Test method

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A test method is a method for a test in science or engineering, such as a physical test, chemical test, or statistical test. It is a definitive procedure that produces a test result. [1] In order to ensure accurate and relevant test results, a test method should be "explicit, unambiguous, and experimentally feasible.", [2] as well as effective [3] and reproducible. [4]

Contents

A test can be considered an observation or experiment that determines one or more characteristics of a given sample, product, process, or service. The purpose of testing involves a prior determination of expected observation and a comparison of that expectation to what one actually observes. [5] The results of testing can be qualitative (yes/no), quantitative (a measured value), or categorical and can be derived from personal observation or the output of a precision measuring instrument.

Usually the test result is the dependent variable, the measured response based on the particular conditions of the test or the level of the independent variable. Some tests, however, may involve changing the independent variable to determine the level at which a certain response occurs: in this case, the test result is the independent variable.

Importance

In software development, engineering, science, manufacturing, and business, its developers, researchers, manufacturers, and related personnel must understand and agree upon methods of obtaining data and making measurements. It is common for a physical property to be strongly affected by the precise method of testing or measuring that property. As such, fully documenting experiments and measurements while providing needed documentation and descriptions of specifications, contracts, and test methods is vital. [6] [2]

Using a standardized test method, perhaps published by a respected standards organization, is a good place to start. Sometimes it is more useful to modify an existing test method or to develop a new one, though such home-grown test methods should be validated [4] and, in certain cases, demonstrate technical equivalency to primary, standardized methods. [6] Again, documentation and full disclosure are necessary. [2]

A well-written test method is important. However, even more important is choosing a method of measuring the correct property or characteristic. Not all tests and measurements are equally useful: usually a test result is used to predict or imply suitability for a certain purpose. [2] [3] For example, if a manufactured item has several components, test methods may have several levels of connections:

These connections or correlations may be based on published literature, engineering studies, or formal programs such as quality function deployment. Validation of the suitability of the test method is often required. [4]

Content

Quality management systems usually require full documentation of the procedures used in a test. The document for a test method might include: [7] [8]

Validation

Test methods are often scrutinized for their validity, applicability, and accuracy. It is very important that the scope of the test method be clearly defined, and any aspect included in the scope is shown to be accurate and repeatable through validation. [4] [7] [9] [10]

Test method validations often encompass the following considerations: [2] [4] [7] [9] [10]

See also

Related Research Articles

Observational error is the difference between a measured value of a quantity and its true value. In statistics, an error is not necessarily a "mistake". Variability is an inherent part of the results of measurements and of the measurement process.

<span class="mw-page-title-main">Statistics</span> Study of the collection, analysis, interpretation, and presentation of data

Statistics is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of surveys and experiments.

Accuracy and precision are two measures of observational error. Accuracy is how close a given set of measurements are to their true value, while precision is how close the measurements are to each other.

Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method. For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated. There are different kinds of replication but typically replication studies involve different researchers using the same methodology. Only after one or several such successful replications should a result be recognized as scientific knowledge.

<span class="mw-page-title-main">Experiment</span> Scientific procedure performed to validate a hypothesis

An experiment is a procedure carried out to support or refute a hypothesis, or determine the efficacy or likelihood of something previously untried. Experiments provide insight into cause-and-effect by demonstrating what outcome occurs when a particular factor is manipulated. Experiments vary greatly in goal and scale but always rely on repeatable procedure and logical analysis of the results. There also exist natural experimental studies.

<span class="mw-page-title-main">Mathematical statistics</span> Branch of statistics

Mathematical statistics is the application of probability theory, a branch of mathematics, to statistics, as opposed to techniques for collecting statistical data. Specific mathematical techniques which are used for this include mathematical analysis, linear algebra, stochastic analysis, differential equations, and measure theory.

A measurement systems analysis (MSA) is a thorough assessment of a measurement process, and typically includes a specially designed experiment that seeks to identify the components of variation in that measurement process. Just as processes that produce a product may vary, the process of obtaining measurements and data may also have variation and produce incorrect results. A measurement systems analysis evaluates the test method, measuring instruments, and the entire process of obtaining measurements to ensure the integrity of data used for analysis and to understand the implications of measurement error for decisions made about a product or process. Proper measurement system analysis is critical for producing a consistent product in manufacturing and when left uncontrolled can result in a drift of key parameters and unusable final products. MSA is also an important element of Six Sigma methodology and of other quality management systems. MSA analyzes the collection of equipment, operations, procedures, software and personnel that affects the assignment of a number to a measurement characteristic.

Validation is the process of establishing documentary evidence demonstrating that a procedure, process, or activity carried out in testing and then production maintains the desired level of compliance at all stages. In the pharmaceutical industry, it is very important that in addition to final testing and compliance of products, it is also assured that the process will consistently produce the expected results. The desired results are established in terms of specifications for outcome of the process. Qualification of systems and equipment is therefore a part of the process of validation. Validation is a requirement of food, drug and pharmaceutical regulating agencies such as the US FDA and their good manufacturing practices guidelines. Since a wide variety of procedures, processes, and activities need to be validated, the field of validation is divided into a number of subsections including the following:

Analytic and enumerative statistical studies are two types of scientific studies:

<span class="mw-page-title-main">Certified reference materials</span> Material traceability inspection

Certified reference materials (CRMs) are 'controls' or standards used to check the quality and metrological traceability of products, to validate analytical measurement methods, or for the calibration of instruments. A certified reference material is a particular form of measurement standard.

In experimental methodology, a round-robin test is an interlaboratory test performed independently several times. This can involve multiple independent scientists performing the test with the use of the same method in different equipment, or a variety of methods and equipment. In reality it is often a combination of the two, for example if a sample is analysed, or one of its properties is measured by different laboratories using different methods, or even just by different units of equipment of identical construction.

In engineering, science, and statistics, replication is the repetition of an experimental condition so that the variability associated with the phenomenon can be estimated. ASTM, in standard E1847, defines replication as "... the repetition of the set of all the treatment combinations to be compared in an experiment. Each of the repetitions is called a replicate."

An independent test organization is an organization, person, or company that tests products, materials, software, etc. according to agreed requirements. The test organization can be affiliated with the government or universities or can be an independent testing laboratory. They are independent because they are not affiliated with the producer nor the user of the item being tested: no commercial bias is present. These "contract testing" facilities are sometimes called "third party" testing or evaluation facilities.

<span class="mw-page-title-main">Data collection</span> Gathering information for analysis

Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. Data collection is a research component in all study fields, including physical and social sciences, humanities, and business. While methods vary by discipline, the emphasis on ensuring accurate and honest collection remains the same. The goal for all data collection is to capture evidence that allows data analysis to lead to the formulation of credible answers to the questions that have been posed.

Verification and validation are independent procedures that are used together for checking that a product, service, or system meets requirements and specifications and that it fulfills its intended purpose. These are critical components of a quality management system such as ISO 9000. The words "verification" and "validation" are sometimes preceded with "independent", indicating that the verification and validation is to be performed by a disinterested third party. "Integration verification and validation" can be abbreviated as "IV&V".

A physical test is a qualitative or quantitative procedure that consists of determination of one or more characteristics of a given product, process or service according to a specified procedure. Often this is part of an experiment.

<span class="mw-page-title-main">Package testing</span>

Package testing or packaging testing involves the measurement of a characteristic or property involved with packaging. This includes packaging materials, packaging components, primary packages, shipping containers, and unit loads, as well as the associated processes.

Quality of measurements made in chemistry and other areas is an important issue in today’s world as measurements influence quality of life, cross-border trade and commerce. In this respect, EN ISO 17025 is the main standard used by testing and calibration laboratories as to appropriately tackle quality management related issues. While chapter four of the standard deals with management requirements, chapter five describes requirements for technical competence. Management related issues can be found in other standards as well e.g. ISO 9000, however the technical requirements are specific for calibration and testing laboratories.

Analytical quality control, commonly shortened to AQC, refers to all those processes and procedures designed to ensure that the results of laboratory analysis are consistent, comparable, accurate and within specified limits of precision. Constituents submitted to the analytical laboratory must be accurately described to avoid faulty interpretations, approximations, or incorrect results. The qualitative and quantitative data generated from the laboratory can then be used for decision making. In the chemical sense, quantitative analysis refers to the measurement of the amount or concentration of an element or chemical compound in a matrix that differs from the element or compound. Fields such as industry, medicine, and law enforcement can make use of AQC.

Floor slip resistance testing is the science of measuring the coefficient of friction of flooring surfaces, either in a laboratory or on floors in situ. Slip resistance testing is usually desired by the building's owner or manager when there has been a report of a slip and fall accident, when there has been a report of a near accident, or (preferably) before the flooring is installed on the property. Flooring is tested using a tribometer to discover if there is a high propensity for slip and fall accidents on it, either dry and/or when wet with water or lubricated with other contaminants such as kitchen grease, hydraulic oil, etc. There have been numerous floor slip resistance testing tribometers and lab devices produced around the world to measure both the static (stationary) and dynamic coefficient of friction, but presently there are only a few that have been proven to be reliable for obtaining useful safety results and that have current official test methods. Static coefficient of friction (SCOF) testing has always been unreliable for assessing safety in the wet condition, so any reliable slip resistance test will be measuring the available slip resistance to someone who is moving (dynamic) across the floor, and therefore will be assessing dynamic coefficient of friction (DCOF). If an instrument has no official published test method, or has a withdrawn test method, then there is a problem with the instrument, often being poor precision.

References

  1. "Form and Style for ASTM Standards". ASTM International. October 2017. Retrieved 8 February 2018.
  2. 1 2 3 4 5 Committee E-11 on Quality Control of Materials (1963). ASTM Manual for Conducting an Interlaboratory Study of a Test Method . American Society for Testing and Materials. p.  3 . Retrieved 8 February 2018.
  3. 1 2 Nigh, P.; Gattiker, A. (2000). "Test method evaluation experiments and data". Proceedings International Test Conference 2000 (IEEE Cat. No.00CH37159). Vol. 2000. pp. 454–463. doi:10.1109/TEST.2000.894237. ISBN   978-0-7803-6546-9. S2CID   41043200.
  4. 1 2 3 4 5 Bridwell, H.; Dhingra, V.; Peckman, D.; et al. (2010). "Perspectives on Method Validation: Importance of Adequate Method Validation". The Quality Assurance Journal. 13 (3–4): 72–77. doi: 10.1002/qaj.473 .
  5. "Glossary: S–Z". Understanding Science. University of California Museum of Paleontology. Retrieved 8 February 2018.
  6. 1 2 "Why are these rest results so different?: The importance of testing methods in chemical and microbiological testing" (PDF). Asia Pacific Laboratory Accreditation Cooperation. January 2008. Retrieved 8 February 2018.
  7. 1 2 3 Snodgrass, B.; Grant, T.; McCallum, K.; et al. (26 July 2014). "ISO 17025 Accreditation/Quality Management Systems Panel Discussion" (PDF). Association of American Feed Control Officials. Retrieved 8 February 2018.
  8. Higgins, C. (2009). "Test Design and Documentation" (PPT). University of Nottingham. Retrieved 8 February 2018.
  9. 1 2 "Test Method, Validation and Verification of Methods: APHL Quality Management System (QMS) Competency Guidelines" (PDF). Association of Public Health Laboratories. Retrieved 8 February 2018.
  10. 1 2 Office of Regulatory Science (12 May 2014). "5.4 Test Methods and Method Validation" (PDF). Laboratory Manual Of Quality Policies For ORA Regulatory Laboratories: Volume 1. U.S. Food and Drug Administration. Retrieved 8 February 2018.

General references, books