Difference Between Quality Assurance (QA) and Quality Control (QC). Overview of 7 QC Tools

  • Home
  • Difference Between Quality Assurance (QA) and Quality Control (QC). Overview of 7 QC Tools
Shape Image One
Difference Between Quality Assurance (QA) and Quality Control (QC). Overview of 7 QC Tools

 “Success is the sum of small efforts, repeated day-in and day-out”, by Robert Collier.

Quality Control and Assurance is another approach whose use is increasing day by day that helps your organization to transform into a better one. It will also help your organization to get built successfully by maintaining a standard of product delivery and customer’s expectations are fulfilled. If you want to eliminate waste, attain higher level of productivity, and make your business efficient, you should read this article which will make your aware about the meaning of Quality Assurance and Quality Control and it’s benefits.

Before we take a look at the difference between Quality Assurance and Quality Control, let’s get to know what these two terms mean.

Handpicked for our Leaders: What exactly is Digital Transformation in 21st Century?

What is Quality Assurance

Quality Assurance is a way of averting errors and the defects present in the manufactured products. It also refers to the avoidance of problems while delivering products and services to consumers. Furthermore, it can also be interpreted as a crucial part of quality management that is focused on giving confidence that the requirements in product quality will be fulfilled. This confidence provided through “Quality Assurance” internally affects the management of an organization, whereas externally affects the customers, government agencies, third parties, etc. By ensuring “Quality Assurance” in an organization, the final product’s standard is observed. Moreover, it also helps in the development and implementation of inspection activities, detection of problems, and delivery of reasonable outcomes.  

What is Quality Control

Quality Control

This term is more like a process in which the quality of all factors that are involved in the production process, is reviewed. Like “Quality Assurance”, “Quality Control” is also a part of management that is concentrated on fulfilling the quality requirements of a product. Through this process, an organization can ensure that the quality of the product is maintained and improved. Usually, it involves the testing of units and determining whether they are under the specifications or not. It can also be defined as the set of actions that helps in controlling the quality of the product by detecting any bugs if present.

Both of the terms, Quality Assurance (QA) and Quality Control (QC), are used interchangeably. Now, that you’ve got an overview of both the terms, let’s take a look at the points of differences between them.

  1. QA is a process that focuses on assuring that the request related to the product’s quality will be accomplished, whereas, QC is the process that concentrates on fulfillment of the quality request.
  2. QA aims to deter any defect and prevent it, whereas, QC aims to identify the defect and improve it as well.
  3. QA is more like a technique where quality is managed, whereas, QC is a method that verifies quality.
  4. QA doesn’t demand the execution of programs, whereas, QC requires the execution of programs.
  5. QA is assured by all team members, whereas, only the testing team is credible for QC.
  6. QA’s statistical technique is known as Statistical Process Control, whereas, the statistical method used in QC is Statistical Quality Control.
  7. QA helps you to be sure that you are doing the right thing, whereas, QC makes sure that the results of what you did are up to your expectations.
  8. QA clarifies the principles and methodologies that need to be followed for meeting the customer requirements, whereas, QC makes sure that the standards are followed along with working on the product. 
  9. The process of QA creates the deliverables, whereas, the process of QC verifies those deliverables.
  10. A QA example is “Verification”, whereas, a QC example is “ Validation”.

Check out the Video-

What are the 7 QC tools

These7 QC Tools were initially created by Kaoru Ishikawa, a Japanese professor of engineering. The goal was the implementation of basic and user-friendly tools that the employees from each background with varied skills could use without any such requirement of extensive training. Later on, these 7 tools were implemented in Japan’s industrial training program that was held during the country’s postwar period. The usage of those 7 tools turned into statistical quality control as a means of quality assurance. Still today, these tools that help in quality management are considered the gold standard for managing a variety of quality-related issues. These tools are often executed along with some of the widely used process improvement methodologies like Six Sigma, Lean Management, etc. Let’s take a glance at those 7 QC tools-

  1. Stratification

The stratification analysis tool is a quality assurance tool that is used to sort data, objects, and people as well into distinct groups. If you segregate your data by using this tool, then you will be able to determine its meaning, or revealing some patterns that wouldn’t have been notified otherwise. Stratified analysis of your data allows you to make sense of your data previously, during, and after its collection. To receive the most out of this tool, you should always consider which type of information about your data’s sources can possibly affect the results of your data analysis. Moreover, you should make sure that your data had been set up in such a way that all the necessary information is included.

  1. Histogram 

Often, the quality specialists are allocated with the work of analyzing and interpreting the different groups of data’s behavior to manage and maintain quality. This is where another QC tool, Histogram comes into action. This particular tool helps you to exemplify the distribution of data clearly. It has a structure identical to the bar graph, where each bar represents a group, whereas, the height of the bar graph represents the frequency of data within that group. This tool helps in breaking down the frequency of your data into categories such as age, days, physical measurements, etc.

Handpicked for our Leaders: What exactly is Digital Transformation in 21st Century?

  1. Check Sheet or Tally Sheet 

Check Sheets are generally used for the collection of qualitative and quantitative data. While collecting quantitative data, this tool is called a Tally sheet. Whereas, a Check sheet collects data in the form of checkmarks that helps to indicate how many times a specific value has occurred. This ultimately helps you to quickly zero the flaws within your process, defect patterns, and also causes of some particular defects. As it has a simple setup and graphics that are simple to understand, this tool makes it easy to record the preliminary frequency distribution of data. 

  1. Cause and Effect Diagram

Also known as the Fishbone diagram, it is a QC tool that operates by defining an issue related to quality on the right-hand side of the diagram. This tool’s causes and sub-causes are mainly grouped into these six groups, measurements, personnel, environment, machines, and methods. These groups help in the identification of the likely source of your problem, while also keeping the diagram structured.

  1. Pareto Chart (80-20 Rule)

The Pareto Chart utilizes the 80-20 rule, where it is assumed that in any process, it’s 80% of problems are caused by 20% of the major factor, whereas, 20% of problems are risen by 80% of minor elements. The Pareto chart is a combination of a bar and a line graph, that portrays the individual values in descending order. This tool aims to highlight the significance of various parameters, which allows you to identify and direct your efforts on such factors that affect the part of the process.

Handpicked for our Leaders: What exactly is Digital Transformation in 21st Century?

  1. Scatter Diagram

This tool is most helpful in illustrating the relationship between two variables and it is suitable for QA professionals. Each dot at the Y-axis (dependent value) and X-axis (independent value) represents a common intersection point. When these points are assembled, they depict the relationship between variables. A stronger correlation in your diagram will assure an even stronger relationship between variables.

  1. Control Chart

Also called the Shewhart chart, this tool helps the experts to determine that a process is predictable or not, which helps you to recognize factors that may lead to any sort of variations. These charts use a central line that depicts upper and lower control limits that are based on historical data. Using this chart will save your organization time and money by foreseeing the performance of a process.

Conclusion

Thus, hereby it can be concluded that both Quality Assurance and Quality Control are significant parts of quality management. The QA process reviews the quality plan and is often used by management to make vital decisions on the improvement of the processes. While the QC process verifies that quality standard quality is executed to the process and is frequently used by the management to accept or reject products. Despite their differences, they work as two critical components in a quality management program. QA and QC function together to assure the ongoing quality of end products along with gaining the satisfaction and confidence of the customers. QA’s and QC’s altogether implementation results in the success of the organization. Lastly, the 7 tools of QC are also vital as they increase the product and process quality adequately.

Leave a Reply