Quality Control

Quality control involves a variety of quality measurements defined in the quality plan. These measurements should be items meaningful to determining whether the product of the project is of the quality required. Quality measurements can be statistical measurements that determine process control (whether the manufacturing process is within the acceptable tolerance of variation), or they can be more simple measurements for nonmanufactured goods, such as software, including walkthroughs, code inspections, and audits.

Quality control outputs help provide the feedback for improvements, acceptance, and, sometimes, rework.


Know the difference between quality control, which focuses on measurement, and quality assurance, which focuses on all the planned and systematic quality activities within a project.

Quality control tools are often associated with manufacturing and process control. Some key quality control tools are listed here:

  • Control charts These are plotted graphs of "tolerance in a process" measurements. Upper and lower boundaries are established, and when a product or process exceeds either boundary, it is considered "out of control," and improvements to the process are warranted. The boundaries are called tolerances.

  • Pareto analysis This is an 80/20 rule and generally involves mapping errors in a histogram to determine which 20% of the errors cause 80% of the problems.

  • Cause-and-effect diagrams Also called fishbone or Ishikawa, these diagrams are useful tools for uncovering root causes of quality problems.

  • Trend analysis This is used to determine whether corrective action needs to take place, or if a variance is simply an aberration. The "rule of sevens" is often cited. This means that if seven results in a row are out of bounds, then the process is likely to be out of control.

  • Statistical sampling This tool is used in manufacturing as well as other disciplines. It can take the form of random code reviews in IT or actual batch sampling of products produced in manufacturing. You are expected to understand statistical methods for the PMI exam.

PMP Exam Cram 2. Project Management Professional
PMP Exam Cram 2. Project Management Professional
Year: 2003
Pages: 169

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