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Modelling and Validation of Industrial Measurement Systems - Aspects of Quality and Human Factors

Wirandi, Jenny LU (2007)
Abstract (Swedish)
Popular Abstract in Swedish

Denna avhandling validerar industriella mätsystem, där både de tekniska och mänskliga aspekterna innefattas. Syfte är att få bättre kunskap om den mätteknik som används för att kunna kvalitetsbestämma produkter och för att slutligen på ett mer pålitligt sätt kunna bestämma kvalitén på den tillverkande produkten. För att kunna göra detta föreslårs en metod som tar fram ett kvalitets index som kan ta hänsyn till både de kvantitativa mätningarna och de kvalitativa omdömena från männsikan. Denna metod är en lovande start inför framtida utvecklande av kvalitets index som baseras på både kvalitativa och kvantitativa faktorer. Ett index som detta gör det även möjligt att bättre kunna jämföra olika... (More)
Popular Abstract in Swedish

Denna avhandling validerar industriella mätsystem, där både de tekniska och mänskliga aspekterna innefattas. Syfte är att få bättre kunskap om den mätteknik som används för att kunna kvalitetsbestämma produkter och för att slutligen på ett mer pålitligt sätt kunna bestämma kvalitén på den tillverkande produkten. För att kunna göra detta föreslårs en metod som tar fram ett kvalitets index som kan ta hänsyn till både de kvantitativa mätningarna och de kvalitativa omdömena från männsikan. Denna metod är en lovande start inför framtida utvecklande av kvalitets index som baseras på både kvalitativa och kvantitativa faktorer. Ett index som detta gör det även möjligt att bättre kunna jämföra olika produkter och service. (Less)
Abstract
Although there is a fairly large number of books and articles concerning the validation of technical measurement systems, there are only a few which take into account the whole measurement system consisting of both technical and non-technical aspects. A measurement system comprises both the measurement process and the human being who conducts the measurement. In this way, the human being may be a part of the initiating process (e.g. sampling), and/or part of the ongoing process (such as manual handling of the sample). The human being, however, is always a part of the final process, where the results are interpreted.



The purpose of this thesis is to validate industrial measurement systems, including both technical and... (More)
Although there is a fairly large number of books and articles concerning the validation of technical measurement systems, there are only a few which take into account the whole measurement system consisting of both technical and non-technical aspects. A measurement system comprises both the measurement process and the human being who conducts the measurement. In this way, the human being may be a part of the initiating process (e.g. sampling), and/or part of the ongoing process (such as manual handling of the sample). The human being, however, is always a part of the final process, where the results are interpreted.



The purpose of this thesis is to validate industrial measurement systems, including both technical and non-technical aspects of these systems, in order to understand them better and to increase the ability to estimate the quality of the product. In order to do so, a general method that estimates a quality index capable of handling both qualitative and quantitative factors is proposed. The suggested method uses a fuzzy neural network as a tool since such a tool has a learning function that allows the integration of the human judgement of quality into a quantitative index. This method thus constitutes a promising starting point for the future development of a representative quality index based on both quantitative and qualitative factors. Such an index may be able to allow better comparison of different products or services.



Part I of this thesis gives a brief overview of the research methods used, the research areas investigated, and the theory behind this field.



This thesis consists of eight papers, presented in Part II. The papers discuss, among other things, the role of the human being in automated measurement systems, problems that occur when implementing advanced measurement concepts to modern industries, automated control of sensors and quality assessments. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Professor Pendrill, Leslie, Statens Tekniska Forskningsinstitut, Borås
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Uncertainty Analysis, Quality Index, Instrumentation technology, Mät- och instrumenteringsteknik, Traceability, Fuzzy Variable, Pulp Quality, Industrial Measurement, Human Factor, GUM, Calibration, Fibre Measurement
publisher
Department of Electrical Measurements, Lund University
defense location
Sal E:1406, E-huset, Ole Römers väg 3, Lunds Tekniska Högskola
defense date
2007-06-13 10:15
external identifiers
  • other:ISRN:LUTEDX/TEEM--1086--SE
ISSN
0346-6221
ISBN
978-91-628-7186-4
language
English
LU publication?
yes
id
ccbe96a0-7074-4a48-8d99-f66b64e93ba8 (old id 548772)
date added to LUP
2007-09-10 15:58:10
date last changed
2016-09-19 08:44:55
@phdthesis{ccbe96a0-7074-4a48-8d99-f66b64e93ba8,
  abstract     = {Although there is a fairly large number of books and articles concerning the validation of technical measurement systems, there are only a few which take into account the whole measurement system consisting of both technical and non-technical aspects. A measurement system comprises both the measurement process and the human being who conducts the measurement. In this way, the human being may be a part of the initiating process (e.g. sampling), and/or part of the ongoing process (such as manual handling of the sample). The human being, however, is always a part of the final process, where the results are interpreted.<br/><br>
<br/><br>
The purpose of this thesis is to validate industrial measurement systems, including both technical and non-technical aspects of these systems, in order to understand them better and to increase the ability to estimate the quality of the product. In order to do so, a general method that estimates a quality index capable of handling both qualitative and quantitative factors is proposed. The suggested method uses a fuzzy neural network as a tool since such a tool has a learning function that allows the integration of the human judgement of quality into a quantitative index. This method thus constitutes a promising starting point for the future development of a representative quality index based on both quantitative and qualitative factors. Such an index may be able to allow better comparison of different products or services.<br/><br>
<br/><br>
Part I of this thesis gives a brief overview of the research methods used, the research areas investigated, and the theory behind this field.<br/><br>
<br/><br>
This thesis consists of eight papers, presented in Part II. The papers discuss, among other things, the role of the human being in automated measurement systems, problems that occur when implementing advanced measurement concepts to modern industries, automated control of sensors and quality assessments.},
  author       = {Wirandi, Jenny},
  isbn         = {978-91-628-7186-4},
  issn         = {0346-6221},
  keyword      = {Uncertainty Analysis,Quality Index,Instrumentation technology,Mät- och instrumenteringsteknik,Traceability,Fuzzy Variable,Pulp Quality,Industrial Measurement,Human Factor,GUM,Calibration,Fibre Measurement},
  language     = {eng},
  publisher    = {Department of Electrical Measurements, Lund University},
  school       = {Lund University},
  title        = {Modelling and Validation of Industrial Measurement Systems - Aspects of Quality and Human Factors},
  year         = {2007},
}