Quality control

Quality control
See also
Quality inspection Quality assurance Jidoka Lean product development PFMEA 5S method Philip B. Crosby Six sigma Cycle time

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.

Examples of Quality control

• Visual Inspection: Visual Inspection is a quality control process wherein a part or product is examined by eyes in order to check if it conforms to the set standards. Visual inspection is a very simple process that can be done without any expensive equipment or special tools. It is used for checking for defects like scratches, cracks, dents, etc.
• Dimensional Measurement: Dimensional Measurement is a quality control process that involves measuring the size and shape of a part or product to determine if it meets the set standards. This process involves the use of specialized tools such as calipers, micrometers, and other measuring devices.
• Dimensional Tolerance: Dimensional Tolerance is a quality control process where the manufactured component is compared to its design specifications to check if the tolerances are within the acceptable range. This process helps to ensure that the component is within the prescribed design parameters so that it will perform correctly in the application.
• Force Testing: Force Testing is a quality control process that involves measuring the amount of force required to operate a component or product. This process helps to determine the strength and durability of a product and can be used to check that it meets the required standards.
• Radiography Testing: Radiography Testing is a quality control process where a component or product is subjected to X-rays in order to check for any internal defects. This process helps to detect flaws and defects that might not be visible to the naked eye, such as cracks, voids, and other imperfections.

Advantages of Quality control

Quality control has multiple advantages, as follows:

• It helps to identify and eliminate process variations which can lead to poor quality products. This helps to reduce waste and maintain customer satisfaction.
• Quality control helps to prevent defects and non-conformities. This ensures that the product meets the specification and customer expectations.
• Quality control helps to improve the efficiency of the production process by identifying areas of waste and inefficiency.
• Quality control helps to reduce costs by improving accuracy and efficiency of production and reducing waste.
• Quality control helps to ensure that products are safe and meet the required standards and regulations. This helps to maintain customer trust.

Limitations of Quality control

• Quality control is a reactive process, which means that it is only used after products have been made, and cannot be used to prevent defects from occurring.
• It is also a subjective process, as the quality inspector has to make a judgement on whether the product meets the quality criteria.
• Quality control is also costly, as it requires additional resources, such as employees, equipment, and materials.
• Quality control may be difficult to implement if the product design is complex or constantly changing.
• Quality control may be difficult to sustain over time, as it requires continuous monitoring and feedback.

Other approaches related to Quality control

In addition to Quality control, there are other approaches related to quality assurance and management, such as:

• Quality Assurance – This approach involves the systematic monitoring and evaluation of the various aspects of a product or service to ensure that standards of quality are being met. Quality assurance takes a proactive approach to ensure that the product meets the desired quality level.
• Quality Management – This approach involves the implementation of a quality management system to ensure that the product or service meets the desired quality standards. Quality management involves the use of quality tools, such as process mapping, data analysis, and customer feedback, to monitor and measure the quality of a product or service.

These approaches are all related to quality assurance and management and are important in ensuring that the product or service meets the desired quality standards. By implementing these approaches, companies can ensure that they are producing a high-quality product or service that meets customer expectations. In summary, quality control, quality assurance, and quality management are all approaches related to quality assurance and management that are necessary to ensure that a product or service meets the desired quality standards.

References

• Benneyan, J. C. (1998). Use and interpretation of statistical quality control charts. Int J Qual Health Care, 10(1), 69-73.
• Ettlie, J. E. (1997). Quality, technology, and global manufacturing. Production and Operations Management, 6(2), 150-166.
• Evans JR, Lindsay WM (1999) The management and control of quality, West Publishing Company, New York
• Ivy, J. S., & Nembhard, H. B. (2005). A modeling approach to maintenance decisions using statistical quality control and optimization. Quality and Reliability Engineering International, 21(4), 355-366.
• Shewhart WA, Edwards Deming W (1939) Statistical method from the viewpoint of quality control, Dover Publications, New York
• Myth of added value of inspection @ wawak.pl.

Author: Slawomir Wawak