Statistical Methods for Quality Improvement

Product Id IQW19B0230
Speaker Steven Wachs
Level Intermediate
Duration 90 Mins
  • Description
  • Why should you attend
  • Areas covered
  • Who will benefit
  • Speaker

This webinar introduces important statistical concepts and methods for making objective decisions to ensure and improve product quality. The methods have many applications including:

  • Determining how well my process/product meets requirements
  • Knowing when a process or system is behaving consistently or differently than before
  • Uncovering which key inputs to my process affect product performance or customer satisfaction
  • Ensuring that I can effectively measure what I need to
  • Comparing groups of data when a random (natural) variation is present
  • Predicting future outcomes using a predictive model

The methods introduced include: Statistical Process Control, Process Capability Assessment, Regression Modeling, Design of Experiments, Hypothesis Testing, and Measurement Systems Assessment.  

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 the best use of the available data achieve a competitive advantage by optimizing their operations and making processor 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. Following the webinar, the participants will possess an understanding of the purpose and benefits of critical methods including:

  • Statistical Process Control
  • Process Capability Assessment
  • Regression Modeling
  • Design of Experiments
  • Hypothesis Testing
  • Measurement Systems Assessment
  • Variation & Quality
  • Process Stability/Statistical Process Control
  • Process Capability Assessment
  • Predictive Models (Regression & Design of Experiments)
  • Hypothesis Testing for Decision Making
  • Measurement Systems Assessment
  • Examples & Applications
  • Quality Personnel
  • Manufacturing Personnel
  • Operations/Production Managers
  • Production Supervisors
  • Supplier Quality personnel
  • Quality Engineering 
  • Quality Assurance Managers, Engineers
  • Process or Manufacturing Engineers or Managers
Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve 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.  
 
Steve 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 to estimate and reduce warranty. In addition to providing consulting services, Steve regularly conducts workshops in industrial statistical methods for companies worldwide.
 
Education:
M.A., Applied Statistics, University of Michigan, 2002
M.B.A, Katz Graduate School of Business, University of Pittsburgh, 1992
B.S., Mechanical Engineering, University of Michigan, 1986

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