The Taguchi method is widely employed in several fields to manage and improve processes. It is interesting that it could be used during product development, considering it as the basic element to quantify the uncertainty of the device performance prediction. During product design, when many design aspects still must be understood by the design team, it is necessary to apply interactive approaches in order to simulate the behaviour of the device, employing CAx tools. Basically it is important to identify the most suitable “loss function” that can be associated with the characteristic function. In order to plane the investigation, the device under development ought to be described in term of the Design Matrix of Axiomatic Design, allowing the designer to characterize the relationship among the functional requirements and the corresponding design parameters. The nature of this relationship, generally not known a priori, can be revealed by the employment of the Taguchi method, once a suitable Objective Function has been chosen and the noise factors are identified. Analysing the performance of a device in a simulation of its behaviour in several operational conditions allows designers to discover whether there are correspondences or contradictions among design parameters. This can be synthetically said a robust design process. In order to enhance these aspects a design of experiment must be planned. The weak point of the procedure consists in the correct choice of the function that characterizes the device behaviour. Considering the wide academic debate on this point, the paper proposes a unique Noise Reduction function to be used in conjunction with all types of “loss function”. The Design Matrix can be checked and its nature can suggest the validity of the product under development and discover contradiction. The paper discusses an interactive procedure able to integrate the Taguchi method and the axiomatic approach.

An interactive robust design approach in product development

Rizzuti, Sergio
;
de Napoli, Luigi
2018-01-01

Abstract

The Taguchi method is widely employed in several fields to manage and improve processes. It is interesting that it could be used during product development, considering it as the basic element to quantify the uncertainty of the device performance prediction. During product design, when many design aspects still must be understood by the design team, it is necessary to apply interactive approaches in order to simulate the behaviour of the device, employing CAx tools. Basically it is important to identify the most suitable “loss function” that can be associated with the characteristic function. In order to plane the investigation, the device under development ought to be described in term of the Design Matrix of Axiomatic Design, allowing the designer to characterize the relationship among the functional requirements and the corresponding design parameters. The nature of this relationship, generally not known a priori, can be revealed by the employment of the Taguchi method, once a suitable Objective Function has been chosen and the noise factors are identified. Analysing the performance of a device in a simulation of its behaviour in several operational conditions allows designers to discover whether there are correspondences or contradictions among design parameters. This can be synthetically said a robust design process. In order to enhance these aspects a design of experiment must be planned. The weak point of the procedure consists in the correct choice of the function that characterizes the device behaviour. Considering the wide academic debate on this point, the paper proposes a unique Noise Reduction function to be used in conjunction with all types of “loss function”. The Design Matrix can be checked and its nature can suggest the validity of the product under development and discover contradiction. The paper discusses an interactive procedure able to integrate the Taguchi method and the axiomatic approach.
2018
Axiomatic design; Design matrix; Noise reduction; Robust design; Taguchi method; Modeling and Simulation; Industrial and Manufacturing Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/268510
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