Statistical Methods for     Process Control

You Have Data ... So Now What?

Many companies face a unique dilemma: they’re data rich but information poor. Now more than ever, manufacturers are swimming in data, but all of this information bears little value without methods to turn it into actionable insights. The companies that fail to leverage their data are chasing (rather than leading) this information age, while their competitors are passing them by, extracting every morsel of value from their data and using it to inform critical operational decisions.

 —> How? With statistical methods like SPC, process optimization & capability assessments. Without them, most manufacturers are missing huge opportunities to:

  • Design and develop products cost-effectively
  • Reduce waste
  • Collect data in more efficient ways– and use it wisely
  • Detect potential manufacturing issues before they blow up
  • Base decisions on facts, not hunches, via properly analyzed data

This webinar exposes the essential statistical concepts and methods that manufacturers can use to intelligently optimize products, processes, and decisions. Following this session,  participants will immediately be able to identify and implement statistical methods for process control and product optimization that will benefit their own operations.

In under an hour, attendees will gain a fresh perspective on:

      • Process and Product Optimization
      • Measurement Systems Assessment
      • Process Stability/Statistical Process Control
      • Process Capability Assessment
      • Predictive Models (Design of Experiments)

Invite your Production, Operations & Quality teams including:

  • Plant, Operations, & Production Managers and Supervisors
  • Process or Manufacturing Engineers & Managers
  • Quality Personnel, including QA, Supplier Quality and Quality Engineering 
  • Design Engineers, R&D Personnel, and Continuous Improvement specialists

About the Panelist

allise-wachs-phd

Allise Wachs, Ph.D.

President, Integral Concepts, Inc.

  • 20 years of experience in the application of statistical methods to optimize product designs and manufacturing processes
  • Areas of expertise include designed experimentation, reliability analysis, general statistical methods, statistical process control, measurement system assessment, and stochastic optimization

Credentials and Professional Honors

  • Has been an adjunct professor, College of Engineering at the University of Michigan
  • Ph.D., Operations Research, University of Michigan, 1998
  • M.S., Industrial and Operations Engineering, University of Michigan, 1993
  • Graduate Program in Statistics, University of Chicago, 1989-1991
  • M.A., Statistics, University of Michigan, 1987
  • B.S., Mathematics, Statistics, University of Michigan, 1986