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TAMPERING VS. IMPROVEMENT In the Red Bead Experiment TAMPERING Tampering (managing by results) means making harmful changes in reaction to chance events (i.e., common causes of variation). Tampering means adding additional variation by unnecessary adjustments made in an attempt to compensate for common cause variation. Tampering is not improvement. Improvement of a stable process requires fundamental change in the process Improvement means reducing a process's variation and establishing an acceptable process average |
(Click on a rule for more information)
| RULE | EXPLANATION |
| 1 | Aim the funnel at the target. Keep it so aimed throughout the experiment. (Visual) |
|
2 |
1. At each drop, move the funnel from
its last position to compensate
for the last error. Measure the deviation from the point at which the marble comes to
rest and the original target (i.e., the bull's eye). Move the funnel an equal distance
in the
opposite direction from its current position. (Visual
1 l Visual 2) Simply put, your reference point for adjustment is the last event. |
| 3 |
Move the funnel from the original target
(i.e., the bull's eye)
to compensate for the last error.
Measure the deviation from the point at which the marble
comes to rest and the original target (bull's eye). Set the funnel an equal distance in
the opposite direction of the error from the original target
(Visual
1|Visual 2). Simply put, your reference point for adjustment is a standard. |
| If the marble ended up n inches northeast of the original target (bull's eye), we position the funnel n inches of the original target (bull's eye). | |
| 4 | At drop n, set the funnel right over the n-1 drop. (Visual) |
For rule 2 and 3, visual 2 is taken from James R. Evans and William M. Lindsay. 2005 (6th ed.). The Management and Control of Quality. Thomson, p. 524.
Here the results of 15 drops with each set being governed by a different rule (P. 205).
Drop |
Rule 1 |
Rule 2 |
Rule 3 |
Rule 4 |
||||
| Funnel | Result | Funnel | Result | Funnel | Result | Funnel | Result | |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
0 |
-3 |
0 |
-3 |
0 |
-3 |
0 |
-3 |
3 |
0 |
3 |
3 |
6 |
3 |
6 |
-3 |
0 |
4 |
0 |
2 |
-3 |
-1 |
-6 |
-4 |
0 |
2 |
5 |
0 |
5 |
-2 |
3 |
4 |
9 |
2 |
7 |
6 |
0 |
-5 |
-5 |
-10 |
-9 |
-14 |
7 |
2 |
7 |
0 |
2 |
5 |
7 |
14 |
16 |
2 |
4 |
8 |
0 |
2 |
-2 |
0 |
-16 |
-14 |
4 |
6 |
9 |
0 |
-2 |
-2 |
-4 |
14 |
12 |
6 |
4 |
10 |
0 |
1 |
2 |
3 |
-12 |
-11 |
4 |
5 |
11 |
0 |
-1 |
-1 |
-2 |
11 |
10 |
5 |
4 |
12 |
0 |
2 |
1 |
3 |
-10 |
-8 |
4 |
6 |
13 |
0 |
-2 |
-2 |
-4 |
8 |
6 |
6 |
4 |
14 |
0 |
2 |
2 |
4 |
-6 |
-4 |
4 |
6 |
15 |
0 |
-4 |
-2 |
-6 |
4 |
0 |
2 |
2 |
Take a look at this simple example of our class's start time
Download and experiment with the funnel simulation (sorry, Windows version only).
Take a look at what this simulation produces (use your browser's BACK button to return to this page).
Take a look at the effect of each tampering method on a system's variance.A good simulator is available at http://www.symphonytech.com/dfunnel.htm
Class Assignments:
Remember:
Tampering is action on the system without action on the fundamental cause of the trouble (p. 67).
A process may be stable (i.e., produce results within predictable limits), yet turn out faulty items and mistakes. To take action on the output of a stable process in response to production of a faulty item or a mistake is to tamper with the process. Put differently, tampering means making harmful changes in reaction to chance events. The result of tampering is only to increase in the future the production of faulty items and mistakes, and to increase costs -- exactly the opposite of what we wish to accomplish (p. 202). Thus, if anyone adjusts a stable process to try to compensate for a result that is undesirable, or a result that is extra good, the output that follows will be worse than if he had left the process alone (Out of the Crisis: 327). The reason being, tampering invariably increases variation in the results of a stable process.
Note, specification limits are not action limits. Severe losses occur when a process is continually adjusted one way and then the other to meet specifications. Control limits must be calculated from pertinent data (pp. 178-9).
Improvement of a stable system requires fundamental change in the process (p. 202).
More on
variation
(For more information, visit the TQM
Dictionary; click on V
for Variation)
Variation is a fact of life. It is random and miscellaneous. Thus, the same process can produce two things that are not alike. In the days of hand-crafted products, this could be accounted for by "fitting" things together. In modern industry where interchangeable parts are assembled into mass-produced final products, controlling variation is critical to customer satisfaction. This is one of the most important tasks a manager faces.
Dr. Walter Shewhart identified two kinds of variation, controlled and uncontrolled.
Controlled Variation/Stable
System:
Uncontrolled Variation/Unstable
System:
Management's job is to manage (reduce and stabilize) variation in order to produce predictable results, such as quality, cost, and production schedules. Since all data contain random variation or noise, the noise must be filtered out, otherwise two kinds of mistakes could arise:
One Last Time: Process Improvement
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Ø A system is a collection of processes Ø Process improvement requires that processes be stable, or under statistical control Ø Statistical control - a state of random variation; it is stable in the sense that the limits of variation are predictable Ø Once the systems has been stabilized, special causes of variation can be dealt with Ø Once special causes of variation have been removed, process improvement can begin Ø We improve processes by investigating and removing common causes Ø Tampering with a system - ascribing a variation, or a mistake, to a special cause when in fact the cause belongs to the system is overadjustment. This adds variation to the system. Ø Ascribing a variation, or a mistake, to the system when in fact the cause is special leads to not doing anything |
