2009AIP conference proceedingsRequires access

Influence Of Runout On The Surface Roughness Obtained In Side Milling Processes

Hernán A. González Rojas, Irene Buj-Corral, Joan Vivancos Calvet, Vicente Jesus Segui

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Abstract

In this paper a numerical model was used to predict the surface roughness of parts machined by contour milling processes, taking into account the runout of the tool as differences in the tool edge radii. The computational model allows determining the value of both average roughness Ra and peak‐to‐valley roughness Rt, and is based on the geometric tool‐part intersection. 8000 runs were performed for each fz value using a random runout in each run in order to get simulated roughness values. Several graphics were obtained with the maximum and minimum value of average roughness Ra and of peak‐to‐valley roughness Rt for each value of feed per tooth and per turn fz, as well as the theoretical or geometric upper and lower reference limits. In addition, frequency histograms were obtained for Ra and Rt. For low feed values, the median of the roughness values is quite similar to the upper limit, which corresponds to the effect of one tool teeth having a higher radius than other radii. For higher feed values, the median of the roughness values remains between the lower and the upper limit. It was observed that the obtained values of average roughness Ra and peak‐to‐valley roughness Rt do not follow a normal distribution even though the values of the radii were randomly taken according to a normal law.

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What this paper is about

In this paper a numerical model was used to predict the surface roughness of parts machined by contour milling processes, taking into account the runout of the tool as differences in the tool edge radii. The computational model allows determining the value of both average roughness Ra and peak‐to‐valley roughness Rt, and is based on the geometric tool‐part intersection. 8000 runs were performed for each fz value using a random runout in each run in order to get simulated roughness values. Several graphics were obtained with the maximum and minimum value of average roughness Ra and of peak‐to‐valley roughness Rt for each value of feed per tooth and per turn fz, as well as the theoretical or geometric upper and lower reference limits. In addition, frequency histograms were obtained for Ra and Rt. For low feed values, the median of the roughness values is quite similar to the upper limit, which corresponds to the effect of one tool teeth having a higher radius than other radii. For higher feed values, the median of the roughness values remains between the lower and the upper limit. It was observed that the obtained values of average roughness Ra and peak‐to‐valley roughness Rt do not follow a normal distribution even though the values of the radii were randomly taken according to a normal law.

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Available abstract

In this paper a numerical model was used to predict the surface roughness of parts machined by contour milling processes, taking into account the runout of the tool as differences in the tool edge radii. The computational model allows determining the value of both average roughness Ra and peak‐to‐valley roughness Rt, and is based on the geometric tool‐part intersection. 8000 runs were performed for each fz value using a random runout in each run in order to get simulated roughness values. Several graphics were obtained with the maximum and minimum value of average roughness Ra and of peak‐to‐valley roughness Rt for each value of feed per tooth and per turn fz, as well as the theoretical or geometric upper and lower reference limits. In addition, frequency histograms were obtained for Ra and Rt. For low feed values, the median of the roughness values is quite similar to the upper limit, which corresponds to the effect of one tool teeth having a higher radius than other radii. For higher feed values, the median of the roughness values remains between the lower and the upper limit. It was observed that the obtained values of average roughness Ra and peak‐to‐valley roughness Rt do not follow a normal distribution even though the values of the radii were randomly taken according to a normal law.

Key concepts: Surface finish, Surface roughness, RADIUS, Histogram, Roughness length, Materials science, Geometry, Limit (mathematics)

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