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ME 498 Lecture 3.1: Inferences about Process Quality I
Online Presentations | 06 Dec 2019 | Contributor(s):: Chenhui Shao
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Feb 25 2019
Software Productivity and Sustainability for CSE and Data Science
The SIAM CSE conference seeks to enable in-depth technical discussions on a wide variety of major computational efforts on large-scale problems in science and engineering, foster the...
https://nanohub.org/events/details/1738
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Muhammad Bilal
Bilal’s research focuses on data-driven solutions for the environmental and health impact assessment of engineered nanomaterials (ENMs) using advanced machine learning/data mining and simulation...
https://nanohub.org/members/179709
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Statistical Process Control (SPC) Learning Module - Instructor Guides
Teaching Materials | 21 Jul 2017 | Contributor(s):: Southwest Center for Microsystems Education (SCME)
Statistical Process Control (SPC) is a set of tools used for continuous improvement and the assurance of quality in an active manufacturing process. This learning module introduces some of the SPC tools used by technicians and engineers, including one of the most common tools - control charts.
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Statistical Process Control (SPC) Learning Module
Teaching Materials | 20 Jul 2017 | Contributor(s):: Southwest Center for Microsystems Education (SCME)
Statistical Process Control (SPC) is a set of tools used for continuous improvement and the assurance of quality in an active manufacturing process. This learning module introduces some of the SPC tools used by technicians and engineers, including one of the most common tools - control...
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S Kiran Kadam
https://nanohub.org/members/172030
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Roger French
Roger H. French is the F. Alex Nason Professor in the Department of Materials Science and Engineering in the Case School of Engineering, Case Western Reserve University, Cleveland, Ohio. He has...
https://nanohub.org/members/81411
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Normal Distribution
Tools | 23 Aug 2011 | Contributor(s):: Ogaga Daniel Odele, Francesca Polo, Hanjun Xian, Krishna P. C. Madhavan
Simulate the normal distribution curve with varying mean and standard deviation