Design Methods for Customized Products when Introducing Additive and Cyclic Manufacturing
Two enablers for efficient product design of customized products are the product architecture and the engineering process. Companies could benefit from the development and standardization of engineering processes that commonly not are formalized at a detailing level that supports efficient customization. The introduction of additive manufacturing technologies may further increase the customization options and can aid the introduction of cyclic manufacture. Additive manufacturing will have a significant impact on product development but processing time is long, secondary processing is required and material properties are not always sufficient. Many components will be manufactured by processes requiring customized tools, e.g. high pressure die casting (HPDC) and sheet metal forming, even in the future. Shorter development and manufacturing lead-times of these tools are required to support higher pace in the introduction of new products on the market. There are also opportunities of increased customization options, stretching the product performance and tailoring properties of tooling by additive manufacturing. Repair, re-use and remanufacture of tooling in a cyclic manufacturing business model can also be supported by additive manufacturing. However, there is a lack of product platform strategies and efficient design support of tooling design when introducing additive and cyclic manufacturing.
The results of this project will add valuable knowledge to the area of platform development and means for efficient customization within an engineer-to-order business model. The overall expected effect for the industrial partners is increased customization options towards customers including shorten engineering and production preparation lead times, optimized quotation and pricing, and efficient management of product and process knowledge.
Project partners: School of Engineering, Intermekano Tools, Maxiom, PLM Group, Comptech, 3D MetPrint
Project time: 2017-2020
Funded by: The Knowledge Foundation and the project partners
Total budget: 7.68 million SEK