MATEC Web Conf.
Volume 178, 201822nd International Conference on Innovative Manufacturing Engineering and Energy - IManE&E 2018
|Number of page(s)||5|
|Section||Industrial And Product Management, Quality and Evaluation|
|Published online||24 July 2018|
A qualitative estimation of the influence of transport factors on the work efficiency
University of Pitesti, Department of Electronics, Computers, Communications and Electrical Engineering, Str. Tg. Din Vale, nr. 1, Pitesti, Romania
2 University of Pitesti, Department of Manufacturing and Industrial Management, Str. Tg. Din Vale, nr. 1, Pitesti, Romania
* Corresponding author: firstname.lastname@example.org
In this paper we make a qualitative estimation of the influence of transport factors on the work efficiency (labour yield). There will be three classes of influence: positive influence, no influence and negative influence. We take into account some transportation factors like the level of noise during the transport, the level of temperature (the thermic comfort), etc. We use a software simulated feed forward neural network in order to solve this classification problem. The network will divide the input data (values for the transport factors) into these three classes. The input data are stored in an XML file, and they are obtained from a questionnaire that was completed by people working in automotive industry. The results are both useful for the transport companies and for the industry managers.
© The Authors, published by EDP Sciences, 2018.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.