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Bergquist, B. & Vanhatalo, E. (2020). In-situ measurement in the iron ore pellet distribution chain using active RFID technology. Powder Technology, 361, 791-802
Open this publication in new window or tab >>In-situ measurement in the iron ore pellet distribution chain using active RFID technology
2020 (English)In: Powder Technology, ISSN 0032-5910, E-ISSN 1873-328X, Vol. 361, p. 791-802Article in journal (Refereed) Published
Abstract [en]

The active radio frequency identification (RFID) technique is used for in-situ measurement of acceleration and temperature in the distribution chain of iron ore pellets. The results of this paper are based on two experiments, in which active RFID transponders were released into train wagons or product bins. RFID exciters and readers were installed downstream in a harbour storage silo to retrieve data from the active transponders. Acceleration peaks and temperatures were recorded. The results imply that in-situ data can aid the understanding of induced stresses along the distribution chain to, for example, reduce pellet breakage and dusting. In-situ data can also increase understanding of product mixing behaviour and product residence times in silos. Better knowledge of stresses, product mixing and residence times are beneficial to process and product quality improvement, to better understand the transportation process, and to reduce environmental impacts due to dusting.

Place, publisher, year, edition, pages
Elsevier, 2020
Keywords
Mining industry, RFID tags, Temperature sensors, Accelerometers, Flow production systems, Supply chain management
National Category
Reliability and Maintenance
Research subject
Quality technology and logistics
Identifiers
urn:nbn:se:ltu:diva-76886 (URN)10.1016/j.powtec.2019.11.042 (DOI)2-s2.0-85076579100 (Scopus ID)
Note

Validerad;2020;Nivå 2;2020-02-27 (alebob)

Available from: 2019-11-27 Created: 2019-11-27 Last updated: 2020-02-27Bibliographically approved
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
Capaci, F., Vanhatalo, E., Kulahci, M. & Bergquist, B. (2019). The Revised Tennessee Eastman Process Simulator as Testbed for SPC and DoE Methods. Quality Engineering, 31(2), 212-229
Open this publication in new window or tab >>The Revised Tennessee Eastman Process Simulator as Testbed for SPC and DoE Methods
2019 (English)In: Quality Engineering, ISSN 0898-2112, E-ISSN 1532-4222, Vol. 31, no 2, p. 212-229Article in journal (Refereed) Published
Abstract [en]

Engineering process control and high-dimensional, time-dependent data present great methodological challenges when applying statistical process control (SPC) and design of experiments (DoE) in continuous industrial processes. Process simulators with an ability to mimic these challenges are instrumental in research and education. This article focuses on the revised Tennessee Eastman process simulator providing guidelines for its use as a testbed for SPC and DoE methods. We provide flowcharts that can support new users to get started in the Simulink/Matlab framework, and illustrate how to run stochastic simulations for SPC and DoE applications using the Tennessee Eastman process.

Place, publisher, year, edition, pages
Taylor & Francis, 2019
Keywords
Simulation, Tutorial, Statistical process control, Design of experiments, Engineering process control, Closed-loop
National Category
Reliability and Maintenance
Research subject
Quality technology and logistics
Identifiers
urn:nbn:se:ltu:diva-66255 (URN)10.1080/08982112.2018.1461905 (DOI)000468617000002 ()2-s2.0-85066129240 (Scopus ID)
Projects
Statistical Methods for Improving Continuous Production
Note

Validerad;2019;Nivå 2;2019-06-11 (johcin)

Available from: 2017-10-25 Created: 2017-10-25 Last updated: 2019-06-18Bibliographically approved
Capaci, F., Bergquist, B., Kulahci, M. & Vanhatalo, E. (2017). Exploring the Use of Design of Experiments in Industrial Processes Operating Under Closed-Loop Control. Quality and Reliability Engineering International, 33(7), 1601-1614
Open this publication in new window or tab >>Exploring the Use of Design of Experiments in Industrial Processes Operating Under Closed-Loop Control
2017 (English)In: Quality and Reliability Engineering International, ISSN 0748-8017, E-ISSN 1099-1638, Vol. 33, no 7, p. 1601-1614Article in journal (Refereed) Published
Abstract [en]

Industrial manufacturing processes often operate under closed-loop control, where automation aims to keep important process variables at their set-points. In process industries such as pulp, paper, chemical and steel plants, it is often hard to find production processes operating in open loop. Instead, closed-loop control systems will actively attempt to minimize the impact of process disturbances. However, we argue that an implicit assumption in most experimental investigations is that the studied system is open loop, allowing the experimental factors to freely affect the important system responses. This scenario is typically not found in process industries. The purpose of this article is therefore to explore issues of experimental design and analysis in processes operating under closed-loop control and to illustrate how Design of Experiments can help in improving and optimizing such processes. The Tennessee Eastman challenge process simulator is used as a test-bed to highlight two experimental scenarios. The first scenario explores the impact of experimental factors that may be considered as disturbances in the closed-loop system. The second scenario exemplifies a screening design using the set-points of controllers as experimental factors. We provide examples of how to analyze the two scenarios

Place, publisher, year, edition, pages
John Wiley & Sons, 2017
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-61872 (URN)10.1002/qre.2128 (DOI)000413906100024 ()2-s2.0-85012952363 (Scopus ID)
Note

Validerad;2017;Nivå 2;2017-11-03 (andbra)

Available from: 2017-02-08 Created: 2017-02-08 Last updated: 2019-06-18Bibliographically approved
Bergquist, B. & Söderholm, P. (2017). Improved Condition Assessment through Statistical Analyses: Case Study of Railway Track. Luleå: Luleå University of Technology
Open this publication in new window or tab >>Improved Condition Assessment through Statistical Analyses: Case Study of Railway Track
2017 (English)Report (Other academic)
Abstract [en]

Traditional practice within railway maintenance is based on engineering knowledge and practical experience, which are documented in regulations. This practice is often time-based, but can also be condition-based by combining time-based inspections with condition-based actions depending on the inspection results. However, the logic behind the resulting regulation is seldom well documented, which makes it challenging to optimise maintenance based on factors such as operational conditions or new technologies, methodologies and best practices. One way to deal with this challenge is to use statistical analysis and build models that support fault diagnostics and failure prognostics. This analysis approach will increase in importance as automated inspections replace manual inspections. Specific measurement equipment and trains are not the only ones producing automated measurements; regular traffic is increasingly often producing measurements. Hence, there will not be any lack of condition data, but the challenge will be to use this data in a correct way and to extract reliable information as decision support. In this context, it is crucial to balance the risks of false alarms and unrecognised faults, but also to estimate the quality of both data and information. The purpose of this work is to use statistics in order to support improved asset management, by building statistical models as a complement to physical models and engineering knowledge. The resulting models combine theories from the field of time-series analysis, statistical process control (SPC) and measurement system analysis. Charts and plots present results and have prognostic capabilities that allow necessary track possession times to be included in the timetable. 

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2017. p. 80
Series
Research report / Luleå University of Technology, ISSN 1402-1528
Keywords
Fault Diagnostics, Failure Prognostics, Measurement System Analysis, Statastical Analysis, Statistical Modelling, Time Series Analysis, Statistical Process Control (SPC), Railway Track, Sweden
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-64094 (URN)978-91-7583-937-0 (ISBN)978-91-7583-938-7 (ISBN)
Projects
Fortsättningsprojekt: Förbättrad tillståndsbedömning genom statistisk analys
Funder
Swedish Transport Administration
Available from: 2017-06-16 Created: 2017-06-16 Last updated: 2018-03-16Bibliographically approved
Capaci, F., Vanhatalo, E., Bergquist, B. & Kulahci, M. (2017). Managerial implications for improvingcontinuous production processes. In: : . Paper presented at 24th EurOMA Conference, Edinburgh, July 1-5, 2017.
Open this publication in new window or tab >>Managerial implications for improvingcontinuous production processes
2017 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Data analytics remains essential for process improvement and optimization. Statistical process control and design of experiments are among the most powerful process and product improvement methods available. However, continuous process environments challenge the application of these methods. In this article, we highlight SPC and DoE implementation challenges described in the literature for managers, researchers and practitioners interested in continuous production process improvement. The results may help managers support the implementation of these methods and make researchers and practitioners aware of methodological challenges in continuous process environments.

Keywords
Productivity, Statistical tools, Continuous processes
National Category
Engineering and Technology Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-65568 (URN)
Conference
24th EurOMA Conference, Edinburgh, July 1-5, 2017
Projects
Statistical Methods for Improving Continuous Production
Funder
Swedish Research Council, 4731241
Available from: 2017-09-11 Created: 2017-09-11 Last updated: 2019-06-18Bibliographically approved
Vanhatalo, E., Kulahci, M. & Bergquist, B. (2017). On the structure of dynamic principal component analysis used in statistical process monitoring. Chemometrics and Intelligent Laboratory Systems, 167, 1-11
Open this publication in new window or tab >>On the structure of dynamic principal component analysis used in statistical process monitoring
2017 (English)In: Chemometrics and Intelligent Laboratory Systems, ISSN 0169-7439, E-ISSN 1873-3239, Vol. 167, p. 1-11Article in journal (Refereed) Published
Abstract [en]

When principal component analysis (PCA) is used for statistical process monitoring it relies on the assumption that data are time independent. However, industrial data will often exhibit serial correlation. Dynamic PCA (DPCA) has been suggested as a remedy for high-dimensional and time-dependent data. In DPCA the input matrix is augmented by adding time-lagged values of the variables. In building a DPCA model the analyst needs to decide on (1) the number of lags to add, and (2) given a specific lag structure, how many principal components to retain. In this article we propose a new analyst driven method to determine the maximum number of lags in DPCA with a foundation in multivariate time series analysis. The method is based on the behavior of the eigenvalues of the lagged autocorrelation and partial autocorrelation matrices. Given a specific lag structure we also propose a method for determining the number of principal components to retain. The number of retained principal components is determined by visual inspection of the serial correlation in the squared prediction error statistic, Q (SPE), together with the cumulative explained variance of the model. The methods are illustrated using simulated vector autoregressive and moving average data, and tested on Tennessee Eastman process data.

Place, publisher, year, edition, pages
Elsevier, 2017
Keywords
Dynamic principal component analysis, Vector autoregressive process, Vector moving average process, Autocorrelation, Simulation, Tennessee Eastman process simulator
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-63377 (URN)10.1016/j.chemolab.2017.05.016 (DOI)000408790200001 ()2-s2.0-85019887093 (Scopus ID)
Funder
Swedish Research Council, 340-2013-5108
Note

Validerad;2017;Nivå 2;2017-06-02 (rokbeg)

Available from: 2017-05-16 Created: 2017-05-16 Last updated: 2018-07-10Bibliographically approved
Bergquist, B. & Collosimo, B. M. (2017). The ENBIS‐16 quality and reliability engineering international special issue. Quality and Reliability Engineering International, 33(6), 1167-1168
Open this publication in new window or tab >>The ENBIS‐16 quality and reliability engineering international special issue
2017 (English)In: Quality and Reliability Engineering International, ISSN 0748-8017, E-ISSN 1099-1638, Vol. 33, no 6, p. 1167-1168Article in journal, Editorial material (Refereed) Published
Place, publisher, year, edition, pages
John Wiley & Sons, 2017
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-64907 (URN)10.1002/qre.2200 (DOI)000410974500001 ()2-s2.0-85026535999 (Scopus ID)
Available from: 2017-07-25 Created: 2017-07-25 Last updated: 2018-07-10Bibliographically approved
Capaci, F., Kulahci, M., Vanhatalo, E. & Bergquist, B. (2016). A two-step procedure for fault detection in the Tennessee Eastman Process simulator (ed.). Paper presented at Annual Conference of the European Network for Business and Industrial Statistics : 11/09/2016 - 15/09/2016. Paper presented at Annual Conference of the European Network for Business and Industrial Statistics : 11/09/2016 - 15/09/2016.
Open this publication in new window or tab >>A two-step procedure for fault detection in the Tennessee Eastman Process simulator
2016 (English)Conference paper, Oral presentation only (Refereed)
Abstract [en]

High-technological and complex production processes and high availability and sample frequencies of data in large scale industrial processes need the concurrent development of appropriate statistical control tools and monitoring techniques. Therefore, multivariate control charts based on latent variables are essential tools to detect and isolate process faults.Several Statistical Process Control (SPC) charts have been developed for multivariate and megavariate data, such as the Hotelling T2, MCUSUM and MEWMA control charts as well as charts based on principal component analysis (PCA) and dynamic PCA (DPCA). The ability of SPC procedures based on PCA (Kourti, MacGregor 1995) or DPCA (Ku et al. 1995) to detect and isolate process disturbances for a large number of highly correlated (and time-dependent in the case of DPCA) variables has been demonstrated in the literature. However, we argue that the fault isolation capability and the fault detection rate for processes can be improved further for processes operating under feedback control loops (in closed loop).The purpose of this presentation is to illustrate a two-step method where [1] the variables are pre-classified prior to the analysis and [2] the monitoring scheme based on latent variables is implemented. Step 1 involves a structured qualitative classification of the variables to guide the choice of which variables to monitor in Step 2. We argue that the proposed method will be useful for many practitioners of SPC based on latent variables techniques in processes operating in closed loop. It will allow clearer fault isolation and detection and an easier implementation of corrective actions. A case study based on the data available from the Tennessee Eastman Process simulator under feedback control loops (Matlab) will be presented. The results from the proposed method are compared with currently available methods through simulations in R statistics software.

National Category
Reliability and Maintenance
Research subject
Quality Technology and Management; Intelligent industrial processes (AERI); Effective innovation and organisation (AERI); Enabling ICT (AERI)
Identifiers
urn:nbn:se:ltu:diva-37881 (URN)c0cb4fc8-2b6b-4c2b-9ce1-c879f319d949 (Local ID)c0cb4fc8-2b6b-4c2b-9ce1-c879f319d949 (Archive number)c0cb4fc8-2b6b-4c2b-9ce1-c879f319d949 (OAI)
Conference
Annual Conference of the European Network for Business and Industrial Statistics : 11/09/2016 - 15/09/2016
Projects
Statistiska metoder för förbättring av kontinuerliga tillverkningsprocesser
Note
Godkänd; 2016; 20160701 (bjarne)Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2018-03-26Bibliographically approved
Eriksson, H., Gremyr, I., Bergquist, B., Garvare, R., Fundin, A., Wiklund, H., . . . Sörqvist, L. (2016). Exploring Quality Challenges and the Validity of Excellence Models (ed.). International Journal of Operations & Production Management, 36(10), 1201-1221
Open this publication in new window or tab >>Exploring Quality Challenges and the Validity of Excellence Models
Show others...
2016 (English)In: International Journal of Operations & Production Management, ISSN 0144-3577, E-ISSN 1758-6593, Vol. 36, no 10, p. 1201-1221Article in journal (Refereed) Published
Abstract [en]

Purpose: The purpose is to identify and explore important quality-related challenges facing organizations, and how current excellence models incorporate these challenges.Methodology: The article is based on a Delphi study in Swedish organizations, 49 challenges were generated and ranked according to importance. The top 10 ranked challenges were compared to the principles of four excellence models.Findings: The excellence models seem to still be relevant since their content matches many of the challenges identified. The MBNQA and the SIQ models were found to have the most comprehensive coverage, while the ISO model had limited coverage. Research Limitations/Implications: Three areas for further research were identified: 1) how QM can evolve in different contexts with varying needs in terms of adaptive and explorative capabilities, 2) the interfaces of QM and sustainability, and ways to understand how customers and stakeholders can be active contributors to improvements and 3) the roles of the owners and board of directors in QM, and how to organize and distribute responsibilities of the QM work.Practical and Social Implications: Three important challenges could be addressed in upcoming revisions of excellence models: 1) making QM a strategic issue for company owners; 2) involving customers in the improvement activities; and 3) developing processes that are robust, while still easily adaptable.Originality/Value: The Delphi study has identified upcoming challenges in the QM area based on input from 188 quality professionals.

Keywords
Business / Economics - Business studies, Ekonomi - Företagsekonomi
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management; Effective innovation and organisation (AERI)
Identifiers
urn:nbn:se:ltu:diva-5988 (URN)10.1108/IJOPM-12-2014-0610 (DOI)000387084100005 ()2-s2.0-84989227524 (Scopus ID)42fcbc13-6e86-4078-bc5a-80a39821b32a (Local ID)42fcbc13-6e86-4078-bc5a-80a39821b32a (Archive number)42fcbc13-6e86-4078-bc5a-80a39821b32a (OAI)
Note

Validerad; 2016; Nivå 2; 2016-10-05 (andbra)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-3911-8009

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