Functional product development is dedicated to, primarily, concept development, where the development of hardware components and services meet in a global, distributed business oriented process. The focus is set on knowledge based, information driven and simulation support in a life cycle perspective to enable the design of a total offer. This focus, in combination with the industries’ need to reduce cost by shorten product development lead time, results in a need for methods and tools for managing requirements from the whole products life cycle, including aftermarket parameters, for instance maintenance, recycling, operation etc. This paper aims to describe knowledge based methods and tools and how they can support functional product development. Knowledge Based Engineering (KBE) (Stokes, 2001) is an engineering method that enables creation of and changes to the product definition, tightly linked with the geometry model. Knowledge is captured trough various sources such as design specifications, standard documentation, optimization routines etc. The methodology is used in both small feature applications as well as larger models where sub- applications can be included to form a more complex generative model. Sandberg, et al.(2005) describes an application to design flanges that automatically executes rules based on the standard specifications where parameters are adjusting the design for standard sizes to minimize the number of different standard components used in the design, this in order to satisfy customer aftermarket requirement for serviceability. Boart, et al. (2006) describes a method to automatically update a derived context model including the mesh that is based on engineering experience from earlier analysis on a component level. This enables CFD-, Weld-, and life cycle-, analysis and simulation for decision support in a functional product perspective. Knowledge based applications combined and implemented as sub-applications form a more complex generic model, capable of topological changes and inheritance of “intelligence” from sub applications. In the Aero engine business the aftermarket can have time spans of up to 30 years, thus aftermarket parameters such as maintenance, recycling, operation, education, services etc. and the knowledge from their design processes need to be available in the early product development stage so that the designer can take aftermarket issues into account when designing the product or total offer. When feeding back downstream knowledge there is a bit of uncertainty inherent; how well known is it? Are all parameters known? Knowing where there is uncertainty and the magnitude of the uncertainty enables designers to take corrective action regarding the uncertainty and thus reduce risk. This is where the measurement of maturity can be used as a way to assess this knowledge. Maturity is about knowing with which certainty a parameter has a specific value. KBE, the methodology and applications support Functional Product Development in the sense that it brings awareness to the designer of downstream processes and also enables simulation and evaluation of design decision impact on the product life-cycle. Finding important aftermarket parameters that affect the total offer and incorporating them into the early stages of the design needs to be investigated to ensure maturity and consistency with the design.
Functional Product Development, Knowledge Based Engineering, Design Support, Maturity
Nergård, H., Andersson, P. & Johansson, C. (2007). Concept automation and decision support in a functional product development perspective. Abstract presented at National Workshop on Functional Products. Luleå, Sweden.