ISSN 2353-6977 (Online)
With regard to adapting enterprise to the Industry 4.0 concept, the first element should be the implementation and use of an information system within a manufacturing company. This article proposes a model, the use
of which will allow the level of automation of a maintenance department to be forecast, depending on the effectivity of the use of the Manufacturing Executions System (MES) within a company. The model was built on the basis of the actual times of business processes completed which were supported by MES in the maintenance departments of two manufacturing enterprises using artificial neural network. As a result of research experiments, it was confirmed that the longer the time taken to complete business processes supported by MES, the higher is the degree of automation in a maintenance department.
- APA 6th style
Halikowski, D., Patalas-Maliszewska, J., & Skrzeszewska, M. (2018). A model for assessing the level of automation of a maintenance department using artificial neural network. Applied Computer Science, 14(4), 70-80. doi:10.23743/acs-2018-30
- Chicago style
Halikowski, Daniel, Justyna Patalas-Maliszewska, and Małgorzata Skrzeszewska. "A Model for Assessing the Level of Automation of a Maintenance Department Using Artificial Neural Network." Applied Computer Science 14, no. 4 (2018): 70-80.
- IEEE style
D. Halikowski, J. Patalas-Maliszewska, and M. Skrzeszewska, "A model for assessing the level of automation of a maintenance department using artificial neural network," Applied Computer Science, vol. 14, no. 4, pp. 70-80, 2018.
- Vancouver style
Halikowski D, Patalas-Maliszewska J, Skrzeszewska M. A model for assessing the level of automation of a maintenance department using artificial neural network. Applied Computer Science. 2018;14(4):70-80.
| < Prev | Next > |
|---|
