Quality control in the context of Binary classification


Quality control in the context of Binary classification

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⭐ Core Definition: Quality control

Quality control (QC) is a process by which entities review the quality of all factors involved in production. ISO 9000 defines quality control as "a part of quality management focused on fulfilling quality requirements".

This approach places emphasis on three aspects (enshrined in standards such as ISO 9001):

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👉 Quality control in the context of Binary classification

Binary classification is the task of putting things into one of two categories (each called a class). As such, it is the simplest form of the general task of classification into any number of classes. Typical binary classification problems include:

When measuring the accuracy of a binary classifier, the simplest way is to count the errors. But in the real world often one of the two classes is more important, so that the number of both of the different types of errors is of interest. For example, in medical testing, detecting a disease when it is not present (a false positive) is considered differently from not detecting a disease when it is present (a false negative).

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Quality control in the context of Relative change

In any quantitative science, the terms relative change and relative difference are used to compare two quantities while taking into account the "sizes" of the things being compared, i.e. dividing by a standard or reference or starting value. The comparison is expressed as a ratio and is a unitless number. By multiplying these ratios by 100 they can be expressed as percentages so the terms percentage change, percent(age) difference, or relative percentage difference are also commonly used. The terms "change" and "difference" are used interchangeably.

Relative change is often used as a quantitative indicator of quality assurance and quality control for repeated measurements where the outcomes are expected to be the same. A special case of percent change (relative change expressed as a percentage) called percent error occurs in measuring situations where the reference value is the accepted or actual value (perhaps theoretically determined) and the value being compared to it is experimentally determined (by measurement).

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Quality control in the context of Acceptance sampling

Acceptance sampling uses statistical sampling to determine whether to accept or reject a production lot of material. It has been a common quality control technique used in industry.

It is usually done as products leave the factory, or in some cases even within the factory. Most often a producer supplies a consumer with several items and a decision to accept or reject the items is made by determining the number of defective items in a sample from the lot. The lot is accepted if the number of defects falls below where the acceptance number or otherwise the lot is rejected.

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Quality control in the context of Agriculturists

An agriculturist, agriculturalist, agrologist, or agronomist (abbreviated as agr.) is a professional in the science, practice, and management of agriculture and agribusiness. It is a regulated profession in Canada, India, Japan, the Philippines, the United States, and the European Union. Other names used to designate the profession include agricultural scientist, agricultural manager, agricultural planner, agriculture researcher, or agriculture policy maker.

The primary role of agriculturists are in leading agricultural projects and programs, usually in agribusiness planning or research for the benefit of farms, food, and agribusiness-related organizations. Agriculturists usually are designated in the government as public agriculturists serving as agriculture policymakers or technical advisors for policy making. Agriculturists can also provide technical advice for farmers and farm workers such as in making crop calendars and workflows to optimize farm production, tracing agricultural market channels, prescribing fertilizers and pesticides to avoid misuse, and in aligning for organic accreditation or the national agricultural quality standards.

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Quality control in the context of Stereo microscope

The stereo, stereoscopic, operation, or dissecting microscope is an optical microscope variant designed for low magnification observation of a sample, typically using light reflected from the surface of an object rather than transmitted through it. The instrument uses two separate optical paths with two objectives and eyepieces to provide slightly different viewing angles to the left and right eyes. This arrangement produces a three-dimensional visualization for detailed examination of solid samples with complex surface topography. The typical range of magnifications and uses of stereomicroscopy overlap macrophotography.

The stereo microscope is often used to study the surfaces of solid specimens or to carry out close work such as dissection, microsurgery, watch-making, circuit board manufacture or inspection, and examination of fracture surfaces as in fractography and forensic engineering. They are thus widely used in manufacturing industry for manufacture, inspection and quality control. Stereo microscopes are essential tools in entomology.

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Quality control in the context of Quality assurance

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 (i.e., a shift to the left of a linear process diagram reading left to right) and on avoiding defects in the first place rather than correcting them after the fact.

The terms "quality assurance" and "quality control" are often used interchangeably to refer to ways of ensuring the quality of a service or product. For instance, the term "assurance" is often used in a context such as: Implementation of inspection and structured testing as a measure of quality assurance in a television set software project at Philips Semiconductors is described. where inspection and structured testing are the measurement phase of a quality assurance strategy referred to as the DMAIC model (define, measure, analyze, improve, control). DMAIC is a data-driven quality strategy used to improve processes. The term "control" is the fifth phase of this strategy.

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Quality control in the context of American Association of State Highway and Transportation Officials

The American Association of State Highway and Transportation Officials (AASHTO) is a standards setting body which publishes specifications, test protocols, and guidelines that are used in highway design and construction throughout the United States. Despite its name, the association represents not only highways but air, rail, water, and public transportation as well.

Although AASHTO sets transportation standards and policy for the United States as a whole, AASHTO is not an agency of the federal government; rather it is an organization of the states themselves. Policies of AASHTO are not federal laws or policies, but rather are ways to coordinate state laws and policies in the field of transportation.

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Quality control in the context of Quality management

Quality management (QM) ensures that an organization, product, or service consistently performs as intended. It has four main components: quality planning, quality assurance, quality control, and quality improvement. Customers recognize that quality is an important attribute when choosing and purchasing products and services. Suppliers can recognize that quality is an important differentiator of their offerings, and endeavor to compete on the quality of their products and the service they offer. Thus, quality management is focused both on product and service quality.

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Quality control in the context of Structured-light 3D scanner

A structured-light 3D scanner is a device used to capture the three-dimensional shape of an object by projecting light patterns, such as grids or stripes, onto its surface. The deformation of these patterns is recorded by cameras and processed using specialized algorithms to generate a detailed 3D model.

Structured-light 3D scanning is widely employed in fields such as industrial design, quality control, cultural heritage preservation, augmented reality gaming, and medical imaging. Compared to laser-based 3D scanning, structured-light scanners use non-coherent light sources, such as LEDs or projectors, which enable faster data acquisition and eliminate potential safety concerns associated with lasers. However, the accuracy of structured-light scanning can be influenced by external factors, including ambient lighting conditions and the reflective properties of the scanned object.

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Quality control in the context of Food rheology

Food rheology is the study of the rheological properties of food, that is, the consistency and flow of food under tightly specified conditions. The consistency, degree of fluidity, and other mechanical properties are important in understanding how long food can be stored, how stable it will remain, and in determining food texture. The acceptability of food products to the consumer is often determined by food texture, such as how spreadable and creamy a food product is. Food rheology is important in quality control during food manufacture and processing. Food rheology terms have been noted since ancient times. In ancient Egypt, bakers judged the consistency of dough by rolling it in their hands.

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Quality control in the context of PH meter

A pH meter is a scientific instrument that measures the hydrogen-ion activity in water-based solutions, indicating its acidity or alkalinity expressed as pH. The pH meter measures the difference in electrical potential between a pH electrode and a reference electrode, and so the pH meter is sometimes referred to as a "potentiometric pH meter". The difference in electrical potential relates to the acidity or pH of the solution. Testing of pH via pH meters (pH-metry) is used in many applications ranging from laboratory experimentation to quality control.

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Quality control in the context of Visual inspection

Visual inspection is a common method of quality control, data acquisition, and data analysis.Visual Inspection, used in maintenance of facilities, means inspection of equipment and structures using either or all of raw human senses such as vision, hearing, touch and smell and/or any non-specialized inspection equipment.Inspections requiring Ultrasonic, X-Ray equipment, Infrared, etc. are not typically regarded as visual inspection as these Inspection methodologies require specialized equipment, training and certification.

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Quality control in the context of Machine smelling

Machine olfaction is the automated simulation of the sense of smell. An emerging application in modern engineering, it involves the use of robots or other automated systems to analyze air-borne chemicals. Such an apparatus is often called an electronic nose or e-nose. The development of machine olfaction is complicated by the fact that e-nose devices to date have responded to a limited number of chemicals, whereas odors are produced by unique sets of (potentially numerous) odorant compounds. The technology, though still in the early stages of development, promises many applications, such as:quality control in food processing, detection and diagnosis in medicine, detection of drugs, explosives and other dangerous or illegal substances, disaster response, and environmental monitoring.

One type of proposed machine olfaction technology is via gas sensor array instruments capable of detecting, identifying, and measuring volatile compounds. However, a critical element in the development of these instruments is pattern analysis, and the successful design of a pattern analysis system for machine olfaction requires a careful consideration of the various issues involved in processing multivariate data: signal-preprocessing, feature extraction, feature selection, classification, regression, clustering, and validation. Another challenge in current research on machine olfaction is the need to predict or estimate the sensor response to aroma mixtures. Some pattern recognition problems in machine olfaction such as odor classification and odor localization can be solved by using time series kernel methods.

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