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Thesis for the Degree of Master of Science

 

Year 2010
Antti Kauhanen

Statistical quality control module in a laboratory information management system


The importance of laboratory information management systems (LIMS), the basic tools of laboratory data handling, has grown continuously during their almost three-decade lifespan. As a result of the automation and complexity of modern measurement devices and interfacing with external systems, the amount of data available in LIMS has increased and the systems have become more intelligent and feature rich.

A LIMS commonly includes some statistical monitoring functionality for ensuring laboratory analysis quality. This functionality is usually implemented with basic SPC-charting. However, during the last few years, the amount and complexity of LIMS data have increased. At the same time, modern multivariate statistical analysis methods have reached a point where they are commonly applied for fault detection, prediction and monitoring. However, these methods are still rarely applied in conjunction with LIMS programs.

In addition to the evolution of monitoring methods, the possibilities provided by software development have increased. With new internet based platforms, open source frameworks and increased computational power, the creation of complex calculation modules has become easier and more cost effective.

The aim of this Master's Thesis was to develop a state-of-the-art, extendable, online supportive monitoring module for LIMS use.

In the literature part of this master's thesis, multiple univariate and multivariate monitoring methods are presented. In addition, a brief look is also taken into LIMS history, laboratory QC and different commercial, third party monitoring applications.

The experimental part of the thesis consists of development of the monitoring module. Different development phases, and the chosen technologies, architecture and development methods are discussed.

A novel software module was developed as the end result of the development project. The module can be used as a basis for implementing a range of advanced LIMS related monitoring methods.


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