曲面(拓扑)
计量系统
计算机科学
工程类
机械工程
实时计算
数学
物理
几何学
天文
作者
Sushil V. Deshpande,Ramkisan S. Pawar,Ashok J. Keche,Anant Sidhappa Kurhade
标识
DOI:10.1142/s0219686725500386
摘要
Surface finish measurements in manual machining were conveyed after manufacturing thereby operating to assess and adjust cutting parameters on self-skill to address targets or discrepancies leading to a chance of unpredictable defects, frequent rejection, rework of workpiece or inefficient performance. To tackle this, automatic surface finish measurement setup empowered by an algorithm with a laser triangulation sensor has been developed to furnish real-time surface finish data of manual turning of shaft. The python-based algorithm automatically computes the roughness value with linear distance of adjacent points sensed over the length of surface of each section and compares it with standard data value in algorithm. This automatic measurement and continuous comparative analysis provides live feedback on the workpiece’s surface status to an operator during manufacturing. The live continued guidance for a rough cut, semi-finish cut and finish cut for operator results through algorithm display ensures the surface finish achievement with ease in manufacturing phase-wise, thereby reducing rejection rate by 20–30%, operator figure relief 80% and increased production by 30% especially with accumulation of present operator, skill set and existing setup. Additionally, with compatibility of workpiece profile change, it saves 10–15 min per piece (26%) compared to general machining, high surface finish accuracy (error between 0.07 [Formula: see text]m and 0.075[Formula: see text]m) which is the acceptable limit vitally reducing the need for manual inspections as compared to general machining, and provides 100% consistent display guidance. Overall, it optimizes efficiency, quality and productivity, proving to be a transformative tool for industrial manufacturing.
科研通智能强力驱动
Strongly Powered by AbleSci AI