@article{
 title = {Parametric process optimization to improve the accuracy of rapid prototyped stereolithography parts},
 type = {article},
 year = {2000},
 identifiers = {[object Object]},
 keywords = {Parameter tuning,Rapid prototyping,Response surface method,Stereolithography,Taguchi method},
 pages = {363-379},
 volume = {40},
 websites = {http://www.sciencedirect.com/science/article/pii/S0890695599000681},
 month = {2},
 id = {32c1b950-bd07-36b9-a6d4-3de90f32975c},
 created = {2016-06-24T20:49:29.000Z},
 accessed = {2014-06-11},
 file_attached = {false},
 profile_id = {954a987f-819f-3985-95a4-2991e0cf0552},
 group_id = {8440dcff-74cc-3783-aef7-fe2749cfc7ef},
 last_modified = {2016-06-24T20:49:29.000Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Zhou2000},
 abstract = {The functional requirements of a rapid prototyping system are speed and accuracy, and they are both functions of vendor defaulted and user selected manufacturing parameters. Accuracy is evaluated by dimensional errors, form errors and surface roughness of manufactured parts. A specially designed specimen with 20 dimensional, geometrical, and surface roughness features has been used in the inspection of RP manufacturing processes. In terms of Taguchi experimental design techniques, an orthogonal array of experiments has been developed which has the least number of experimental runs and desired process parameter settings. Using a 3-D coordinate measuring machine and surface profilometer, a series of measurements in evaluating the SLA parts quality has been conducted to find the functional relationships between the output part quality and input manufacturing process parameters. Two analysis tools, response surface methodology and Analysis of Variance (ANOVA), have been used to evaluate the SLA RP process and to perform the product optimization. The optimal setups of SLA manufacturing parameters for both individual features and a general part with various features have been concluded from this study.},
 bibtype = {article},
 author = {Zhou, Jack G. and Herscovici, Daniel and Chen, Calvin C.},
 journal = {International Journal of Machine Tools and Manufacture},
 number = {3}
}

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