5 papers
A Data-Driven Framework for Unsupervised Monitoring of Transmission Systems Using End-of-Line Testing Data: A Case Study at Ford Motor Company
Mohammad N. Bisheh, Mehrdad Moradi, Parinaz Farajiparvar +6
Sensing technologies have advanced rapidly across industries ranging from energy to automotive manufacturing. These systems generate high-dimensional (HD) data characterized by com…
Low-Rank and Structured Sparse Tensor Decomposition for Anomaly Detection in Multivariate Functional Data
Mohammad N. Bisheh, Che-Yi Liao, Kamran Paynabar
Multivariate functional data arise in many modern manufacturing systems, where multiple sensors record densely sampled process trajectories. Monitoring such data is challenging bec…
Stagewise Anomaly Detection for E-Transaxle Quality Monitoring Using Wavelet and STFT Features
Mohammad N. Bisheh, Rajesh Gupta, Qian Wang +5
This paper presents two interpretable machine-learning frameworks for quality screening of e-transaxle assemblies in electric vehicles: a Stagewise Wavelet Isolation Forest (SWIF)…
Tensor-on-tensor Regression Neural Networks for Process Modeling with High-dimensional Data
Qian Wang, Mohammad N. Bisheh, Kamran Paynabar
Modern sensing and metrology systems now stream terabytes of heterogeneous, high-dimensional (HD) data profiles, images, and dense point clouds, whose natural representation is mul…
A New Inventory Control Approach For Considering Customer Classes In An Integrated Supply Chain Management
Mohammad Najjartabar Bisheh, Hamid Davoudpour, G. Reza nasiri
Supply chain management is an integrated approach for planning and controlling materials, information, and finances as they move in a process which begins from suppliers and ends w…