Hand scraping (kisage) is a precision finishing technique in which a skilled craftsperson uses a hardened scraping tool to selectively remove minute amounts of metal from a workpiece surface, achieving flatness and surface texture unattainable by conventional machine processes. This technique continues to play a decisive role in the manufacture of high-precision machine tools—particularly for guideway and datum surfaces—yet it faces a serious skill-succession crisis driven by the retirement of master craftspeople and the absence of systematic transmission mechanisms. This paper provides a comprehensive review of hand scraping technology, tracing its historical origins and fundamental principles and organizing the current research landscape into four interrelated pillars structured along two analytical levels: (1) skill digitization and transmission, (2) surface measurement and evaluation, (3) tooling and process innovation, and (4) automation systems. Primary qualitative field data gathered at a specialist machine tool repair company—Ando Kikai Kogyo Co., Ltd. (Ome, Tokyo)—are used to provide evidence on the realities of skill transmission in industrial practice. Building on this analysis, the paper discusses the prospects for artificial intelligence integration, from AI-assisted contact-pattern recognition to semi-automated scraping systems, and proposes a near-future roadmap centered on Human–AI collaboration rather than full automation. The paper argues that genuine mastery of scraping cannot be separated from its physical enactment—that knowledge of scraping and the action of scraping are inseparable—and that the appropriate response is to design Human–AI systems that augment and preserve this embodied knowledge rather than seek to replace it.
Hirotaka TSUTSUMI (Thu,) studied this question.