Abstract
The automotive industry supply chain has been subjected to new and global competition pressures, which are pushing for collaborative, interdependent and strategic product development partnerships among its agents, with the objective of improving the processes and responsiveness to product engineering requirements. Thus, some research has been dedicated to the analysis and translation of these user needs into product engineering requirements in order to provide methods to increase the conversion responsiveness. However, there is an additional conversion phase which is the definition of the product architecture to meet those requirements. So, the objective of this paper is to present a method and case study where button parameters are related to its architecture elements by applying Morphological Analysis and Artificial Neural Networks on the data collected from measurements made on in – car radio interfaces. The precision power of the models was demonstrated, meaning that it is possible to have an expected haptic behavior for the button, predicted in the form of a set of relevant haptic characteristics, based on the button architecture, and so, facilitating the initial detail design stages of in-car radio interfaces and potentially increasing its responsiveness to the client needs.
•In – car button haptic characteristics are related to button internal architecture.•The relationships between button morphological elementary parts and their haptic characteristics is made with neural network models.•The neural models have a high prediction power, meaning an expected haptic behavior from button morphological elements.•The models performance points to the value of the approach to support the requirements negotiation process for interface detail design.
Systematic method to design automotive kinematic systems with ergonomic issues in mind. Application on an empirical case study of in – car radio push buttons.