1.
1. What are the three primary technical tools for quality control and improvement? Briefiy
discussed each.
2. Explain why it is necessary to consider variability around the mean or nominal dimension as a
measured of quality?
3. Explain why it is important to separate sources of variability into special or assignable causes
and common or chance causes?
4. Suppose that during the analyze phase an obbvious solution is discovered. Should that solution
be immediately implemented and the remaining steps of DMAIC abandoned? Discuss your
answer
Solution
1.)))
The three primary technical tools for quality control and improvement are statistical
process control (SPC), design of experiments, and acceptance sampling. SPC uses a control
chart to monitor quality and technique. Design of experiments is helpful in identifying key
variables influencing quality characteristics. Acceptance sampling uses inspection and
testing of products to ensure quality
2.)))
The primary objective of quality engineering efforts is the systematic reduction of variability in
the key quality characteristics of the product. The introduction of statistical process control will
help to stabilize processes and reduce their variability. However, it is not satisfactory just to meet
requirements - further reduction of variability around the mean or nominal dimension often also
leads to better product performance and enhanced competitive position
3.)))

2.
Common and special causes have distinct origins of variation in context to a process. Common
causes, also called Natural patterns , are the usual, historical, quantifiable variation in a system,
while "special causes" are unusual, not previously observed, non-quantifiable variation.
4.)))
The purpose of the analyze phase is to allow the project team to target improvement
opportunities by taking a closer look at the data to determine the root causes of the process
problems and inefficiencies. This involves discovering why defects are generated by further
probing into the key variables (identified in the previous measure phase) that are most likely to
cause process variation. Statistical analysis is a key component of this phase and used to
demonstrate and confirm these relationships. If a solution is discovered in the analysis phase, it
should not be implemented till the improve phase is implemented as that phase is likely to
modify the solution or find a better solution.