Operations Management For Dummies
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All quality management and improvement movements share the same basic foundation, regardless of what your company calls its quality program (some companies spend more time coming up with clever names for the program than actually implementing it). This foundation is built on continuous improvement and statistical analysis.

Several tools are commonly used to support this foundation. (Do be aware that they may be called by different names.)

  • Process flow diagram: This diagram is at the heart of continuous improvement. It represents everything that happens in a process, and you must complete it before embarking on process improvement. The initial process flow diagram is necessary to understand what’s actually being done and provides a document that you can use to communicate process changes.

  • Histogram: You may remember the histogram from school because it’s a basic method to display data. The histogram simply displays the frequency of different measurements and shows their distribution.

    For example, you can use a histogram to show the distribution of test grades to students. A range of the students’ scores is plotted on the x-axis, and the frequency of those grades is usually represented by a bar chart on the y-axis. The histogram is very useful to identify any outliers from the rest of the data.

  • Pareto chart: Another common bar chart is the Pareto chart. In this chart, the events are displayed on the x-axis, and the number of occurrences is displayed on the y-axis. The Pareto chart allows you to instantly identify the vital few events that are causing most of your problems.

    You want to allocate your limited resources to these high-frequency events because you’ll get a bigger bang for your buck if you can solve the higher-frequency issues.

  • Ishikawa diagram: The Ishikawa diagram (often called a fishbone diagram because of its resemblance to a fish skeleton) is one of many cause-and-effect tools. The diagram starts at the head with a problem statement. Running along the spine are possible causes for the problem.

    These causes are usually grouped in categories such as management, manpower, materials, methods, or machines. The fishbone diagram provides a useful visual tool to identify the root cause of a problem.

  • Failure mode and effects analysis (FMEA): You can use this tool to identify the root cause of a problem. It’s a very structured approach that begins by identifying all possible things that can go wrong, or the failure modes of your process or product.

    After you identify the failure modes, you rank each one according to the likeliness of it occurring, its impact if it did occur, and the likelihood of it being discovered before reaching the customer. You calculate a risk priority number (RPN) from these rankings, which can help prioritize the critical failure modes.

  • Run chart: This chart is a simple but powerful tool used to monitor a process over time. You can use it to identify changes in mean measurement and trends that may occur. Unlike the control chart discussed next, the run chart doesn’t require any statistical analysis.

  • Control chart: Statistical process control (SPC) is a statistical technique used to monitor and control processes. The most common SPC tool is the control chart, which is usually a line graph showing a particular measurement taken over time.

    The control chart is a simple visual tool you can use to monitor a process to see whether it’s performing as expected. Using the recorded data from a run chart, you can calculate upper and lower control limits. You plot these limits on the control chart and compare them to additional measurements. A measurement that falls outside the limit indicates that something has happened to the process, and you may need to take action.

About This Article

This article is from the book:

About the book authors:

Mary Ann Anderson is Director of the Supply Chain Management Center of Excellence at the University of Texas at Austin.

Edward Anderson, PhD, is Professor of Operations Management at the University of Texas McCombs School of Business.

Geoffrey Parker, PhD, is Professor of Engineering at Dartmouth College.

Mary Ann Anderson is Director of the Supply Chain Management Center of Excellence at the University of Texas at Austin.

Edward Anderson, PhD, is Professor of Operations Management at the University of Texas McCombs School of Business.

Geoffrey Parker, PhD, is Professor of Engineering at Dartmouth College.

Mary Ann Anderson is Director of the Supply Chain Management Center of Excellence at the University of Texas at Austin.

Edward Anderson, PhD, is Professor of Operations Management at the University of Texas McCombs School of Business.

Geoffrey Parker, PhD, is Professor of Engineering at Dartmouth College.

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