Digital Themes

Quality Engineering and Assurance

Quality engineering and assurance (QEA) is an aspect of quality management, particularly the business process of ensuring that quality control measures and checks are integrated at every step of product or software development. It is the combination of quality assurance (QA) and quality engineering (QE). QA is a set of procedural activities that aims to ensure proper safety and quality of any delivered products and services. QE, on the other hand, considers the proper safety and quality involved in the development of software programs, and generally uses an ecosystem approach. This means that the entire ecosystem of production is considered under different quality control measures. The combination of both QE and QA ideals shifts the focus from the end product to ensuring the quality of every step of the process. QEA is designed to enhance both the quality and speed of production.

Generally, QEA will include automation and machine learning as part of the development process. This means that there will oftentimes be test automation in applicable processes, such as software testing. A separate program will be used to interact with the software or product in the ways a consumer would be expected to, and then determine how those outcomes compare to the predicted or desired outcomes. These tests are generally programmed specifically in response to the target application and will often use machine learning to make predictions around how most people will use the software, which helps guarantee that the software quality matches the expectations. Intelligent and automated tests can also be done in other areas, such as automating actual product tests or for application testing. Automated tasks can run with little oversight and can generally be completed more quickly than manual processes. This helps speed up the testing process without compromising quality. Automated tasks also have the benefit of automatically generating data that can be stored and then further analyzed using artificial intelligence and machine learning.

Oftentimes QEA will utilize cloud based platforms for the product development and design processes, and implementing such a system is a common step in a digital transformation. These platforms can help ensure that all generated data has a clear pipeline to the next phase. Different systems can be fully integrated into one another, so that all data is clearly conveyed from one step to the next. This is further beneficial as it limits the amount of man hours needed at each step, because the data is clearly presented, often with analyses already performed. QEA enables businesses to speed up development processes without compromising on the quality of the product.

QEA is beneficial to businesses and organizations as it can help:

  • Improve customer experiences: By ensuring quality through every step of the development process, organizations can help limit the frustration that customers feel when using a new product, service, or software. Through the use of quality standards and extensive testing, businesses can identify and fix potential pain points before the final product is presented to real customers.

  • Ensure regulatory compliance: As part of a robust QEA system, regulatory compliance should be checked as new products or processes are used. This helps ensure that businesses are following all relevant laws and regulations, and can help protect them from costly fines or lawsuits.
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