Optimal Calibration Interval Research Articles

Model of operation of computer measuring system

The implementation of the concepts of a smart home - smart city implies a high level of automation using control and measuring devices and equipment, as well as computer and informational technologies. One of the effective trends of automation is the widespread use of computer measuring systems Article presents the model of operation of a computer measuring system with digital data processing is proposed. The presented model is based on the semi-Markov model of operation of an analog-to-digital converter, on the semi-Markov model of an embedded personal computer, on the analytical formula for calculating the availability factor of computer measuring system. The analytical expression for the availability factor of a computer measuring system includes both the technical and operational characteristics of the computer, as well as the metrological and technical characteristics of the analog-to-digital converter. The specified expression allows to find the optimal value of calibration and verification interval. Determination of the optimal calibration interval required to control the metrological characteristics during long-term operation of the computer measuring system. The developed model can be used to set requirements for the metrological support of instruments and de-vices used in the framework of the automation trend in the sphere of housing and communal services.

Numerical Experiments on the Application of Markov Chain Monte Carlo for the Establishment of Calibration Intervals

This study presented a new approach for conducting measurement reliability analysis and establishing calibration intervals based on Markov chain Monte Carlo (MCMC). Calibration records following the Weibull and lognormal reliability models were generated under various calibration conditions, and they were used to test the validity of the method proposed in this study. Numerical experiments were used to obtain the estimates for the measurement reliability model, and the optimum calibration interval was obtained for the simulated calibration records. The results showed that the measurement reliability models obtained using the MCMC method were consistent with those obtained using the S3 method, which is considered to be the most advanced approach. In particular, both methods exhibited strong agreement in the estimation of calibration records simulated under the renew-if-failed policy. The MCMC method allows sampling to estimate the distribution, and this feature can be employed to calculate the uncertainty of the measurement reliability model and the optimal calibration interval. This uncertainty provides the reliability of the estimation and is expected to help manage the risk of establishing the calibration interval and maintaining measurement quality.

Automation of solving problems of optimization of parameters of metrological maintenance system of measuring equipment

Automation of the metrological service of the enterprise allows to reduce the use of labor to perform tasks of maintenance of measuring equipment and reduce staff errors. At the same time, the process of creating appropriate automated systems requires solving a number of problems related to the need to optimize the parameters of the designed system to ensure its highest efficiency. This article attempts to solve the problem of covering various models in the synthesis and study of simulation computer models that actively use the database of measuring instruments of enterprises. Developed and software implemented a model that allows interactive mode, taking into account the characteristics coming from the calibration laboratories of the service, and given economic and metrological criteria, to determine the values of optimal calibration and repair intervals, the optimal number of inspections in the repair interval and other parameters. The dependence of FTA reliability indicators on the quality of metrological maintenance and repair was investigated by simulation. The influence of inter - repair and inter - calibration intervals on economic efficiency of metrological service is investigated. As a result, the dependences are obtained, which also allow to investigate the influence of service quality parameters on complex reliability indicators. The use of research results allows in the dialog mode of the automated workplace of the metrologist to solve problems of optimization of parameters of metrological service on eco-nomic criteria and restrictions of concrete production on indicators of metrological reliability of measuring instruments, to carry out diagnostics and to forecast metrological reliability of measuring instruments. measurement accuracy and reduce the likelihood of hidden failures.

MEASURING EQUIPMENT CALIBRATION AND DETERMINATION OF THE INITIAL CALIBRATION INTERVAL

<jats:p>To optimize measurement procedures in laboratories, in terms of the balance between economics and risk, determination of the optimal calibration interval for measuring equipment has significant importance. This paper will show an approximate, but effective method for determination of initial calibration interval, regarding “ILAC” guidelines and original recommendations based on authors’ experience. The presented applied method is adapted for the equipment used in a laboratory for building materials and structural testing, and the results of its application are shown on the examples of several different instruments. Impact factors on calibration intervals are analyzed, and the basic recommendations for revision of the initial calibration intervals are given.</jats:p>

Determination of optimal calibration intervals by balancing financial exposure against measurement costs

Maintenance strategies associated with fiscal measurement systems have traditionally been based on time-based approach when calibration activities are scheduled at fixed intervals without much consideration to the previous performance of measuring instruments. The current economic challenges encourage abandoning the time-based maintenance in favour of other strategies, such as risk-based approach to maintenance. This approach is used to determine an appropriate calibration frequency by balancing financial exposure against measurement costs.There is not a universally applicable single best practice for determination of calibration intervals, this is reflected in a few officially published documents which provide only a general guidance. Addressing the need for better understanding of the mechanism required for determination of the optimal calibration intervals the detailed calculation algorithm suitable for practical use is developed based on the general guidance on risk-based approach to maintenance.The calculation algorithm is based on statistical analysis of calibration data of an individual measuring instrument which defines the progressive change of a measurement error as a nonstationary random process. The measurement error together with the selected loss function defines the financial exposure which forms the ‘total cost’ function by summation with the measurement costs, determined as the cost of ownership of the measurement instrument. A minimum of the total costs function determines the optimal calibration interval of the measuring instrument.The case study of the ultrasonic flow meters, operating in the custody-transfer gas flow measurement system, are used to illustrate the calculation algorithm. It has been shown that the determination of calibration intervals is a complex mathematical and statistical process requiring accurate and sufficient data including calibration results and registered costs. Application of the suggested calculation algorithm can be beneficial in assessment and minimisation of financial risks associated with currently implemented maintenance strategies as well as in review of calibration intervals to balance financial exposure and measurement costs.

Optimization of calibration intervals for automatic test equipment

Abstract This paper proposed an approach for evaluating the optimal calibration interval of ATE. The on-station calibration strategy of ATE is analysed on the basis of the metrology chain. The calibration interval of a single instrument is determined by a grey prediction model based on fresh information. The out of tolerance-calibration matrix, which is used to calculate the metrology contribution rate, is established according to the multi-signal flow model. The calibration interval of ATE is optimized by weighted average to overcome the disadvantages of the traditional experiential method. The results demonstrate that compared with the cannikin principle and criteria of the highest rank of the metrology chain principle, our approach can make better use of test resources and save more time.

Quantifying Sources of Low-Frequency Drift During Single-Molecule Experiments

Single-molecule techniques have evolved to the point where quantitative force measurements on biological systems can be performed down into the femtonewton range. As resolution is constantly improving, the pinpointing and elimination of noise sources become increasingly important. Complementary to Fourier analysis, Allan-variance analysis is ideally suited for this task; adjacent time series are recorded and the variations between observation intervals are calculated. Here, we provide a comprehensive toolbox consisting of acquisition and analysis software as well as fitting scripts to directly extract parameters of noise and low-frequency drift sources [1].Furthermore, the validity and robustness of Allan-variance analysis is demonstrated in data obtained from various optical-tweezers setups wherein laboratory-specific noise sources are detected. This allows for a quantitative discrimination as well of common detection systems as of different calibration methods. In addition, we demonstrate how our toolbox can be applied during single-molecule experiments. Here, we determine the optimal calibration interval for any setup, suitable settings for variance and update rates in force-feedback loops, and variations due to the geometrical constraints of the sample chamber.As outlook, we present data from other single-molecule techniques such as solid-state nanopores and magnetic tweezers. These emphasize the fact that Allan-variance analysis can be used as a standard tool enabling precise quantification of noise and drift effects.[1] F. Czerwinski, A.C. Richardson, and L.B. Oddershede, “Quantifying Noise in Optical Tweezers by Allan Variance,” Opt. Express 17, 13255-13269 (2009)

Optimal Calibration Interval in Case of Integrated Brownian Behavior: The Example of a Rubidium Frequency Standard

In this paper, two different techniques are considered in order to determine the optimal calibration interval: the intervals that are obtained using a mathematical model and those that are calculated with an iterative technique referred to as a simple response method. It is shown that both techniques provide useful information for an accurate calibration of a rubidium frequency standard. The authors have chosen this example because the degradation of its calibration condition can be modeled by the use of a quite complex stochastic process called the integrated Brownian motion, which is also of interest in other different contexts. The rubidium frequency standard is diffused in industrial calibration laboratories

Stochastic and Reactive Methods for the Determination of Optimal Calibration Intervals

The recommended length of calibration intervals of measurement instrumentation can be determined by means of several techniques. In this paper, three different methods are compared for the establishment of optimal calibration intervals of atomic clocks. The first one is based on a stochastic model and provides the estimation of the calibration interval also in the transient situation, while the others pertain to the class of the so-called reactive methods, which determine the value of the optimal interval on the basis of the last calibration outcomes. Algorithms have been applied to experimental data, and the obtained results have been compared in order to determine the most effective technique. Since the analyzed reactive methods present a long transient time, a new algorithm is proposed and applied to the available data.

A Gray System Modeling Approach to the Prediction of Calibration Intervals

This paper discusses a class of data-preprocessed statistical models for evaluating the optimal calibration interval of a measuring instrument. These models are based on the assumption that the calibration status of a measuring instrument can be predicted using the instrument's historical calibration data. On the basis of the gray threshold value prediction method, a series of historical calibration data are preprocessed so that a monotone-increasing series of data points will be created. Then, the first-order gray model, exponential regression, linear regression, and general polynomial regression are applied to fit the series of preprocessed data points to predict the time at which the measured value of the instrument will be outside of the allowable tolerance range. The effectiveness of each developed model was evaluated through the actual data collected in a calibration laboratory. Results demonstrate that the gray threshold value prediction based on second-order polynomial model, a modified autoregressive model, is the best method for forecasting the calibration interval of a measuring instrument.

Accuracy Comparison Between Techniques for the Establishment of Calibration Intervals: Application to Atomic Clocks

This paper deals with two different techniques for the establishment of the optimal calibration intervals of cesium atomic clocks. In particular, the intervals obtained using a mathematical model derived from a metrological analysis are compared with those calculated with an iterative technique referred to as simple response method (SRM). The remarkable consistency between the results achieved with these different calibration strategies not only provides an experimental cross-validation of both techniques, but it also allows the definition of two interchangeable criteria to ensure the metrological confirmation of any atomic clock of this type.

Monitoring the calibration status of a measuring instrument by a stochastic model

The paper discusses a class of stochastic models for evaluating the optimal calibration interval in measuring instruments. The model is based on the assumption that the calibration status of a measuring instrument can be monitored by means of one observable parameter. The observable parameter is undergoing a stochastic drift process. The paper introduces and compares stochastic drift models of different nature, and estimates the first passage time of the monitored parameter on a preset limit. The calibration interval is determined as a suitable percentile of the distribution function of the first passage time. A preliminary validation of the model, based on a sample of experimental data collected on a class of instruments, is finally reported.