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    The American Society of Mechanical Engineers

    Special Issue on Additive Manufacturing Qualification

    Journal of Computing and Information Science in Engineering
    Journal of Computing and Information Science in Engineering icon
    While additive manufacturing (AM) has transformed many industries, several critical hurdles such as quality remain for widespread industrial adoption. Material inconsistency and process variability result in variability in mechanical properties. AM qualification is essential for industries with strict safety requirements, including aerospace, defense, and medical devices, to ensure that additively manufactured parts can be consistently produced and reliably used in critical applications. AM qualification verifies the raw materials, the process, and the final part. However, conventional AM qualification techniques rely heavily on non-destructive and destructive testing which are costly and time consuming. This special issue aims to collect contributions that address AM qualification by combining computational and experimental methods.

    Topic Areas

    THE SCOPE OF THIS ISSUE INCLUDES BUT IS NOT LIMITED TO:

    • In-situ monitoring and digital twins for defect detection in AM
    • Computational methods that predict and control grain size and phase composition
    • Physics-informed machine learning methods for understanding process-structure-property relationships
    • Physics-based or data-driven or hybrid predictive modeling of the mechanical behavior of additively manufactured materials
    • Physics-based or data-driven or hybrid predictive modeling of additive manufacturing processes
    • Computational design methods that reduce manufacturing-induced defects
    • Process control algorithms that prevent defects or reduce part-to-part variations
    • Uncertainty quantification for AM qualification

    Special Issue Publication Dates


    Paper submission deadline: December 31, 2026
    Initial review completed: February 28, 2027
    Publication date: October 2026

    Submission Instructions

    Papers should be submitted electronically to the journal through the ASME Journal Tool. If you already have an account, log in as an author and select Submit Paper. If you do not have an account, you can create one here. 

    Once at the Paper Submittal page, select the Journal of Computing and Information Science in Engineering, and then select the Special Issue on Additive Manufacturing Qualification.

    Papers received after the deadline or papers not selected for the Special Issue may be accepted for publication in a regular issue.

    Guest Editors

    Dr. Dazhong Wu, University of Central Florida, USA (dazhong.wu@ucf.edu)

    Dr. David Rosen, ASTAR, Singapore (David_William_Rosen@a-star.edu.sg)

    Dr. Wentao Yan, National University of Singapore, Singapore (mpeyanw@nus.edu.sg)

    Dr. Shanmugam Kumar, University of Glasgow, UK (Msv.Kumar@glasgow.ac.uk)

    Dr. Yan Lu, National Institute of Standards and Technology, USA (yan.lu@nist.gov)