Which are some of the Quality Tools you can Use for Process Improvement?

Quality Tools for Process Improvement:

Process Maps                                

They visually represent the relationship between activities and tasks that comprise the process and are used at the beginning of the process improvement event. You begin by describing the process event, frequencies, and timing at the highest level downwards. This quality tool will help you analyze and improve the process at high levels.

Fishbone

It visually represents the causes or effects of a problem and assists you in determining the cause of the problem. It is referred to as a fishbone diagram due to its appearance. The cause-and-effect diagram is often used in cause analysis to determine and organize the cause of a problem and prioritize it.

Check Sheets

These are matrices intended to assist in recording, tallying, and analyzing event occurrences or test results. They are one of the quality tools used in production to collect process data and count defects to help identify opportunities for improvement.

Histogram Charts

They consist of side-by-side and vertical bars that help you understand the relationships between data over time and represent frequency distributions in tables of numbers. This quality tool is most often used during the process improvement analysis.

Pareto Charts

This quality tool views that 20% of some factors often account for 80% of potential complications. It ranks causes, defects, and other data from the most important to the least in descending order. Of the seven tools, only this tool can distinguish between the vital few from the many trivial ones.

Scatter Charts

This quality tool displays the relationship between dependent and independent variables used during the hypothesis testing to determine the correlation between two variables and the strength of their correlation. Less scattering indicates a stronger correlation.

Control Charts

This statistical process tool helps plot performance over time against lower and upper control limits. Therefore, it is easy to identify process variations and determine common causes.