Rapid hard tooling process selection using QFD‐AHP methodology

Abstract

PurposeTo provide a systematic framework for mold designers, that can be used for rapid tooling (RT) process selection and prioritization of process parameters.Design/methodology/approachThis paper presents a QFD‐AHP methodology which has three phases. The first phase involves prioritizing the tooling requirements (driven by customer preferences) against a set of die/mold development attributes (such as product material, geometry, and die material and production order) through pair‐wise comparison using analytical hierarchal process (AHP). These priority ratings are used for selecting the most appropriate tooling process using quality function deployment (QFD) in the second phase. Finally, QFD is used again for identifying critical process parameters (such as layer thickness, scan pitch and laser power) for the selected RT process.FindingsThe QFD‐AHP methodology has been illustrated with industrial examples on RT for molded parts. The molds were fabricated using direct metal laser sintering and spray metal tooling processes, for example, 1 and 2, respectively, to prove that the methodology can be easily implemented in tool rooms. The issues noted in these experimental studies are also discussed for the benefit of researchers.Research limitations/implicationsThe capabilities of the RT processes presented in the paper reflect the experience of the research team in RT development. The QFD‐AHP methodology will give progressively better results with a growing body of RT process knowledge.Practical implicationsThis investigation is a key step towards the goal of developing a comprehensive system for RT process selection and manufacturability evaluation. The mold designer can use this QFD‐AHP process selection methodology, prior to detailed manufacturability analysis, to better realize the benefits of RT technologies.Originality/valueThe proposed QFD‐AHP methodology is a new approach for the tooling process selection domain, and has not been reported earlier; this can be easily used for similar applications for any manufacturing domain.