Applied Statistics for product and process evaluation in design and manufacturing


John Robinson

Evaluating product and processes is an imperative for almost all design and/or manufacturing companies. These are the reasons for which this evaluation needs to be made:

oManaging risks

oValidation of processes

oEstablishing product/process specifications to QC to such specifications

oMonitoring compliance to such specifications

Lack of proper and thorough grasp of and correct implementation of statistical methods leads a company to having to face significant increases in its complaint rates, scrap rates, and time-to-market. As a result, such companies churn out poor quality in their products, leading to lowered customer satisfaction levels, severely impacting their bottom line.

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A learning session to help understand statistical methods

In order to help professionals in process and manufacturing meet challenges associated with statistical methods with greater confidence, GlobalCompliancePanel, a highly reputable provider of professional trainings for the regulatory compliance areas, is organizing a highly educative two-day seminar on the topic, Applied Statistics, with Emphasis on Verification, Validation, and Risk Management, in R&D, Manufacturing, and QA/QC.

John N. Zorich, Statistical Consultant & Trainer, Ohlone College & SV Polytechnic, will be the Director at this seminar, which has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion.

To enroll for this seminar, participants can log on to

Hands on approach to statistical methods toolbox

The aim of this seminar is to offer a hands-on approach by which the participants could comprehend the ways to interpret and use a standard tool-box of statistical methods that consist of confidence intervals, t-tests, Normal K-tables, Normality tests, confidence/reliability calculations, AQL sampling plans, measurement equipment analysis, and Statistical Process Control.

The Director will equip the seminar delegates with clarity on how to accurately employ and administer statistical methods, which can be used as a launchpad for introducing new products.

This two-day session will help participants understand the proper way of avoiding issues relating to these aspects of statistical methods. John will explain how to apply statistics to manage risk in R&D, QA/QC, and Manufacturing by giving real life examples derived mainly from the medical device design/manufacturing industry.

The 2-day seminar explains how to apply statistics to manage risks and verify/validate processes in R&D, QA/QC, and Manufacturing, with examples derived mainly from the medical device design/manufacturing industry. The flow of topics over the 2 days is as follows:

ISO standards and FDA/MDD regulations regarding the use of statistics.

Basic vocabulary and concepts, including distributions such as binomial, hypergeometric, and Normal, and transformations into Normality.

Statistical Process Control

Statistical methods for Design Verification

Statistical methods for Product/Process Qualification

Metrology: the statistical analysis of measurement uncertainty, and how it is used to establish QC specifications

How to craft “statistically valid conclusion statements” (e.g., for reports)

Summary, from a risk management perspective

Almost all design and/or manufacturing companies evaluate product and processes either to manage risks, to validate processes, to establish product/process specifications, to QC to such specifications, and/or to monitor compliance to such specifications.

The various statistical methods used to support such activities can be intimidating. If used incorrectly or inappropriately, statistical methods can result in new products being launched that should have been kept in R&D; or, conversely, new products not being launched that, if analyzed correctly, would have met all requirements. In QC, mistakenly chosen sample sizes and inappropriate statistical methods may result in purchased product being rejected that should have passed, and vice-versa.

This seminar provides a practical approach to understanding how to interpret and use more than just a standard tool-box of statistical methods; topics include: Confidence intervals, t-tests, Normal K-tables, Normality tests, Confidence/reliability calculations, Reliability plotting (for extremely non-normal data), AQL sampling plans, Metrology (i.e., statistical analysis of measurement uncertainty ), and Statistical Process Control. Without a clear understanding and correct implementation of such methods, a company risks not only significantly increasing its complaint rates, scrap rates, and time-to-market, but also risks significantly reducing its product and service quality, its customer satisfaction levels, and its profit margins.


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