مدل‌سازي زبري سطح و بيشينه ضخامت براده‌ي تغيير شكل نيافته در سنگ‌زني تخت

SURFACE ROUGHNESS AND MAXIMUM UNDEFORMED CHIP THICKNESS MODELING IN SURFACE GRINDING

در اين نوشتار مدلي جديد براي پيش‌بيني زبري سطح قطعه‌كار در فرايند سنگ‌زني تخت، براساس مدل‌سازي بيشينه ضخامت براده‌ي تغيير شكل نيافته ارايه مي‌‌شود. براي اين منظور با لحاظ ‌كردن ماهيت تصادفي توزيع و هندسه‌ي دانه‌هاي ساينده و درنتيجه عمق نفوذ متغير آنها، از مفهوم تابع چگالي احتمال استفاده شده است. با مقايسه‌ي توابع توزيع مهم در هيستوگرام ضخامت براده، تابع چگالي احتمال گاما به‌عنوان بهترين تابع تعيين شد و بر‌مبناي آن مدل‌سازي ضخامت براده‌ي تغيير شكل نيافته انجام گرفت. بيان ضخامت براده در مدل پيشنهادي تابعي از پارامترهاي سنگ‌زني، ميكروساختار سنگ و شرايط سينماتيكي فرايند است. مدل زبري با انجام آزمايش‌هاي سنگ‌زني تخت روي پوشش‌دهي WC-10Co-4Cr با پاشش حرارتي ارزيابي شد و نتايج حاصله بيان‌گر تطابق قابل قبول مقادير پيش‌بيني شده و مقادير اندازه‌گيري شده است. اين مسيله با محاسبه‌ي ميانگين درصد خطاي نسبي بين مقادير پيش‌بيني شده و نتايج آزمايش‌ها نيز تاييد شده است.

Grinding is a surface finishing process, and surface roughness is one of the most important factors in evaluating the performance of the finished component. The development of a comprehensive model that can predict surface roughness over a wide range of operating conditions is still a key issue for the grinding process. In this paper, a new predictive surface roughness model for the surface grinding process is developed, based on maximum undeformed chip thickness modeling. By considering the random nature of grit distribution and grit geometry and, thus, variations in the depth of grain penetration, the concept of a probability density function (PDF) has been utilized. Gamma PDF has been determined to be the best function, by comparing the main distribution functions in a histogram graph of chip thickness, and, based on this PDF, maximum undeformed chip thickness modeling has been carried out. The representation of chip thickness in the proposed model is a function of grinding parameters, the wheel microstructure and process kinematic conditions. The developed model for surface roughness prediction is based on the geometrical analysis of the grooves left on the surface due to the grit-workpiece interaction, and has been resulted using maximum undeformed chip thickness modeling. The surface roughness model has been validated by the experimental results of the surface grinding of a thermally sprayed WC-10Co-4Cr coating. Reasonable agreement has been observed between predictions from the proposed model and the experimentally measured surface roughness. This is also supported by the values of the average percentage of error between predicted and experimental results. The average value of relative error between predicted and measured values of surface roughness was 8.53%. According to these results, it can be concluded that the proposed surface roughness model is an effective prediction technique.