on Tools & Techniques

When applied properly, SPC provides manufacturers a proven method to increase profitability and achieve a deeper understanding of their processes..  Additionally, SPC can prevent problems—saving companies money that would have been lost in scrap, rework, warranty, litigation, and market share decline.  A key factor in obtaining these SPC benefits is the proper deployment of control charts.  Correctly designed control charts identify significant changes to a process.  These can be changes that are still within specification, but are statistically different than where the process was previously running.  By identifying the changes, personnel can determine what caused the change and potentially improve the process or prevent the production of inferior products.   [Read more…]

In this week’s article entry, we discuss some guidelines for conducting an experiment.  As we discussed in an earlier post, planning the study is critical for a successful outcome.  A good plan makes the conduct of the study straightforward.

Below are some key aspects of conducting the study: [Read more…]

In this article post, we discuss several important techniques to consider when conducting and analyzing an experiment.  They are summarized in the table below and next we discuss each one in a bit more detail.  Some of these techniques are bit more advanced (e.g. Blocking, Covariates), but they are introduced here.    [Read more…]

An earlier article focused on the conceptual application of appropriate sample sizes for X-bar charts.  As we discussed, the purpose of control charts is to detect significant process changes when they occur.  When the proper sample size is selected, X-bar charts will detect process shifts (that have practical significance) in a timely manner. [Read more…]

In this article post, we discuss the suggested steps for planning a Designed Experiment.

Step #1 – Clearly Define the Problem and Objectives

It is critical to clearly define the problem before beginning experimentation.  When the problem is not clearly defined and described, there will be confusion in designing and executing effective studies.  To define appropriate responses to measure requires that the problem be understood and agreed on.  Also, it is key to define the objectives of the actual experiment.  If the problem is to reduce scrap rate, how much of a reduction is targeted? [Read more…]

The purpose of control charts is to detect significant process changes when they occur.  In general, charts that display averages of data/measurements (X-bar charts) are more useful than charts of individual data points or measurements.  Charts of individuals are not nearly as sensitive as charts of averages at detecting process changes quickly.  X-bar charts are far superior at detecting process shifts in a timely manner, and the sample size is a crucial element in ensuring that appropriate chart signals are produced. [Read more…]

While the construction of control charts is relatively straight-forward, often a more difficult question is “how do I know what process characteristic to control in the first place?”  Clearly, controlling “everything” is not feasible or a smart use of limited resources.   [Read more…]

In this article post, we formally define or describe the basic terminology that is commonly used in Design of Experiments.  Some of the terms we have already been using in prior posts, but they will also be presented here for completeness.  This is Part I of a two part article covering DOE Terminology.  [Read more…]