QC stands for Quality Control, which is the package of activities that ensure quality on product level, by finding and identifying defects and failure sources with using various quality tools and methods.
Quality control is emphasizing testing and validation. So it is more reactive, less proactive. But the outputs (data, information) of quality control can also lead to preventive measures. Which help later the preventive Quality Assurance (QA) of product realization.
What exactly QC is?
Typical examples for quality control are testing, product validation, inspection. When the controlled product is measured, compared against a defined requirement or specification. Based on Juran’s methodology, the key deliverables and inputs / outputs of Quality Control (QC) are the following:
QC Measurements
As the goal of QC is to identify and correct failures on a product, three decisions may apply after testing / measurement:
- Accept / release (OK product)
- Reject / scrap (NOK product)
- Rework / repair (NOK product that can be restored to the intended condition with 100% reliability)
In addition, it can happen that the subject of a decision is not only the product, but also the control process.
For example: an SPC based control procedure starts to detect products out of the tolerance range for a given characteristic, and based on the numbers it seems. That the issue has risen due to a systematic root cause. In such a case, it is quite desirable to implement a temporary 100% testing instead of relying solely on the statistical process control.
Quality control maintains the control of products or services, comparing measured data to references during manufacturing.
Many control methods exist, based on technology, fit for purpose, frequency. In many cases companies apply only sampling tests or inspection.
While some product characteristics require focused testing in 100% on all of the products.
Some examples for quality control:
- Visual inspection of product with magnifier or microscope.
- 100% capacity range measurement of capacitors with a “fit-for-purpose” device.
- Measuring electrical characteristics of various semiconductor components with ICT (In-circuit test).
- Measurement of cylinder block dimensions with 3D coordinate measuring machine.
- Statistical Process Control (SPC): controlling the whole population by measuring a smaller population (samples).
Quality Improvement (QI) and Quality Planning (QP) have a huge impact on Quality Control (QC). First, planning a robust product and process design desires less quality control, as it brings decreased Cost of Poor Quality (CoPQ). On the other hand, quality improvement advances the manufacturing process (and product design as well), also decreasing the need of managing issues that already happened, with other words “firefighting”.
QC & QA Relations
It must be pointed out, that Quality Assurance (QA) is not equal to Quality Control (QC). While QA is the bunch of proactive and systematic activities to ensure quality during the product realization, QC is a completely reactive process that aims to identify and eliminate failures.
Simply: QA is a preventive process-oriented methodology, while QC is a reactive product-oriented process. Decades before, QA was mainly considered as a performance evaluation after operations, but nowadays it means much more: ensuring quality, defect prevention, verification of processes (process oriented).
Conclusion
- Quality Control (QC) is used to ensure quality during the operation (manufacturing process).
- QC is generally reactive, but its outputs and results may lead to preventive process improvements.
- Typical QC examples are testing, validation, etc.
- Quality Control shouldn’t be mixed with Quality Assurance (QA).