{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:37:03Z","timestamp":1760243823604,"version":"build-2065373602"},"reference-count":12,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2011,7,6]],"date-time":"2011-07-06T00:00:00Z","timestamp":1309910400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Plasma process tools, which usually cost several millions of US dollars, are often used in the semiconductor fabrication etching process. If the plasma process is halted due to some process fault, the productivity will be reduced and the cost will increase. In order to maximize the product\/wafer yield and tool productivity, a timely and effective fault process detection is required in a plasma reactor. The classification of fault events can help the users to quickly identify fault processes, and thus can save downtime of the plasma tool. In this work, optical emission spectroscopy (OES) is employed as the metrology sensor for in-situ process monitoring. Splitting into twelve different match rates by spectrum bands, the matching rate indicator in our previous work (Yang, R.; Chen, R.S. Sensors 2010, 10, 5703-5723) is used to detect the fault process. Based on the match data, a real-time classification of plasma faults is achieved by a novel method, developed in this study. Experiments were conducted to validate the novel fault classification. From the experimental results, we may conclude that the proposed method is feasible inasmuch that the overall accuracy rate of the classification for fault event shifts is 27 out of 28 or about 96.4% in success.<\/jats:p>","DOI":"10.3390\/s110707037","type":"journal-article","created":{"date-parts":[[2011,7,6]],"date-time":"2011-07-06T11:15:00Z","timestamp":1309950900000},"page":"7037-7054","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Real-Time Fault Classification for Plasma Processes"],"prefix":"10.3390","volume":"11","author":[{"given":"Ryan","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan"}]},{"given":"Rongshun","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan"}]}],"member":"1968","published-online":{"date-parts":[[2011,7,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Hong, SJ, and May, GS (2003). Neural network based time series modeling of optical emission spectroscopy data for fault detection in reactive ion etching. Proc SPIE, 5041.","DOI":"10.1117\/12.485230"},{"key":"ref_2","unstructured":"Bunkofske, R, Ambrozic, C, and Sanders, M (2001, January 6\u201311). The Use of Multivariate Statistical Techniques in Semiconductor Manufacturing. Banff, AB, Canada."},{"key":"ref_3","unstructured":"Ison, AM, Li, W, and Spanos, CJ (1997, January 6\u20138). Fault Diagnosis of Plasma Etch Equipment. San Francisco, CA, USA."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Love, PL, and Simaan, M (1989, January 25\u201326). A Knowledge-Based System for the Detection and Diagnosis of Out-of-Control Events in Manufacturing Processes. Arlington, VA, USA.","DOI":"10.23919\/ACC.1989.4790591"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1109\/66.210656","article-title":"Automated malfunction diagnosis of semiconductor fabrication equipment: A plasma etch application","volume":"6","author":"May","year":"1993","journal-title":"IEEE Trans. Semiconduct. Manuf"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1109\/3476.650961","article-title":"Equipment fault detection using spatial signatures","volume":"20","author":"Gardner","year":"1997","journal-title":"IEEE Trans. Compon. Packag. Manuf. C"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1002\/cem.689","article-title":"Application of PARAFAC2 to fault detection and diagnosis in semiconductor etch","volume":"15","author":"Wise","year":"2001","journal-title":"Chemometrics"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1109\/66.983447","article-title":"A wavelet-based procedure for process fault detection","volume":"15","author":"Lada","year":"2002","journal-title":"IEEE Trans. Semiconduct. Manuf"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Gallagher, NB, and Wise, BM (1997, January 26\u201328). Development and Benchmarking of Multivariate Statistical Process Control Tools for A Semiconductor Etch Process: Improve Robustness Through Model Updating. Hull, UK.","DOI":"10.1016\/S1474-6670(17)43143-0"},{"key":"ref_10","unstructured":"Anderson, H, Gunther, S, and Fry, B (2001, January 9\u201312). Plasma Etch Endpoint and Fault Detection Along with UV-Vis Absorption Spectroscopy from a Single Compact Solid State Detector. Pennsylvania State University, State College, PA, USA."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"778","DOI":"10.1149\/1.1623772","article-title":"Simultaneous fault detection and classification for semiconductor manufacturing tools","volume":"150","author":"Goodlin","year":"2003","journal-title":"J. Electrochem. Soc"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"5703","DOI":"10.3390\/s100605703","article-title":"Real-time plasma process condition sensing and abnormal process detection","volume":"10","author":"Yang","year":"2010","journal-title":"Sensors"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/11\/7\/7037\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:56:40Z","timestamp":1760219800000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/11\/7\/7037"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011,7,6]]},"references-count":12,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2011,7]]}},"alternative-id":["s110707037"],"URL":"https:\/\/doi.org\/10.3390\/s110707037","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2011,7,6]]}}}