Surface Texture Calculator

Analyze surface roughness parameters (Ra, Rz, Rmax) and texture characteristics for CNC machined components with micrometer precision and ISO standards compliance.

Ra/Rz Analysis ISO Standards 3D Mapping

Measurement Parameters

Surface Roughness Data

Manufacturing Process

Quality Requirements

Understanding Surface Texture Analysis

Surface Roughness Parameters

Ra (Arithmetic Average Roughness) is the most commonly used parameter, representing the arithmetic mean of the absolute values of the profile deviations from the mean line.

Rz (Average Roughness) is the average distance between the five highest peaks and five deepest valleys within the sampling length.

Rmax (Maximum Height) is the maximum peak-to-valley height within the evaluation length.

Rq (RMS Roughness) is the root mean square average of the profile deviations from the mean line.

Measurement Standards

ISO 4287 defines the terms, definitions and surface texture parameters for surface texture assessment.

ISO 4288 specifies the rules and procedures for the assessment of surface texture using profile methods.

Sampling Length should be chosen based on the expected roughness and manufacturing process.

Cutoff Filter separates roughness from waviness and form errors in the measurement.

Manufacturing Impact

Tool Geometry significantly affects surface finish - sharper tools generally produce better finishes.

Feed Rate has a direct relationship with surface roughness - lower feed rates typically improve finish.

Cutting Speed optimization can reduce built-up edge formation and improve surface quality.

Material Properties influence machinability and achievable surface finish quality.

Quality Control

Functional Requirements determine the appropriate surface finish specification for the application.

Measurement Location should be representative of the functional surface area.

Statistical Analysis of multiple measurements provides confidence in surface quality assessment.

Process Control uses surface texture measurements to monitor and optimize manufacturing processes.