Statistical Process Control

It is candidly realized today that in the world of cut throat competition, only defect-free products can lead to satisfaction of internal and external customers at competitive prices. Defect-free products (goods and services) can be produced by a defect-free process alone. In this regard a manufacturing process is no exception. Making a process defect-free, therefore assumes great significance

It is well known that results of repeated assessment or measurement often are numerical data, on a process parameter or product characteristic exhibit variation, when compared to each other or with the requirements. One important aspect which cannot be realized so easily is these results conceal key and important information about the process. Extraction of this information is possible only by Statistical tools and techniques. Once extracted the information is very useful in taking critical decisions to improve the process.

Statistical process control (SPC) involves using several techniques to measure and detect variation in processes. The intent of a SPC solution is to continuously monitor product quality based on measurable Parameters to keep processes based on fixed targets.

ez consultant’s On-line SPC is a custom built powerful tool that can provide an information powerhouse to aid management decisions based on solid data. Data can be manually entered or be acquired from multiple channels/probes is acquired in real time & processed as per SPC rules to display charts & Graphs. The SPC analysis software can be implemented on multi-gauging special purpose machine (SPM).

SPC Charts & Graphs

X bar R chart

In this chart, the sample ranges are plotted in order to control the variability of a variable.

Consolidated X bar R chart

A consolidated X bar R chart for 10 parameters with zoom facility for a parameter selected.

X bar S chart

The sample standard deviations are plotted in order to control the variability of a variable.

X chart

In this chart the sample values are plotted in order to control the value of a variable (e.g., size of piston rings, strength of materials, etc.)