David Dornfeld

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We developed computer-aided planning tools for waterjet cleaning processes incorporating experimental results. We designed experiments to determine the influence of key waterjet parameters on cleaning effect and devised a computer-aided visualization and optimization scheme incorporating these parameters. In addition, we developed a particle dynamics model(More)
Recent advances in machine automation and sensing technology offer new opportunities for continuous condition monitoring of an operating machine. This paper describes an intelligent machine monitoring framework that integrates and utilizes data collection, management, and analytics to derive an adaptive predictive model for the energy usage of a milling(More)
INTRODUCTION Additive Manufacturing (AM) can improve flexibility and convenience, lower manufacturing costs, and reduce time to market for many manufacturing applications [1,2]. Successfully implementing and expanding AM requires improvements in surface quality, shear and tensile strength, build time, accuracy, and precision of these processes [3]. Of these(More)
The use of data-driven predictive models is becoming increasingly popular in engineering and manufacturing sectors. This paper discusses the deployment of Gaussian Process Regression (GPR) predictive models for smart manufacturing. A scoring engine is developed based on the Predictive Model Markup Language (PMML) standard to illustrate the portability of(More)
Increasing awareness of energy consumption and its environmental impacts has prompted a need to better predict the energy consumption of various industrial processes, including manufacturing. Modeling can allow manufacturers to optimize the efficiency of their manufacturing processes. Highly accurate, data-driven models of energy consumption of CNC milling(More)
Improved data quality and availability, along with lower computation costs, have generated interest in sensor-based tool condition monitoring technologies. In this study, an integrated vibration and acoustic sensor is used for tool condition monitoring, particularly for chatter detection and tool condition classification. Based on feature extraction in the(More)
This paper describes a real-time data collection framework and an adaptive machining learning method for constructing a real-time energy prediction model for a machine tool. To effectively establish the energy consumption pattern of a machine tool over time, the energy prediction model is continuously updated with new measurement data to account for(More)
Micron-sized subwavelength structured photonic sensors could allow critical thermo-mechanical phenomena in manufacturing processes to be monitored, while offering tremendous advantages. To implement these novel sensors into real manufacturing processes, the microring sensors can be embedded at critical locations in metallic structures, which are heavily(More)
Recent developments in integrated microphotonics have led to unprecedented potential towards robust sensor enhancements for manufacturing systems. These micron-sized subwavelength structured photonic sensors could allow critical thermo-mechanical phenomena in manufacturing processes to be monitored while offering immunity to electromagnetic interference,(More)