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Manual thickness measurement of thin-walled parts is largely demanded in industrial applications. Repetitive manual interventions and poor consistency of measurement data are two of the critical existing problems for manual thickness measurement, which reduce the measuring accuracy and efficiency. To address these problems, this article combines digital ultrasonic thickness with an augmented reality (AR)-based system to assist the manual thickness measurement of the thin-walled parts. A simple adaptive pattern projection method is proposed to replace the manual drawing of grids and thickness states on the part. A multifunctional tool is developed to automatically visualize and record the measured thickness data in real-time, which guarantees the consistency of measurement data. The communication within the proposed system is established to enhance the human–machine interaction experience, allowing the operator to focus on the thickness measurement itself. The accuracy of the projection position is analyzed and the maximum deviation is 1.5 mm. A case study is conducted to validate the proposed system. The proposed system largely improves digitization and decreases the workload of manual thickness measurement. The measurement time is shortened compared to the conventional thickness measurement method. [ABSTRACT FROM AUTHOR]

On-machine measurement (OMM) is increasingly used to inspect freeform surfaces without unloading the workpiece from the machine tool. Compared to the mechanical probe deployed in many OMM processes, a laser displacement sensor has its advantage of high scanning efficiency. However, the accuracy has been a bottleneck limiting its application in precision inspection, due to the lack of a rigorously planned path. In this work, an error compensation model is established and verified considering laser triangulation error, misalignment from calibration, tooling error, and preevaluated error. Essentially, error modeling contributes to improve the measurement accuracy of laser triangulation OMM (LTOMM). After understanding these errors, a reliable measuring path is crucial to maintain the given accuracy of LTOMM. This path generated is capable of minimizing the measurement time at a given accuracy constraint. In a particular case study, a turbine blade surface was inspected using LTOMM following generated path against a built-in probe. The measurement time was reduced by 77.4% for a constraining accuracy of $\pm 10~\mu \text{m}$. The time could be further reduced by 38.6%, for a constraining accuracy of $\pm 13~\mu \text{m}$. This study has demonstrated that LTOMM could potentially replace the on-machine probe during measurement of freeform surfaces, toward more efficient industrial applications in the future. [ABSTRACT FROM AUTHOR]