Lab_03.doc

Introduction to Engineering Technology
Lab #3 - Introduction to SPC / Name______

Introduction: In this lab, we will use a spreadsheet to analyze a batch of 250 resistors using Statistical Process Control (SPC).

SPC is a method that was developed to improve manufacturing in the early 1920s by Dr. Walter Shewhart. Dr W. Edwards Deming, a student of Dr. Shewhart, applied SPC to manufacturing in Japan after World War II with great success. During this time the United States rejected SPC. In the 1980s, Ford motor company adopted SPC, in order to compete with Japanese imports. Since then, SPC has helped the United States become more competitive in the automotive industry and to dominate the semiconductor industry.

Supplies/Equipment:

  • Batch of 250 Resistors in a sleeve
  • Digital Multimeter (DMM)

Directions:

  1. Organize the class into groups of three students. Two students will take the resistance measurements. The third student will open the Lab #3 template spreadsheet and record the resistances in the resistor data worksheet. Measure the batch of 250 resistors by measuring 5, then skip 5, etc. You will have 125 resistance measurements to enter in the spreadsheet.
  1. Examine the X bar and R charts and identify any special causes (outliers, trends, patterns, etc.). Use the following rules to identify special causes:

Western Electric Rules

(Source:

The Western Electric Rules are general rules for detecting "out-of-control" or non-random conditions for data plotted on a run chart (plot of data as a function of time). There are 5 basic rules with respect to how the data is situated on a control chart to indicate if it is not in statistical control (i.e., special causes of variation are present instead of random sources). These are as follows:

Rule 1: Any single data point falls beyond 3 standard deviations from the centerline (i.e., any points fall outside of the upper or lower control limits);

Rule 2: Two out of three consecutive points fall beyond 2 standard deviations from the centerline, on the same side of the centerline;

Rule 3: Four out of five consecutive points fall beyond 1 standard deviation, on the same side of the centerline;

Rule 4: Eight consecutive points fall on the same side of the centerline;

Rule 5: Fifteen consecutive points fall within one standard deviation of the centerline.

If the data satisfy any of these conditions then it can be said that special cause(s) of variation in the data is present. Each of the rules has about the same probability of occurrence (approximately 3 in 1000).

A 6th rule is sometimes used, where if a trend of six consecutive points increasing or decreasing is observed then the data is also considered to exhibit non-random behavior.