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Publications (10 of 68) Show all publications
Lindström, J., Viklund, P., Fredrik, T., Berndt, H. & Jonny, E. (2019). Oh, no – not another policy! Oh, yes - an OT-policy!. In: Peter Butala, Edvard Govekar, Rok Vrabič (Ed.), Procedia CIRP, vol 81: . Paper presented at 52nd CIRP Conference on Manufacturing Systems (CMS), Ljubljana, Slovenia, June 12-14, 2019 (pp. 582-587). Elsevier, 81
Open this publication in new window or tab >>Oh, no – not another policy! Oh, yes - an OT-policy!
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2019 (English)In: Procedia CIRP, vol 81 / [ed] Peter Butala, Edvard Govekar, Rok Vrabič, Elsevier, 2019, Vol. 81, p. 582-587Conference paper, Published paper (Refereed)
Abstract [en]

The paper addresses the need for a policy document in organizations concerned with Operational Technologies (OT) within their production and operational environments, and secondly how such an OT policy was developed and crafted by a Swedish municipality and its water production and wastewater management department. The first initial design criteria was to clearly distinguish the IT environment from the OT environment and the second design criteria was to achieve an improved, affordable and maintainable cybersecurity level for the OT environment. The results of the paper are an initial OT policy and an action plan for the necessary technical and organizational change in the OT environment.

Place, publisher, year, edition, pages
Elsevier, 2019
Series
Procedia CIRP, ISSN 2212-8271 ; 81
Keywords
cybersecurity, Operational Technology (OT), OT policy, production systems
National Category
Engineering and Technology Information Systems, Social aspects
Research subject
Information systems
Identifiers
urn:nbn:se:ltu:diva-75113 (URN)10.1016/j.procir.2019.03.159 (DOI)
Conference
52nd CIRP Conference on Manufacturing Systems (CMS), Ljubljana, Slovenia, June 12-14, 2019
Available from: 2019-06-28 Created: 2019-06-28 Last updated: 2019-07-08Bibliographically approved
Lindström, J., Lejon, E., Kyösti, P., Mecella, M., Heutelbeck, D., Hemmje, M., . . . Gunnarsson, B. (2019). Towards intelligent and sustainable production systems with a zero-defect manufacturing approach in an Industry4.0 context. In: Edited by Peter Butala, Edvard Govekar, Rok Vrabič (Ed.), Procedia CIRP, vol 81: . Paper presented at 52nd CIRP Conference on Manufacturing Systems (CMS), Ljubljana, Slovenia, June 12-14, 2019 (pp. 880-885). Elsevier, 81
Open this publication in new window or tab >>Towards intelligent and sustainable production systems with a zero-defect manufacturing approach in an Industry4.0 context
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2019 (English)In: Procedia CIRP, vol 81 / [ed] Edited by Peter Butala, Edvard Govekar, Rok Vrabič, Elsevier, 2019, Vol. 81, p. 880-885Conference paper, Published paper (Refereed)
Abstract [en]

The paper addresses intelligent and sustainable production achieved through combination and integration of online predictive maintenance, monitoring of process parameters and continuous quality control of both input materials and output from the process. This enables production systems, within both manufacturing and process industries, to move towards zero-defect manufacturing. Such a zero-defect manufacturing approach allows for earlier identification of problems or issues, which will or already negatively affect the output. The paper outlines the first part of the second cycle of an action research effort at Gestamp HardTech AB in Sweden, whose objective is to keep its position as a world-leading provider of press-hardened vehicle parts. In order to fully implement the zero-defect manufacturing approach, 4-6 action research cycles are expected to be needed in order to iteratively refine the approach. During the first cycle, various methods and solutions for some of the individual issues/problems have been conceptualized, realized and initially tested. The selected design criteria for the action research efforts were: simplicity, low cost, robustness, high-quality output and future-proofing. The result from the research in the second cycle so far is an action plan for the technical change and a set of challenges/problems which need additional investigation.

Place, publisher, year, edition, pages
Elsevier, 2019
Series
Procedia CIRP, vol 81, ISSN 2212-8271
Keywords
continuous quality controlI, Industry4.0, intelligent, online predictive maintenance, production, sustainable, zero-defect manufacturing
National Category
Engineering and Technology Information Systems, Social aspects Control Engineering Applied Mechanics
Research subject
Information systems; Experimental Mechanics; Control Engineering
Identifiers
urn:nbn:se:ltu:diva-75114 (URN)10.1016/j.procir.2019.03.218 (DOI)
Conference
52nd CIRP Conference on Manufacturing Systems (CMS), Ljubljana, Slovenia, June 12-14, 2019
Available from: 2019-06-28 Created: 2019-06-28 Last updated: 2019-07-08Bibliographically approved
Källström, E., Lindström, J., Håkansson, L., Karlberg, M. & Lin, J. (2019). Vibration-based Condition Monitoring of Heavy Duty Machine Driveline Parts: Torque Converter, Gearbox, Axles and Bearings. International Journal of Prognostics and Health Management, 10, Article ID 014.
Open this publication in new window or tab >>Vibration-based Condition Monitoring of Heavy Duty Machine Driveline Parts: Torque Converter, Gearbox, Axles and Bearings
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2019 (English)In: International Journal of Prognostics and Health Management, ISSN 2153-2648, E-ISSN 2153-2648, Vol. 10, article id 014Article in journal (Refereed) Published
Abstract [en]

As more features are added to the heavy duty construction equipment, its complexity increases and early fault detection of certain components becomes more challenging due to too many fault codes generated when a failure occurs. Hence, the need to complement the present onboard diagnostic methods with more sophisticated diagnostic methods for adequate condition monitoring of the heavy duty construction equipment in order to improve uptime. Major components of the driveline (such as the gearbox, torque converter, bearings and axles) are such components. Failure of these major components of the driveline may results in the machine standing still until a repair is scheduled. In this paper, vibration based condition monitoring methods are presented with the purpose to provide a diagnostic framework possible to implement onboard for monitoring of critical driveline parts in order to reduce service cost and improve uptime. For the development of this diagnostic framework, sensor data from the gearbox, torque converter, bearings and axles are considered. Further, the feature extraction of the data collected has been carried out using adequate signal processing methods, which includes, Adaptive Line Enhancer, Order Power Spectrum respectively. In addition, Bayesian learning was utilized for adaptively learning of the extracted features for deviation detection. Bayesian learning is a powerful prediction method as it combines the prior information with knowlegde measured to make update. The results indicate that the vibration properties of the gearbox, torque converter, bearings and axle are relevant for early fault detection of the driveline. Furthermore, vibration provide information about the internal features of these components for detecting deviations from normal behavior.

In this way, the developed methods may be implemented onboard for the continuous monitoring of these critical driveline parts of the heavy duty construction equipment so that if their health starts to degrade a service and/or repair may be scheduled well in advance of a potential failure and in that way the downtime of a machine may be reduced and costly replacements and repairs avoided.

Place, publisher, year, edition, pages
PHM Society, 2019
Keywords
Automatic Transmission, Adaptive Filtering, Adaptive Line Enhancer, Axle, Bearings, Bayesian Learning, Gearbox, Order Analysis, Order Power Spectrum, Torque Converter and Vibration
National Category
Other Mechanical Engineering Other Civil Engineering Information Systems, Social aspects
Research subject
Computer Aided Design; Operation and Maintenance; Information systems
Identifiers
urn:nbn:se:ltu:diva-68353 (URN)
Note

Validerad;2019;Nivå 1;2019-08-15 (johcin)

Available from: 2018-04-15 Created: 2018-04-15 Last updated: 2019-08-15Bibliographically approved
Lindström, J., Eliasson, J., Hermansson, A., Blomstedt, F. & Kyösti, P. (2018). Cybersecurity level in IPS2: A case study of two industrial internet-based SME offerings. Paper presented at 10th CIRP Conference on Industrial Product-Service Systems, IPS2 2018, Linköping, Sweden, 29-31 May 2018. Procedia CIRP, 73, 222-227
Open this publication in new window or tab >>Cybersecurity level in IPS2: A case study of two industrial internet-based SME offerings
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2018 (English)In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 73, p. 222-227Article in journal (Refereed) Published
Abstract [en]

n a case study comprising two SMEs offering Industrial Product-Service Systems (IPS2) based on the industrial internet the paper addresses the current cybersecurity level of the two SMEs and the perceived need for added cybersecurity features. Cybersecurity is of crucial importance for most IPS2-offerings if they involve data communications, data collection and storage, and are also part of the customers’ critical processes (i.e., the core processes that always need to work with a high level of availability). The case study reveals that both IPS2-offerings have a basic level of core security spanning IoT-devices, IoT-networks, cloud services and users as well as administrators. Further, of interest is that the SMEs would like to add security cloud services with advanced security functionality in order to achieve scalability and efficiency regarding security- and general management as well as lifecycle management functionality. However, most of the security cloud services are mainly aimed at larger companies and not adapted for SMEs in terms of required knowledge, time and effort required to keep the security configurations up-to-date.

Place, publisher, year, edition, pages
Elsevier, 2018
National Category
Control Engineering
Research subject
Control Engineering; Control Engineering
Identifiers
urn:nbn:se:ltu:diva-70221 (URN)10.1016/j.procir.2018.03.302 (DOI)2-s2.0-85054495739 (Scopus ID)
Conference
10th CIRP Conference on Industrial Product-Service Systems, IPS2 2018, Linköping, Sweden, 29-31 May 2018
Note

Konferensartikel i tidskrift;2018-08-06 (andbra)

Available from: 2018-08-06 Created: 2018-08-06 Last updated: 2018-11-21Bibliographically approved
Lejon, E., Kyösti, P. & Lindström, J. (2018). Machine learning for detection of anomalies in press-hardening: Selection of efficient methods. Paper presented at 51st CIRP Conference on Manufacturing Systems, Stockholm, 16-18 May 2018. Procedia CIRP, 72, 1079-1083
Open this publication in new window or tab >>Machine learning for detection of anomalies in press-hardening: Selection of efficient methods
2018 (English)In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 1079-1083Article in journal (Refereed) Published
Abstract [en]

The paper addresses machine learning methods, utilizing data from industrial control systems, that are suitable for detecting anomalies in the press-hardening process of automotive components. The paper is based on a survey of methods for anomaly detection in various applications. Suitable methods for the press-hardening process are implemented and evaluated. The result shows that it is possible to implement machine learning for anomaly detection by non-machine learning experts utilizing readily available programming libraries/APIs. The three evaluated methods for anomaly detection in the press-hardening process all perform well, with the autoencoder neural network scoring highest in the evaluation.

Place, publisher, year, edition, pages
Elsevier, 2018
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-69984 (URN)10.1016/j.procir.2018.03.221 (DOI)2-s2.0-85049586782 (Scopus ID)
Conference
51st CIRP Conference on Manufacturing Systems, Stockholm, 16-18 May 2018
Note

Konferensartikel i tidskrift;2018-06-29 (andbra)

Available from: 2018-06-29 Created: 2018-06-29 Last updated: 2018-08-10Bibliographically approved
Källström, E., Olsson, T., Lindström, J., Håkansson, L. & Larsson, J. (2018). On-board Clutch Slippage Detection and Diagnosis in Heavy Duty Machine. International Journal of Prognostics and Health Management, 9(1), Article ID 007.
Open this publication in new window or tab >>On-board Clutch Slippage Detection and Diagnosis in Heavy Duty Machine
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2018 (English)In: International Journal of Prognostics and Health Management, ISSN 2153-2648, E-ISSN 2153-2648, Vol. 9, no 1, article id 007Article in journal (Refereed) Published
Abstract [en]

In order to reduce unnecessary stops and expensive downtime originating from clutch failure of construction equipment machines; adequate real time sensor data measured on the machinein combination with feature extraction and classification methods may be utilized.

This paper, based on a study at Volvo Construction Equipment,presents a framework with feature extraction methods and an anomaly detection module combined with Case-Based Reasoning (CBR) for on-board clutch slippage detection and diagnosis in a heavy duty equipment. The feature extraction methods used are Moving Average Square Value Filtering (MASVF) and a measure of the fourth order statistical properties of the signals implemented as continuous queries over data streams. The anomaly detection module has two components,the Gaussian Mixture Model (GMM) and the Logistics Regression classifier. CBR is a learning approach that classifies faults by creating a new solution for a new fault case from the solution of the previous fault cases. Through use of a data stream management system and continuous queries (CQs), the anomaly detection module continuously waits for a clutch slippage event detected by the feature extraction methods, the query returns a set of features which activates the anomaly detection module. The first component of the anomaly detection module trains a GMM to extracted features while the second component uses a Logistic Regression classifier for classifying normal and anomalous data. When an anomalyis detected, the Case-Based diagnosis module is activated for fault severity estimation.

Place, publisher, year, edition, pages
PHM Society, 2018
National Category
Engineering and Technology Control Engineering Other Mechanical Engineering
Research subject
Computer Aided Design; Control Engineering
Identifiers
urn:nbn:se:ltu:diva-67976 (URN)2-s2.0-85044281699 (Scopus ID)
Note

Validerad;2018;Nivå 1;2018-03-19 (rokbeg)

Available from: 2018-03-17 Created: 2018-03-17 Last updated: 2018-05-16Bibliographically approved
Lindström, J. & Hanken, C. (2018). Wearable Computing: Security Challenges, BYOD, Privacy and Legal Aspects. In: Hamid R. Nemati (Ed.), Wearable technologies: concepts, methodologies, tools, and applications (pp. 1043-1067). Paper presented at . Hershey, PA: IGI Global
Open this publication in new window or tab >>Wearable Computing: Security Challenges, BYOD, Privacy and Legal Aspects
2018 (English)In: Wearable technologies: concepts, methodologies, tools, and applications, Hershey, PA: IGI Global, 2018, p. 1043-1067Chapter in book (Refereed)
Abstract [en]

Wearable computing is gaining more and more interest as new "wearables," intended for both work and leisure, are introduced. This trend brings benefits and challenges; for instance, the potential to improve work processes and issues related to IT management and privacy. The introduction and use of wearable computing provides opportunities to improve and reengineer work processes in organizations but can at the same time introduce alignment problems, as users in organizations may adopt the new technology before organizations are prepared. Further, alignment problems posed by the emerging trend, "Bring Your Own Device" (BYOD), are discussed. In addition, as in the cloud computing area, needed and necessary supportive legal frameworks have not yet fully addressed the new wearable computing technology. In the light of recent developments regarding global intelligence gathering, security and privacy concerns must be given careful consideration. Different alignment concepts for managing security challenges and legal aspects related to wearable computing, such as cultivation, care, hospitality, and care with hospitality, are discussed in the chapter. © 2018 by IGI Global. All rights reserved.

Place, publisher, year, edition, pages
Hershey, PA: IGI Global, 2018
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-68806 (URN)10.4018/978-1-5225-5484-4.ch047 (DOI)2-s2.0-85046584280 (Scopus ID)9781522554844 (ISBN)9781522554851 (ISBN)
Available from: 2018-05-21 Created: 2018-05-21 Last updated: 2018-05-21Bibliographically approved
Rönnberg Sjödin, D., Parida, V. & Lindström, J. (2017). Barriers and conditions of open operation: a customer perspective on value co-creation for integrated product-service solutions. International Journal of Technology Marketing, 12(1), 90-111
Open this publication in new window or tab >>Barriers and conditions of open operation: a customer perspective on value co-creation for integrated product-service solutions
2017 (English)In: International Journal of Technology Marketing, ISSN 1741-878X, E-ISSN 1741-8798, Vol. 12, no 1, p. 90-111Article in journal (Refereed) Published
Abstract [en]

Enabling value co-creation between provider and customer is a key requirement for successful adoption of integrated product-service offerings in a capital good industrial setting. However, little is known about the barriers and conditions explaining customers willingness to open up their internal processes for value co-creation with providers. Based on a multiple exploratory case studies with four customers and four providers within the manufacturing and process industries, this study identifies three barriers to open operation (operational cultural resistance, loss of operational know-how and risk of operational conflict) which may restrict the potential for increased value co-creation and must be managed to support the adoption of integrated solutions. In addition, we identify two key conditions related to the criticality of the operational process and the state of operational competences as strong influences for which form of open operation engagement would be favoured by customer. The study holds both theoretical and practical implications.

Place, publisher, year, edition, pages
InderScience Publishers, 2017
National Category
Other Engineering and Technologies not elsewhere specified
Research subject
Entrepreneurship and Innovation; Control Engineering
Identifiers
urn:nbn:se:ltu:diva-59885 (URN)10.1504/IJTMKT.2017.10002376 (DOI)2-s2.0-85033216602 (Scopus ID)
Note

Validerad; 2017; Nivå 1; 2017-02-28 (rokbeg)

Available from: 2016-10-24 Created: 2016-10-24 Last updated: 2018-11-20Bibliographically approved
Lindström, J., Källström, E. & Kyösti, P. (2017). Development and Operation of Functional Products: Improving knowledge on availability through use of monitoring and service related data. In: Redding, Louis, Roy, Rajkumar, Shaw, Andy (Ed.), (Ed.), Through-life Engineering Services: (pp. 113-132). Paper presented at . Springer International Publishing
Open this publication in new window or tab >>Development and Operation of Functional Products: Improving knowledge on availability through use of monitoring and service related data
2017 (English)In: Through-life Engineering Services / [ed] Redding, Louis, Roy, Rajkumar, Shaw, Andy, Springer International Publishing , 2017, p. 113-132Chapter in book (Refereed)
Abstract [en]

The book chapter addresses which measures five manufacturing companies have taken, or plan to take, regarding use of data originating from monitoring, service, support, maintenance, repairs as well as other sources, in order to improve the knowledge on availability in the context of providing Functional Products. Commonly, the objective of Functional Products is to provide a function to customers with a specified level of availability (or improvement of productivity or efficiency). The results indicate that systematic planning and collection of relevant data, which is either pre-processed on-board (i.e., locally) or sent as is to central or cloud-based storage and processing, in combination with additional necessary data from other sources, is crucial to build knowledge in order to uphold and improve the level of availability agreed upon with customers. As the use of software in Functional Products increases, the knowledge on availability related to software must be augmented—which can be a challenge for many companies whose operations have been rooted in hardware. Further, the results reveal that getting high-quality input is key in order to use the collected data for analytics and to find root causes. The latter may change how the current value-chain operates and secures the quality of necessary data when providing functions to customers if partners are involved in the provider consortium.

Place, publisher, year, edition, pages
Springer International Publishing, 2017
Series
Decisions Engineering, ISSN 1619-5736 ; 1
National Category
Control Engineering Other Mechanical Engineering
Research subject
Computer Aided Design; Control Engineering; Centre - The Faste Laboratory
Identifiers
urn:nbn:se:ltu:diva-20676 (URN)10.1007/978-3-319-49938-3 (DOI)705becc4-95dc-4035-b761-2cefb8de2157 (Local ID)9783319499376 (ISBN)9783319499376 (ISBN)705becc4-95dc-4035-b761-2cefb8de2157 (Archive number)705becc4-95dc-4035-b761-2cefb8de2157 (OAI)
Projects
Fastelaboratoriet - VINNEXC
Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2019-03-29Bibliographically approved
Källström, E., Lindström, J., Håkansson, L., Karlberg, M. & Öberg, O. (2017). Identification of Vibration Properties of Wheel Loader Driveline Parts as a Base for Adequate Condition Monitoring: Bearings. In: Gibbs B. (Ed.), : . Paper presented at 24th International Congress on Sound and Vibration, London, 23-24 July, 2017. International Institute of Acoustics and Vibration
Open this publication in new window or tab >>Identification of Vibration Properties of Wheel Loader Driveline Parts as a Base for Adequate Condition Monitoring: Bearings
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2017 (English)In: / [ed] Gibbs B., International Institute of Acoustics and Vibration , 2017Conference paper, Published paper (Refereed)
Abstract [en]

In order to reduce costly downtime, adequate condition monitoring of the automatic transmission components in heavy duty construction equipment is necessary. The transmission in such equipment enables to change the gear ratio automatically. Further, the bearings in an automatic transmission provide low friction support to its rotating parts and act as an interface separating stationary from rotating components. Wear or other bearing faults may lead to an increase in energy consumption as well as failure of other related components in the automatic transmission, and thus costly downtime. In this study, different sensor data (particularly vibration) was collected on the automatic transmission during controlled test cycles in an automatic transmission test rig to enable adequate condition monitoring.

An analysis of the measured vibration data was carried out using signal processing methods. The results indicate that predictive maintenance information related to the automatic transmission bearings may be extracted from vibrations measured on an automatic transmission. This information may be used for early fault detection, thus improving uptime and availability of heavy duty construction equipment.

Place, publisher, year, edition, pages
International Institute of Acoustics and Vibration, 2017
Keywords
Automatic Transmission, Adaptive Line Enhancer (ALE), Bearings, Order Power Spectrum, Order Modulation Spectrum, Recursive Least Squares (RLS), and Vibration.
National Category
Engineering and Technology Signal Processing Other Mechanical Engineering
Research subject
Signal Processing; Computer Aided Design
Identifiers
urn:nbn:se:ltu:diva-63304 (URN)2-s2.0-85029451185 (Scopus ID)
Conference
24th International Congress on Sound and Vibration, London, 23-24 July, 2017
Available from: 2017-05-10 Created: 2017-05-10 Last updated: 2018-05-16Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2356-7830

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