Quality control

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Quality control
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Quality control is a process of ensuring that a manufactured product fulfils quality criteria and meets requirements of producer and consumer. It is the second stage of evolution of quality approach after quality inspection and before quality assurance and quality management. In quality control there is a feedback link between quality inspector and workers at the production line. The feedback enables improvement of the process. Workers can improve their work thanks to information about quality.

The idea of quality control arose in early years of XX century. It was developed in first half of the XX century. The key improvement was implementation of statistical tools. Walter A. Shewhart designed methods that allowed early identification of quality problems. The main tool was a control chart. Thanks to this improvement, workers could react faster to problems.

Quality control using statistical tools is called in literature statistical quality control or statistical process control. The latter term is newer, however it describes the same set of tools.

Quality control vs. quality assurance

The difference between quality inspection and quality control was described in article about Quality inspection.

Quality control is a one feedback loop system. Quality inspector sends feedback information to workers who can improve their work. This can help to increase quality of work and sometimes also identify problems with tools and machines. However one loop system is not able to change itself. If the flaw is in the system, workers are not able to solve the problem.

Quality assurance is a two feedback loop system. The first loop works exactly as in quality control. The second loop sends information to managers, designers, technologists who can modify the system. The quality assurance includes into the system stages of product design and technology design. If the identified problem is related to product design or flaw in technology, the quality assurance system is able to solve it.

Development of quality approach

Off-line and on-line quality control

Off-line quality control is related to prevention of failures. Managers try to set up the production process to limit the number of failures. E.g. drill can be set to lower number of revolutions per minute to reduce vibrations and temperature hike. Such a change doesn't impact on product or technology. It's just changing some parameters in the process.

On-line quality control is related to real-time production. If the off-line quality control wasn't able to solve the problem, on-line actions are required. E.g. during the production worker checks temperature and pauses when it reaches too high level.

Off-line solutions are generally better, because they don't require additional tasks during the process. There is less room for error.

Sample size

See: sampling for more information. Due to improvement of statistical methods 100% sample is not necessary, and it never have been efficient. In practice errors made by quality inspectors lead to sending low quality products to customers. The most efficient way is quality self-assessment and protective actions. In fact, many scholars and managers point that quality inspection does not create value to the customer (e.g. Genichi Taguchi).

  • Inspection one hundred percent - consists of subjecting the inspection of all units produced. Due to time-consuming, this method is applied only to products manufactured individually or in small series. It was typical for phase of quality inspection
  • Statistical inspection - a lot of statistical inspection is assessed on the basis taken in a random sample. Therefore, this form of control is called a sample inspection. Depending on the size and frequency of sampling and the use of audit information to reverse effects on the production process, inspection may be statistical in nature. This method was typical in early phase of quality control.
  • Statistical process control (SPC) is an idea created by Walter A. Shewhart who created methodology for using statistics to detect potential errors before they happen. Thanks to Shewhart's control charts managers can predict errors based on information about production process malfunctions. This method was popularized in phase of quality control and is used in quality assurance and quality management approaches.

References

Author: Slawomir Wawak