IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i14p5998-d1434681.html
   My bibliography  Save this article

Lean-and-Green Fractional Factorial Screening of 3D-Printed ABS Mechanical Properties Using a Gibbs Sampler and a Neutrosophic Profiler

Author

Listed:
  • Tryfonas Pantas

    (Mechanical Engineering Department, The University of West Attica, 12241 Egaleo, Greece
    Advanced Industrial and Manufacturing Systems Graduate Program, Kingston University, Kingston upon Thames KT1 2EE, UK)

  • George Besseris

    (Mechanical Engineering Department, The University of West Attica, 12241 Egaleo, Greece
    Advanced Industrial and Manufacturing Systems Graduate Program, Kingston University, Kingston upon Thames KT1 2EE, UK)

Abstract

The use of acrylonitrile butadiene styrene (ABS) in additive manufacturing applications constitutes an elucidating example of a promising match of a sustainable material to a sustainable production process. Lean-and-green datacentric-based techniques may enhance the sustainability of product-making and process-improvement efforts. The mechanical properties—the yield strength and the ultimate compression strength—of 3D-printed ABS product specimens are profiled by considering as many as eleven controlling factors at the process/product design stage. A fractional-factorial trial planner is used to sustainably suppress by three orders of magnitude the experimental needs for materials, machine time, and work hours. A Gibbs sampler and a neutrosophic profiler are employed to treat the complex production process by taking into account potential data uncertainty complications due to multiple distributions and indeterminacy issues due to inconsistencies owing to mechanical testing conditions. The small-data multifactorial screening outcomes appeared to steadily converge to three factors (the layer height, the infill pattern angle, and the outline overlap) with a couple of extra factors (the number of top/bottom layers and the infill density) to supplement the linear modeling effort and provide adequate predictions for maximizing the responses of the two examined mechanical properties. The performance of the optimal 3D-printed ABS specimens exhibited sustainably acceptable discrepancies, which were estimated at 3.5% for the confirmed mean yield strength of 51.70 MPa and at 5.5% for the confirmed mean ultimate compression strength of 53.58 MPa. The verified predictors that were optimally determined from this study were (1) the layer thickness—set at 0.1 mm; (2) the infill angle—set at 0°; (3) the outline overlap—set at 80%; (4) the number of top/bottom layers—set at 5; and (5) the infill density—set at 100%. The multifactorial datacentric approach composed of a fractional-factorial trial planner, a Gibbs sampler, and a neutrosophic profiler may be further tested on more intricate materials and composites while introducing additional product/process characteristics.

Suggested Citation

  • Tryfonas Pantas & George Besseris, 2024. "Lean-and-Green Fractional Factorial Screening of 3D-Printed ABS Mechanical Properties Using a Gibbs Sampler and a Neutrosophic Profiler," Sustainability, MDPI, vol. 16(14), pages 1-29, July.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:14:p:5998-:d:1434681
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/14/5998/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/14/5998/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ifeoluwa Elemure & Hom Nath Dhakal & Michel Leseure & Jovana Radulovic, 2023. "Integration of Lean Green and Sustainability in Manufacturing: A Review on Current State and Future Perspectives," Sustainability, MDPI, vol. 15(13), pages 1-25, June.
    2. Jasgurpreet Singh Chohan & Raman Kumar & Aniket Yadav & Piyush Chauhan & Sandeep Singh & Shubham Sharma & Changhe Li & Shashi Prakash Dwivedi & S. Rajkumar & Jiafu Su, 2022. "Optimization of FDM Printing Process Parameters on Surface Finish, Thickness, and Outer Dimension with ABS Polymer Specimens Using Taguchi Orthogonal Array and Genetic Algorithms," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-13, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Michel Leseure & David Bennett, 2024. "Adopting the Materiality Principle in Sustainable Operations Management," Sustainability, MDPI, vol. 16(15), pages 1-18, July.
    2. Viktoria Mannheim & Judit Lovasné Avató, 2023. "Life-Cycle Assessments of Meat-Free and Meat-Containing Diets by Integrating Sustainability and Lean: Meat-Free Dishes Are Sustainable," Sustainability, MDPI, vol. 15(15), pages 1-24, August.
    3. M. Florentina Abreu & Anabela C. Alves & Francisco Moreira, 2024. "Business Overall Performance and Sustainability Effectiveness: An Indicator to Measure Companies’ Lean–Green Compliance," Sustainability, MDPI, vol. 16(11), pages 1-27, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:14:p:5998-:d:1434681. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.