Optimizing Target Weights for Foods and Beverages

Speaker

Instructor: Steven Wachs
Product ID: 704366
Training Level: Intermediate

Location
  • Duration: 75 Min
This training program will elaborate factors affecting the target weight decision and help determine the tolerable risks of under-filling and the costs of over-filling. Attendees will gain an understanding of process stability and process capability concepts and methods for process optimization.
RECORDED TRAINING
Last Recorded Date: Feb-2024

 

$249.00
1 Person Unlimited viewing for 6 month info Recorded Link and Ref. material will be available in My CO Section
(For multiple locations contact Customer Care)

$299.00
Downloadable file is for usage in one location only. info Downloadable link along with the materials will be emailed within 2 business days
(For multiple locations contact Customer Care)

 

 

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Why Should You Attend:

In order to maximize profitability while complying with government regulations regarding net package contents, food manufacturers and packagers must achieve an optimal balance. Consistent overfilling to minimize risk is inefficient and sacrifices profitability, while aggressive filling practices result in significant risks of non-compliance with net contents regulations leading to potential penalties, loss of reputation, and impaired customer relations. Statistical process control and process capability methods may be utilized to determine optimal targets for product fill weights or volumes for a given process. Subsequent focused efforts to minimize variation will allow the target to be further optimized, resulting in less waste without compromising risk.

This webinar will illustrate the use of statistical process control and process capability methods for optimizing product target weights given the inherent tradeoffs between minimizing overfills and minimizing risks of non-compliance to government regulations. This webinar will also briefly discuss methods for reducing excessive variability which may be necessary to achieve optimal results.

Learning Objectives:

  • Understand factors affecting the target weight decision

  • Determine the tolerable risks of under-filling and the costs of over-filling

  • Estimate the proportion of non-conforming product
  • Understand process stability and process capability concepts
  • Determine and justify targets for product weights
  • Understand methods for process optimization

Areas Covered in the Webinar:

  • U.S. regulatory requirements for net contents of foods (NIST Handbook 133)

  • Estimating the risk of non-compliance
  • Assessing process stability
  • Process capability
  • Z values and proportion non-conforming

  • Determining target weights
  • Process optimization

Who Will Benefit:

  • Manufacturing Personnel
  • Quality and Process Engineers
  • Plant Operations Personnel
  • Plant Management
  • Quality Management
  • Personnel utilizing data to make decisions and improve processes
Instructor Profile:
Steven Wachs

Steven Wachs
Principal Statistician, Integral Concepts, Inc

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.

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