QA6640 Chat Room Transcript
January 31, 2007
Prof. Atkins 20:18:18
The chat room is closed for this evening. It will reopen next Wednesday at 7:35
PM.
J Scott 20:14:50
Good Night All
Rich Weaver 20:12:23
good night!
Prof. Atkins 20:11:48
If there are no questions, we can close the chat room for this evening.
Prof. Atkins 20:05:49
The thirty-minutes are now up. Responses posted after this message appears will
not be evaluated for chat room participation credit.
If you have a question, you may ask it at this
time.
el hamraoui hanane 20:03:34
Hanane El Hamraoui
helhamra@spsu.edu
I used to manage a clothing store where we get lots of cloths in a daily basis
from national clothing manufacturers (suppliers)
In our warehouse a quality control process has to be done to detect any
nonconformities in the lots received. For this purpose the quality department
use the p charts to estimate the percent defective that does not satisfy one or
more of the product specifications of all lots shipped.
We use the percent nonconforming as 100% times the fraction nonconforming of
all lots shipped to the warehouse.
komic 20:02:57
The company I work for is Cardinal Health Snowden Pencer Products. We
manufacture surgical instruments. Some of the products is packaged in the Clean
Room environment. The Clean Room is classified as ISO Class 8. This mean that
maximum permitted airborne particle (particle size 0.5 micrometers) per cube
meter is 3, 520,000.00.
After initial classification, the air
cleanliness must be controlled and maintained. To do so we established the
upper control limit by collecting the data over 6 months period.
Samples were taken once a month at nine locations within clean Room.
We used x-bar chart for this purpose. As per
Bossert text “X-bar and R-charts are used when there are subgroups or data that
are collected”.
We took samples at nine locations as determined
for the size room we had (aprox 52 sq.meters).
At each sampling location 5 single volumes were
taken.
The particle concentration at each location obtained from the measurements were
recorded.
Average particle per cubic ft was calculated for each location.
Overall mean of the averages were calculated.
Average of averages was calculated after six months data collection.
Standard deviation was calculated for the six months averages.
Upper control limit was determined as average of averages + 3 st. deviation.
The benefit of using this chart is simple
control of the air cleanliness of the Clean Room. Each month we are taking
samples at all nine locations, calculate average and monitor cleanliness by
using this chart and established control limit.
Michael Ginn 20:02:38
Michael Ginn
Email: ginnmichael@hotmail.com
1. X-bar and range/standard deviation charts
The company I will reference to is a tier one
automotive supplier (Transmission Supplier to the Big-Three). I worked there as
a SPC technician. This company is a fairly large plant (200-250 employees).
They supplied a total of 12 different models of transmissions. Being a SPC technician
I directly controlled and monitored the control charts used throughout the
plant.
Through out the plant we used SPC to control all critical characteristics.
These characteristics could be a bore position, bore diameter, or even a
depth/length. These X-bar and range/standard deviation charts we used so any
out of control feature could be caught faster. The chart has a target (x-bar)
and upper and lower control limits. The target and control limits would only be
adjusted if a process change justified a recalculation. Very rarely was a chart
recalculated. The operators of the processes where trained that process should
stay with-in its limits. Any out of control processes were shut-down for a
pending investigation. Also, trends or runs would justify a process being
shut-down. A trend or run is where an operator would seven or more points
moving in the same direction. The methodology for this is that if the process
continues to run in the same fashion the trend/run will eventually go out of
control. Upon implementation of the X-bar and range/standard deviation charts
processes where controlled much better. This impart lowered scrap costs also.
The charts made the operators visual aware of how their machine was running.
Before the charts the operator could not tell you how their machine was running
other then it’s in tolerance. A good example of one of the features controlled
by X-bar and range/standard deviation chart is the dowel bore. The
specification for this bore is 12.037 +/- 0.008. The x-bar would normally be
around nominal (12.037) because the bore was cut with a diamond reamer, and the
limits would be +/- 0.006. If I remember correctly?
Joel 20:02:23
QA6640
Joel Centeno
jcenteno@twt.com
Company: Boston Scientific
Boston Scientific engages in the development, production, and marketing of a
variety of medical devices for cardiovascular, endosurgery, and neurological
use. The specific division I worked for was the Grinding & Straightening
Subassembly Guidewire Business Unit with focus on endoscopy, urology and
peripheral vascular medical device product lines.
Type of Control Chart: p-chart
This type of control chart looks at the percent defective of all lots shipped
Example: Nitinol Guidewire spool monitoring
In the unit that I worked, we manufactured about
6,000 guidewires per day. Before wires were ground, they needed to go through a
straightening process and heat treatment to achieve the desired mechanical
properties. The straightening operation began with a spool of wire (about 100
yards of wire wound in a single spool). With such mass production, spools of
wire came in from supplier at a very fast rate (almost 500 spools per day per
supplier). The receiving inspection department sampled each lot of units
shipped using a specific sampling plan. I believed they sampled about 50 spools
or so. This was not a destructive test and it was relatively simple acceptance
criteria. If they starting unwinding the wire from the spool and upon the first
few yards of wire they saw kinks, bends, or inability of the wire to retain
memory the spool was rejected. Based on the amount rejected and the sampling
plan, the lot of 500 spools would pass, be inspected 100%, or returned to the
vendor. On a weekly basis, the quality engineers would gather the data of the
of defects found in one lot and would accumulate the data for a 3 month period
for all lots for one supplier and created p-charts for each supplier (about 3 I
believe). The data serve greatly in determining the consistency of each
supplier and making decisions of any corrective actions needed for supplier to
send us better material. It also allowed us to allocate resources in working
with the suppliers who showed the most problems.
Natasha_Romero 20:02:11
Natasha Romero
nromero@spsu.edu
p Chart
1. I currently work for Sandia National
Laboratory. We are a contractor to the Department of Energy and Department of
Defense. Our mission is national security.
2. The p chart as described by Bossert, “is used to estimate the percent
defective of all lots shipped.” The use of this enables the customer or in the
case of the Shipping and Receiving Department which is discussed below to make
decisions about how the process of production or performance. This type of
chart can help identify areas for improvement.
3. In the Shipping and Receiving Department measurement and analysis is
conducted through the use of an electronic system which collects data about
when an item is received at Sandia National Laboratories and when the item has
reached its final destination. These metrics are used to produce a p Chart
which shows the percentage of time it takes for an item to be delivered for a
particular route. This p Chart enables management/supervisors to track and
monitor the disbursement of items to their final destination. Through the
review of the p Chart management/supervisors could potentially identify a
delivery route that is taking longer than average to deliver items to their
final destination or a route that is taking less than average to deliver items
to their final destination. Management/supervisors can then investigate into
the reason as to why these types of behavior are happening and improve their
route system so that the delivery time of an item from the time it is received
at Sandia National Laboratories and the time it reaches its final destination
is as close to the average time deliver time. It could also be discovered that
the route for delivery is going to have a lower or high delivery time due to
some type of extenuating circumstances such as the route final destination is
located at a 20 min drive from the shipping/receiving warehouse in comparison
to the other routes which only have a 5 – 10 min drive.
Bossert, James L. The Supplier Management
Handbook Sixth Edition. ASQ Customer-Supplier Division.
gstevens 20:01:50
Module 3 Discussion
Glenn Stevens
Email: Anandale@comcast.net
Date: Wednesday, January 31, 2007
Company Selected: Home Depot, this company is a major retailer of home
improvement products. Most of their decisions are based on sales data information.
That is information is collected daily from the 1800 stores, processes and then
redistributed to the business end user community to make decisions.
Chart Type: The chart type selected is the X-bar
and range/standard deviation chart. This type of chart allowed data to be
collected in lots and averages determined, upper and lower limits (range) and
standard deviations derived and the actual or observed data values compared
against these threshold values to determine variances. Such variances allow for
analysis to determine root cause.
Example: This example examines the use of the
chart type in collecting daily sales data for the company’s stores and
performing quality measurements to ascertain on time arrival of the sales data
and the accuracy of the sales data.
A software program was developed that calculated
the moving daily average of the sales for stores based on the sales data for
the past 5 weeks for the same day as well as the daily range. That is the
average was calculated based on the last 5 same day of the week. Also the
standard deviations were also calculated. The sales amount from each of the
stores received was then compared against the average for the last 5 days
(X-bar). Additionally the actual sales amount for each store was calculated and
this had to be within 4 standard deviations. The range was also calculated and
compared with the reference range.
Benefits
Because the measurements were automated, stores were easily identified that
exceeded any of the three threshold values. Based on the magnitude of the
difference between the actuals and the average or the falling outside the
defined range, specific actions would be taken. The greatest value was that the
data processing department was able to advise their end user customer that the
data to be supplied had questionable data before they actually encountered it.
These stores whose data were outside the thresholds were contacted to determine
the cause. Over time it was seen that certain stores were showing a pattern.
For instance it was discovered one store in Hawaii and an old modem which had
problems in transmitting the data. In other cases, the variance could be
explained. A store was closed because the president was visiting the area, and
hence had to be closed impacting sales. Other discoveries revealed a shooting
occurred at the store, a fire was at the store, or a weather related event
occurred. One problem however was that because the average was moving, the
abhorrent values also influenced the new averages. Most importantly, the method
allowed for early detection of a problem before the data was passed to the end
user customer without knowing, allowed the supplier (store) to be contacted to
determine root cause and to take measures where necessary to prevent the
recurrence of the cause of the problem where possible.
J Scott 20:00:22
I previously worked for Delta Air Lines in the continuous improvement group. We
were examining a bearing machining process due to the fact that landing gear
bearings received from the machine shop were either getting stuck during
installation or could not achieve the tolerance for the .001 interference fit.
We started our analysis by checking each bearing coming off the large lathe
that was being used to machine the mating surface. We used the Individual and
moving range chart on a initial sample of 12 bearings. The IMr chart chart uses
individual points plotted on a chart. Upper and lower spec limits are used to
set the limits. The range is measured to determine the variation between
points. The individual and moving rang chart showed that 4 of the 12 bearings
had exceed the upper control limits at various stages. To bring the process
into control, we developed a standardized procedure for machining and checking
the bearings. We also started checking the bearings after they had been cooled
to about 65 degrees, due to the cooler environment where they were installed.
Another run of 12 bearings showed that we had stabilized the process but we had
too much variation in the process. We developed a procedure for chucking the
bearings in the fixture and also ensured that our gauge was calibrated. After
another run of 12 bearings, we had brought the process into a sufficient amount
of control. All Individual points were within control limits and the range
(variation) between points was also reduced.
The control chart enabled us to more effectively
analyze our process without a shotgun approach to problem solving. By using the
control limits, we were able to tell when we had sufficiently brought the
process into stability. After, the machining process was stable, we were able
to make adjustments to the process to improve the machining of the bearings.
The results were very favorable with very few complaints. The benefits of the
analysis showed that temperature and the lathe bearing fixture was inducing
variation into the process.
Rich Weaver 19:59:40
Having the supplier provide data can be beneficial for both parties; the
supplier provides documented evidence that their process is in control, and the
customer develops a level of confidence that the source is monitoring
themselves, and is capable of detecting a mean shift or increased variability,
and will take corrective action before discrepant parts are shipped.
Recently, we experienced a quality problem with
the front axle drive shafts (FADS). The FADS connect the transmission and the
front hubs. The correct diameter of the lip of the drive shaft (where it mates
to the transmission) is a critical characteristic. Too large, and the FADS will
not properly snap into the transmission. Too small, and there is the potential
for leaks or premature wear.
There were a number of complaints in a short
period of time about the drive shafts coming out of the transmission. In all
cases, the lip of the drive shaft had not been fully seated. There are a number
of variables in our own process that can affect this operation; correct
alignment of the FADS relative to the transmission is critical. This is
complicated by the fact that there are over 30 “body trucks”, and variation in
the body trucks can cause improper alignment.
As is often the case, the consensus among the
plant floor people was that the problem was with the shafts. (There had been no
revisions to the trucks in several months.) Source was contacted, and sent in a
representative. The shafts that he examined were within specs.
Things were at a standoff until our plant asked
for data from the supplier on the dimension in question. They have a strong SPC
orientation, and were able to provide historical data, in the form of X-bar and
R charts, which demonstrated exceptional control. The source representative was
able to show that the sample means were consistently within the control limits,
and that the sample ranges were in control as well. A (GM Central Office) Supplier
Quality rep visited the supplier facility, and was able to vouch for the
controls in place.
In conclusion, it’s hard to argue with data.
They were able to provide proof that there was only common cause variation in
the size of the drive shaft diameter over time. Besides providing evidence for
this particular problem, their use of data and SPC techniques to monitor their
processes was impressive and instructive to the production organization in our
own plant.
By the way, the problem turned out to be lack of
maintenance, on our part, on the body trucks. The detail that supports the
other end of the drive shaft had deteriorated on several of the body trucks,
allowing the FADS to align at an incorrect angle.
Gleiter 19:59:19
Kimberly Gleiterkgleiter@hedonline.comSC Packaging produces foam molded parts.
One of their critical specifications is the weight of the part. The weight can
tell them if the correct density of material has been used in production. They
utilize X-bar and range/standard deviation charts to graph the results of their
subgroups. So for example, they would weigh 5 parts and graph the average of
the results. The downfall to this process was that it was not graphed in real
time. The operators did not have access to a computer, so they would record the
information manually and later someone would graph it electronically. By the
time the data was entered and the out of control occurrence was detected,
nearly an entire shift of product may have been run. Once it was graphed
however, they could quickly detect whether something out the ordinary was going
on (typically the press was hooked up to the wrong bag of material). Because it
was such a rare occurrence that the wrong bag was used, management did not see
the benefit in tracking this in real time (providing computers to production
personnel), but they continued to record the data in order to meet a customer
requirement.
Brad McGuire 19:58:45
QA6640 - Brad McGuire
bmcguire@spsu.edu
1) I will be using my organization – Lockheed Martin Aeronautics Company in
Marietta, GA
2) I will discuss the u-chart (total defects per unit) as it relates to the
communication process between QA and C/A Engineering in F-22 Final Assembly.
3) As part of my regular job assignments, I’m tasked with performing a Radar
Cross Section Walk-Around in final assembly to ensure all aircraft panels are
installed with acceptable mismatch and gap per specs and engineering drawings.
Once I have completed this walk-around process, I ask QA Inspection to document
all of the out-out-tolerance findings (if any) and submit these rejections to
MRB Engineering for repair dispositions. I then, submit the following to
Corrective Action Engineering for feedback purposes: 1) rejection document
number, area of aircraft – panel numbers, out-of-tolerance measurements, and
the history of this rejection (if any). In addition to this, I also submit the
total number of nonconformities (step or gap) on the aircraft to QE and C/A
Management via u-chart that illustrates the number of findings per jet going
back approximately 50 ships. This u-chart data is extremely useful in that I’m
able to easily extrapolate a control chart with upper and lower limits. This
chart identifies whether or not the RCS process is in or out of a state of
statistical control and dictates whether or not Corrective Action has been
validated. Other benefits include: simplicity of maintenance, shows logical
sequence of jet rejections, trends can be easily recognized, and is the primary
tool used when reporting overall percentage of rejections, cost and recurring
problem areas. And perhaps most of all, as I work with Production and
Corrective Action Engineering toward reducing these rejections, management can
easily recognize this by seeing the u-chart defect numbers decrease.
Chris Wellman 19:58:27
Christopher J. Wellman
Chart Type: X-bar and range/standard deviation charts
Company: Kollmorgen Corporation
Kollmorgen is a Contractor to the Department of
Defense; we design and build complicated Sensor Systems as large projects in a
very low quantity. From initial contract kick-off to shipment of a system it
typically takes about 1.5 years. Generally, we work on no more than a couple of
systems each year for a given program. The business is divided into three
business areas.
We use the X-bar and range/standard deviation
charts, which you can use to identify to “unusual occurrences that cause an
out-of –control condition” as discussed in Pages 34 to 35 in the Bossert
textbook for a given business area.
This chart quickly shows if our process for
handling problem, that is our ability to quickly resolve them. As you can
imagine with Thousands of parts that make-up a system it is important to
quickly close-out problems or something that was not critical can quickly end
up on our project critical path. So, the visibility provided by our -bar and
range/standard deviation charts for problem management is important to identify
when we are not keeping portions of the project moving along on schedule.
The visibility of the charts allows us to
prevent schedule problems which might otherwise cripple a project. The three
business area representative meets regularly to share common problems and
solutions. This way we can bring additional resources from other groups to bear
on areas that are not in control as demonstrated by the charts.
Alan Dial 19:52:51
Alan Dial
Dalzell22a@yahoo.com
I have chosen to discuss GE Contractual Services (GECS). GE Energy is a primary
business unit of General Electric. GE Contractual Services is a division of GE
Energy. GE Energy provides power technology solutions for Independent Power
Producers (IPP) and public utilities. The business provides consulting, sales
of turbine packages, installation of such packages, operation and maintenance,
as well as service contracts for the warranty of these packages. Contractual
Services provides long-term contractual and financing solutions for companies
on purchased GE OEM equipment.
I chose to discuss how our business uses the I&MR Chart for chemical
analysis. These charts are excellent for tracking long-term variation changes.
Because they use a single measurement for each data point, they are not a tool
of choice where measurement variation is involved, such as with part
dimensions. They work well with temperatures, pressures, concentration, etc.
The I&MR is used at our Operations & Maintenance facilities. In this
portfolio, GECS operates and maintains the power plant for a contractual
customer. GECS performs a chemistry analysis on the Boilers at the combined
cycle facilities. GECS chemistry technicians will plot the data in an I&MR
chart to monitor the change in pH and Phosphate concentration. Because there is
little variation in the measurement due to utilizing highly calibrated and
automatic equipment, I&MR is a good tool for measurement. As well, an
individual point is being measured, not a subgroup.
Prof. Atkins 19:34:31
CHAT ROOM DISCUSSION QUESTION:
You have thirty-minutes to answer the following
chat room question:
On Pages 34 to 35 in the Bossert textbook there
is a very brief discussion of the six basic types of control charts:
1. X-bar and range/standard deviation charts.
2. Individual with a moving range charts.
3. p charts (percent defective charts).
4. c charts (defect charts).
5. np charts (number of rejects charts).
6. u charts (defects per unit charts).
Select any ONE of the above six types of control
charts and discuss it in detail as it applies to a SPECIFIC example that you
are familiar with.
You may discuss your example in reference to any
ONE of the following:
The company you now work for, or
a company you have worked for before, or
any company you are familiar with.
Your discussion should cover the following three
issues:
1. Briefly describe the company you have chosen.
2. Briefly describe the type of control chart you will discuss.
3. Use a specific example to help explain the BENEFITS derived from the control
chart, and include as much detail as possible without exceeding the
thirty-minute time limit for your response.
It is suggested that you type your answer into a
Microsoft WORD file. When you have finished answering the chat room question,
then you should copy and paste your entire answer into the Message window
above. Then click the [POST] button. Your answer will then appear in the chat
room for everyone to read.
You MUST post your answer in the chat room no
later than thirty-minutes AFTER this question first appears in the chat room.