2^3 Design
Mathews Malnar and Bailey, Inc.

Quality engineering, applied statistical consulting,
and training services for R&D, product, process,
and manufacturing engineering organizations.
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The Quality Engineers Network (QEN) is sponsored by Geauga Growth Partnership. Meeting announcements are in reverse order with the most recent meeting at the top. All meetings are free and everyone is welcome to present or to recommend a topic. Please e-mail me at paul@mmbstatistical to be added to the mailing list.

Use these meetings to earn recertification units (RUs) for your ASQ certifications.


Process Capability, 11 October 2019, 7:30-9:00AM, at GGP
At this month's QEN meeting we will continue our discussion of process capability. We'll review the basic process capability statistics Cp, Cpk, Pp, and Ppk and their confidence intervals and how to interpret them. We'll use those observations to develop sample size guidelines for process capability studies. We'll also look at methods of assessing distribution shape (the common process capability statistics require a normal distribution) and the use of transformations to convert non-normal distributions back to normal distributions.


Process Capability, 13 September 2019, 7:30-9:00AM, at GGP
At this month's QEN meeting we will take up a discussion of process capability. We'll review the basic process capability statistics Cp, Cpk, Pp, and Ppk and then discuss their use, interpretation, and the conditions required for their validity. We'll start a more advanced discussion of how to do process capability under complicated conditions, such as for non-normal distributions, and we'll take up that topic again at the October meeting.


Design and Analysis of Gage R&R Studies (Part 2), 9 August 2019, 7:30-9:00AM, at GGP
At last month's QEN meeting we started a discussion of the design and analysis of gage R&R studies. We'll take up the topic again this month by going into more details of the classic operator by part crossed experiment, paying particular attention to the number of and selection of operators, parts, and trials for the study. We'll also discuss extensions of the classic design including nested designs, designs with additional study variables (i.e. "expanded" designs), and studies with attribute responses. We may pick up one or more of these advanced topics in a third session.


Design and Analysis of Gage R&R Studies (Part 1), 12 July 2019, 7:30-9:00AM, at GGP
Measurement reliability is determined by measurement accuracy which is established by calibration and measurement precision which is quantified in a gage repeatability and reproducibility or GR&R study. If a measurement is both accurate and precise then it may be appropriate for its intended purpose.

The best known GR&R study design is the classic operator by part crossed design with 3 operators, 10 parts, and 2 trials. Most references don't give any guidance about why those numbers are used but good guidance is presented in books like Design and Analysis of Gauge R&R Studies by Burdick, Borror, and Montgomery. At this month's QEN meeting we will talk about how to choose the number of operators, parts, and trials for your GR&R studies and we'll also discuss other issues like randomization and blocking in the experiment design, consequences for the interpretation of the GR&R study report, and how to integrate instrument type, measurement procedure, the use or not of a jig or fixture, and other variables into your GR&R study design. If we have time, we'll start talking about the analysis and interpretation of GR&R studies but we'll resume that discussion in more detail at the next meeting.


A Quality Cost Interpretation for Acceptance Sampling Plans, 14 June 2019, 7:30-9:00AM, at GGP

At last month's QEN meeting we discussed how to design attribute and variable sampling plans to control defective rates relative to specification limits. The design of these plans required us to specify AQL (acceptable quality level) and RQL (rejectable quality level) conditions that lead to a unique sample size and acceptance criterion. Although these methods are well known and easily understood by quality engineers, the AQL and RQL concepts can be too abstract for others (especially managers) so an alternate, easier to understand approach is desired. The solution comes by applying quality cost methods to the acceptance sampling problem. By specifying the necessary cost inputs (material and labor cost, inspection cost, and external failure cost) we can express the performance of a sampling plan in terms of its net income and cost of poor quality (COPQ). This approach also allows for easy-to-understand comparisons between different sampling plans such as the special cases of no inspection and 100% inspection. Even when the cost information isn't available for a specific process, understanding the general behavior of quality cost in acceptance sampling can provide significant insight into the benefits and risks of the method.


An Introduction to Acceptance Sampling for Attributes and Variables, 10 May 2019, 7:30-9:00AM, at GGP
Acceptance sampling in quality control is a huge topic but the simplest acceptance sampling methods are pretty easy to understand. In a classic acceptance sampling for attributes (i.e. for pass/fail inspection) application a single random sample is drawn from a lot and inspected for defectives. If the number of defectives in the sample is less than or equal to a critical value, called the acceptance number, the lot is accepted. If the number of defectives in the sample is greater than the acceptance number then the lot is rejected. A similar strategy is used for measurement responses by comparing the mean of a random sample to a critical acceptance value.

Attributes and variables sampling plans are usually designed to meet two input criteria which may be:
1) Provide a high probability of accepting good product and a low probability of accepting bad product
2) Provide a high probability of accepting good product with a zero acceptance number sampling plan
3) Provide a low probability of accepting bad product with a zero acceptance number sampling plan

These plans provide different protections for the manufacturer and for the consumer so it is crucial to understand what you're getting when you choose a sampling plan. At this month's QEN meeting we will discuss the design of simple attributes and variables sampling plans and we'll talk about some of the issues in setting up and operating them.


Inaugural Meeting: A Survey of Quality Engineering Methods, 12 April 2019, 7:30-9:00AM, at GGP
The first QEN meeting will be held on Friday, April 12th, from 7:30-9:00 AM at GGP's location in Newbury Business Park when Paul Mathews and Rick Ales will present a survey of quality engineering methods for the purpose of assessing the interests and needs of participants. Learn about the program and facilitators Paul Mathews and Rick Ales here. To attend email info@geaugagrowth.com or register here.

The topics to be discussed are but are not limited to:




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