For machining operations, preparation work called a “setting operation” is always required in advance. The setting operation, which affects the lead time and machining accuracy, strongly depends on the skill level of the operator. Therefore, to improve the quality of machining operations, skill transfer is necessary by extracting and generalizing the skills related to the setting operation. In addition, a variety of accidents often occur during the setting operation. This can lead to machine tool failure or a serious incident involving the operator. Thus, skill transfer to an unskilled operator is also important for work safety. On the other hand, augmented reality (AR) is a promising human-computer interaction technology to support skill transfer at the manufacturing site. An AR technology generally overlays virtual images on the real-world environment. In this study, an AR-based system is developed to demonstrate a recommended workpiece fixturing method in turning operations for assisting unskilled operators as the first step of skill transfer. In turning operations, two types of fixturing are usually assumed: outer diameter clamping and inner diameter clamping. The dimensions of the targeted product shape are detected, and the workpiece shape is obtained. The removal volume to be machined is calculated as the difference between the targeted product shape and workpiece shape. The fixturing method is determined to avoid contact between the removal volume and the assumed jaw. The results of a case study show that the developed AR-based system is effective for skill transfer of workpiece fixturing by demonstrating the recommended fixturing method using skills acquired from operators.

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