化学检测实验室内部质量控制方式探讨及结果评价

质量控制是指实验室利用现代科学管理的方法和技术控制与分析有关的各个环节,目的是把分析测试的误差控制在允许的范围内,保证分析的准确度和精密度,它贯穿于实验室全部质量活动的始终,包括分析前质量保证、分析中质量控制和分析后质量评估三个阶段。其中分析中质量控制又称检测结果的质量保证,实验室的其它质量活动对其提供保证或促进作用。本文从质量控制图、标准物质、回收试验、实验     

质量控制图的修正及其在化学计量测试中的应用

质量控制图是制造业控制产品规格质量过程中经常使用的一项技术工具[1],等同采用ISO 8258-1991的GB/T 4091-2001《常规控制图》[2]中提供了常规控制图的绘制方法。近年来,随着对化学分析测试过程质量控制要求的不断提高,起源于制造业的GB/T 4091-2001广泛被检测实验室用于分析和控制测试系统的稳定状态。但因制造和分析测     

质量控制图用于评价分析化学实验教学及实验数据质量

本文将两种在分析工作中已被广泛应用的质量控制图 (ＱｕａｌｉｔｙＣｏｎｔｒｏｌＣｈａｒｔ,ＱＣＣ)应用于评价分析化学实验教学及学生实验数据质量。实际应用表明 ,这样能直观地对学生实验数据作出判断 ,同时也能比较各个实验小组及班级之间总体实验水平 ,及时发现实验准备工作中及实验方法本身的有关问题 ,这对于因材施教、改进实验教学方法和提高教学效果是很有帮助的。计算机的普及应用使得这种方法便于推广应用。1　分析化学实验教学中质量控制图的建立方法　　ＱＣＣ是用作图的方式来表达受管理的质量指标。将某组分的质量分数或某…     

标准物质在检测实验室质量控制中的应用

【】 本文介绍了检测中使用标准物质进行质量控制的重要意义,分别在盲样测试、期间核查和质量控制图应用方面提出了使用标准物质进行质量控制的三种方法,并通过在实验室获得的检测数据对上述应用方法作了实例说明,对检测实验室应用标准物质进行质量控制工作具有指导意义。     

液相色谱响应因子控制图在标准物质质量控制中的应用

本文拟通过液相色谱中标准溶液的响应因子绘制平均值-极差控制图,监控标准物质的稳定性和有效性,实现对标准物质质量控制,进而保证分析结果的准确性。     

激光粒度分析技术在药物研究和质量控制中的应用进展

近年来,激光粒度分析技术广泛应用于药物的质量研究和质量控制领域.从激光散射测定粒度的原理、仪器的一般要求和影响测试结果的因素、方法验证的要求以及该技术在药物领域中最新应用等方面进行综述,为激光粒度分析技术在药物中的应用开发提供有益的参考.     

金测定的方法验证及质量控制图的建立

对DZ/T 0279.19–2016 《区域地球化学样品分析方法第19部分:金量测定泡沫塑料富集–石墨炉原子吸收光谱法》进行了实验室方法验证,并建立了相应的质量控制图。结果表明,实验室具备采用泡沫塑料富集–石墨炉原子吸收光谱法测定金的资源和技术能力,建立的质量控制图能够对分析系统进行有效核查。     

(?)_i±kIS_(xy)线性质量控制图的制备

实验室取得可信数据与多方面因素有关,其中对所得数据进行严格的分析质量控制,是重要的措施之一。目前被广泛采用的X—SD控制图和X—R控制图,在实际使用中碰到了一些问题,其中突出的问题是控制点的被测物浓度与样品中待测物的浓度相差悬殊,导致两者的实际离散度不一致,而使分析数据失去控制。为了使控制图能适应于不同浓度样品的控制,并减少制备控制图的工作量,本文利用回归参数提出了线性分析质量控制图,即(?)±kIS_(xy)分析质量控制图。 1 原理 分析方法的工作曲线一般符合(?)=a+bx直线方程,其理论相关系数为1,回归线的剩余标准差为S_(xy)=∨∑(Y—y)~2/(n—2),表示X与Y之间线性关系以外的其它变异因素所引起的(?)线的波动程度,即代表(?)线的离散程度,(?)线的95％可信区间为:     

质量控制图在监视直读光谱仪检测数据稳定性中的应用

DV4–1000型直读光谱仪(美国BAIRD公司)其重要光学部件易受温度、湿度、使用年限等因素影响,检测数据有不同程度的波动。结合质量管理中控制图统计方法 (6σ原理)和数理统计最小概率原理,利用在相对恒温、恒湿的环境条件下在一段时间内积累的数据,绘制成X–R控制图,用判异准则判别直读光谱仪是否处于稳定的状态。     

Excel VBA在化学分析质量控制中的应用

采用Excel VBA开发了化学分析质量控制图系统。用VBA语言编制出质控图生成、判定程序,再利用Excel内置图表功能将所有的质控图像显示在操作界面。该系统可对录入的原始数据进行审查并自动生成质量控制图表,在日常的质控活动时可以自动判定所分析的质控样结果是否满足质量控制要求。该系统的判定结果与理论统计结果一致。     

仪器分析的质量保证探讨

探讨了仪器分析过程中的质量分析方法及分析中的数据处理、方法选择、质量监控、质量评估和信息管理等质量保证问题，为进一步提高仪器分析质量水平和管理水平经及最大限度地发挥仪器分析的作用作了一些有益的探索。     

Metrological role of neutron activation analysis. III. Role of INAA in sampling behavior characterization

The minimum sample size, usually 100 mg or larger, is often the only information given on certificates of existing certified reference materials (CRMs) to describe sampling behavior. This value is not only too large for quality control requirements of microanalysis, but also too general to reflect the strong element-specific nature of the sampling behavior of solid materials. In this paper, the third and final of the series, we explain the need for CRMs with sampling behavior characterized for individual elements and describe the unique role of instrumental neutron activation analysis in sampling behaviour characterization. Received: 19 March 2001 Accepted: 2 October 2001     

A model for the evaluation of uncertainty in routine multi-element analysis

A model for calculating uncertainty in routine multi-element analysis is described. The model is constructed according to the principles of GUM/EURACHEM. Control chart results are combined with other existing data and results from the actual measurement into a concentration-dependent estimate of combined standard uncertainty. Since possible sources of bias are included in the calculation, overall bias as estimated from the data is used only as a control to identify needs for modification of the model and/or the analytical procedure. For each individual sample, uncertainty can be calculated automatically based on two pre-calculated parameters together with measured concentration and instrumental standard deviation. As an example, the model is demonstrated for inductively coupled plasma-mass spectrometry (ICP-MS) analysis of sewage sludge including laboratory sub-sampling, sample preparation, and instrumental determination.     

Analytical quality by design in the development of a cyclodextrin‐modified capillary electrophoresis method for the assay of metformin and its related substances

Quality by Design (QbD) is a new paradigm of quality to be applied to pharmaceutical products and processes, recently encouraged by International Conference on Harmonisation guidelines. In this paper QbD approach was applied to the development of a CE method for the simultaneous assay of metformin hydrochloride (MET) and its main impurities. QbD strategy was focused on electrophoretic process understanding, and the analytical method was thoroughly evaluated by applying risk assessment and chemometric tools. Method scouting allowed CD‐CZE based on the addition of carboxymethyl‐β‐CD to Britton‐Robinson acidic buffer to be chosen as operative mode. Seven critical process parameters (CPPs) were selected, related to capillary, injection, BGE and instrumental settings. The effect of the different levels of the CPPs on critical quality attributes (CQAs), e.g. critical resolution values and analysis time, was evaluated in a screening study. Response surface methodology led to draw contour plots and sweet spot plots. The definition of design space was accomplished by applying Monte‐Carlo simulations, thus identifying by risk of failure maps a multivariate zone where the CQAs fulfilled the requirements with a selected probability. Finally, a control strategy was designed and the method was applied to a real sample of MET tablets.     

Quality control of uranium concentration measurements

Quality assurance and quality control are necessary to ascertain the output of any instrument with a certain level of confidence and maintain the measurement process in a state of statistical control. Data generated by three laser fluorimeters, used for analysing mass concentration of total uranium in liquid samples, were used in the present study. Erroneous data values, called outliers, were detected by Dixon test, Discordance outlier test, Rosner outlier test and Box plot. The distribution fitted to the data, was tested by Kolmogorov–Smirnov test, Chi-square test and Shapiro–Wilks test. From Shewart Control Charts it was concluded that the instruments were not in statistical control and an instrumental problem existed. The instrumental problem was solved and the instruments were subjected to quality control exercise again. Statistical parameters of the data from the detectors were compared before and after servicing. The improvement of the quality of detector output was evident.     

Importance of quality control in a gas chromatographic method to characterize crude oils

A quality control scheme has been developed to achieve reproducible capillary GC characterization of crude oils and petroleum condensates. The method uses an internal standard to quantify the amount of non-eluted material in the crude oil sample. Correlation between the gas chromatographic results and actual distillation was 2 %. After repeated use, however, weekly analysis of the same standard crude oil did not give the correct composition. This was a result of discrimination, which worsened with time, as a result of leaks in the septum or the graphite ferrules. More reproducible results were obtained by performing frequent analyses of quality control samples to ensure that the gas chromatographic system was operating properly. The use of quality control charts was a convenient way of ensuring correct operation and identifying the need for corrective action on the gas chromatographic system.     

Computer graphics for quality control in the INAA of geological samples

A data reduction system for the routine instrumental activation analysis of samples is described, with particular emphasis on interactive graphics capabilities for evaluating analytical quality. Graphics procedures have been developed to interactively control the analysis of selected photopeaks during spectral analysis, and to evaluate detector performance during a given counting cycle. Graphics algorithms are also used to compare the data on reference samples with accepted values, to prepare quality control charts to evaluate long term precision and to search for systematic variations in data on reference samples as a function of time.     

Quality assurance in analytical measurement

 The peculiarities of analytical measurement require to check characteristics of the error (its components) of the obtained analysis results to assure the quality of the measurements. This article deals with the various quality assurance procedures and algorithms which are used to check the quality indices, i.e. the accuracy, reproducibility, certainty and repeatability of analytical measurements: These procedures include: laboratory rapid control; Intra-laboratory statistical control (statistical selection control by alternative attribute, statistical selection control by quantity method of periodic check of the analysis procedure for conformity to the specified requirements) and external control (inter-laboratory control checks, inter-laboratory comparison tests, and intra-laboratory control algorithms carried out by the appropriate supervisory body.) in the separately taken laboratory. The respective algorithms, control plans and control requirements, specified according to the different control aims and assurance tasks, enable the quality and certianty of analytical information obtained in laboratories in Russia to be assured. Received: 9 November 1998 / Accepted: 24 November 1998     

Quality control techniques for chemical analysis: some current shortcomings and possible future developments

Current approaches to quality control in chemical analysis are examined. Issues that frequently cause problems are proposed. Future developments relating to ways in which the incidence of mistakes might be reduced are discussed as possible supplements to more well-established quality control measures.