Abstract
The finished geometry of a welded structure is greatly affected by heat-induced distortion from the welding process. This often requires correction by straightening and top-level machining to ensure manufacturing quality. Distortion is sensitive to weld sequencing and manufacturing environment. Optimal weld sequencing can significantly reduce distortion and manufacturing cost. However, an optimal weld sequence is not always intuitively obvious, especially for large structures with many welds. Virtual Fabrication Technology (VFT) is Caterpillar's proprietary software for the simulation of welding physics via finite element analysis. Powered by the highly successful VFT platform, a combinatorial genetic algorithm based optimization approach combined with an uncertainty quantification (UQ) module for evaluating robustness has been developed at Caterpillar for weld sequence optimization (WSO). WSO has been successfully applied to more than 50 structures, resulting in the minimization of straightening operations. The combined VFT and robust WSO approach results in an accelerated manufacturing process development schedule. We will present a summary of our WSO approach and some results that demonstrate how WSO has proven to be a transformative manufacturing planning technology at Caterpillar.
| Original language | English |
|---|---|
| Pages (from-to) | 342-350 |
| Number of pages | 9 |
| Journal | Procedia Computer Science |
| Volume | 140 |
| DOIs | |
| State | Published - 2018 |
| Externally published | Yes |
| Event | Complex Adaptive Systems Conference with Theme: Cyber Physical Systems and Deep Learning, CAS 2018 - Chicago, United States Duration: Nov 5 2018 → Nov 7 2018 |
Keywords
- Genetic algorithms
- Sequence optimization
- Uncertainity quantification
- Virtual manufacturing
- Welding simulation