Quality control refers to the process of systematically detecting errors in the laboratory testing results to ensure both that the accuracy and reliability of test results are maintained and best possible testing results are supplied to customers. Unreliable and inaccurate testing results can result in faulty failures, degraded field performance of engineering materials and products. it is therefore of great importance to ensure all results provided are accurate, reliable and consistent.
Alfort and Beaty define quality control as;
“Quality control is the mechanism by which products are made to measure up to the specifications determined from the customer’s demands and transform into sales, engineering and manufacturing requirements. It is concerned with making things right rather than discovering and rejecting those made wrong. Quality control is a technique by means of which products of uniform acceptable quality are manufactured.”
A mechanical and materials testing laboratory tests all kinds of materials at all stages of product engineering, from the raw material stage to performance characterization and durability testing of finished ready to market products.
The range and types of instruments to test these materials and product range from simplest to complex. Instruments such as density meter and hardness meters are the simple instruments, while SEMs, fatigue test benches, high strain rate equipments etc., are complex instruments that also have a significant learning curve. Only qualified engineers and analysts would be conducting the tests with the help of calibrated instruments to make sure that the data obtained is reliable and accurate.
Achieving quality in a mechanical and materials testing laboratory requires the use of many tools, instruments and machinery. These include UTMs, hardness meters, fatigue testing rigs, and also various custom made test benches. An established maintenance schedule, calibration, quality assurance program, training and quality control are pre-requisites. Calculations and maintenances of QC Statistics for systematic analysis of historical standard deviations, covariances, uncertainty calculations etc., is also required.
Data integrity refers to completeness, consistency and accurateness of the raw data generated in the testing laboratory during the course of its work. It means that the raw data has to be reliable, consistent and accurate and that no modifications, changes or deletions cannot be caried out by any person or machine.
Raw data in the quality control laboratory can be generated by testing machnes, DAQ systems, and computer systems as well as by laboratory staff as paper records and reports. Ensuring integrity of data starts from the proper design of the procedural documents, level of access provided to authorized persons, physical reliablility of the infrastructure and training of laboratory personnel. An appropriately designed procedure is uniquely named and numbered has sufficient leeway for records to be stored comfortably digitally and physically and distribution are strictly controlled at all levels.
Having established all the QC standard protocols at AdvanSES, we take pride in our work and our protocols are available for audit at any time.