Article: The case of ISO 9000

What role does statistical process control software play in helping organisations to meet ISO 9000? This extract from the current ‘NWA Casebook’ from Adept Scientific outlines the basics.

If the purpose of ISO 9000 is to ensure you maintain high quality standards in the goods you produce and the services you provide, then the purpose of SPC (statistical process control) is to monitor how well you’re achieving this, helping you sail through quality audits (we hope). It’s not in any way a method of meeting ISO 9000 in itself, but it is important in assessing where you stand.

SPC uses statistical methods such as control charts, capability analysis and exception reporting to monitor and control a process. These identify variations within the process that can indicate areas for quality improvement.

SPC also shows you how the process functions over time, so you can monitor the effect of improvements and predict how the process will run in the future, based on how it ran in the past. It helps you see if the process is currently capable of producing output that meets or exceeds specifications (and customer expectations) 100% of the time.

SPC control charts identify data that falls outside defined limits, indicating variations in the process that indicate where quality standards are not being met, or where improvements can be made, so that appropriate action can be taken.

As an example, let’s imagine a circuit board manufacturing plant. A proportion of finished boards fail the final quality inspection. Some boards may have missing or misplaced components; others may have soldering faults or broken connections. By feeding that information into an SPC program such as NWA Quality Analyst and producing, say, a Pareto chart, it’s easy to identify which is the most common type of fault and therefore the primary area for improvement.

By comparing the data taken, say, a month later, you can demonstrate and measure exactly how much improvement there has been; and what is now the main problem that needs to be addressed.

The flexibility of good SPC software, and its ability to maintain data links with corporate database, LIMS and SAPS software, allows you to decide which criteria to measure and address. You could, for example, use a quantitative metric (e.g which component causes the largest number of failures). Or you could prioritise the factors which affect costs and profitability: for example, a controller fuse may fail three times a week, but takes minutes and costs pennies to replace; while a motor which fails three times a year may result in a week’s lost production each time.

In this way SPC provides a tool that identifies where quality improvements can be made, gives you the information to choose which areas of improvement will provide the most benefit, and documents how effective the improvements you make are in achieving better quality.

The statistical methods inherent in SPC allow you to predict the effect of corrective actions, and document the accuracy of these predictions. SPC provides the evidence which ISO 9000 requires to prove the effect of your quality improvements.