User Case

Lund University & Sandvik: Determining the optimum surface finish for tooth flanks of gears

In joint research, SANDVIK Coromant & LUND University use Alicona surface finish measurement systems to verify new gear manufacturing methods.

To help prevent cost-intensive postprocessing, Lund University used a simulation to calculate the ideal machine parameters for a form milling cutter. This was to ensure the tool would produce tooth flanks with optimum surface quality. The research team used Alicona systems at Sandvik Coromant to validate the mathematical models and verify their suitability for practical use. "Thanks to the high working distance, we were able to measure the roughness of tooth flanks that were previously inaccessible to us," lead researcher Mattias Svahn confirms. 

Mattias Svahn, Division of Machine Elements at Lund University

Matthias Svahn,
Lund University 

"Thanks to Alicona, we have been able to minimize the time and cost-intensive refining steps of gears. We were blown away by the capabilities of the InfiniteFocus system we got to know at Sandvik Coromant. There is no measurement system we know that is capable of measuring critical form and positional tolerances and roughness of tooth flanks in this way with just one system."

Increase efficiency in gear manufacturing with ideal surface quality

Due to global competition, cost pressure is constantly on the rise. This makes it necessary to increase the efficiency of processes in the manufacture of gearings. One of the major cost factors is post-processing, including refining steps such as grinding and honing to ensure the correct roughness of tooth flanks. This process could be minimized if it were possible to produce virtually perfect gears with optimum surface quality that need little to no post-processing. To make this a reality and ensure gears are produced with the desired roughness, it is critical to calculate the correct machine parameters for the tool used, e.g. for a form milling cutter. Roughness is chiefly determined by feed and cutting speed. These parameters also have an effect on gears' service life, fatigue and uniform transmission of motion. It is therefore of great economical interest to predict which roughness values result from different machine parameters.

Mathematical model calculates ideal machining parameters

For this reason, Lund University (Sweden) initiated a research project to investigate this exact question by way of a simulation. The research team created a mathematical model to calculate the machine parameters for the production of gears with optimum surface quality. This was accomplished in cooperation with a renowned Swedish tool manufacturer that was planning on launching a new form milling cutter.

Alicona form measurement of tooth flanks

Alicona is also used for form measurement of gears/tooth flanks. Users benefit from comparing measurement results to CAD data and positional tolerances.

Optical measurement used to verify machining capabilities

Alicona systems were used to verify whether the roughness values calculated in the model could actually be produced in reality. Areal roughness measurement enabled Lund University to validate the model at the required level of quality. "We carried out the areal roughness measurement on-site at Sandvik Coromant and got to know Alicona in the process. The high precision and speed of the measurements immediately convinced us to purchase our own InfiniteFocus system," lead researcher Mattias Svahn explains.

Surface quality is determined by roughness and geometry of tooth flank 

The quality of a tooth flank is determined by both its roughness and its geometry. The roughness of the tooth flank plays an important role in several ways. For example, it directly affects noise generation. The rougher the surface, the noisier the gear. Uniform transmission of motion, on the other hand, mainly depends on the form and positional tolerances of the tooth flank. It is therefore vital to measure both roughness and form to ensure proper quality assurance of gears. When measuring roughness, it is important to consider the dominant surface structure of gears and choose the appropriate measurement technology for this purpose.

Alicona surface roughness measurement

Calculated roughness versus measured roughness: The research team developed a mathematical model in order to investigate how machine parameters and possible error sources find their impact on the cut surface roughness.

Importance of areal surface texture parameters Sa, Sq, Sz

Mattias Svahn used an Alicona system, as he knew that mere profile-based roughness measurement would not deliver useful results. "Profile-based measurement allows me to map the surface only partially. Depending on the direction of the profile, roughness values are subject to intense scattering. The resulting measurement values are simply not useful for creating and validating the calculation model," lead researcher and measurement expert Mattias Svahn explains. By contrast, Alicona's measurement systems make it possible to map the roughness of the entire surface, even of the tooth flanks—fast, repeatably, and at high resolutions. The surface texture parameters Sa, Sq, and Sz allow precise assessment of the surface quality. 

Measurement of form deviations

Form deviations can be made visible using difference measurement. This is accomplished by comparing measurement results to a CAD dataset and/or form and positional tolerances. In addition to form and roughness measurement, Lund University also makes use of the visualization of 3D data sets. The large lateral and vertical scanning areas make it possible to map the topography of the entire gear cutting.

At one glance:

  • Alicona was used to validate a mathematical model to investigate how machine parameters and possible error sources find their impact on the cut surface roughness.
  • In particular, areal roughness measurement helped to validate the model at the required level of quality. 
  • Sa, Sq Sz parameters were measured at tooth flanks that have not been accessible before.
  • The measurement of form deviations to reference geometry was performed by using defference measurement. This is accomplished by comparing measurement results to a CAD dataset and/or form and positional tolerances. 

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