Monitoring the Improvement

Besides we have standardization for implementation of improvement, we also have a monitoring system to control the improvement. Monitoring commonly use the graphical chart such as control chart, etc. Monitoring by using control chart aim to quickly detect the occurrence of assignable causes of process shift so that investigation of the process and corrective action may be undertaken before many nonconforming units are occurred. Monitoring implementation must be sustained in order to gaining success of improvement cycles.

In this phase, monitoring activities will focus on the result (Y) of the process. But, better result we must also control the factors (X) after improvement. Such as analyze concept, to control Y, we must control X’s.

Setup of control chart same like we get the data of capability process. Rational sub grouping needed to get the data point summary (as the representative of the groups, mean or range). Conducting Rational sub grouping is not a ‘must’ but ‘recommended’ in order to get better result. Subgroup size usually have a sample around 4 ~ 5.

Picture C.2 Outlook of Control Chart (Monitoring System)

Control chart will automatically set the control limit as +/- 3 sigma. We expect that this control limit is lower than product/services spec because inside of control limit is process in control equal that this data still inside the spec. But, if data is out of control limit, it’s not meaning out of spec, but the data get closer to the spec limit so we need quick action to investigate and finding the problem in order to not reach the spec limit.

Based on area limit; control chart has three main areas. Area one sigma called save area. We may not fully concern if data spread in this area. Second areas are 2 sigma area or Warning Limit area. If data spread in this area, we must be aware of data spreading and anticipate the action. Third area is +/- 3 sigma area or Action Limit area. If data spread in this area, we must investigate about the causes and finding the solution to control that. In other words, each step in control limit (control chart) makes us to be aware of the data spreading. This activity to ensure whether our improvement run well as the plan and ensure that organization sustain implementing improvement as the result of Improvement phase.

How to detect the uncontrolled data point of the Control Chart?

By using control chart as the main tools to monitoring system, we must know-how to use this tool. We must know how to interpreting data in the control chart. To know whether data is controllable or not, we can perform test of our control chart. There are eight tests to perform control chart monitoring.

1. 1 point more than 3s from center line

2. 9 point in a row on same side of center line

3. 6 point in a row, all increasing or all decreasing

4. 14 points in a row, alternating up and down

5. 2 out of 3 points > 2s from center line (same side)

6. 4 out of 5 points > 1s from center line (same side)

7. 15 points in a row within 1s of center line (either side)

8. 8 points in a row > 1s from center line (either side)

Let us check of control chart bellow:

Picture C.3 Test Performance of Control Chart (1)

Test Results for I Chart of Weight

TEST 1. One point more than 3.00 standard deviations from center line.

Test Failed at points: 14, 23, 30, 31, 44, 45

TEST 2. 9 points in a row on same side of center line.

Test Failed at points: 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 33, 34, 35, 36

TEST 5. 2 out of 3 points more than 2 standard deviations from center line (on one side of CL).

Test Failed at points: 24, 30, 31, 45

TEST 6. 4 out of 5 points more than 1 standard deviation from center line (on one side of CL).

Test Failed at points: 5, 6, 7, 29, 30, 31, 32, 45

Interpreting the results

The individuals chart shows six points outside the control limits and 22 points inside the control limits exhibiting a nonrandom pattern, suggesting the presence of special causes (Unusual occurrences that are not normally part of the process). See the Session window results for a list of the points that failed each test.

Picture C.4 Test Performance of Control Chart (1)

TEST 6. 4 out of 5 points more than 1 standard deviation from center line (on one side of CL).

Test Failed at points: 5

Interpreting the results

Subgroup 5 failed Test 6, meaning it is the fourth point in a row in Zone B (1 to 2 standard deviations from the center line). This suggests the presence of special causes

Type of Control Chart

Type of control chart is varying. The usages of each type must be applied properly based on the data type and other option rule. Bellow the summary of the Control Chart Type.

Picture C.5 The Application of Control Chart

The application of control chart in general divided due to the type of the data, attribute or continuous data. More detail cases and application of control chart can be learned in Tool Categories.