Evaluation of the applicability of design for six sigma to metal additive manufacturing technology

Cindy Sithole*, Ian Gibson, Sipke Hoekstra

*Corresponding author for this work

Research output: Contribution to journalConference articleAcademicpeer-review

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Abstract

Design for Six Sigma has been applied in traditional and conventional manufacturing technologies to enhance both products and manufacturing processes. It has yielded great results and proven to be a key driver for quality improvement using Six Sigma strategy. Design for Six Sigma uses an organized methodology for designing new products and processes using statistical tools to minimize defects and process deviations. Modern manufacturing technologies such as Additive Manufacturing are complex and require a lot of consideration in terms of selected process parameters that affect part quality. The quality of the resultant parts in additive manufacturing is influenced and affected by the design of the parts to be fabricated, the build process and the chosen process parameters. Quality deviations in additive manufacturing can be observed within a batch of similar parts and from batch to batch production. Due to the complexity of Additive Manufacturing technology and its application, defect reduction remains a key barrier towards further acceptance in highly regulated industries. This paper aims to evaluate the applicability of design for Six Sigma principle to Additive Manufacturing. It seeks to outline how Design for Six Sigma can be applied to Additive Manufacturing to reduce variability and which tools can be used to enhance the quality of the resultant parts. The study critically reviews best practices for Design for Six Sigma to evaluate its applicability to modern manufacturing.
Original languageEnglish
Pages (from-to)798-803
Number of pages6
JournalProcedia CIRP
Volume100
DOIs
Publication statusPublished - 2 Jun 2021
Event31st CIRP Design Conference 2021 - University of Twente, Online Conference, Netherlands
Duration: 19 May 202121 May 2021
Conference number: 31
https://www.sciencedirect.com/science/journal/22128271/100/supp/C

Keywords

  • Design for Six Sigma
  • Additive manufacturing (AM)
  • Quality
  • variability

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