The seven basic quality tools
last edited by: Moloy Chakraborty on May 10, 2018 12:00 PM  login/register to edit this page 
The seven basic quality tools, also known in the industry as 7QC Tools, are used within the context of the PDCA Cycle to solve qualityrelated problems. The Seven basic quality control tools are as follows  1. Causeandeffect diagrams 2. Flowcharts 3. Check sheets 4. Pareto Diagram 5. Histogram 6. Control Chart 7. Scatter Diagrams 1. Causeandeffect diagrams  Causeandeffect diagrams, which are also known as fishbone diagrams or as Ishikawa diagrams. The problem statement placed at the head of the fishbone is used as a starting point to trace the problem’s source back to its actionable root cause. The problem statement typically describes the problem as a gap to be closed or as an objective to be achieved. The causes are found by looking at the problem statement and asking “why” until the actionable root cause has been identified or until the reasonable possibilities on each fishbone have been exhausted. Fishbone diagrams often prove useful in linking the undesirable effects seen as the special variation to the assignable cause upon which project teams should implement corrective actions to eliminate the special variation detected in a control chart. 2. Flowcharts  Flowcharts, which are also referred to as process maps because they display the sequence of steps and the branching possibilities that exist for a process that transforms one or more inputs into one or more outputs. Flowcharts show the activities, decision points, branching loops, parallel paths, and the overall order of processing by mapping the operational details of procedures that exist within a horizontal value chain of a SIPOC model. Flowcharts may prove useful in understanding and be estimating the cost of quality in a process. This is obtained by using the workflow branching logic and associated relative frequencies to estimate expected monetary value for the conformance and nonconformance work required to deliver the expected conforming output. 3. Check sheets  Check sheets, which are also known as tally Sheets and may be used as a checklist when gathering data Check sheets are used to organize facts in a manner that will facilitate the effective collection of useful data about a potential quality problem. They are especially useful for gathering attributes data while performing inspections to identify defects. For example, data about the frequencies or consequences of defects collected in check sheets are often displayed using Pareto diagrams. 4. Pareto Diagram  Pareto Diagram, exist as a special form of the vertical bar chart and are used to identify the vital few sources that are responsible for causing most of a problem’s effects. The categories shown on the horizontal axis exist as a valid probability distribution that accounts for 100% of the possible observations. The relative frequencies of each specified cause listed on the horizontal axis decrease in magnitude until the default source named “other” account for any nonspecified causes. Typically, the Pareto diagram will be organized into categories that measure either frequencies or consequences. 5. Histogram  Histogram, are a special form of a Bar chart and are used to describe the central tendency, dispersion, and shape of a statistical distribution. Unlike the control chart, the histogram does not consider the influence of time on the variation that exists within a distribution. It is a vertical bar chart showing the frequency of occurrence of a particular variable. The height of each column represents the relative frequency of the variable. 6. Control Chart  Control Chart, is used to determine whether or not a process is stable or has predictable performance. Upper and lower specification limits are based on requirements of the agreement. They reflect the maximum and minimum values allowed. There may be penalties associated with exceeding the specification limits. Upper and lower control limits are different from specification limits. The control limits are determined using standard statistical calculations and principles to ultimately establish the natural capability for a stable process. The project manager and appropriate stakeholders may use the statistically calculated control limits to identify the points at which corrective action will be taken to prevent unnatural performance. The corrective action typically seeks to maintain the natural stability of a stable and capable process. For repetitive processes, the control limits are generally set at ±3 s around a process mean that has been set at 0 s. A process is considered out of control when: (1) a data point exceeds a control limit; (2) seven consecutive plot points are above the mean; or (3) seven consecutive plot points are below the mean. Control charts can be used to monitor various types of output variables. Although used most frequently to track repetitive activities required for producing manufactured lots, control charts may also be used to monitor cost and schedule variances, volume, and frequency of scope changes, or other management results to help determine if the project management processes are in control. 7. Scatter Diagrams  Scatter Diagrams, plot ordered pairs (X, Y) and are sometimes called correlation charts because they seek to explain a change in the dependent variable, Y, in relationship to a change observed in the corresponding independent variable, X. The direction of correlation may be proportional (positive correlation), inverse (negative correlation), or a pattern of correlation may not exist (zero correlation). If the correlation can be established, a regression line can be calculated and used to estimate how a change to the independent variable will influence the value of the dependent variable.


last edited by: Moloy Chakraborty on May 10, 2018 12:00 PM  login/register to edit this page 
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