Abstract
Part production requires constant monitoring to assure the effective manufacturing of high-quality components. The choice of monitoring methods can become a crucial factor in the decisions made during and prior to manufacturing. In an ideal world, designers and manufacturers will work together to interpret manufacturing and part data to assure the elimination of faults in manufacturing. However, manufacturing still lacks mathematically robust means of interpreting the manufacturing data so that a channel of communication can be established between design and manufacturing. To address part production concerns, we present a systematic methodology to interpret manufacturing data based on signals from manufacturing (e.g., tool vibrations, part surface deviations). These signals are assumed to contain a fingerprint of the manufacturing condition. The method presented in this paper is based on a mathematical transform to decompose the signals into their significant modes and monitor their changes over time. The methodology is meant to help designers and manufacturers make informed decisions about a machine and/or part condition. An example from a milling process is used to illustrate the method’s details.
Model-Based Control Design and Integration of Cyberphysical Systems: An Adaptive Cruise Control Case Study
