This paper proposes a temporal UV exposure path generation algorithm driven by visual semantic parameterised mapping for photosensitive resin curing. Structural rhythm, spatial hierarchy, and morphological tension are encoded into a continuous semantic parameter field and jointly modelled with UV exposure intensity, density coefficients, and priority factors, then converted into machine-executable exposure trajectories, establishing a direct pathway from visual semantics to physical curing instructions. Experimental results show that the proposed method achieves significantly higher morphological tension intensity (0.87) and rhythmic change rate (0.83) than static exposure strategies (0.42 and 0.35). Curing analysis further verifies effective characterisation of nonlinear resin curing behaviour, demonstrating a controllable and expressive morphology generation framework for digital cultural and visual communication applications.
  Keywords: visual semantic parameterisation; time-series UV exposure path generation; photosensitive resin curing; visual communication; closed-loop coupling mechanism.
  DOI: 10.1504/IJMPT.2026.10079716
   
  

• Open Access

  An algorithm for ranking environmentally friendly material floor plan design schemes integrating life cycle assessment ( Free Full-text Access )

  by Shuqin Zhang, Hongying Yan, Yanchi Fan, Yangyang Ma, Xizhan Tu 
  Abstract: Current evaluation of environmentally friendly material floor plan designs in exhibition design lacks a life cycle perspective considering design contexts such as service life and disassembly frequency, and subjective design preferences are difficult to effectively integrate with objective environmental data. To address this, this paper constructs a ranking algorithm framework for environmentally friendly material floor plan design schemes that integrates life cycle assessment (LCA) within the exhibition design context. This framework first constructs an LCA model covering the entire process of raw material acquisition, manufacturing, transportation, installation and dismantling, use and maintenance, and decommissioning, using each square metre/single exhibition period as a functional unit. The model explicitly incorporates assumptions about material lifespan and dismantling frequency to address the issue of traditional evaluations neglecting differences in usage stages. This method can provide a quantifiable, interpretable, and context- and uncertainty-tested decision support tool for selecting environmentally friendly materials in exhibition design.
  Keywords: environmentally friendly materials; scheme ranking; life cycle assessment; LCA; relative proximity; exhibition design; multi-criteria decision making; service life.
  DOI: 10.1504/IJMPT.2026.10079717
   
  

• Open Access

  Optimisation design of clothing 3D printing materials by combining machine learning and computer graphics ( Free Full-text Access )

  by Pei Wen, Yingqi Fu 
  Abstract: This paper addresses the challenges of poor forming accuracy, low design efficiency, and comfort in 3D clothing printing. It proposes an intelligent optimisation framework integrating computer graphics and machine learning, shifting from experience-driven to closed-loop optimisation. Implicit surface modelling and finite element simulation are used to extract geometric and physical features, while a deep neural network surrogate model enables rapid prediction of forming performance. The multi-objective Bayesian optimisation (MOBO) algorithm optimises lattice parameters and printing paths for comfort and material efficiency. A parametric-machine learning collaborative design framework supports large-scale parameter optimisation. Experimental results show high geometric forming accuracy, with average root mean square error (RMSE) values of 0.081 mm (shoulder), 0.092 mm (armhole), 0.073 mm (waistline), and 0.087 mm (hem). Average printing time is reduced to 85.3 minutes, and average material consumption is only 100.4 grams. The method successfully achieves multi-objective synergistic optimisation of forming quality, mechanical properties and wearing comfort.
  Keywords: machine learning; computer graphics; 3D printing of garments; implicit surface modelling; multi-objective Bayesian optimisation; MOBO; material forming accuracy.
  DOI: 10.1504/IJMPT.2026.10079855
   
  

• Open Access

  Zonal material design and performance evaluation of cooling protective clothing based on human body thermal moisture distribution map ( Free Full-text Access )

  by Xiaoxi Zhao, Feifei Song 
  Abstract: In the design of protective clothing for high-temperature operations, this paper addresses the issues of insufficient overall thermal comfort and redundant material functions caused by differences in local thermal and moisture loads on the human body. A zonal material design method based on measured thermal and moisture distribution maps is adopted. The core of this method is to map the measured human body thermal and moisture load distribution into a spatial demand map, and accordingly divide it into high, medium and low functional zones. For each zone, thermal conductivity and moisture permeability parameters are precisely matched to construct a differentiated material library. Zonal cutting is performed based on a three-dimensional human body model, and a seamless hot-pressing process is used to achieve multi-material integration. Furthermore, gradient transition rules between materials and a double-layer composite structure are defined to ensure interface thermal and moisture compatibility and dynamic wearing stability, forming a closed-loop design system from physiological data to product structure.
  Keywords: high-temperature work; cooling protective clothing; thermal and humidity distribution map; zoned materials; 3D human body model.
  DOI: 10.1504/IJMPT.2026.10079856