1. Tools for Problem Analysis

2. Outline Cause-and-effect chart Root cause analysis Scatter chart
Histogram
Scatter chart
Cause and effect
Histogram

3. Cause and effect chart
Classical and most widely used tools in quality management
Main purpose is to identify possible causes for an effect
Effect analyzed can be:
An experienced problem
Future hoped-for state
Chart can be used for:
Finding causes for problem
Planning how to reach a state where problem no longer occur
Types:
Fishbone chart
Process chart

4. Fishbone Chart Traditional way of constructing cause-and-effect charts
Main product is a chart that resembles a fishbone
Two ways of creating the chart:
Dispersion analysis: effect being analyzed is drawn on the right side of the chart and groups of possible causes are identified
Cause enumeration: where all possible causes are simply brainstormed and listed in the order they are generated

5. Fishbone chart with dispersion analysis
The chart gives better result when created in group  first step, assemble a suitable group possessing the necessary knowledge about the area to be analyzed
Describe the effect for which causes are sought e.g. low performance
Draw the effect at the end of a large arrow

6. Identify main categories of possible causes  place at branches emanating from the large arrows
For physical processes
main categories:
People
Machines and equipment
Materials
Methods
Measures
For service processes
main categories:
People
Machines and equipment
Frame conditions
Work environment

7. 5. Brainstorm all possible causes and place these in the suitable area of the chart
Brief and succinct description
Proceed through the chart one main category at the time  but include surfacing suggestions
Causes that belong to more than one category are placed in all relevant position
6. Analyze the identified causes to determine the most important ones

8. Example Identifying the causes of dimension errors Methods Employees
Low motivation
Unsuitable process route
Poor training
Unsuitable hardening
Dimension errors
Poor maintenance
Wrong coolant
Often temperature too low
Too infrequent tool sharpening
Environment
Equipment

9. Process Chart
Variant of Cause and effect chart that directly aimed at improvement of business process
Main steps in the process to be improved are drawn
For each step of the process believed to create problems or contribute to low level performance a fishbone chart is constructed

10. Root cause analysis Also known as “why-why chart” and “five whys”
The purpose is to find the true root cause of a problem
Can be used in connection with cause-and-effect chart  to ensure if each identified cause really is the root cause of the problem

11. Root cause analysis procedure
Determine the starting point, either a problem or a high-level cause that should be further analyzed
Use brainstorming to find causes at the level below the starting point
For each identified cause, pose the question, “why is this a cause for the original problem?”
For each new answer to the question, ask the question again and again until no new answer results. This will probably be one of the root causes for the problem  usually requires five rounds of the question “why”
If the question is twisted slightly to asking “how” instead of asking “why” the technique can be used to find root means for reaching a desired state or effect

12. Low level of work-in-progress
Example
Finding means for reducing the amount of work-in-progress in a manufacturing company
Low level of work-in-progress
How?
Maintain no stock of finished goods
How?
Short manufacturing time
How?
Run small batch sizes
How?
Frequent and swift deliveries from the suppliers
How?
Extremely good relationships to the suppliers

13. Contoh Root Cause Analysis

14. Analisis Hasilnya

15. Scatter chart Used to show the relationship between two variables
The variables can be process characteristics, performance measures, or other conditions
Usually measured at specified time intervals

16. Relations in scatter diagram
When one of the factors increases, the other can either also:
Increase
decrease or
display random variation
If the two variables seem to change in synchronization  it might mean that they are related and impact each other
Number of defects increases in proportion with the amount of overtime used
Synchronized variation does not always mean that there is a cause-and-effect relationship between variables!

17. Different Degrees of Correlation
Strong positive correlation
Possible positive correlation
No correlation
Strong negative correlation
Possible negative correlation

18. Developing a scatter chart
Select the two variables, one independent and one dependent, to be examined
For each value of the independent variable, the corresponding value of the dependent value is measured
Typically, should be at least 30
Preferrably more than 100 data pairs
Draw the chart itself placing the independent variable (the expected cause) on the x axis, and the dependent (effect) on the y axis
Plot the collected data pairs on the chart and analyze it

19. Interpreting scatter chart
If chart indicates a relationship  variables should be analyzed further to confirm the relationship
Chart showing no relationship should not automatically lead to a conclusion that no relationship exists

20. Using Scatter chart x Diskusikan bersama satu teman:
Customer waiting time
Number of complaints
Diskusikan bersama satu
teman:
Jika anda adalah seorang
pengambil keputusan
apa yang akan anda
lakukan setelah melihat kedua
diagram ini?
Number of defects

21. Histogram Also called a bar chart
Used to display the distribution and variation for a measure
Measure can be length, diameter, duration, costs etc.
Information can be presented in table  difficult to spot important patterns in the data material

22. Constructing a Histogram
Count the number of data points in the data material (labeled N). Should be at least 50 data points
Determine the numerical distance, R, between the largest and the smallest value in the data material
Depending on the number of data points, R is divided into a number of equally large classes C

23. Number of classes, C The number of data points N
The number of classes C
Less than 50
5 – 7
50 – 100
6 – 10
100 – 250
7 – 12
More than 250

24. Constructing a histogram contd.
Determine the width of the class, labeled H using the following formula:
H = R/C
Width should always have the same decimals as the data points
Determine the lower and upper values for individual classes
Find the smallest value in the data material as the lower value for the first class
Upper value for this class = lower value + width
Insert data material into a check
Create histogram based on the check sheet
Classes are marked along the horizontal axis
Frequency along the vertical axis

25. Histogram Menunjukkan variabilitas sebuah proses Frequency Frequency
Order processing time (days)
Frequency
Order processing time (days)

26. Tugas Kumpulkan data tinggi dan berat masing-masing anggota kelas
Tentukan dependent variable (Y) dan independent variable (X)
Buat diagram scatter dan histogramnya
Analisis hasilnya dan Simpulkan
Kerjakan secara kelompok
Kumpulkan minggu depan dalam bentuk tulisan tangan dan garis-garis diagram yang rapi
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