JNTU B.Tech IV TOTAL QUALITY MANAGEMENT Previous Question Paper (September - 2020 - R16)

Statistical Process Control (SPC) charts are graphical tools used to monitor, control, and improve processes by distinguishing between common cause variation and special cause variation. They are essential for maintaining process stability and ensuring that outputs meet quality specifications.

The charts are broadly categorized into two types based on the nature of the data collected:

1. Variables Control Charts: Used for continuous numerical data (e.g., length, weight, temperature).
   • X-bar and R Chart: Used to monitor the process mean and range for small subgroup sizes.
   • X-bar and S Chart: Used for larger subgroup sizes where the standard deviation provides a more accurate measure of dispersion.
   • I-MR Chart: Used when data is collected individually rather than in subgroups.
2. Attributes Control Charts: Used for discrete data (e.g., count of defects or defective items).
   • p-Chart: Monitors the proportion of defective units in a sample.
   • np-Chart: Monitors the actual number of defective units in a constant sample size.
   • c-Chart: Monitors the total number of defects in a constant area of opportunity.
   • u-Chart: Monitors the average number of defects per unit when the area of opportunity varies.

The primary purposes for applying these charts include:

• Process Stability: Determining if a process is in a state of statistical control by identifying if variation is random or due to assignable causes.
• Early Detection: Providing an early warning system to detect shifts or trends in process performance before non-conforming products are produced.
• Process Improvement: Serving as a baseline to evaluate the effectiveness of process changes or interventions.
• Decision Making: Providing objective, data-driven evidence for management to decide whether to adjust a process or leave it alone, thereby preventing over-adjustment.