Quality engineering is the discipline of engineering concerned with the principles and practice of product and service quality assurance and control. In software development, it is the management, development, operation and maintenance of IT systems and enterprise architectures with a high quality standard.
Description
Quality engineering is the discipline of engineering that creates and implements strategies for quality assurance in product development and production as well as software development.
Quality Engineers focus on optimizing product quality which W. Edwards Deming defined as:
Quality engineering body of knowledge includes: Management and leadership The quality system Elements of a quality system Product and process design Classification of quality characteristics Design inputs and review Design verification Reliability and maintainability Product and process control Continuous improvement Quality control tools Quality management and planning tools Continuous improvement techniques Corrective action Preventive action Statistical process control (SPC) Risk management
Roles
Auditor: Quality engineers may be responsible for auditing their own companies or their suppliers for compliance to international quality standards such as ISO9000 and AS9100. They may also be independent auditors under an auditing body.
Process quality: Quality engineers may be tasked with value stream mapping and statistical process control to determine if a process is likely to produce defective product. They may create inspection plans and criteria to ensure defective parts are detected prior to completion.
Supplier quality: Quality engineers may be responsible for auditing suppliers or performing root cause and corrective action at their facility or overseeing such activity to prevent the delivery of defective product.
Software
IT services are increasingly interlinked in workflows across platform boundaries, device and organisational boundaries, for example in cyber-physical systems, business-to-business workflows or when using cloud services. In such contexts, quality engineering facilitates the necessary all-embracing consideration of quality attributes.
In such contexts an "end-to-end" view of quality from management to operation is vital. Quality engineering integrates methods and tools from enterprise architecture-management, Software product management, IT service management, software engineering and systems engineering, and from software quality management and information security management. This means that quality engineering goes beyond the classic disciplines of software engineering, information security management or software product management since it integrates management issues (such as business and IT strategy, risk management, business process views, knowledge and information management, operative performance management), design considerations (including the software development process, requirements analysis, software testing) and operative considerations (such as configuration, monitoring, IT service management). In many of the fields where it is used, quality engineering is closely linked to compliance with legal and business requirements, contractual obligations and standards. As far as quality attributes are concerned, reliability, security and safety of IT services play a predominant role.
In quality engineering, quality objectives are implemented in a collaborative process. This process requires the interaction of largely independent actors whose knowledge is based on different sources of information.
Quality objectives
Quality objectives describe basic requirements for software quality. In quality engineering they often address the quality attributes of availability, security, safety, reliability and performance. With the help of quality models like ISO/IEC 25000 and methods like the Goal Question Metric approach it is possible to attribute metrics to quality objectives. This allows measuring the degree of attainment of quality objectives. This is a key component of the quality engineering process and, at the same time, is a prerequisite for its continuous monitoring and control. To ensure effective and efficient measuring of quality objectives the integration of core numbers, which were identified manually (e.g. by expert estimates or reviews), and automatically identified metrics (e.g. by statistical analysis of source codes or automated regression tests) as a basis for decision-making is favourable.