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

The increased international competition forces companies to sustain and improve market share through the production of a high quality product in a cost effective manner and in a shorter time. Set‑based concurrent engineering (SBCE), which is a core element of lean product development approach, has got the potential to decrease time‑to‑market as well as enhance product innovation to be produced in good quality and cost effective manner. A knowledge‑based environment is one of the important requ irements for a successful SBCE implementation. One way to provide this environment is the use of trade‑off curves (ToC). ToC is a tool to create and visualise knowledge in the way to understand the relationships between various conflicting design parame ters to each other. This paper presents an overview of different types of ToCs and the role of knowledge‑based ToCs in SBCE by employing an extensive literature review and industrial field study. It then proposes a process of generating and using knowledg e‑based ToCs in order to create and visualise knowledge to enable the following key SBCE activities: (1) Identify the feasible design space, (2) Generate set of conceptual design solutions, (3) Compare design solutions, (4) Narrow down the design sets, (5) Achieve final optimal design solution. Finally a hypothetical example of a car seat structure is presented in order to provide a better understanding of using ToCs. This example shows that ToCs are effective tools to be used as a knowledge sou rce at the early stages of product development process

Physics-based trade-off curves to develop a control access product in set-based concurrent engineering environment

Purpose This paper aims to present a process to generate physics-based trade-off curves (ToCs) to facilitate lean product development processes by enabling two key activities of set-based concurrent engineering (SBCE) process model that are comparing alternative design solutions and narrowing down the design set. The developed process of generating physics-based ToCs has been demonstrated via an industrial case study which is a research project. Design/methodology/approach The adapted research approach for this paper consists of three phases: a review of the related literature, developing the process of generating physics-based ToCs in the concept of lean product development, implementing the developed process in an industrial case study for validation through the SBCE process model. Findings Findings of this application showed that physics-based ToC is an effective tool to enable SBCE activities, as well as to save time and provide the required knowledge environment for the designers to support their decision-making. Practical implications Authors expect that this paper will guide companies, which are implementing SBCE processes throughout their lean product development journey. Physics-based ToCs will facilitate accurate decision-making in comparing and narrowing down the design-set through the provision of the right knowledge environment. Originality/value SBCE is a useful approach to develop a new product. It is essential to provide the right knowledge environment in a quick and visual manner which has been addressed by demonstrating physics knowledge in ToCs. Therefore, a systematic process has been developed and presented in this paper. The research found that physics-based ToCs could help to identify different physics characteristics of the product in the form of design parameters and visualise in a single graph for all stakeholders to understand without a need for an extensive engineering background and for designers to make a decision faster

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