| Real-time History Preventing Tomorrow's
Defects Today |
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written by Dirk Dean,
Hitachi Computer Products America, Inc.
The Problem: A challenge facing
Hitachi Computer Products America, Inc. was readily available
information on the historical quality performance for the
product being run, at the time of the run. The production
schedule calls for a low volume high mix of complicated
circuit board assembles (PCBA), and to just remember the
historical defects and potential risks is difficult. The
historical information is available but is trapped in databases,
reports, and other electronic data storage locations and
is not easily available to the line operators. If the "Quality
Performance History" information was available to the operators
when they needed it, it would allow them the opportunity
to prevent potential future defects.
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| Uses of the Range Chart |
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by Marilyn & Robert Hart
All quality control professionals
are familiar with the range (R) chart as a control chart
to monitor the variability of the product. Actually, in
its normal use, the R chart monitors the total variability
of the product and the measurement system. A second use
of the R chart is to monitor the variability if the measurement
system and knowing that, the actual variability of just
the product can be found.
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How to Get More
from a Metric Like PPM-D (Parts-Per-Million Defective)
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A
Supplier Quality Engineer (SQE), across a broad range
of industries, is often the gateway for information from
suppliers regarding the conformance to specification (e.g.
Quality Acceptance Certificates or Letters) concerning
shipments entering the supply chain. Additionally, as
part of a purchase contract or working agreement, supplemental
information from the Supplier regarding the production
of parts is included with the shipment. By requesting
and monitoring the right statistics, the SQE can glean
insights into events on the ground at the supplier site
that might not be forthcoming during regular interactions.
This article delves into an example of
monitoring a simple statistic (Quality Metric), Parts-per-Million
Defective, to discover a potential process change at the
supplier, which may have been unanticipated, and how to
automate data acquisition and analysis with the goal being
maximal visibility of quality data and use of the
underlying natural distribution of the Quality Metric
to enhance the relationship with your supplier.
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| Quality Q&A: P Charts are Best
for Yield Data |
Q. Which is the better
chart to use for analysis of yield data: the p-chart or
the individual-moving range chart? I am trying to better
understand the changes in the weekly test yields on our
electronic product lines. I've used both p-charts and
individual charts with different results. The p-chart
seems much more sensitive and provides many more out-of-control
indications than the individual chart.
A. Your observation
that the p-chart is more sensitive is correct and statistically
expected. The p-chart is designed for data in the form
of proportions and takes into account the sample size
when calculating the control limits. As the sample size
goes up, the sensitivity of all control charts increases.
This increased sensitivity means that the p-chart is better
able to detect process changes as they occur.
Although it is technically
possible to make an individual chart using the individual
yield proportions, it is not the correct chart to use
for this type of data, as explained below.
Read
on...
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| Statit Software Releases Statit e-QC
4.0 |
Statit Software is pleased to announce the
release of Statit
e-QC 4.0, the latest version of its leading web solution
for process and performance improvement initiatives.
Hundreds of organizations worldwide use
Statit solutions to access the information they need to
monitor, analyze, and improve key quality metrics.
This new release of Statit e-QC contains
many key enhancements including:
- Enhanced usage reporting tracks activity
and users in the application
- Run Statit e-QC reports directly from
links on your intranet pages without having to log into
the application
- Password security enhancements provides
for additional levels of password sophistication
- Login pass-throughs allows login information
from intranet pages or desktop application to be passed
directly to Statit e-QC.
Statit e-QC 4.0 is now available.
For more information on the new release or a short WebEx
demonstration of these new capabilities, contact Statit
Software at (800) 478-2892 or email info@statit.com.
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| Something You'd Like to See? |
Is there a topic you'd like us to discuss?
Have a process improvement question? If so, submit a topic
request and we'll see that your topic gets covered in
an upcoming edition of the Statit Bulletin.
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| First Pass Yield |
In
this complimentary webinar,
Guy March, Vice President of Professional Services for
Statit Software, will discuss First Pass Yield. We
will look at different charting solutions and examine
different ways to better understand underlying issues.
First Pass Yield is an important measure, whether we are
talking about a process step pass, system pass, or Rolled
throughput yield. We will examine these and associated
questions using Statit
e-QC.
By attending this webcast, you will:
- Examine several methods of viewing First Pass Yield
- Understand how to get to the underlying causes of
FPY issues
- Use Statit e-QC to understand failures and potential
sources of yield loss
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