Amfax Limited

Amfax Limited

Unit 3 Clump Farm Industrial Estate, Blandford, Dorset, DT11 7TD, United Kingdom

Test data management

Test data management

When testing your products, the measurement and test data produced is invaluable in helping your improve your product quality. Most companies do nothing with their test data apart from storing on a hard drive somewhere. Accessing it and using this data is the most valuable way of gaining insights into your manufacturing performance and enabling you to make immediate improvements to help increase product quality whilst reducing the likelihood of unwelcome field failures and expensive product recall events.

If your product fails first time during manufacturing it takes time to find the fault and carry out the rework necessary. If your product fails in the field or needs regular maintenance it also takes time and engineering bandwidth. These costs are normally absorbed by your company but add significantly to the overall cost of building your products. Test data management software tools help reduce the time taken to find and repair faults, reducing your manufacturing costs and improving your overall product quality.

Historically, companies have been able to manage any product quality issues internally or with their customers. These days with the proliferation of social media no company is immune from the damage caused by unexpected product recall events. External failure costs are generally significant and unplanned. Investing in solutions to help reduce the potential for such events is vital for companies as they try to successfully expand their business.

SPC, Cp, Cpk andTrends - Analysis tools to help you identify quality problems

There are a number of well established mechanisms available to help you gain insights into the quality of your manufacturing process. SPC (Statistical Process Control) is a type of quality control using statistical methods. Cp and Cpk are used to evaluate whether your test measurements are safely within limits. Trends can be used to look at test measurements over time to evaluate if a failure is potentially going to happen at some time in the future.

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