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Probabilistic Model for Online 3D Printing Service Evaluation

[+] Author Affiliations
Jin Cui, Lin Zhang, Lei Ren

Beihang University, Beijing, China

Paper No. MSEC2017-2747, pp. V003T04A032; 6 pages
  • ASME 2017 12th International Manufacturing Science and Engineering Conference collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing
  • Volume 3: Manufacturing Equipment and Systems
  • Los Angeles, California, USA, June 4–8, 2017
  • Conference Sponsors: Manufacturing Engineering Division
  • ISBN: 978-0-7918-5074-9
  • Copyright © 2017 by ASME


By enabling consumer products to be made on-demand and eliminating waste from overproduction and transport, online 3D printing service is more and more popular with unprofessional customers. As a growing number of 3D printers are becoming accessible on various online 3D printing service platforms, there raises the concern over online 3D printing service evaluation and selection for novices as well as users with 3D printing experience. In this paper, we analyze this problem using information transformation techniques and multinomial distribution probabilistic model. Evaluation factors, the major attributes that significantly affect the performance of an online 3D printing service, are described with standard description form. Meanwhile, historical service data is introduced to identify and update these evaluation factor values. Based on these parameters, evaluation and comparison can be implemented upon online 3D printing services using the probabilistic model. An example is presented to illustrate the assessment process based on the proposed evaluation model. The presented objective probabilistic evaluation method can serve as the basis of online 3D printing service evaluation and selection on an online 3D printing service platform. Although the focus of the work was on 3D printing service, the idea can be applied to other online rapid prototyping sharing systems.

Copyright © 2017 by ASME



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