This study demonstrates the use of an additive fuzzy system to control the velocity and gap of cars in a single lane two-car platoon. A throttle- only controller and a combined throttle and braker controller were tested. Simulation results show that follower cars with a combined brake/ throttle controller can maintain a constant gap when the platoon goes down hills and slows. An adaptive throttle controller uses a neural system to learn the fuzzy rules for different vehicle types.

In this paper, three different sensors were used to measure multi-scale phenomena in chemical mechanical planarization. A piezoelectric force sensor, Hall effect sensor and acoustic emission sensor (AE) were installed in CMP equipment and the signals were measured simultaneously during the polishing process. The results showed that the sensors measuring frictional behaviour, such as the Hall effect sensor and force transducer, produced a clear end point signal in the case of the friction characteristics are distinguishable for each material. Also, if there is difference in hardness between materials, then a sharp end point signal is detected with the AE sensor even though the friction characteristic is similar between the two materials. Therefore, using multi-sensors having different bandwidths is complementary for not only process monitoring but also end point detection.

Chemical mechanical planarization (CMP) of Cu interconnects is a critical bottleneck technology for semiconductor manufacturing at the 65 nm technology node and beyond. The pad condition in CMP is of utmost importance in maintaining acceptable production quality and throughput, as it directly affects many different parameters in CMP including material removal rate (MRR) and process uniformity. Acoustic emission (AE) is a proven technique for in-situ monitoring of a wide range of manufacturing processes, and has been demonstrated for the in-situ monitoring of various phenomena in the CMP process such as endpoint and MRR detection. A novel graphical mapping approach of sensor signal for monitoring pad condition during Cu CMP is proposed and tested, with AE demonstrating improved sensitivity over that of friction force.