Improving Systems by Combining Axiomatic Design, Quality Control Tools and Designed Experiments

摘要

This paper presents an approach for solving design problems in existing designs. A design analysis with Axiomatic Design, called Design Object Analysis, describes a product or a system in terms of Customer Needs (CNs), Functional Requirements (FRs), Design Parameters (DPs) and Process Variables (PVs), as well as their associated Design Matrices (DMs). In this paper, the design analysis is combined with a thorough investigation of possible problems within the design, utilizing the seven quality tools, noise factor analysis, and designed experiments to form an approach for quality improvements and problem solving. The Design Object Analysis helps secure valid input-factors to the designed experiments, and the designed experiments correct or improve the assumptions made in the Design Object Analysis. Thus, a combination of product modeling by Axiomatic Design and designed experiments overcomes shortcomings of the two methods. The benefits of performing a Design Object Analysis, as compared to other methods, become clear when it comes to evaluating the results from the designed experiment, and preventing the problem. Once the critical parameters are confirmed, and the design matrices are updated, suggested design improvements can then be checked against the design matrices, and the system effect of a design-change-order can be estimated. The approach described in this paper was successfully applied and verified in a case study at a large automotive company.