A MODEL OF KNOWLEDGE ACQUISITION IN THE MAINTENANCE DEPARTMENT OF A PRODUCTION COMPANY
Małgorzata ŚLIWA
m.sliwa@iizp.uz.zgora.plUniversity of Zielona Góra, Institute of Machine Construction and Operations Engineering, Prof. Z. Szafrana 4, 65-516 Zielona Góra (Poland)
Ewelina KOSICKA
Lublin University of Technology, Department of Production Engineering,Nadbystrzycka 36, 20-618 Lublin, (Poland)
Abstract
The knowledge acquisition model proposed in this paper is designed to assist with the acquisition of knowledge in a company possessing its own maintenance department. The model is built on the basis of knowledge bases. The authors focus on basic information required for maintenance department operation and expert archiving of technical documentation. Three main areas are covered by the model: knowledge acquisition and formalization, knowledge systematization and knowledge retrieval by problem or field. It is assumed that the implementation of the model coupled with an electronic knowledge acquisition report and with an application for information retrieval will bring benefits for the company.
Keywords:
maintenance, knowledge acquisition, knowledge management, knowledge bases, electronic reportReferences
Bernaert, M., & Poels, G. (2011). The Quest for Know-How, Know-Why, Know-What and KnowWho: Using KAOS for Enterprise Modelling. Advanced Information Systems Engineering Workshops, 83, 29–40.
DOI: https://doi.org/10.1007/978-3-642-22056-2_4
Google Scholar
Beyer, K. (2011). Wiedza jako kluczowy zasób w nowej gospodarce. Studia i prace Wydziału Nauk Ekonomicznych i Zarządzania, 21, 7–16.
Google Scholar
Dąbrowski, K., & Patalas – Maliszewska, J. (2016). Knowledge Transfer in the International Scientific Project Groups. In: T. A. Grzeszczyk (Ed.), Challenges of New Technology Applications in Project Management and Evaluation (pp. 59–73). Warszawa: Wyd. Politechniki Warszawskiej.
Google Scholar
Falkenberg, L., Woiceshyn, J., & Karagianis, J. (2017, April 10). Knowledge sourcing: internal or external? Theme: Strategy, Competitiveness and Learning. Conference: Organizational Learning and Knowledge, Lancaster, UK, Volume: 5th International Conference 2003. Retrieved from https://www2.warwick.ac.uk/fac/soc/wbs/conf/olkc/archive/olk5/papers/paper16.pdf
Google Scholar
Fazlagić, J. (2014). Innowacyjne zarzadzanie wiedzą. Warszawa: Wyd. Difin.
Google Scholar
Gasik, S. (2011). A Model of Project Knowledge Management. Project Management Journal, 42(3), 23–44. doi: 10.1002/pmj.20239
DOI: https://doi.org/10.1002/pmj.20239
Google Scholar
Grabowski, M., & Zając, A. (2009). Dane, informacja, wiedza - próba definicji. Zeszyty Naukowe, Uniwersytet Ekonomiczny w Krakowie, 798, 99–116.
Google Scholar
http://cmms.net, Retrieved May 15, 2017.
Google Scholar
http://maintpartner.fi/index.php/en/, Retrieved May 15, 2017.
Google Scholar
http://www.komtech.pl, Retrieved May 15, 2017.
Google Scholar
http://www.utrzymaniemaszyn.pl Retrieved May 15, 2017.
Google Scholar
Kosicka, E., & Mazurkiewicz, D. (2015). Support of predictive maintenance processes using mobile devices. In: R. Knosala (Ed.), Innowacje w zarządzaniu i inżynierii produkcji. T. 2 (pp. 536–543). Opole: Oficyna Wydawnicza Polskiego Towarzystwa Zarządzania Produkcją.
Google Scholar
Maier, R. (2002). Knowledge Management Systems. Information and Communication Technologies for Knowledge Management. Springer-Verlag Berlin Heidelberg.
DOI: https://doi.org/10.1007/978-3-662-04380-6
Google Scholar
Mendryk, I. (2011). Źródła wiedzy organizacyjnej – wyniki badań polskich przedsiębiorstw. Zeszyty naukowe: Współpraca w łańcuchach dostaw a konkurencyjność przedsiębiorstw i kooperujących sieci, 32, 315–331.
Google Scholar
Nonaka, I., Ryoko, T., & Konno, N.(2000). SECI, Ba and Leadership: a Unified Model of Dynamic Knowledge Creation. Long Range Planning, 33, 5–34.
DOI: https://doi.org/10.1016/S0024-6301(99)00115-6
Google Scholar
Padzich, K. (2004). Zastosowanie technologii informacyjnej (IT) w podnoszeniu efektywności pracy zespołowej. Model organizacji transmutacyjnej (doctoral dissertation). Wydział Zarządzania UW, Warszawa.
Google Scholar
Piotrowska, A. (2012). Wiedza jawna i niejawna jako zasób decyzyjny w zarządzaniu personelem. In A. Grzegorczyk (Ed.), Procesy decyzyjne w warunkach niepewności (pp. 79–95). Warszawa, Wyd. Wyższa Szkoła Promocji.
Google Scholar
Rybińska, M., & Sekieta, M. (2009). Komputerowe wspomaganie zarządzania utrzymaniem ruchu. Komputerowo zintegrowane zarządzanie, t.2 (pp. 369–376). Opole: Oficyna Wydawnicza Polskiego Towarzystwa Zarządzania Produkcją.
Google Scholar
Skarka, W. (2007). Metodologia procesu projektowo-konstrukcyjnego opartego na wiedzy. Gliwice, Wyd. Politechniki Śląskiej.
Google Scholar
Śliwa, M., & Patalas-Maliszewska, J. (2015). Model of converting tacit knowledge into explicit knowledge on the example of R&D department of the manufacturing company, including evaluation of knowledge workers' usefulness. Journal of Theoretical and Applied Computer Science, 9(3), 25–34.
Google Scholar
Śliwa, M., & Patalas-Maliszewska, J. (2016). A Strategic Knowledge Map for the Research and Development Department in a Manufacturing Company. Foundations of Management. International Journal, 8(1), 151-166. https://doi.org/10.1515/fman-2016-0012
DOI: https://doi.org/10.1515/fman-2016-0012
Google Scholar
Tabaszewska, E. (2008). Nowoczesne koncepcje zarządzania – zarządzanie wiedzą. Wrocław, Wyd. Uniwersytetu Ekonomicznego.
Google Scholar
Wąsowicz, M. (2013). Zarządzanie wiedzą w portfelach projektów. In G. Bełz, M. Hopej, & A. Zgrzywa (Eds.), Wiedza w zarządzaniu współczesną organizacją (pp. 130–137). Uniwersytet Ekonomiczny we Wrocławiu.
Google Scholar
Authors
Małgorzata ŚLIWAm.sliwa@iizp.uz.zgora.pl
University of Zielona Góra, Institute of Machine Construction and Operations Engineering, Prof. Z. Szafrana 4, 65-516 Zielona Góra Poland
Authors
Ewelina KOSICKALublin University of Technology, Department of Production Engineering,Nadbystrzycka 36, 20-618 Lublin, Poland
Statistics
Abstract views: 37PDF downloads: 1
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.
Most read articles by the same author(s)
- Marcin Topczak, Małgorzata Śliwa, ASSESSMENT OF THE POSSIBILITY OF USING BAYESIAN NETS AND PETRI NETS IN THE PROCESS OF SELECTING ADDITIVE MANUFACTURING TECHNOLOGY IN A MANUFACTURING COMPANY , Applied Computer Science: Vol. 17 No. 1 (2021)
Similar Articles
- Siti ROHAJAWATI, Hutanti SETYODEWI, Ferryansyah Muji Agustian TRESNANTO, Debora MARIANTHI, Maruli Tua Baja SIHOTANG , KNOWLEDGE MANAGEMENT APPROACH IN COMPARATIVE STUDY OF AIR POLLUTION PREDICTION MODEL , Applied Computer Science: Vol. 20 No. 1 (2024)
- Daniel HALIKOWSKI, Justyna PATALAS-MALISZEWSKA, Małgorzata SKRZESZEWSKA, A MODEL FOR ASSESSING THE LEVEL OF AUTOMATION OF A MAINTENANCE DEPARTMENT USING ARTIFICIAL NEURAL NETWORK , Applied Computer Science: Vol. 14 No. 4 (2018)
- Bartosz CIEŚLA, Grzegorz GUNIA, DEVELOPMENT OF INTEGRATED MANAGEMENT INFORMATION SYSTEMS IN THE CONTEXT OF INDUSTRY 4.0 , Applied Computer Science: Vol. 15 No. 4 (2019)
- Eduardo Sánchez-García, Javier Martínez-Falcó, Bartolomé Marco-Lajara, Jolanta Słoniec, ANALYZING THE ROLE OF COMPUTER SCIENCE IN SHAPING MODERN ECONOMIC AND MANAGEMENT PRACTICES. BIBLIOMETRIC ANALYSIS , Applied Computer Science: Vol. 20 No. 1 (2024)
- Aneta KARASEK, IT TOOLS SUPPORTING EMPLOYEE MANAGEMENT IN A HIGH-TECH ENTERPRISE , Applied Computer Science: Vol. 15 No. 1 (2019)
- Konrad BIERCEWICZ, Mariusz BORAWSKI, Anna BORAWSKA, Jarosław DUDA, DETERMINING THE DEGREE OF PLAYER ENGAGEMENT IN A COMPUTER GAME WITH ELEMENTS OF A SOCIAL CAMPAIGN USING COGNITIVE NEUROSCIENCE TECHNIQUES , Applied Computer Science: Vol. 18 No. 4 (2022)
- Mouna TARIK, Ayoub MNIAI, Khalid JEBARI, HYBRID FEATURE SELECTION AND SUPPORT VECTOR MACHINE FRAMEWORK FOR PREDICTING MAINTENANCE FAILURES , Applied Computer Science: Vol. 19 No. 2 (2023)
- Monika KULISZ, Aigerim DUISENBEKOVA, Justyna KUJAWSKA, Danira KALDYBAYEVA, Bibigul ISSAYEVA, Piotr LICHOGRAJ, Wojciech CEL, IMPLICATIONS OF NEURAL NETWORK AS A DECISION-MAKING TOOL IN MANAGING KAZAKHSTAN’S AGRICULTURAL ECONOMY , Applied Computer Science: Vol. 19 No. 4 (2023)
- Piotr WITTBRODT, Iwona ŁAPUŃKA, Gulzhan BAYTIKENOVA, Arkadiusz GOLA, Alfiya ZAKIMOVA, IDENTIFICATION OF THE IMPACT OF THE AVAILABILITY FACTOR ON THE EFFICIENCY OF PRODUCTION PROCESSES USING THE AHP AND FUZZY AHP METHODS , Applied Computer Science: Vol. 18 No. 4 (2022)
- KK Praneeth Tellakula, Saravana Kumar R, Sanjoy Deb, A SURVEY OF AI IMAGING TECHNIQUES FOR COVID-19 DIAGNOSIS AND PROGNOSIS , Applied Computer Science: Vol. 17 No. 2 (2021)
You may also start an advanced similarity search for this article.
