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Quality assurance (QA) is the term used in both manufacturing and service industries to describe the systematic efforts taken to assure that the product(s) delivered to customer(s) meet with the contractual and other agreed upon performance, design, reliability, and maintainability expectations of that customer. The core purpose of Quality Assurance is to prevent mistakes and defects in the development and production of both manufactured products, such as automobiles and shoes, and delivered services, such as automotive repair and athletic shoe design. Assuring quality and therefore avoiding problems and delays when delivering products or services to customers is what ISO 9000 defines as that "part of quality management focused on providing confidence that quality requirements will be fulfilled". This defect prevention aspect of quality assurance differs from the defect detection aspect of quality control and has been referred to as a shift left since it focuses on quality efforts earlier in product development and production and on avoiding defects in the first place rather than correcting them after the fact.
Hazard analysis and critical control points, or HACCP, is a systematic preventive approach to food safety from biological, chemical, and physical hazards in production processes that can cause the finished product to be unsafe and designs measures to reduce these risks to a safe level. In this manner, HACCP attempts to avoid hazards rather than attempting to inspect finished products for the effects of those hazards. The HACCP system can be used at all stages of a food chain, from food production and preparation processes including packaging, distribution, etc. The Food and Drug Administration (FDA) and the United States Department of Agriculture (USDA) require mandatory HACCP programs for juice and meat as an effective approach to food safety and protecting public health. Meat HACCP systems are regulated by the USDA, while seafood and juice are regulated by the FDA. All other food companies in the United States that are required to register with the FDA under the Public Health Security and Bioterrorism Preparedness and Response Act of 2002, as well as firms outside the US that export food to the US, are transitioning to mandatory hazard analysis and risk-based preventive controls (HARPC) plans.
Automotive engineering, along with aerospace engineering and naval architecture, is a branch of vehicle engineering, incorporating elements of mechanical, electrical, electronic, software, and safety engineering as applied to the design, manufacture and operation of motorcycles, automobiles, and trucks and their respective engineering subsystems. It also includes modification of vehicles. Manufacturing domain deals with the creation and assembling the whole parts of automobiles is also included in it. The automotive engineering field is research intensive and involves direct application of mathematical models and formulas. The study of automotive engineering is to design, develop, fabricate, and test vehicles or vehicle components from the concept stage to production stage. Production, development, and manufacturing are the three major functions in this field.
Control charts are graphical plots used in production control to determine whether quality and manufacturing processes are being controlled under stable conditions. The hourly status is arranged on the graph, and the occurrence of abnormalities is judged based on the presence of data that differs from the conventional trend or deviates from the control limit line. Control charts are classified into Shewhart individuals control chart and CUSUM(CUsUM)(or cumulative sum control chart)(ISO 7870-4).
Engineering tolerance is the permissible limit or limits of variation in:
- a physical dimension;
- a measured value or physical property of a material, manufactured object, system, or service;
- other measured values ;
- in engineering and safety, a physical distance or space (tolerance), as in a truck (lorry), train or boat under a bridge as well as a train in a tunnel ;
- in mechanical engineering, the space between a bolt and a nut or a hole, etc.
Design for Six Sigma (DFSS) is a collection of best-practices for the development of new products and processes. It is sometimes deployed as an engineering design process or business process management method. DFSS originated at General Electric to build on the success they had with traditional Six Sigma; but instead of process improvement, DFSS was made to target new product development. It is used in many industries, like finance, marketing, basic engineering, process industries, waste management, and electronics. It is based on the use of statistical tools like linear regression and enables empirical research similar to that performed in other fields, such as social science. While the tools and order used in Six Sigma require a process to be in place and functioning, DFSS has the objective of determining the needs of customers and the business, and driving those needs into the product solution so created. It is used for product or process design in contrast with process improvement. Measurement is the most important part of most Six Sigma or DFSS tools, but whereas in Six Sigma measurements are made from an existing process, DFSS focuses on gaining a deep insight into customer needs and using these to inform every design decision and trade-off.
Reliability engineering is a sub-discipline of systems engineering that emphasizes the ability of equipment to function without failure. Reliability describes the ability of a system or component to function under stated conditions for a specified period of time. Reliability is closely related to availability, which is typically described as the ability of a component or system to function at a specified moment or interval of time.
The process capability is a measurable property of a process to the specification, expressed as a process capability index or as a process performance index. The output of this measurement is often illustrated by a histogram and calculations that predict how many parts will be produced out of specification (OOS).
Environmental stress screening (ESS) refers to the process of exposing a newly manufactured or repaired product or component to stresses such as thermal cycling and vibration in order to force latent defects to manifest themselves by permanent or catastrophic failure during the screening process. The surviving population, upon completion of screening, can be assumed to have a higher reliability than a similar unscreened population.
Process analytical technology (PAT) has been defined by the United States Food and Drug Administration (FDA) as a mechanism to design, analyze, and control pharmaceutical manufacturing processes through the measurement of critical process parameters (CPP) which affect the critical quality attributes (CQA).
Production Part Approval Process (PPAP) is used in the Aerospace or automotive supply chain for establishing confidence in suppliers and their production processes. Actual measurements are taken from the parts produced and are used to complete the various test sheets of PPAP.
"All customer engineering design record and specification requirements are properly understood by the supplier and that the process has the potential to produce product consistently meeting these requirements during an actual production run at the quoted production rate." Version 4, 1 March 2006
Software Quality Management (SQM) is a management process that aims to develop and manage the quality of software in such a way so as to best ensure that the product meets the quality standards expected by the customer while also meeting any necessary regulatory and developer requirements, if any. Software quality managers require software to be tested before it is released to the market, and they do this using a cyclical process-based quality assessment in order to reveal and fix bugs before release. Their job is not only to ensure their software is in good shape for the consumer but also to encourage a culture of quality throughout the enterprise.
In business, engineering, and manufacturing, quality – or high quality – has a pragmatic interpretation as the non-inferiority or superiority of something ; it is also defined as being suitable for the intended purpose while satisfying customer expectations. Quality is a perceptual, conditional, and somewhat subjective attribute and may be understood differently by different people. Consumers may focus on the specification quality of a product/service, or how it compares to competitors in the marketplace. Producers might measure the conformance quality, or degree to which the product/service was produced correctly. Support personnel may measure quality in the degree that a product is reliable, maintainable, or sustainable. In such ways, the subjectivity of quality is rendered objective via operational definitions and measured with metrics such as proxy measures.
Process Window Index (PWI) is a statistical measure that quantifies the robustness of a manufacturing process, e.g. one which involves heating and cooling, known as a thermal process. In manufacturing industry, PWI values are used to calibrate the heating and cooling of soldering jobs while baked in a reflow oven.
Process validation is the analysis of data gathered throughout the design and manufacturing of a product in order to confirm that the process can reliably output products of a determined standard. Regulatory authorities like EMA and FDA have published guidelines relating to process validation. The purpose of process validation is to ensure varied inputs lead to consistent and high quality outputs. Process validation is an ongoing process that must be frequently adapted as manufacturing feedback is gathered. End-to-end validation of production processes is essential in determining product quality because quality cannot always be determined by finished-product inspection. Process validation can be broken down into 3 steps: process design, process qualification, and continued process verification.
Continued process verification (CPV) is the collection and analysis of end-to-end production components and processes data to ensure product outputs are within predetermined quality limits. In 2011 the Food and Drug Administration published a report outlining best practices regarding business process validation in the pharmaceutical industry. Continued process verification is outlined in this report as the third stage in Process Validation.
Process qualification is the qualification of manufacturing and production processes to confirm they are able to operate at a certain standard during sustained commercial manufacturing. Data covering critical process parameters must be recorded and analyzed to ensure critical quality attributes can be guaranteed throughout production. This may include testing equipment at maximum operating capacity to show quantity demands can be met. Once all processes have been qualified the manufacturer should have a complete understanding of the process design and have a framework in place to routinely monitor operations. Only after process qualification has been completed can the manufacturing process begin production for commercial use. Equally important as qualifying processes and equipment is qualifying software and personnel. A well trained staff and accurate, thorough records helps ensure ongoing protection from process faults and quick recovery from otherwise costly process malfunctions. In many countries qualification measures are also required, especially in the pharmaceutical manufacturing field.
Process performance qualification protocol is a component of process validation: process qualification. This step is vital in maintaining ongoing production quality by recording and having available for review essential conditions, controls, testing, and expected manufacturing outcome of a production process. The Food and Drug Administration recommends the following criteria be included in a PPQ protocol:
Predictive engineering analytics (PEA) is a development approach for the manufacturing industry that helps with the design of complex products. It concerns the introduction of new software tools, the integration between those, and a refinement of simulation and testing processes to improve collaboration between analysis teams that handle different applications. This is combined with intelligent reporting and data analytics. The objective is to let simulation drive the design, to predict product behavior rather than to react on issues which may arise, and to install a process that lets design continue after product delivery.
References
- ↑ "Determining Criticality-Process Parameters and Quality Attributes Part I: Criticality as a Continuum". biopharminternational. Archived from the original on 10 November 2014. Retrieved 10 November 2014.
- ↑ "Critical Process Parameters and Critical Quality Attributes: Why Does the Selection Process Take so Long?". ProPharma Group. Retrieved 10 November 2014.
- ↑ "Critical Process Parameters (CPP)". Atris Information Systems. Retrieved 10 November 2014.
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