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Lundkvist, Peder
Publications (7 of 7) Show all publications
Lundkvist, P., Bergquist, B. & Vanhatalo, E. (2020). Statistical Methods - Still Ignored?: The Testimony of Swedish Alumni. Total Quality Management and Business Excellence, 31(3-4), 245-262
Open this publication in new window or tab >>Statistical Methods - Still Ignored?: The Testimony of Swedish Alumni
2020 (English)In: Total Quality Management and Business Excellence, ISSN 1478-3363, E-ISSN 1478-3371, Vol. 31, no 3-4, p. 245-262Article in journal (Refereed) Published
Abstract [en]

Researchers have promoted statistical improvement methods as essential for product and process improvement for decades. However, studies show that their use has been moderate at best. This study aims to assess the use of statistical process control (SPC), process capability analysis, and design of experiments (DoE) over time. The study also highlights important barriers for the wider use of these methods in Sweden as a follow-up study of a similar Swedish study performed in 2005 and of two Basque-based studies performed in 2009 and 2010. While the survey includes open-ended questions, the results are mainly descriptive and confirm results of previous studies. This study shows that the use of the methods has become more frequent compared to the 2005 study. Larger organisations (>250 employees) use the methods more frequently than smaller organisations, and the methods are more widely utilised in the industry than in the service sector. SPC is the most commonly used of the three methods while DoE is least used. Finally, the greatest barriers to increasing the use of statistical methods were: insufficient resources regarding time and money, low commitment of middle and senior managers, inadequate statistical knowledge, and lack of methods to guide the user through experimentations.

Place, publisher, year, edition, pages
Taylor & Francis, 2020
Keywords
statistical process control, capability analysis, design of experiments, implementation barriers, statistical thinking, longitudinal study, Swedish organizations.
National Category
Reliability and Maintenance
Research subject
Quality technology and logistics
Identifiers
urn:nbn:se:ltu:diva-67189 (URN)10.1080/14783363.2018.1426449 (DOI)000505886200002 ()
Funder
Swedish Research Council, 340-2013-5108
Note

Validerad;2020;Nivå 2;2020-01-27 (johcin)

Available from: 2018-01-08 Created: 2018-01-08 Last updated: 2020-01-27Bibliographically approved
Lundkvist, P. (2015). Application of Statistical Methods: Challenges Related to Continuous Industrial Processes (ed.). (Doctoral dissertation). Paper presented at . : Luleå tekniska universitet
Open this publication in new window or tab >>Application of Statistical Methods: Challenges Related to Continuous Industrial Processes
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

For decades, many efficient statistical improvement methods have been available to improve the quality of processes and products. Statistical process control (SPC), process capability analysis (CA), and design of experiments (DoE) are among the most powerful process monitoring and problem-solving methods in the quality engineering toolbox. SPC and CA are methods that are more directed toward monitoring existing processes and assessing their capability related to customer requirements, while DoE typically is used to improve products and processes. It is increasingly difficult to understand and control industrial processes and products because of the increasing complexity of technical systems. Among the complications for statistical analysis of measurements in continuous industrial processes are the multitude of variables and the combination of high-frequency sampling of the measurement systems and process dynamics. Therefore, in industry today, process data are often multivariate as well as autocorrelated (i.e., dependent in time).The purpose of this research is to support the application of SPC, CA, and DoE. More specifically, the aims of this research are: [1] to analyze the use, and related barriers, of SPC, CA, and DoE in organizations; [2] to provide guidance in selection of appropriate decision methods for Cpk when data are autocorrelated; and [3] to adapt methods for analyzing designed experiments to manage dynamic process behavior and autocorrelation in continuous processes.The main contribution of this research is that it explicitly illustrates and describes special considerations and problems that can be encountered when planning, conducting, and analyzing real experiments in continuous industrial processes. Other contributions of this research are: the practical use and development of adapted analysis procedures for experiments in continuous processes; the presentation of comparative data that helps in the selection of decision methods for Cpk when data are autocorrelated; and the analysis of barriers that hinder the use of statistical methods in Swedish organizations.

Place, publisher, year, edition, pages
Luleå tekniska universitet, 2015
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-17048 (URN)14ed19b3-12d2-4855-87ba-7104e5fde858 (Local ID)978-91-7583-372-9 (ISBN)978-91-7583-373-6 (ISBN)14ed19b3-12d2-4855-87ba-7104e5fde858 (Archive number)14ed19b3-12d2-4855-87ba-7104e5fde858 (OAI)
Note
Godkänd; 2015; 20150420 (pedlun); Nedanstående person kommer att disputera för avläggande av teknologie doktorsexamen. Namn: Peder Lundkvist Ämne: Kvalitetsteknik/Quality Technology & Management Avhandling: Application of Statistical Methods Challenges Related to Continuous Industrial Processes Opponent: Dr Bart De Ketelaere, Research Manager, Division Mechatronics, Biostatistics and Sensors (MeBioS), Faculty of Bioscience Engineering, Katholieke, Universiteit Leuven, Leuven, Belgium Ordförande: Professor Bjarne Bergquist, Avd för industriell ekonomi, Institutionen för ekonomi, teknik och samhälle, Luleå tekniska universitet, Luleå Tid: Onsdag 16 september kl 13.00 Plats: A109, Luleå tekniska universitetAvailable from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved
Lundkvist, P. & Bergquist, B. (2014). Experimental Study of Oscillation Mark Depth in Continuous Casting of Steel (ed.). Paper presented at . Ironmaking & steelmaking, 41(4), 304-309
Open this publication in new window or tab >>Experimental Study of Oscillation Mark Depth in Continuous Casting of Steel
2014 (English)In: Ironmaking & steelmaking, ISSN 0301-9233, E-ISSN 1743-2812, Vol. 41, no 4, p. 304-309Article in journal (Refereed) Published
Abstract [en]

Mould oscillation is needed to reduce friction and thus prevent sticking and breakout of the liquid metal during casting. However, this oscillation is known to cause surface defects in the solidified steel slabs, so called oscillation marks. In this paper, the depth and the depth variation of these oscillation marks were studied using a two-level full factorial experiment (24) with four additional centre point runs. Four factors were studied: stroke length of the mould, oscillation frequency, motion pattern (strip factor) and casting speed. The stroke length affected the depth of the marks the most, where larger strokes created deeper marks. The interaction between the oscillation frequency and the strip factor of the mould also affected the oscillation mark depth. The oscillation mark depth variation was also increased by increased stroke lengths and at higher oscillation frequencies. The largest effect on the oscillation depth variation was found for the interaction between the stroke length and the oscillation frequency.

National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-7249 (URN)10.1179/1743281213Y.0000000132 (DOI)000337064600012 ()2-s2.0-84899982253 (Scopus ID)596d057f-a7e4-4c5b-ae4d-c7de33d6dd8c (Local ID)596d057f-a7e4-4c5b-ae4d-c7de33d6dd8c (Archive number)596d057f-a7e4-4c5b-ae4d-c7de33d6dd8c (OAI)
Note
Validerad; 2014; 20121005 (pedlun)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Lundkvist, P. & Vanhatalo, E. (2014). Identifying Process Dynamics through a Two-Level Factorial Experiment (ed.). Paper presented at . Quality Engineering, 26(2), 154-167
Open this publication in new window or tab >>Identifying Process Dynamics through a Two-Level Factorial Experiment
2014 (English)In: Quality Engineering, ISSN 0898-2112, E-ISSN 1532-4222, Vol. 26, no 2, p. 154-167Article in journal (Refereed) Published
Abstract [en]

Industrial experiments are often subjected to critical disturbances and in a small design with few runs the loss of experimental runs may dramatically reduce analysis power. This article considers a common situation in process industry where the observed responses are represented by time series. A time series analysis approach to analyze two-level factorial designs affected by disturbances is developed and illustrated by analyzing a blast furnace experiment. In particular, a method based on transfer function-noise modeling is compared with a ‘traditional’ analysis using averages of the response in each run as the single response in an analysis of variance (ANOVA).

Abstract [en]

Dynamic processes undergo a transition time when changing experimental factors and therefore an experimenter is often interested in estimating effect dynamics alongside effect sizes. This article illustrates an eight-step analysis procedure for model identification of a multiple-input transfer function–noise model for the response from a two-level factorial experiment in a blast furnace process. Because real data often are affected by disturbances and missing observations, our proposed procedure deals with these problems and results in a transfer function–noise model that captures system dynamics and provides effect estimates from the experiment.

National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-11505 (URN)10.1080/08982112.2013.830738 (DOI)000334045900002 ()2-s2.0-84899029765 (Scopus ID)a7ef5a7e-a6a1-4b17-946c-d502bf8ef379 (Local ID)a7ef5a7e-a6a1-4b17-946c-d502bf8ef379 (Archive number)a7ef5a7e-a6a1-4b17-946c-d502bf8ef379 (OAI)
Note
Validerad; 2014; 20120810 (pedlun)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Lundkvist, P., Vännman, K. & Kulahci, M. (2012). A Comparison of Decision Methods for Cpk When Data are Autocorrelated (ed.). Paper presented at . Quality Engineering, 24(4), 460-472
Open this publication in new window or tab >>A Comparison of Decision Methods for Cpk When Data are Autocorrelated
2012 (English)In: Quality Engineering, ISSN 0898-2112, E-ISSN 1532-4222, Vol. 24, no 4, p. 460-472Article in journal (Refereed) Published
Abstract [en]

In many industrial applications, autocorrelated data are becoming increasingly common due to, for example, on-line data collection systems with high-frequency sampling. Therefore the basic assumption of independent observations for process capability analysis is not valid. The purpose of this article is to compare decision methods using the process capability index Cpk, when data are autocorrelated. This is done through a case study followed by a simulation study. In the simulation study the actual significance level and power of the decision methods are investigated. The outcome of the article is that two methods appeared to be better than the others.

National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-10842 (URN)10.1080/08982112.2012.710165 (DOI)000309123100003 ()2-s2.0-84867036649 (Scopus ID)9b84bc86-6817-4134-bc6a-cbd60fb9011e (Local ID)9b84bc86-6817-4134-bc6a-cbd60fb9011e (Archive number)9b84bc86-6817-4134-bc6a-cbd60fb9011e (OAI)
Note
Validerad; 2012; 20120810 (pedlun)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Lundkvist, P. (2012). Experiments and Capability Analysis in Process Industry (ed.). (Licentiate dissertation). Paper presented at . Luleå: Luleå tekniska universitet
Open this publication in new window or tab >>Experiments and Capability Analysis in Process Industry
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Alternative title[sv]
Experiment och duglighetanalys i processindustrin
Abstract [en]

The existence of variation has been a major problem in industry since the industrial revolution. Hence, many organizations try to find strategies to master and reduce the variation. Statistical analysis, such as process capability analysis and Design of Experiments (DoE), often plays an important role in such a strategy. Process capability analysis can determine how the process performs relative to its requirements or specifications, where an important part is the use of process capability indices. DoE includes powerful methods, such as factorial designs, which helps experimenters to maximize the information output from conducted experiments and minimize the experimental work required to reach statistically significant results.Continuous processes, frequently found in the process industry, highlight special issues that are typically not addressed in the DoE literature, for example, autocorrelation and dynamics. The overall purpose of this research is to contribute to an increased knowledge of analyzing DoE and capability in process industry, which is achieved through simulations and case studies of real industrial processes. This research focus on developing analysis procedures adapted for experiments and comparing decision methods for capability analysis in process industry.The results of this research are presented in three appended papers. Paper A shows how the use of a two-level factorial experiment can be used to identifying factors that affect the depth and variation of the oscillation mark that arises from the steel casting process. Four factors were studied; stroke length of the mold, oscillation frequency, motion pattern of the mold (sinus factor), and casting speed. The ANOVA analysis turned out to be problematic because of a non- orthogonal experimental design due to loss of experimental runs. Nevertheless, no earlier studies where found that shows how the sinus factor is changed in combination with the oscillation frequency so that the interaction effect could be studied. Paper B develops a method to analyze factorial experiments, affected by process interruptions and loss of experimental runs, by using time series analysis. Paper C compares four different methods for capability analysis, when data are autocorrelated, through simulations and case study of a real industrial process. In summary, it is hard to recommend one single method that works well in all situations. However, two methods appeared to be better than the others. Keywords: Process industry, Continuous processes, Autocorrelation, Design of Experiments, Process capability, Time series analysis.

Abstract [sv]

Förekomsten av variation i tillverkningsprocesser har varit ett problem redan sedan den industriella revolutionen. Därför har många organisationer försökt hitta en strategi för att hantera och reducera variationen. Statistiska metoder som duglighetsanalys och försöksplanering spelar ofta en viktig roll i dessa sammanhang. Duglighetsanalys bedömer hur processen presterar i relation till dess krav eller specifikationer, där en viktig del är användningen av duglighetsindex. Försöksplanering omfattar kraftfulla metoder, exempelvis faktorförsök, för att hjälpa den som utför experiment att maximera informationsutbytet vid experiment och samtidigt minimera de resurser som krävs för att nå statistiskt säkerställda resultat.Kontinuerliga processer, vilka är frekvent förekommande i processindustrin, ger upphov till speciella problem vid experiment som normalt inte behandlas i litteraturen, exempelvis autokorrelation och dynamik. Det övergripande syftet med forskningen i denna avhandling är att bidra till en ökad kunskap om analysen av försöksplanering och duglighet i process industri, vilket uppnås genom simuleringar och fallstudier av verkliga industriella processer.Denna forskning fokuserar på att föreslå och utveckla analysmetoder anpassade för experiment samt att jämföra olika beslutsmetoder för duglighetsanalys i industriella processer.Resultaten av forskningen presenteras i tre bifogade artiklar. Artikel A visar hur ett två-nivåers faktorförsök kan användas för att identifiera de faktorer som påverkar oscillationsmärkesdjupet som uppstår från stålstränggjutnings¬processen. Fyra faktorer studerades; slaglängden av gjutform, svängnings¬frekvensen, rörelsemönstret av gjutform (sinusfaktor) och gjuthastigheten. ANOVA analys visade sig vara problematiskt eftersom försöksdesignen inte var ortogonala på grund av förlorade försöksomgångar. Trots det har inga tidigare studier hittats som visar hur sinusfaktorn ändras i kombination med svängnings¬frekvensen så att samspelseffekten kan studeras. Artikel B utvecklar en metod för att analysera faktorförsök, påverkat av processavbrott och förlust av experimentomgångar, baserat på tidsserieanalys. Artikel C jämför fyra olika metoder för duglighetsanalys, när data är autokorrelerad, genom simuleringar och fallstudie av en faktisk industriell process. Sammanfattningsvis är det svårt att rekommendera en metod som fungerar bra i alla situationer. Resultaten pekar på att två metoder är bättre än de andra.

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2012. p. 25
Series
Licentiate thesis / Luleå University of Technology, ISSN 1402-1757
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-17276 (URN)28c79275-d381-4e15-af34-c1d790ee4dbf (Local ID)978-91-7439-488-7 (ISBN)28c79275-d381-4e15-af34-c1d790ee4dbf (Archive number)28c79275-d381-4e15-af34-c1d790ee4dbf (OAI)
Note
Godkänd; 2012; 20121001 (pedlun); LICENTIATSEMINARIUM Ämne: Kvalitetsteknik/Quality Technology & Management Examinator: Professor Bjarne Bergquist, Institutionen för ekonomi, teknik och samhälle, Luleå tekniska universitet Diskutant: Docent Peter Söderholm, Trafikverket, Luleå Tid: Onsdag den 31 oktober 2012 kl 10.00 Plats: A109, Luleå tekniska universitetAvailable from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved
Lundkvist, P. (2012). Forskningsrapport: Planering av brikettförsök vid masugn 3 (ed.). Paper presented at . Luleå: Luleå tekniska universitet
Open this publication in new window or tab >>Forskningsrapport: Planering av brikettförsök vid masugn 3
2012 (Swedish)Report (Other academic)
Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2012. p. 17
Series
Research report / Luleå University of Technology, ISSN 1402-1528
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-25348 (URN)ed24705f-d478-4be6-af4b-f65aae4d0595 (Local ID)978-91-7439-535-8 (ISBN)ed24705f-d478-4be6-af4b-f65aae4d0595 (Archive number)ed24705f-d478-4be6-af4b-f65aae4d0595 (OAI)
Note
Godkänd; 2012; 20121122 (pedlun)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved
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