Understanding Surface Quality: Beyond Average Roughness (Ra)

Chittaranjan Sahay; Suhash Ghosh

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Conference: 2018 ASEE Annual Conference & Exposition
Location: Salt Lake City, Utah
Publication Date: June 23, 2018
Start Date: June 23, 2018
End Date: July 27, 2018
Conference Session: Manufacturing Curriculum and Course Innovations
Tagged Division: Manufacturing
Page Count: 20
DOI: 10.18260/1-2--31176
Permanent URL: https://peer.asee.org/31176
Download Count: 18685

Paper Authors

biography

Chittaranjan Sahay P.E. University of Hartford

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Dr. Sahay has been an active researcher and educator in Mechanical and Manufacturing Engineering for the past four decades in the areas of Design, Solid Mechanics, Manufacturing Processes, and Metrology. He is a member of ASME, SME,and CASE.

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Suhash Ghosh University of Hartford

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Dr. Ghosh has been actively working in the areas of advanced laser manufacturing processes modeling and simulations for the past 12 years. His particular areas of interests are thermal, structural and materials modeling/simulation using Finite Element Analysis tools. His areas of interests also include Mechanical Design and Metrology.

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Abstract

Understanding Surface Quality: Beyond Average Roughness (Ra)

Design of machine parts routinely focus on the dimensional and form tolerances. In applications where surface quality is critical and requires a characterizing indicator, surface roughness parameters, Ra (roughness average) is predominantly used. Traditionally, surface texture has been used more as an index of the variation in the process due to tool wear, machine tool vibration, damaged machine elements, etc., than as a measure of the performance of the component. There are many reasons that contribute to this tendency: average roughness remains so easy to calculate, it is well understood, and vast amount of published literature explains it, and historical part data is based upon it. It has been seen that Ra, typically, proves too general to describe surface’s true functional nature. Additionally, the push for complex geometry, coupled with the emerging technological advances in establishing new limits in manufacturing tolerances and better understanding of the tribological phenomena, implies the need for surface characterization to correlate surface quality with desirable function of the surface. In turn, the surface quality over the entire area, not just the 2D Ra parameter, dictates the performance and reliability of the part.

Both ISO and ASME current standards on surface texture have a range of 3D surface quality parameters. This is further aided by the availability of modern equipment to accurately measure them. Despite these advances, design and quality professionals continue to specify surface finish based solely on the value of Ra. The same outlook trails in graduate and undergraduate education and their textbooks. This article explores how these multitudes of 2D and 3D surface quality parameters are to be understood in the design and development of high performance surfaces, and the strong need for them to be incorporated into graduate undergraduate engineering curriculum, and be taught as an improved toolkit to the aspiring engineers, process engineers and quality control professionals. Included case studies can be used to captivate the attention of the students (target audience would include industry professionals as well) and route their inquisitiveness into why they need to think beyond Ra in this era of advanced manufacturing.

Citation
Format

Sahay, C., & Ghosh, S. (2018, June), Understanding Surface Quality: Beyond Average Roughness (Ra) Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--31176

TY - CPAPER
AB - Understanding Surface Quality: Beyond Average Roughness (Ra)

Design of machine parts routinely focus on the dimensional and form tolerances. In applications where surface quality is critical and requires a characterizing indicator, surface roughness parameters, Ra (roughness average) is predominantly used. Traditionally, surface texture has been used more as an index of the variation in the process due to tool wear, machine tool vibration, damaged machine elements, etc., than as a measure of the performance of the component. There are many reasons that contribute to this tendency: average roughness remains so easy to calculate, it is well understood, and vast amount of published literature explains it, and historical part data is based upon it. It has been seen that Ra, typically, proves too general to describe surface’s true functional nature. Additionally, the push for complex geometry, coupled with the emerging technological advances in establishing new limits in manufacturing tolerances and better understanding of the tribological phenomena, implies the need for surface characterization to correlate surface quality with desirable function of the surface. In turn, the surface quality over the entire area, not just the 2D Ra parameter, dictates the performance and reliability of the part.

Both ISO and ASME current standards on surface texture have a range of 3D surface quality parameters. This is further aided by the availability of modern equipment to accurately measure them. Despite these advances, design and quality professionals continue to specify surface finish based solely on the value of Ra. The same outlook trails in graduate and undergraduate education and their textbooks. This article explores how these multitudes of 2D and 3D surface quality parameters are to be understood in the design and development of high performance surfaces, and the strong need for them to be incorporated into graduate undergraduate engineering curriculum, and be taught as an improved toolkit to the aspiring engineers, process engineers and quality control professionals. Included case studies can be used to captivate the attention of the students (target audience would include industry professionals as well) and route their inquisitiveness into why they need to think beyond Ra in this era of advanced manufacturing.

AU - Chittaranjan Sahay P.E.
AU - Suhash Ghosh
CY - Salt Lake City, Utah
DA - 2018/06/23
PB - ASEE Conferences
TI - Understanding Surface Quality: Beyond Average Roughness (Ra)
UR - https://peer.asee.org/31176
DO - 10.18260/1-2--31176
ER -