Liang Hou

TL;DR: In this article, the societal impact of additive manufacturing from a technical perspective is reviewed, and an abundance of evidences are found to support the promises of additive-manufacturing in the following areas: (1) customized healthcare products to improve population health and quality of life, (2) reduced environmental impact for manufacturing sustainability, and (3) simplified supply chain to increase efficiency and responsiveness in demand fulfillment.

TL;DR: In this paper, the impact of additive manufacturing (AM) technology on the aircraft spare parts supply chain has been evaluated based on the well-known supply chain operation reference model and three supply chain scenarios are investigated; namely, conventional (as-is) supply chain, centralized AM supply chain and distributed additive manufacturing supply chain.

TL;DR: The results demonstrate that the two-channel (Ay, Az) strategies based on signal processing and feature ranking/selection give the best performance in classification of the stable and unstable tests.

TL;DR: A novel feature extraction approach for chatter detection by using image analysis of dominant frequency bands from the short-time Fourier transform (STFT) spectrograms to indicate the efficiency of the time-frequency image features from dominant Frequency bands for chatter Detection and their better performance than the time domain features and wavelet-based features in terms of their separability capabilities.

TL;DR: An intelligent chatter detection method based on image features and the support vector machine is introduced and presents a better classification performance than the two additional methods, indicating the efficiency of the proposed method for chatter detection.