Why Should You 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 introduces important statistical concepts and methods for making objective decisions to ensure and improve product quality.
The methods have many applications including:
This webinar provides a solid introduction of important statistical concepts and methods that are essential for making objective decisions related to product quality.
Areas Covered in the Webinar:
Who Will Benefit:
The target audience includes personnel involved in product/process development and manufacturing.
Physical CD-DVD of recorded session will be despatched after 72 hrs on completion of payment
Recorded video session
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.