International Journal of Manufacturing Research (6 papers in press)

Regular Issues

• Simulation and Analysis of Pore Evolution in 316L Stainless Steel Formed by PBF.LB with Laser Remelting Post-treatment  
  by Zhiwen Li, Yonghong Zhu, Xin Chen, Yanping Miao, Jieyong Deng, Wei Wei 
  Abstract: In the process of laser based powder bed fusion (PBF.LB), pore defects can seriously affect the quality of formed parts. In this paper, the effectiveness of laser remelting to eliminate the pore defects of PBF.LB formed parts were analyzed experimentally. It was found that the porosity of PBF.LB formed parts decreased from 2.15% to 0.65% after laser remelting. Based on the level set method, a numerical simulation of a multi-physics field finite element model was established to conduct a detailed analysis of the mechanism of pore evolution during laser remelting. It is found that the pore evolution is significantly affected by the Marangoni effect at the micro scale. Affected by the Marangoni effect, the porosity does not rise vertically during the evolution process, but moves to the tail area of the molten pool during the rising process. The essence of pore evolution is fluid mass transfer.
  Keywords: Additive manufacturing;PBF.LB;Pore evolution;316L stainless steel?Laser remelting?Marangoni effect.
  DOI: 10.1504/IJMR.2025.10074730
   
  
• AI tools for advancement of manufacturing sector: a systematic review, bibliometric analysis, thematic synthesis and technological framework development  
  by Kunal Sharma, Vikrant Sharma, Mukheshwar Yadav 
  Abstract: The burgeoning field of artificial intelligence (AI) has had a profound impact on a wide range of industrial sectors. This transformative paradigm shift aims to fundamentally change traditional manufacturing methodologies. The primary goal of this study is to provide a comprehensive overview of the current state and future path of AI applications in manufacturing settings. A bibliometric analysis is carried out to determine the evolutionary path of AI-centric research in the manufacturing domain. Subsequently, a thematic synthesis is performed to categorise and combine the findings, revealing overarching themes. Furthermore, this study adds significantly to the field by providing a technological framework for the integration and deployment of AI tools aimed at augmenting manufacturing processes. Research into AI in the manufacturing sector has increased dramatically since 2019, concentrating mainly on machine learning, deep learning and computer vision. The framework outlines major barriers, factors that help and practical uses of AI, giving industry partners valuable ideas. The combined insights from this study provide a solid foundation for informed decision-making, strategic planning, and the development of future innovations at the intersection of AI and manufacturing. [Submitted 11 April 2024; Accepted 1 July 2025]
  Keywords: artificial intelligence; AI; AI tools; manufacturing sector; bibliometric analysis; thematic analysis; framework development.
  DOI: 10.1504/IJMR.2025.10072918
   
  
• New method for estimating additive blooming on the surface of vulcanised rubbers  
  by José De Jesús Cabrera-Castro, Roberto Zitzumbo-Guzmán, María Blanca Becerra-Rodríguez, Anayansi Estrada-Monje 
  Abstract: The blooming phenomenon in vulcanised rubber samples characterised by the migration of additives to the surface, as whitish stains was evaluated using two methods: a traditional gravimetric method and a newly developed Euclidean distance method. The latter integrates artificial vision, image processing, and a mathematical model. While statistical analysis showed no significant difference between both methods, the Euclidean distance method offers notable advantages. It enables temporal monitoring of surface changes on the same sample by comparing images taken at various time intervals. Moreover, it distinguishes between initial surface defects and components that emerge from vulcanisation over time. R² values confirmed that a Fick-type diffusion model (linear with t^1/2) suitably describes the blooming process. Both Spearman (ρ = 1.0, p = 0.000) and Pearson (r > 0.91) correlations were strong, validating the method has ability to accurately capture the temporal dynamics of blooming. [Submitted 14 October 2024; Accepted 15 July 2025]
  Keywords: t-test statistics; blooming; vulcanised rubber; image processing; Euclidean distance; ED; aesthetic quality of rubber; mechanical properties.
  DOI: 10.1504/IJMR.2025.10072983
   
  
• A meta-heuristic-based framework for sustainable P-hub network design of perishable items under fuzzy time uncertainty  
  by Saeed Zameni, Seyed Esmaeil Najafi, Seyed Mohammad Haji Molana, Seyed Mojtaba Sajadi 
  Abstract: In this paper, a novel mathematical model is presented for designing a sustainable hub network for perishable commodity transportation, taking into account social responsibility, environmental impact, and economic viability. As many real world problems have non-deterministic parameters, the time parameters are considered fuzzy numbers in the model. To validate the model, the model is solved on a small scale using GAMS software after linearisation. However, due to the non-deterministic polynomial time nature of the problem, an efficient meta-heuristic algorithm is proposed using MATLAB software. The algorithm has been validated on small and medium scale instances using the AP and CAB datasets. The results show that the proposed NSGA-II algorithm achieves an average solution gap of 0.017% while significantly reducing computational time compared to exact methods. The proposed model and algorithm can assist decision makers in designing sustainable and efficient supply chain networks for perishable products. [Submitted 30 September 2024; Accepted 1 July 2025]
  Keywords: p-hub location; hub location problem; sustainable supply chains; food logistics; fuzzy optimisation; multi-objective optimisation; nonlinear programming; perishable goods.
  DOI: 10.1504/IJMR.2025.10073024
   
  
• Microstructural and mechanical characteristics of 308L stainless steel walls manufactured by wire arc additive manufacturing with interpass time variation  
  by Cássio Emanuel Ribeiro Martins, Ariel Rodriguez Arias, Hellen Cristine Prata De Oliveira, Fagner Guilherme Ferreira Coelho 
  Abstract: The wire arc additive manufacturing (WAAM), uses conventional welding process, the parts experience a build-up of heat, which influences their microstructural and macrostructural properties. This article analyses the influence of the time interval between passes on the properties of components produced using 308L stainless steel. Two walls were built with natural convection cooling conditions, with time intervals from 60 to 180 seconds. The tensile tests showed similar results, however, there was a difference in the hardness of the intermediate region between the two-time conditions analysed. Consequently, the wall that underwent a cooling interval of 180 seconds showed higher hardness values. The results suggest that cooling by the time between the deposition could be a viable approach to improving the properties of 308L stainless steel components manufactured using the WAAM process. [Submitted 1 August 2024; Accepted 17 April 2025]
  Keywords: additive manufacturing; 308 L stainless steel; microstructure; hardness; tensile.
  DOI: 10.1504/IJMR.2025.10074366
   
  
• Optimising the design and development of bio-inspired soft robotic grippers: a Taguchi-based approach enhanced by TOPSIS multi-objective technique  
  by Prabhu Sethuramalingam, Arvindkumar Ranganathan, M. Uma, M.M. Reddy 
  Abstract: This study presents the design and optimisation of a bellow-type soft robotic gripper inspired by a bird's claw, featuring distinct flexible finger and rigid claw sections for enhanced gripping. Traditionally fabricated using elastomers via casting, recent advances in additive manufacturing enable the use of flexible thermoplastic urethane filaments. Achieving a balance between flexibility and output force poses a key challenge, addressed here using finite element analysis combined with design of experiment (DOE) techniques, including Taguchi analysis, AHP, and TOPSIS. Regression analysis explores input-output relationships, while ANOVA validates result variations. The multidisciplinary approach supports systematic optimisation for applications in flexible robotics and automation. TOPSIS and Taguchi methods identified optimal finger designs with bending angles of 143° and 158° and stresses of 0.97444 MPa and 1.1119 MPa. For the claw section, optimal angles of 124° and 119° with stresses of 3.1757 MPa and 3.1670 MPa were achieved. [Submitted 2 March 2024; Accepted 27 September 2025]
  Keywords: finite element analysis; FEA; Taguchi analysis; regression analysis; analysis of variance; ANOVA; analytical hierarchy process; AHP; TOPSIS.
  DOI: 10.1504/IJMR.2025.10074483