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Generalized Intelligent Grinding Advisory System

Summary
The Generalized Intelligent Grinding Advisory System (GIGAS) has been developed to optimize complex manufacturing processes. This software based optimization incorporates mathematical models and experimental data to allow grinding to be done as quickly as possible, while maintaining or improving the desired surface finish. To optimize an installed grinding machine, a user with little training can input the type of machine, materials being ground, the desired outcome along with several other variables, and the software will optimize the process. With this technology, manufacturers could typically see a 10 to 15 percent reduction in grinding times, with reductions of up to 65 percent possible, along with a 10 percent reduction in cost. As this technology is software based, it requires little to no capital investment and has a return on investment of under one year. The current market for this technology is $10 billion. The software currently supports surface, cylindrical plunge, and cylindrical traverse grinding processes, but can easily be expanded to other grinding processes such as centerless and internal grinding.
Technology Benefits
Automated grinding optimizationSupports multiple types of grinding optimizations
Technology Application
MaterialsManufacturingSoftware
Detailed Technology Description
Yung ShinManufacturing LaboratoryPurdue Mechanical Engineering
Countries
United States
Application No.
None
*Abstract

*Background
Grinding processes in manufacturing are diverse and complex with many variables affecting the process. Traditional grinding techniques believe a slow, very fine grind produces a smooth surface finish. Conventional optimization strategies try to produce the same results f often involve the use of trial and error and are of limited effectiveness.
*IP Issue Date
None
*IP Type
Cont-in-Part
*Stage of Development
Prototype Testing in Economic Run
*Web Links
Purdue Office of Technology CommercializationPurdueInnovation and EntrepreneurshipYung ShinManufacturing LaboratoryPurdue Mechanical Engineering
Country/Region
USA

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