Geometric planning and analysis for hybrid re‐configurable molding and machining process

Abstract

PurposeThe objective of this paper is to develop geometric algorithms and planning strategies to enable the development of a novel hybrid manufacturing process, which combines rapidly re‐configurable mold tooling and multi‐axis machining.Design/methodology/approachThe presented hybrid process combines advantages of both reconfigurable molding and machining processes. The mold's re‐configurability is based on the concept of using an array of discrete pins. By positioning the pins, the reconfigurable molding process allows forming the mold cavity directly from the object's 3D design model, without any human intervention. After a segment of the part is molded using the reconfigurable molding process, a multi‐axis machining operation is used to create accurate parts with better surface finish. Geometric algorithms are developed to decompose the design model into segments based on the part's moldability and machinability. The decomposed features are used for planning the reconfigurable molding and the multi‐axis machining operations.FindingsComputer implementation and illustrative examples are also presented in this paper. The results showed that the developed algorithms enable the proposed hybrid re‐configurable molding and multi‐axis machining process. The developed decomposition and planning algorithms are used for planning the reconfigurable molding and the multi‐axis machining operations. Owing to the decomposition strategy, more geometrically complex parts can be fabricated using the developed hybrid process.Originality/valueThis paper presents geometric analysis and planning to enable the development of a novel hybrid manufacturing process, which combines rapidly re‐configurable mold tooling and multi‐axis machining. It is expected that the proposed hybrid manufacturing process can produce highly customized parts with better surface finish, and part accuracy, with shorter build times, and reduced setup and tooling costs.