In the present report, estimates of test–retest and between-site reliability of fMRI assessments were produced in the context of a multicenter fMRI reliability study (FBIRN Phase 1, www.nbirn.net). Five subjects were scanned on 10 MRI scanners on two occasions. The fMRI task was a simple block design sensorimotor task. The impulse response functions to the stimulation block were derived using an FIR-deconvolution analysis with FMRISTAT. Six functionally-derived ROIs covering the visual, auditory and motor cortices, created from a prior analysis, were used. Two dependent variables were compared: percent signal change and contrast-to-noise-ratio. Reliability was assessed with intraclass correlation coefficients derived from a variance components analysis. Test–retest reliability was high, but initially, between-site reliability was low, indicating a strong contribution from site and site-by-subject variance. However, a number of factors that can markedly improve between-site reliability were uncovered, including increasing the size of the ROIs, adjusting for smoothness differences, and inclusion of additional runs. By employing multiple steps, between-site reliability for 3T scanners was increased by 123%. Dropping one site at a time and assessing reliability can be a useful method of assessing the sensitivity of the results to particular sites. These findings should provide guidance to others on the best practices for future multicenter studies.

Cast aluminum wheels must be deburred and polished before chrome plating operation. Manual deburring and polishing is tedious and monotonous. Industrial robots are attracting more and more attention for the deburring applications. However, Each wheel path program was taking eight to ten weeks to create because the position and orientation of the deburring tool must be accurately identified based on the curvature of the wheel. To solve this problem, we developed a practical 6 DOF robot path generation method using hybrid force and visual servoing methodology. The force servoing keeps the robot tool continuously contacting with the wheel surface and the visual servoing controls the robot tool to follow a marked tool path on the wheel while the position and orientation are controlled and recorded. A robot path is then generated from the recorded data. Experiments are performed and the experimental results demonstrate that the developed algorithm can be used to automatically generate accurate 6 DOF robot paths for deburring aluminum wheels in less than an hour. This significantly reduces the robot programming time. The developed technology can also be used for robot path generation in many other manufacturing applications, such as welding and strip painting.

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