Remote Data Collection Motivational Drivers, Challenges, and Potential Solutions in Industrial SME Companies

Teemu Mäkiaho; Topias Kallio; Henri Vainio; Jouko Laitinen; Kari Koskinen

doi:10.1007/978-3-031-25448-2_17

Remote Data Collection Motivational Drivers, Challenges, and Potential Solutions in Industrial SME Companies

Teemu Mäkiaho, Topias Kallio, Henri Vainio, Jouko Laitinen, Kari Koskinen

Automation Technology and Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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Abstract

Data collected from industrial machines enable companies to pursue new servitization offerings such as machine health condition monitoring as well as to monitor the machine behavior for research and development purposes. In this study, qualitative data was collected from four different industrial SME companies to create a better understanding of the motivational drivers industrial companies may have to create remote data collection systems. The results will discuss the initial motivational drivers for data collection setup construction as well as the challenges companies were facing along the way in designing and implementing their systems. Based on the empirical research results, the recognition of internal motivational drivers and data utilization targets should be clear before proceeding to further development of data collection infrastructure. Generally, the research results recognize various areas that an automation industry company needs to consider before planning and implementing an online data collection system, what challenges they may face as well as generalized proposed solutions are presented.

Original language	English
Title of host publication	16th WCEAM Proceedings, 2022
Editors	Adolfo Crespo Márquez, Juan Francisco Gómez Fernández, Vicente González-Prida Díaz, Joe Amadi-Echendu
Publisher	Springer
Pages	172-181
Number of pages	10
ISBN (Print)	9783031254475
DOIs	https://doi.org/10.1007/978-3-031-25448-2_17
Publication status	Published - 2023
Publication type	A4 Article in conference proceedings
Event	World Congress on Engineering Asset Management - Seville, Spain Duration: 5 Oct 2022 → 7 Oct 2022

Publication series

Name	Lecture Notes in Mechanical Engineering
ISSN (Print)	2195-4356
ISSN (Electronic)	2195-4364

Conference

Conference	World Congress on Engineering Asset Management
Country/Territory	Spain
City	Seville
Period	5/10/22 → 7/10/22

Publication forum classification

Publication forum level 1

ASJC Scopus subject areas

Automotive Engineering
Aerospace Engineering
Mechanical Engineering
Fluid Flow and Transfer Processes

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10.1007/978-3-031-25448-2_17

Remote Data Collection Motivational Drivers
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Mäkiaho, T., Kallio, T., Vainio, H., Laitinen, J., & Koskinen, K. (2023). Remote Data Collection Motivational Drivers, Challenges, and Potential Solutions in Industrial SME Companies. In A. Crespo Márquez, J. F. Gómez Fernández, V. González-Prida Díaz, & J. Amadi-Echendu (Eds.), 16th WCEAM Proceedings, 2022 (pp. 172-181). (Lecture Notes in Mechanical Engineering). Springer. https://doi.org/10.1007/978-3-031-25448-2_17

Mäkiaho, Teemu ; Kallio, Topias ; Vainio, Henri et al. / Remote Data Collection Motivational Drivers, Challenges, and Potential Solutions in Industrial SME Companies. 16th WCEAM Proceedings, 2022. editor / Adolfo Crespo Márquez ; Juan Francisco Gómez Fernández ; Vicente González-Prida Díaz ; Joe Amadi-Echendu. Springer, 2023. pp. 172-181 (Lecture Notes in Mechanical Engineering).

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title = "Remote Data Collection Motivational Drivers, Challenges, and Potential Solutions in Industrial SME Companies",

abstract = "Data collected from industrial machines enable companies to pursue new servitization offerings such as machine health condition monitoring as well as to monitor the machine behavior for research and development purposes. In this study, qualitative data was collected from four different industrial SME companies to create a better understanding of the motivational drivers industrial companies may have to create remote data collection systems. The results will discuss the initial motivational drivers for data collection setup construction as well as the challenges companies were facing along the way in designing and implementing their systems. Based on the empirical research results, the recognition of internal motivational drivers and data utilization targets should be clear before proceeding to further development of data collection infrastructure. Generally, the research results recognize various areas that an automation industry company needs to consider before planning and implementing an online data collection system, what challenges they may face as well as generalized proposed solutions are presented.",

author = "Teemu M{\"a}kiaho and Topias Kallio and Henri Vainio and Jouko Laitinen and Kari Koskinen",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; World Congress on Engineering Asset Management ; Conference date: 05-10-2022 Through 07-10-2022",

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language = "English",

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series = "Lecture Notes in Mechanical Engineering",

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Mäkiaho, T, Kallio, T, Vainio, H , Laitinen, J & Koskinen, K 2023, Remote Data Collection Motivational Drivers, Challenges, and Potential Solutions in Industrial SME Companies. in A Crespo Márquez, JF Gómez Fernández, V González-Prida Díaz & J Amadi-Echendu (eds), 16th WCEAM Proceedings, 2022. Lecture Notes in Mechanical Engineering, Springer, pp. 172-181, World Congress on Engineering Asset Management, Seville, Spain, 5/10/22. https://doi.org/10.1007/978-3-031-25448-2_17

Remote Data Collection Motivational Drivers, Challenges, and Potential Solutions in Industrial SME Companies. / Mäkiaho, Teemu; Kallio, Topias; Vainio, Henri et al.
16th WCEAM Proceedings, 2022. ed. / Adolfo Crespo Márquez; Juan Francisco Gómez Fernández; Vicente González-Prida Díaz; Joe Amadi-Echendu. Springer, 2023. p. 172-181 (Lecture Notes in Mechanical Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Remote Data Collection Motivational Drivers, Challenges, and Potential Solutions in Industrial SME Companies

AU - Mäkiaho, Teemu

AU - Kallio, Topias

AU - Vainio, Henri

AU - Laitinen, Jouko

AU - Koskinen, Kari

PY - 2023

Y1 - 2023

N2 - Data collected from industrial machines enable companies to pursue new servitization offerings such as machine health condition monitoring as well as to monitor the machine behavior for research and development purposes. In this study, qualitative data was collected from four different industrial SME companies to create a better understanding of the motivational drivers industrial companies may have to create remote data collection systems. The results will discuss the initial motivational drivers for data collection setup construction as well as the challenges companies were facing along the way in designing and implementing their systems. Based on the empirical research results, the recognition of internal motivational drivers and data utilization targets should be clear before proceeding to further development of data collection infrastructure. Generally, the research results recognize various areas that an automation industry company needs to consider before planning and implementing an online data collection system, what challenges they may face as well as generalized proposed solutions are presented.

AB - Data collected from industrial machines enable companies to pursue new servitization offerings such as machine health condition monitoring as well as to monitor the machine behavior for research and development purposes. In this study, qualitative data was collected from four different industrial SME companies to create a better understanding of the motivational drivers industrial companies may have to create remote data collection systems. The results will discuss the initial motivational drivers for data collection setup construction as well as the challenges companies were facing along the way in designing and implementing their systems. Based on the empirical research results, the recognition of internal motivational drivers and data utilization targets should be clear before proceeding to further development of data collection infrastructure. Generally, the research results recognize various areas that an automation industry company needs to consider before planning and implementing an online data collection system, what challenges they may face as well as generalized proposed solutions are presented.

U2 - 10.1007/978-3-031-25448-2_17

DO - 10.1007/978-3-031-25448-2_17

M3 - Conference contribution

AN - SCOPUS:85151122249

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A2 - Crespo Márquez, Adolfo

A2 - Gómez Fernández, Juan Francisco

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A2 - Amadi-Echendu, Joe

PB - Springer

T2 - World Congress on Engineering Asset Management

Y2 - 5 October 2022 through 7 October 2022

ER -

Mäkiaho T, Kallio T, Vainio H , Laitinen J , Koskinen K. Remote Data Collection Motivational Drivers, Challenges, and Potential Solutions in Industrial SME Companies. In Crespo Márquez A, Gómez Fernández JF, González-Prida Díaz V, Amadi-Echendu J, editors, 16th WCEAM Proceedings, 2022. Springer. 2023. p. 172-181. (Lecture Notes in Mechanical Engineering). doi: 10.1007/978-3-031-25448-2_17

Remote Data Collection Motivational Drivers, Challenges, and Potential Solutions in Industrial SME Companies

Abstract

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ASJC Scopus subject areas

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