Abstract
Nowadays, academics and industrial practitioners widely consider additive manufacturing systems to enhance overall production and operational effectiveness and efficiency, owing to the concepts of Industry 4.0 and 5.0. This paper proposes a structural equation model to evaluate the impact of customisation experience and perceived value within a data-driven additive manufacturing system. To deepen the understanding of customer-perceived value and its connection to additive manufacturing, this study defines four new sources of perceived value: reliability, performance, aesthetics, and features. All of these new values are based on utilitarian value, and four of them exhibit statistical significance in relation to utilitarian value. In order to apply these new values to additive manufacturing, it is necessary to conduct mechanical testing and studies to identify the ideal parameter set for 3D printing that aligns with customer-perceived value regarding these new values.
Acknowledgement
This work was supported by the Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong (RK9D), Aston University, United Kingdom. Our gratitude is also extended to the Research Committee and the Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, the Laboratory for Artificial Intelligence in Design, Hong Kong SAR, Hong Kong (Project Code: RP2-1).
Disclosure statement
No potential conflict of interest was reported by the author(s).