A Data Processing Pipeline for Prediction of Milling Machine Tool Condition from Raw Sensor Data [0.03%]
基于原始传感器数据的加工中心主轴状态预测及数据处理方法研究
M Ferguson,R Bhinge,J Park et al.
M Ferguson et al.
With recent advances in sensor and computing technology, it is now possible to use real-time machine learning techniques to monitor the state of manufacturing machines. However, making accurate predictions from raw sensor data is still a di...
Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML) [0.03%]
预测模型标记语言(PMML)中的高斯过程回归(GPR)表示法
J Park,D Lechevalier,R Ak et al.
J Park et al.
This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic m...
A Classification Scheme for Smart Manufacturing Systems' Performance Metrics [0.03%]
智能制造系统性能指标分类体系研究
Y Tina Lee,Senthilkumaran Kumaraguru,Sanjay Jain et al.
Y Tina Lee et al.
This paper proposes a classification scheme for performance metrics for smart manufacturing systems. The discussion focuses on three such metrics: agility, asset utilization, and sustainability. For each of these metrics, we discuss classif...
Toward a Digital Thread and Data Package for Metals-Additive Manufacturing [0.03%]
面向金属增材制造的数字线程和数据包
D B Kim,P Witherell,Y Lu et al.
D B Kim et al.
Additive manufacturing (AM) has been envisioned by many as a driving factor of the next industrial revolution. Potential benefits of AM adoption include the production of low-volume, customized, complicated parts/products, supply chain effi...