Estimation and Improvement of the Achievable Tolerance Interval in Material Extrusion Additive Manufacturing through a Multi-State Machine Performance Perspective

• Published in: Applied sciences 2021-06, Vol.11 (12), p.5325
• Main Authors: Beltrán, Natalia, Álvarez, Braulio J., Blanco, David, Noriega, Álvaro, Fernández, Pedro
• Format: Article
• Language: English
• Subjects: Additive manufacturing; Case studies; Design; design for additive manufacturing; Design for manufacturability; Design optimization; Extrusion; machine performance; Manufacturing; Mass production; material extrusion; Process parameters; Production planning; quality assurance; State machines
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app11125325

Dimensional quality is still a major concern in additive manufacturing (AM) processes and its improvement is key to closing the gap between prototype manufacturing and industrialized production. Mass production requires the full working space of the machine to be used, although this arrangement could lead to location-related differences in part quality. The present work proposes the application of a multi-state machine performance perspective to reduce the achievable tolerance intervals of features of linear size in material extrusion (MEX) processes. Considering aspecific dimensional parameter, the dispersion and location of the distribution of measured values between different states are analyzed to determine whether the production should be treated as single-state or multi-state. A design for additive manufacturing strategy then applies global or local size compensations to modify the 3D design file and reduce deviations between manufactured values and theoretical values. The variation in the achievable tolerance range before and after the optimization of design is evaluated by establishing a target machine performance index. This strategy has been applied to an external MEX-manufactured cylindrical surface in a case study. The results show that the multi-state perspective provides a better understanding of the sources of quality variability and allows for a significant reduction in the achievable tolerance interval. The proposed strategy could help to accelerate the industrial adoption of AM process by reducing differences in quality with respect to conventional processes.