D2 Article in a professional research book (incl. editor’s introduction)

CASE KONECRANES: The Crane as Process Performance Analyzer


Open Access publication

Publication Details
Authors: Mesiä Heikki, Malysheva Julia, Eerola Tuomas, Kälviäinen Heikki, Lensu Lasse
Edition name or number: DIMECC Publications Series, No.11
Publishing place: Tampere, Finland
Publication year: 2017
Language: English
Related Journal or Series Information: DIMECC Publication series
Title of parent publication: S-STEP–Smart Technologies for Lifecycle Performance, Final Report 1/2017
Start page: 23
End page: 25
Number of pages: 3
ISBN: 978-952-238-178-1
eISBN: 978-952-238-179-8
eISSN: 2342-2696
JUFO-Level of this publication: 0
Open Access: Open Access publication

Abstract

The intelligent machines of today are aware of their use and state, but they should also become more aware of their close environment. This challenge can be solved by adopting physical and virtual sensor systems that fit the purpose. Intelligent ‘soft’ sensing enables the gathering of information that is difficult to measure directly. The applicable solutions include the use of multisensory and model-based indirect measurement methods that combine readily available machine data with measurements, thus creating soft sensor combinations. By communicating with each other, the sensor systems can produce value-adding information for other machines, applications, and operators. Process cranes are operated high above the production lines. They have a splendid bird’s eye view over their working area, but this advantage is not fully exploited. The S-STEP research has targeted adding to the crane the senses it needs. With its enhanced capabilities, the crane, in addition to its primary functions, becomes a source of reliable dynamic information for the factory, supporting the efficiency and safety of the processes.


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Last updated on 2018-19-10 at 07:55