SLM additive manufacture of H13 tool steel with conformal cooling and structural lattices

By Maciej Mazur, Martin Leary, M. Mcmillan, J. Elambasseril, Milan Brandt. 2016

175 citations recorded by the source corpus.

Purpose Additive manufacture (AM) such as selective laser melting (SLM) provides significant geometric design freedom in comparison with traditional manufacturing methods. Such freedom enables the construction of injection moulding tools with conformal cooling channels that optimize heat transfer while incorporating efficient internal lattice structures that can ground loads and provide thermal insulation. Despite the opportunities enabled by AM, there remain a number of design and processing uncertainties associated with the application of SLM to injection mould tool manufacture, in particular from H13/DIN 1.2344 steel as commonly used in injection moulds. This paper aims to address several associated uncertainties. Design/methodology/approach A number of physical and numerical experimental studies are conducted to quantify SLM-manufactured H13 material properties, part manufacturability and part characteristics. Findings Findings are presented which quantify the effect of SLM processing parameters on the density of H13 steel components; the manufacturability of standard and self-supporting conformal cooling channels, as well as structural lattices in H13; the surface roughness of SLM-manufactured cooling channels; the effect of cooling channel layout on the associated stress concentration factor and cooling uniformity; and the structural and thermal insulating properties of a number of structural lattices. Originality/value The contributions of this work with regards to SLM manufacture of H13 of injection mould tooling can be applied in the design of conformal cooling channels and lattice structures for increased thermal performance.

Subfields: Automotive Engineering, Industrial and Manufacturing Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/2ff978ec15614211f0deb23b2241f0cd97a61e11

How researchers see this paper

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In Automotive Engineering

  1. Martin Leary
  2. Milan Brandt
  3. M. Qian
  4. Maciej Mazur
  5. Matthijs Langelaar

In Industrial and Manufacturing Engineering

  1. Matthijs Langelaar

In Mechanical Engineering

  1. Milan Brandt
  2. M. Qian
  3. Martin Leary
  4. H. Li
  5. Maciej Mazur
  6. A. Pramanik
  7. Guy Littlefair

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