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Marti Bigorra, A., Isaksson, O. & Karlberg, M. (2019). Aspect-based Kano categorization. International Journal of Information Management, 46, 163-172
Open this publication in new window or tab >>Aspect-based Kano categorization
2019 (English)In: International Journal of Information Management, ISSN 0268-4012, E-ISSN 1873-4707, Vol. 46, p. 163-172Article in journal (Refereed) Published
Abstract [en]

Customers commonly share opinions and experiences about products via the internet by means of social media and networking sites. The generated textual data is often analysed by means of Sentiment Analysis (SA) as means to assess customer opinions on product features more efficiently than through surveys. To enable a more objective product target setting, the impact of product feature performance changes on customer satisfaction is essential. Kano et al. (1984) presented a survey-based model to classify product features based on their impact on customer satisfaction to aid designers in their product target setting. Approaches extending the Kano model rely on customer surveys as input data. In addition, existing studies classifying extracted product features from textual data (e.g. product reviews) rarely provide a clear separation in terms of Kano categories. Thus, the impact of identified product features on customer satisfaction remains unknown to product designers. This paper presents a methodology for autonomously classifying extracted aspects from textual data into Kano categories. For verification purposes, two examples using coffee machine and smartphone user reviews are presented. Results indicate that the proposed methodology efficiently provides product designers with insightful customer information through the proposed aspect categorization.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Aspect, Categorization, Kano, Sentiment Analysis (SA), Target setting
National Category
Other Mechanical Engineering
Research subject
Computer Aided Design
Identifiers
urn:nbn:se:ltu:diva-71652 (URN)10.1016/j.ijinfomgt.2018.11.004 (DOI)000461899300013 ()2-s2.0-85058698469 (Scopus ID)
Note

Validerad;2019;Nivå 2;2019-01-07 (svasva)

Available from: 2018-11-28 Created: 2018-11-28 Last updated: 2019-04-05Bibliographically 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
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
Zhang, Y., Andrews, J., Reed, S. & Karlberg, M. (2017). Maintenance Processes Modelling and Optimisation. Paper presented at 9th International Conference on Modelling in Industrial Maintenance and Reliability (MIMAR), London, UK, 12–14 July, 2016. Reliability Engineering & System Safety, 168, 150-160
Open this publication in new window or tab >>Maintenance Processes Modelling and Optimisation
2017 (English)In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 168, p. 150-160Article in journal (Refereed) Published
Abstract [en]

A Maintenance Procedure is conducted in order to prevent the failure of a system or to restore the functionality of a failed system. Such a procedure consists of a series of tasks, each of which has a distribution of times to complete and a probability of being performed incorrectly. The inclusion of tests can be used to identify any maintenance errors which have occurred. When an error is identified it can be addressed through a corresponding correction sequence which will have associated costs and add to the maintenance process completion time. A modified FMEA approach has been used to identify the possible tests. By incorporating any selection of tests into the maintenance process it can then analysed using a discrete-event simulation to predict the expected completion time distribution. The choice of tests to perform and when to do them is then made to successfully complete the maintenance objective in the shortest possible time using a genetic algorithm. The methodology is demonstrated by applying it to the repair process for a car braking system. The developed method is suitable for application in abroad range of industries.

Place, publisher, year, edition, pages
Elsevier, 2017
National Category
Other Mechanical Engineering
Research subject
Computer Aided Design
Identifiers
urn:nbn:se:ltu:diva-62209 (URN)10.1016/j.ress.2017.02.011 (DOI)000413878100016 ()2-s2.0-85014076702 (Scopus ID)
Conference
9th International Conference on Modelling in Industrial Maintenance and Reliability (MIMAR), London, UK, 12–14 July, 2016
Note

Konferensartikel i tidskrift

Available from: 2017-02-28 Created: 2017-02-28 Last updated: 2018-04-20Bibliographically approved
Lindström, J. & Karlberg, M. (2017). Outlining an overall Functional Product lifecycle: combining and coordinating its economic and technical perspectives (ed.). CIRP - Journal of Manufacturing Science and Technology, 17, 1-9
Open this publication in new window or tab >>Outlining an overall Functional Product lifecycle: combining and coordinating its economic and technical perspectives
2017 (English)In: CIRP - Journal of Manufacturing Science and Technology, ISSN 1755-5817, E-ISSN 1878-0016, Vol. 17, p. 1-9Article in journal (Refereed) Published
Abstract [en]

Currently, industry is showing increasing interest in performance-based business models. Functional Products is one such business model, where the provider offers a function to customers at an agreed-upon level of availability, productivity or efficiency, etc. A Functional Product comprises the following four main constituents: hardware, software, service support system and management of operation, which together deliver value to customers on a long-term basis. This paper, based on empirical data, provides an outline and starts the verification of a proposed overall Functional Product lifecycle combining and coordinating its economic- and technical perspectives. The perspectives are combined and the key aspects of the necessary coordination between and within the perspectives, i.e., sustainable win-win situations and coordination of sub-lifecycles for the economic perspective, and the need for coordination between the Functional Products’ technical perspective's four sub-lifecycles (hardware, software, service-support system and management of operation), are elaborated and discussed. Further, addition of new functionality, contract management, and long-term management of operation are discussed in the light of managing fleets/individual customers, assets and availability. The proposed overall Functional Product lifecycle is further analyzed from a number of views and aspects.

Place, publisher, year, edition, pages
Elsevier, 2017
National Category
Control Engineering Other Mechanical Engineering
Research subject
Control Engineering; Computer Aided Design
Identifiers
urn:nbn:se:ltu:diva-10186 (URN)10.1016/j.cirpj.2016.08.005 (DOI)000401724400001 ()2-s2.0-84995521178 (Scopus ID)8f23d7ad-6e6a-4790-a0d0-9d2483f7bc47 (Local ID)8f23d7ad-6e6a-4790-a0d0-9d2483f7bc47 (Archive number)8f23d7ad-6e6a-4790-a0d0-9d2483f7bc47 (OAI)
Projects
Fastelaboratoriet - VINNEXC
Note

Validerad;2017;Nivå 2;2017-06-01 (rokbeg)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2019-08-16Bibliographically approved
Sas, D., Kyösti, P., Karlberg, M. & Reed, S. (2017). Toward an improved strategy for Functional Product development by predicting environmental and economic sustainability. Paper presented at 5th International Conference on Through-life Engineering Services (TESConf 2016), Cranfield University, 1-2 November 2016. Procedia CIRP, 59, 208-213
Open this publication in new window or tab >>Toward an improved strategy for Functional Product development by predicting environmental and economic sustainability
2017 (English)In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 59, p. 208-213Article in journal (Refereed) Published
Abstract [en]

Functional Product (FP) has emerged as a business concept aimed at offering a function or performance, mainly in business-to- business applications, on an agreed upon level of availability and cost as well as at providing incitements towards a sustainable growth. Today the literature expanded into various specific approaches and IT solutions measuring sustainability. However, the literature lacks such approaches within the FP context. This explorative paper proposes on a conceptual level a strategy to predict a sustainability impact of an FP in terms of environmental and economic sustainability and optimize the FP configuration. This strategy is based on scenario modelling and simulation -driven approach. The practical significance of the proposed strategy lies in its implication to avoid costly “trial and error” method performed in the real world and to enable the development of more sustainable products. Through the proposed strategy, it is foreseen that sustainability impact can be quantified and minimised during the FP system development.

Place, publisher, year, edition, pages
Elsevier, 2017
Keywords
Functional Product, sustainability, assessment process, simualtions, optimzation
National Category
Other Mechanical Engineering Control Engineering Signal Processing
Research subject
Computer Aided Design; Signal Processing; Control Engineering
Identifiers
urn:nbn:se:ltu:diva-60299 (URN)10.1016/j.procir.2016.09.002 (DOI)000398834200036 ()2-s2.0-85017470539 (Scopus ID)
Conference
5th International Conference on Through-life Engineering Services (TESConf 2016), Cranfield University, 1-2 November 2016
Projects
Faste Laboratory
Funder
VINNOVA
Note

2017-03-02 (andbra);Konferensartikel i tidskrift

Available from: 2016-11-11 Created: 2016-11-11 Last updated: 2019-03-18Bibliographically approved
Källström, E., Lindström, J., Håkansson, L., Karlberg, M., Renderstedt, R. & Larsson, J. (2016). Identification of Vibration Properties of Heavy Duty Machine Driveline Parts as a Base for Adequate Condition Monitoring: Axle (ed.). In: (Ed.), Vogiatzis, K; Kouroussis, G; Crocker, M; Pawelczyk, M (Ed.), ICSV 2016 - 23rd International Congress on Sound and Vibration: From Ancient to Modern Acoustics. Paper presented at International Congress on Sound & Vibration : 10/07/2016 - 14/07/2016.
Open this publication in new window or tab >>Identification of Vibration Properties of Heavy Duty Machine Driveline Parts as a Base for Adequate Condition Monitoring: Axle
Show others...
2016 (English)In: ICSV 2016 - 23rd International Congress on Sound and Vibration: From Ancient to Modern Acoustics / [ed] Vogiatzis, K; Kouroussis, G; Crocker, M; Pawelczyk, M, 2016Conference paper, Published paper (Refereed)
Abstract [en]

With increasing complexities in the heavy duty construction equipment, early fault detection of certain components in the machine becomes more and more challenging due to too many fault code generated when a failure occurs. The axle is one of such component. The axle transfers driving torque from the transmission to the wheels and axle failure may result in costly downtime of construction equipment. To reduce service cost and to improve uptime, adequate condition monitoring based on sensor data from the axle is considered. Vibration is measured on the axle. Analysis of the data has been carried out using adequate signal processing methods. The results indicate that the vibration properties of the axle are relevant for early fault detection of the axle. In this way; the health of the axle may be continuously monitored on-board using the vibration information and if the axle health starts to degrade a service and/or repair may be scheduled well in advance of a potential axle failure and in that way the downtime of a machine may be reduced.

Series
Proceedings of the International Congress on Sound and Vibration, ISSN 2329-3675
Keywords
Order Power Spectrum, Order Modulation Spectrum, Product Development, Information technology - Signal processing, Informationsteknik - Signalbehandling
National Category
Other Mechanical Engineering
Research subject
Computer Aided Design
Identifiers
urn:nbn:se:ltu:diva-27469 (URN)000388480402101 ()2-s2.0-84987920136 (Scopus ID)0ef78cf3-88bb-4c49-ae23-ca4971f5e423 (Local ID)9789609922623 (ISBN)0ef78cf3-88bb-4c49-ae23-ca4971f5e423 (Archive number)0ef78cf3-88bb-4c49-ae23-ca4971f5e423 (OAI)
Conference
International Congress on Sound & Vibration : 10/07/2016 - 14/07/2016
Projects
Fastelaboratoriet - VINNEXC
Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-05-16Bibliographically approved
Källström, E., Lindström, J., Håkansson, L., Karlberg, M., Öberg, O., Renderstedt, R. & Larsson, J. (2016). Identification of Vibration Properties of Heavy Duty Machine Driveline Parts as a Base for Adequate Condition Monitoring: Torque Converter (ed.). In: (Ed.), Vogiatzis, K; Kouroussis, G; Crocker, M; Pawelczyk, M (Ed.), ICSV 2016 - 23rd International Congress on Sound and Vibration: From Ancient to Modern Acoustics. Paper presented at International Congress on Sound & Vibration : 10/07/2016 - 14/07/2016.
Open this publication in new window or tab >>Identification of Vibration Properties of Heavy Duty Machine Driveline Parts as a Base for Adequate Condition Monitoring: Torque Converter
Show others...
2016 (English)In: ICSV 2016 - 23rd International Congress on Sound and Vibration: From Ancient to Modern Acoustics / [ed] Vogiatzis, K; Kouroussis, G; Crocker, M; Pawelczyk, M, 2016Conference paper, Published paper (Refereed)
Abstract [en]

Improving uptime is paramount in the heavy duty construction equipment business. Failure ofcritical components in the heavy duty machine may lead to unnecessary stops and expensive downtime. The torque converter, a complex omponent of the driveline, transmits and multiplies torque from the engine to the gearbox, and its failure may not only lead to the machine standing still but may also lead to damage of other parts of the automatic transmission. For adequate condition monitoring of the torque converter, different sensor data are measured on a construction equipment machine during controlled driving sessions. Vibration has been measured on the torque converter. An initial investigation of the vibration measured on the torque converter has been carried out to identify its vibration properties in order to enable its health monitoring to prevent failure. Initial signal analysis of the data have been carried out using Order Power Spectrum and Order Modulation Spectrum methods. The results indicate that the torque converter vibration properties contain information relevant for early fault detection.

Series
Proceedings of the International Congress on Sound and Vibration, ISSN 2329-3675
Keywords
Order Power Spectrum, Order Modulation Spectrum, Torque Converter, Product Development, Information technology - Signal processing, Informationsteknik - Signalbehandling
National Category
Other Mechanical Engineering
Research subject
Computer Aided Design
Identifiers
urn:nbn:se:ltu:diva-40279 (URN)000388480402086 ()2-s2.0-84987896981 (Scopus ID)f5a03c2c-018a-403c-96bf-6d799be06eb9 (Local ID)9789609922623 (ISBN)f5a03c2c-018a-403c-96bf-6d799be06eb9 (Archive number)f5a03c2c-018a-403c-96bf-6d799be06eb9 (OAI)
Conference
International Congress on Sound & Vibration : 10/07/2016 - 14/07/2016
Projects
Fastelaboratoriet - VINNEXC
Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2018-05-16Bibliographically approved
Vingbäck, J., Lideskog, H., Karlberg, M. & Jeppsson, P. (2016). Obstacle identification through fast vector analysis (ed.). In: (Ed.), ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference: . Paper presented at 18th International Conference on Advanced Vehicle Technologies; 13th International Conference on Design Education; 9th Frontiers in Biomedical Devices Charlotte, North Carolina, USA, August 21–24, 2016. New York: American Society of Mechanical Engineers, 3, Article ID DETC2016-59881.
Open this publication in new window or tab >>Obstacle identification through fast vector analysis
2016 (English)In: ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, New York: American Society of Mechanical Engineers , 2016, Vol. 3, article id DETC2016-59881Conference paper, Published paper (Refereed)
Abstract [en]

During road travel, obstacles can impede productivity or durability for many different vehicles and render discomfort or injuries for the people within. Using remote sensing techniques, information from the surroundings can be acquired and analysed to identify obstacles ahead. The subsequent analysis can create a decision support for how the vehicle or driver should act upon encountered obstacles, through either autonomous control, guidance to the driver or a combination of both. In this paper, an experimental setup was created to mimic an obstacle in the shape of a speed bump on a flat road. An RGB-D camera was used to acquire information while travelling towards the speed bump. Afterwards, the acquired information was analysed by an estimation of the normal vector for each point in a 2D depth map. The resulting data from the experiments had sufficient resolution, speed and quality to retrieve proper identify obstacles or targets indoors with an accuracy of 2%. Obstacles were measured and identified in less than 20~ms where processing time mainly comprised data transfer from the USB-bus. The obstacle identification can be used to e.g. actively control the vehicle suspension, send feedback to the driver about obstacles ahead or optimise speed and direction for autonomous vehicles.

Place, publisher, year, edition, pages
New York: American Society of Mechanical Engineers, 2016
National Category
Other Mechanical Engineering
Research subject
Computer Aided Design; Smart machines and materials (AERI)
Identifiers
urn:nbn:se:ltu:diva-35094 (URN)10.1115/DETC2016-59881 (DOI)000393364300002 ()2-s2.0-85007352519 (Scopus ID)97be841e-7edc-40c1-90ac-1e74fabab71d (Local ID)9780791850138 (ISBN)97be841e-7edc-40c1-90ac-1e74fabab71d (Archive number)97be841e-7edc-40c1-90ac-1e74fabab71d (OAI)
Conference
18th International Conference on Advanced Vehicle Technologies; 13th International Conference on Design Education; 9th Frontiers in Biomedical Devices Charlotte, North Carolina, USA, August 21–24, 2016
Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-05-14Bibliographically approved
Lideskog, H. & Karlberg, M. (2016). Simulated continuous mounding improvements through ideal machine vision and control (ed.). Silva Fennica, 50(2), Article ID 1386.
Open this publication in new window or tab >>Simulated continuous mounding improvements through ideal machine vision and control
2016 (English)In: Silva Fennica, ISSN 0037-5330, E-ISSN 2242-4075, Vol. 50, no 2, article id 1386Article in journal (Refereed) Published
Abstract [en]

To promote the growth and survival of regenerated forests, site preparation prior to tree planting on clearcuts is necessary. This is often performed with scarifiers, either through trenching or mounding. Mounding is generally considered better in a plant survival perspective but is inefficient on obstacle-rich clearcuts. By utilising machine vision through e.g. remote sensing methods, new strategies can enable efficient mound positioning. In this paper, three realistic strategies utilizing ideal clearcut object identification through machine vision have been developed that can be used for more efficient mounding. The results show that mounding efficiency can be significantly improved with a new mound positioning strategy that employs ideal object identification, especially on obstacle-rich clearcuts.

National Category
Other Mechanical Engineering
Research subject
Computer Aided Design; Smart machines and materials (AERI)
Identifiers
urn:nbn:se:ltu:diva-13421 (URN)10.14214/sf.1386 (DOI)2-s2.0-84961262902 (Scopus ID)ca597abb-2bcf-4948-8a67-498c63e59b31 (Local ID)ca597abb-2bcf-4948-8a67-498c63e59b31 (Archive number)ca597abb-2bcf-4948-8a67-498c63e59b31 (OAI)
Projects
Fastelaboratoriet - VINNEXC
Note

Validerad; 2016; Nivå 2; 20130904 (haklid)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2342-1647

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