Demo Data from SIGIR 2026 / reviewers in the wild / expert
Stephen J. Rhee
dblp:97/4266
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1999
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Computational fabrication · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational fabrication
assembly planning |
0.0 | 1 | 1999 | Design-specific approach to design for assembly (DFA) for complex mechanical assemblies · IEEE Trans. Robotics Autom. 1999 |
Computational fabrication › design for manufacturing
design for assembly |
0.0 | 1 | 1999 | Design-specific approach to design for assembly (DFA) for complex mechanical assemblies · IEEE Trans. Robotics Autom. 1999 |
Methods — techniques the papers use, named apart from their topics
kinematic degree-of-freedom analysis · 0.0genetic algorithm · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1999 | Design-specific approach to design for assembly (DFA) for complex mechanical assembliesabstractUses assembly sequence analysis (ASA) to explore design for assembly (DFA), subassembly partitioning, and assembly sequence choice for two complex assemblies. Complex assemblies have very high parts-counts, a final assembly organized as an assembly of subassemblies, and offer limited redesign options. ASA addresses combinatorial aspects of complex assemblies that conventional DFA ignores: choice and partitioning of subassemblies, and assembly sequence choice. The paper describes criterion-based searches for favorable subassembly partitioning and assembly sequences that use genetic algorithm techniques to spread assembly move difficulty across entire final assembly sequences while satisfying all logical constraints imposed on the assembly sequence by part geometry. The measure of assembly move difficulty, a count of kinematic degrees of freedom secured during each final assembly step, is measured on an absolute scale. We find that ASA can pinpoint candidate DFA-related redesigns and can suggest assembly issues to designers. Logical assembly issues dominate quantitatively-characterized issues when selecting assembly sequence or subassembly partitioning. After logical issues are addressed, the sequence choice criterion defined here often duplicates choices made by experienced analysts. Finally, the sequence choice criterion favors in-line over branched final assembly lines. Thomas L. DeFazio, Stephen J. Rhee, Daniel E. Whitney |
IEEE Trans. Robotics Autom. | 2 |