SQC vs. SPC – Which is right for my manufacturing process? Both SQC and SPC play an important role in optimizing your operations so you can get the best result and most efficient output. Here we’re going to dive into the identifiable differences between the two and what role they play in the grand scheme of your manufacturing operations. GREAT NEWS! We start off with the definitions, so if you’re here simply for a technical explanation of what SPC and SQC are, than you are in luck and this will be quick. Statistics– is the study of the collection, analysis, interpretation, presentation, and organization of data. Statistical tools– is the application of statistics for the purpose of visualizing, identifying and predicting results based on the data collected. Statistical Process Control (SPC)– is the recording and measuring of the parameters of a process such as speed, pressure, caliper etc against a set of standards using statistical methods to verify they are within required limits. Objective: Minimize variation and run to optimum target Statistical Quality Control (SQC)– is typically the measuring and recording of data against specific requirements for a product ensuring they meet the necessary requirements – size, weight, colour etc. Objective: Auditing process validating outputs from a process meet the requirements of the ultimate customer or next stage of the manufacturing process. Some believe that both items fit under the title “SPC Manufacturing”. That very well may be true but in a typical manufacturing facility there are two distinct roles. Production makes the products and Quality Control/Assurance verifies the products manufactured meets the requirements – an auditing role. SQC vs. SPC – Why should I care? Because they both play an integrated role in seeing you achieve operational success! While the two roles exist in a facility there is a move to do more of the SQC validation directly to the manufacturing floor decreasing the time lag between finding a problem and fixing it. The important part of both of these responsibilities is to ensure that both roles are being performed and more importantly checking the right parameters and measuring on the right frequency. This is where Statistical tools come into play and are very important. Applying statistical tools to the data collected allows for the detection of immediate issues like being outside specification or control limits. These would be detected based on the setting of these limits and measuring against them. This is done through the use of alarm-type screens like the Rule Violation Screen in QW 5. It can also be observed using visual tools like the Control Chart Screen in QW 5. The next set of statistical tools involve what is termed descriptive statistics. Descriptive statistics are applied to a population of data and are used to describe the data in that population. – Statistics like Average, Mean, and Standard Deviation. QW 5 provides an extensive list of these Statistics to select from to best suit any population of data collected in a QW 5 application. A key understanding of statistics is that they act as indicators, like blood pressure and heart rate, to help diagnose or better understand the data collected. “Statistics are valuable representations of data that assist in the analysis and decision making process” Another valuable tool is Inferential Statistics which are still based on a population of data like Descriptive statistics but “speculate” based on that population. An example would be the Descriptive statistic Observed Out of Specification where each data point in the population is measured against fixed specification limits to determine the number that exceed the specification limits. The inferential example would be the Calculated out of specification which is based on the volatility of the data. It speculates on whether there would be more out of specification values found if more samples were taken. It can be used as a test on whether the testing frequency is correct based on the variation detected in the data collected. So in summary SPC is focused on minimizing variation in a process and running at target , while SQC, using similar tools, is the auditing method of insuring outputs meet exact requirements. Quality Window 5 provides an adaptable solution for both Statistical Process Control and Statistical Quality Control applications. In addition its failure analysis capabilities to capture, analyze and eliminate productivity losses like Downtime, Defects and Waste making it the complete cost effective solution for the manufacturing floor.