A3 Refereed book chapter or chapter in a compilation book
Effect of Computational Generative Product Design Optimization on Part Mass, Manufacturing Time and Costs: Case of Laser-Based Powder Bed Fusion
Authors: Nyamekye, Patricia; Lakshmanan, Rohit; Piili, Heidi
Editors: Tuovinen, Tero; Periaux, Jacques; Knoerzer, Dietrich; Bugeda, Gabriel; Pons-Prats, Jordi
Publisher: Springer
Publication year: 2024
Book title : Advanced Computational Methods and Design for Greener Aviation
Journal name in source: Computational Methods in Applied Sciences
Series title: Computational Methods in Applied Sciences
Number in series: 59
Volume: 59
First page : 257
Last page: 273
ISBN: 978-3-031-61108-7
eISBN: 978-3-031-61109-4
ISSN: 1871-3033
eISSN: 2543-0203
DOI: https://doi.org/10.1007/978-3-031-61109-4_17
Web address : https://doi.org/10.1007/978-3-031-61109-4_17
Light weight and high-performance metals are usually desired for transport applications for economic and environmental benefits, especially in automotive and aerospace. Conventional manufacturing (CM) methods used in manufacturing motor vehicle and aircraft components often lead to compromises, for example by adding non-function excess materials for ease of manufacturing or incur extra cost with the removal of enormous start up preforms. The manufacturability limitations of CM and supporting digital software previously constrained product design and manufacturing flexibilites to allowable geometrical features, tools and fixtures. Additive manufacturing (AM) is a manufacturing method allowing unprecedented design and manufacturing freedom and flexibilities. The evolvement AM from being a mere consumer goods, prototyping, and tooling manufacturing method to include functional end-use parts help optimize performance and economic value. AM allows to manufacture lightweight and intricate geometrical designs which are otherwise impossible via CM methods. AM uses a layerwise approach to manufacture components using digitally defined data. AM is often criticized, especially the metal based, for the need of supports, post-processing, high investment cost, high energy consumption, low build rate, and poor surface quality. Hollows and overhangs designs require sacrificial supports that are removed prior to or during the post-processing phase. Technological advances in AM such as generative design and process simulations have helped users reduce or omit some of the limitations to adoption. Digital tools allow a swift optimizing of the process parameters and manufacturing including part placement, build orientation and support structures prior physical build. Simulation-assisted product design for AM parts allow generative optimized design iterations in consideration of predefined AM parameters and rules and end-application requirements. This study provides an overview and exemplary application of digital tools in product design (simulation and optimization). A case study demonstrating product designs highlights the potential benefits of comparable optimized plate designs to mass, time and cost savings using laser assisted powder bed fusion (L-PBF), one of the subcategory of AM. The aim of this study was to highlight a strategic adoption of L-PBF via offered potentials of intricacy, lightweight and hierarchical gradient design via simulation assisted product design for AM parts. This study proposes a strategic adoption plan which potentially maximizes resource efficiency via digital tools in AM. The results provide insight into the potential benefits of L-PBF and demonstrate the potential of such approach to enhance the confidence in adopting PBF for metals.
