24 CONTROL CHARTS, CONTINUOUS DATA, PART 1

24 CONTROL CHARTS, CONTINUOUS DATA
In the 24th Minitab tutorial, we are in the die-casting production facility of Smartboard Company. Skateboard axles are manufactured here by using two die-casting systems. The central quality feature of the skateboard axles, is the axle strength. Smartboard Company’s customers require an average axle strength of 400 megapascals, plus minus five megapascals. As part of this training session, we will accompany the Smartboard Company quality team and experience, how the corresponding quality control charts are used to analyze, whether the die casting process can be classified as a stable process, in terms of the customer specification and in terms of the Automotive Industry Action Group standards, AIAG. We will see how the quality team first uses descriptive statistics to gain an initial impression of the average process situation and process variation, before the actual process stability analysis and then evaluates the quality of the process stability, by using corresponding quality control charts. We will learn that different types of quality control charts are used, depending on the scale level and subgroup size. In this context, we will first deal with the scattering behavior of individual values and mean values, by using a simple data set in order to better understand the so-called statistical parameter standard error. We will become familiar with the so-called quality individual chart, also known as the I chart, the mean value chart Xbar chart, and the standard deviation chart, known as the s-chart. For didactic reasons, we will also manually calculate the respective upper and lower control limits in the quality control charts step by step for better understanding, and compare them with the results in the output window. On this occasion, we will also use the so-called Range chart, also known as the R-chart. And also, manually derive the corresponding control limits for this. We will then learn in detail the eight most important control tests established in the industry, based on the Automotive Industry Action Group standards AIAG, which can help us to detect any process instabilities. We will experience, that if a quality control chart is selected incorrectly, there is always a risk that the control tests will react less sensitively to existing process instabilities. And in this context, we will also learn how an overall process can be divided into two sub-processes by using the useful function: Form subset of worksheet. With the knowledge we have learned so far, we will become familiar with the so-called moving range chart, commonly referred to as the M-R chart. And we will learn, that the combined individual and moving range chart, I-M-R chart, is always very useful when individual values are to be compared with each other that are not summarized in subgroups.

MAIN TOPICS MINITAB TUTORIAL 24, part 1

• Assessment of the data landscape using descriptive statistics
• Process stability versus process capability
• Structure of control charts using the example of the I-chart and Xbar chart
• Identify process instabilities using tests for exceptional conditions

MAIN TOPICS MINITAB TUTORIAL 24, part 2:

• Process analysis using the combined Xbar/R- chart
• Identification of process instabilities using the control tests according to AIAG
• Manual derivation of the control limits in the S-map
• Manual derivation of the control limits in the Xbar map
• Manual derivation of the control limits in the R-map
• Plant-related process analysis through partial sub set formation
• Integration of customer specification limits and process target limits
• Working with the time stamp in control charts
• Division of an overall process into several sub-processes
• Alignment of scale labels in quality control charts

MAIN TOPICS MINITAB TUTORIAL 24, part 3:

• individual value chart I chart
• moving range chart MR chart
• Derivation of the control limits in the MR chart
• Derivation of the control limits in the I chart