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PurposeThe purpose of this research is to extend the previous approach to software error compensation to fused deposition modeling (FDM) machines and explores the approach to apply compensation by correcting slice files.Design/methodology/approachIn addition to applying the stereolithography (STL) file‐based compensation method from earlier research; a new approach using the slice file format to apply compensation is presented. Under this approach, the confounded effects of all errors in a FDM machine are mapped into a “virtual” parametric machine error model. A 3D artifact is built on the FDM machine and differences between its actual and nominal dimensions are used to estimate the coefficients of the error functions. A slice file compensation method is developed and tested on two types of parts as a means for further improving the error compensation for feature form error improvement. STL file compensation is also applied to a specific FDM 3000 machine and the results are compared with those of a specific SLA 250 machine.FindingsThe two compensation methods are compared. Although, the slice file compensation method theoretically allows higher compensation resolution, the actual machine control resolution of the FDM machine can be a limitation which makes the difference between STL compensation and slice file compensation indistinguishable. However, as the control resolution is increased, this method will make it possible to provide a higher degree of compensation.Originality/valueCompensation method applied to slice file format is developed for FDM machines and its limitations are explored. Based on the experimental study, dimensional accuracy of parts is considerably improved by the software error compensation approach.

This paper discusses the past 25 years of research in feature recognition. Although a great variety of feature recognition techniques have been developed, the discussion here focuses on the more successful ones. These include graph based and “hint” based methods, convex hull decomposition, and volume decomposition-recomposition techniques. Recent advances in recognizing features with free form features are also presented. In order to benchmark these methods, a frame of reference is created based on topological generality, feature interactions handled, surface geometry supported, pattern matching criteria used, and computational complexity. This framework is used to compare each of the recognition techniques. Problems related to domain dependence and multiple interpretations are also addressed. Finally, some current research challenges are discussed.

Photoactivation of titanium dioxide nanoparticles (TiO2NPs) can produce reactive oxygen species (ROS). Over time, this has the potential to produce cumulative cellular damage. To test this, we exposed zebrafish (Danio rerio) to two commercial TiO2NP preparations at concentrations ranging from 0.01 to 10,000 ng/mL over a 23 day period spanning embryogenesis, larval development, and juvenile metamorphosis. Fish were illuminated with a lamp that mimics solar irradiation. TiO2NP exposure produced significant mortality at 1 ng/mL. Toxicity included stunted growth, delayed metamorphosis, malformations, organ pathology, and DNA damage. TiO2NPs were found in the gills and gut and elsewhere. The two preparations differed in nominal particle diameter (12.1 ± 3.7 and 23.3 ± 9.8 nm) but produced aggregates in the 1 μm range. Both were taken up in a dose-dependent manner. Illuminated particles produced a time- and dose-dependent increase in 8-hydroxy-2'-deoxyguanosine DNA adducts consistent with cumulative ROS damage. Zebrafish take up TiO2NPs from the aqueous environment even at low ng/mL concentrations, and these particles when illuminated in the violet-near UV range produce cumulative toxicity.