project quality management

Topics: Control chart, Chart, Problem solving Pages: 7 (1756 words) Published: March 3, 2014
Summary of tools and techniques

It helps to organize tools and techniques into a systematic summary if possible. A useful list that organizes quality tools is on the website

Collecting Understanding Understanding Analyzing Solving Data Data Processes Processes Problems ________ ___________ ___________ ________ ___________

-Checksheet - Graphs - Flowchart - Cause & - Force Field - Histograms - Run Chart Effect Analysis - Pareto Charts - Control Diagrams - Brain- - Scatter Charts - Pillar storming Diagrams Diagrams - Affinity Diagrams

Each of the column headings in this summary table (collecting data, understanding data, understanding processes, analyzing processes, and solving problems) are further discussed in this file. Let’s start with collecting and understanding data and how that data is used to spotlight problems.

Collecting and understanding data: Using charts to spotlight problems

Collecting Data:

Checksheet. The checksheet is one of the seven basic tools of quality control. It is a simple document that is used for collecting data in real-time and at a location where the data is generated. It can be used for quantitative or qualitative information. The checksheet is sometimes called a “tally sheet.” There are five basic types of checksheets:

Classification – A trait such as a defect or failure is classified by a specific category. Location – The presence or absence of a trait or combination of traits. Frequency – The presence or absence of a trait or combination of traits as indicated. Measurement Scale – A measurement scale is divided into intervals and measurements are indicated by checking an appropriate interval. Checklist – The items to be performed for a task are listed so that as each is accomplished, it can be indicated as having been completed.

Understanding Data:

Graphs. Why graph data? A picture has been said to be worth a thousand words. Graphs can be used to explore data to show relationships and trends not readily apparent in tables or text. Graphs can clarify large sets of data with multiple variables. Graphics should be supported with basic statistical analysis in order to ensure that the conclusions drawn are as accurate as possible.

Histograms. A histogram is a specialized type of bar chart. Individual data points are grouped together in classes so that an idea of how frequently data in each class occurs within the data set. High bars indicate more points within a class and low bars indicate less points. The strength of the histogram is that it provides an easy-to-read picture of the location and variation in a data set. The weaknesses to guard against: Histograms can be misleading if the bars are not properly designed for the data to be evaluated. They can also obscure the time differences among data sets.

Let’s move our discussion from collecting data to understanding data through various quality management techniques.

Quality techniques: The use of graphs, histograms, pareto charts, scatter diagrams, cause/effect diagrams, run charts, flow charts, nominal group technique, Brainstorming, Affinity Diagram, Force Field Analysis

Pareto Charts. Vilfredo Pareto was a turn of the century Italian economist who characterized the understanding of distributions. It is a fairly...
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