Knowledge creation and visualisation by using trade-off curves to enable set-based concurrent engineering applications

Inefficiencies that could be avoided during the product development process account for a large percentage of the manufacturing cost. To introduce innovative, high-quality products in a time- and cost-efficient manner, companies need to improve the performance of their product development processes. Set-based concurrent engineering (SBCE) has the capability of addressing this issue if the right knowledge-environment is provided. Trade-off curves (ToCs) are effective tools to provide this environment through knowledge creation and visualisation. However, there are several challenges that designers face during their product development activities such as rework, inaccurate decisions, and failure in design performance, which eventually cause waste. Therefore, the aim of this thesis is to eliminate waste by developing a systematic approach for generating and using ToCs. These then serve as a guide for designers to support their decision-making and achieve an efficient product development performance in an SBCE environment. To achieve this aim, qualitative research methods were employed. Following an extensive literature review, industrial field study and industrial applications, three processes were developed to generate ToCs and validated with five industrial case studies. The process for generating knowledge-based ToCs describes how to create and visualise knowledge that is obtained from historical data and/or experience. This process facilitates the reuse of knowledge about existing products, in order to reduce the requirement for resources (e.g. product development time). The process for generating physics-based ToCs describes an approach to creating knowledge that is obtained from understanding the physics and functionality of the product under development. Thus, the practitioners gain sufficient confidence for identifying a compromise between conflicting design parameters. Finally, the process for using ToCs within the SBCE process model presents a technique to use generated knowledge-based and physics-based ToCs in order to enable key SBCE activities. These activities are (1) Identifying the feasible design area, (2) Developing a design-set, (3) Comparing possible design solutions, (4) Narrowing down the design-set and (5) Achieving the final optimal design solution. For validation, the developed processes were applied in five industrial case studies, and two expert judgements were obtained. Findings showed that ToCs are essential tools in several aspects of new product development, specifically by reducing the lead time through enabling more confident and accurate decisions. Additionally, it was found that through ToCs, the conflicting relationships between the characteristics of the product can be understood and communicated effectively among the designers. This facilitated the decision-making on an optimal design solution in a remarkably short period of time. The design performance of this optimal design increased by nearly 60% in a case study of a surface jet pump. Furthermore, it was found that ToCs have the capability of storing useful data for knowledge creation and reusing the created knowledge for the future projects.