Industry 4.0 Desiderata as Micro Foundations in the Assessment of Companies' Maturity - Case Study

• Autorzy: Bogdan Nogalski , Przemysław Niewiadomski
• Języki publikacji: EN

Abstrakty

EN

The industry transformation to the digital model 4.0 will be a significant change from the perspective of the organisation and processes. In the context of the above, the research was undertaken, the principal aim of which constituted the attempt to answer the question concerning the technological advancement level of manufacturing companies operating in the agricultural machinery sector. It is about identifying what adaptation projects in the context of the fourth generation industry era should be undertaken by the Polish manufacturers operating in the agricultural machinery sector. The achievement of the main objective required formulation and implementation of partial objectives, which, according to the authors, include: C(1) - defining the Industry 4.0 axiom merit; C(2) - using the subject literature reconstruction and interpretation methods - nomination of areas, on the one hand essential from the perspective of the model 4.0, and on the other hand those that may demonstrate the maturity in the domain of the adopted desiderata; C(3) - compilation of the research model, in the form of an assessment sheet, being a resultant of literature studies and research conducted among deliberately selected domain experts; C(4) - based on the selected indicators, the technological advancement level recognition of the studied companies; specification of a technological gap (questioning among experts). (original abstract)

Słowa kluczowe

PL

Przemysł 4.0; Digitalizacja; Modele biznesowe; Produkcja rolna; Mechanizacja rolnictwa

EN

Industry 4.0; Digitizing; Business models; Agricultural production; Agricultural mechanization

• Czasopismo: Management and Production Engineering Review
• Rocznik: 2020
• Tom: 11
• Numer: nr 4
• Strony: 92-103

Twórcy

autor

Bogdan Nogalski

• WSB University in Gdańsk, Poland

autor

Przemysław Niewiadomski

• University of Zielona Góra, Poland

Bibliografia

• Lasi H., Fettke, P., Kemper, H., Feld, T., Hoffmann M., Industry 4.0, Business & Information Systems Engineering, 6, 239-242, 2014.
• Garrett G.A., Parrott G.A., E-Business - Understanding Key Trends and Applaying Best Practices, Contract Management, 7, 34-42, 2005.
• Nogalski B., Niewiadomski P., Szpitter A., Fourth Generation Industry and Strategic Adaptation Activities of Polish Agricultural Machinery Manufacturers [in Polish: Przemysł czwartej generacji a strategiczne działania dostosowawcze polskich wytwórców sektora maszyn rolniczych, Przeglad Organizacji, 11, 6-13, 2018.
• Fischer M., Glass industry 4.0, i.e. the fourth industrial revolution [in Polish: Przemysł szklarski 4.0 czyli czwarta rewolucja przemysłowa, Swiat Szkła, No. 2, 2018.
• Atzori L., Iera, A., Morabito G., The Internet of Things: A survey, Computer Networks, 54, 15, 2787-2805, 2010.
• BCG - Boston Consulting Group (Hg.), Industry 4.0: The Future of Productivity and Growth in Manufacturing Industries, M¨unchen 2015.
• Fallera C., Feldmüllera D., Industry 4.0 Learning Factory for regional SMEs, Procedia CIRP, 32, 88- 91, 2015.
• Gamst G., Meyers L.S, Guarino A.J., Analysis of Variance Designs. A Conceptual and Computational Approach with SPSS and SAS, Cambridge University Press, New York, 2008.
• Hirsch-Kreinsen H., Wandel von Produktionsarbeit - "Industrie 4.0", Soziologisches Arbeitspapier, No. 38, 2014.
• https://przemyslprzyszlosci.gov.pl/artykuly/; date of access: 24.01.2020.
• Kagermann H., Wahlster W., Helbig J., Recommendations for implementing the strategic initiative Industrie 4.0: Final report of the Industrie 4.0, National Academy of Science and Engineering, Munich, 2013.
• Lasi H., Industrial intelligence - a business intelligence-based approach to enhance manufacturing engineering in industrial companies, Procedia CIRP, 12, 384-389, 2013.
• Lee J., Industry 4.0 in Big Data Environment, German Harting Magazine, pp. 8-10, 2013.
• Lee J., Kao H-A, Yang S., Service innovation and smart analytics for Industry 4.0 and big data environment, Procedia CIRP, 16, 3-8, 2014.
• Qin J., Liu Y., Grosvenor R., A Categorical Framework of Manufacturing for Industry 4.0 and Beyond, Procedia CIRP, 52, 173-178, 2016.
• Roland Berger Strategy Consultants, Industry 4.0. The new industrial revolution How Europe will succeed, March 2014.
• Schlund S., Hämmerle M., Strölin T., Industrie 4.0 eine Revolution der Arbeitsgestaltung - Wie Automatisierung und Digitalisierung unsere Produktion verändern wird, Ingenics AG, Ulm-Stuttgart, 2014.
• Schmidt R., Möhring M., Härting R.C., Reichstein C., Neumaier P., Jozinovic, P., Industry 4.0 - Potentials for Creating Smart Products: Empirical Research Results, [in:] Business Information Systems, Abramowicz W. [Ed.], Switzerland: Springer International Publishing, pp. 16-27, 2015.
• Subashini S., Kavitha V., A survey on security issues in service delivery models of cloud computing, Journal of Network and Computer Applications, 34, 1, 1-11, 2011.
• This World Economic Forum white paper, Readiness for the Future of Production: Country Profiles, March 2017.
• Zuehlkea D., SmartFactory - Towards a factory-ofthings, Annual Reviews in Control, 34, 1, 129-138, 2010.
• Okoli C., Pawlowski S., The Delphi Method as a Research Tool: An Example, Design Considerations and Applications, Information & Management, 42, 1, 15-29, 2014.
• Paliwoda S.J., Predicting the Future Using Delphi, Management Decision, 21, 1, 31-38, 1993.

Identyfikatory

DOI

10.24425/mper.2020.136123