Quality Improvement 2020 - Statistical Methods for Quality Improvement

His webinar introduces important statistical concepts and methods for assessing and ensuring product quality.
The methods include: Statistical Process Control, Process Capability Assessment, Regression Modeling, Design of Experiments, Hypothesis Testing, and Measurement Systems Assessment.
The methods have many applications including:
Ensuring that I can effectively measure key characteristics
Determining how well my process/product meets requirements
Knowing when a process or system is behaving consistently (stable) or differently (unstable) than before
Uncovering which key inputs to my process affect product performance or customer satisfaction
Predicting future outcomes using a predictive model
Comparing groups of data when random (natural) variation is present?
Ensuring adequate sample sizes for making decisions
Why you should Attend: Many companies are swimming in data yet raw data is mostly useless without methods to turn this data into useful and actionable information. Those individuals and companies that make best use of the available data achieve a competitive advantage by optimizing their operations and making superior decisions. Companies that fail to take advantage of data are resigned to chasing rather than leading in this information age.
This webinar provides a solid introduction of important statistical concepts and methods that are essential for making objective decisions related to product quality. These methods are based on process data and allow optimal decisions to be made. Participants will understand the purpose and value provided for each of the methods discussed and understand their place in a data driven quality system.
In a relatively short session, participants will receive a solid overview of essential quantitative methods for developing process understanding, assessing current performance, and identifying methods for process improvement. Following this session, participants should be immediately be in a position to make improvements by identifying applications in their own operations.
Areas Covered in the Session:
Variation & Quality
Measurement Systems Assessment
Process Stability/Statistical Process Control
Process Capability Assessment
Predictive Models (Design of Experiments & Regression Modeling)
Hypothesis Testing for Decision Making
Examples & Applications
Who Will Benefit:
Quality Personnel
Manufacturing Personnel
Operations / Production Managers
Production Supervisors
Supplier Quality personnel
Quality Engineering
Quality Assurance Managers, Engineers
Process or Manufacturing Engineers or Managers
Speaker Profile
Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. He has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control. Mr. Wachs is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Mr. Wachs regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.
He has an M.A. in Applied Statistics from the University of Michigan, an M.B.A, Katz Graduate School of Business from the University of Pittsburgh, 1992, and a B.S., Mechanical Engineering from the University of Michigan.
Event link:
https://www.compliance4all.com/webinar/--502852LIV...
Contact Info
Compliance4all
Email: support-AT-compliance4All.com
Phone: +1-800-447-9407
Website: https://www.compliance4all.com/