Smart Process INdustry CranEs — SPRINCE

The problem addressed

Cranes are the most dangerous equipment in industrial and construction sites. A tipped, dropped or mishandled load can directly injure workers or potentially upset the equipment. Their dangerousness has special relevance in the chemical process industry and intermodal transport, where accidental events could cause the release of hazardous substances. The SPRINCE project is based on the idea that crane accidents caused by obstructed view and visual tension problems are preventable, thus it promotes a real-time computer-aided visual feedback and gives its assessment. The project aims to find the best platform which can improve the positioning phase performance of industrial cranes by offering high execution speed, ease of integration, low cost, low power consumption, less computer memory and good support with precise position visual guidance (video tracker with web cameras) used to navigate the object into the correct position.

Keywords: risk indicator industrial crane

Research questions

The literature has highlighted the main needs for crane design (capability to be safely operated, easy maintenance and reduction of typical human problem factors), but up to now research has not been focused on the crane navigation system. Typical crane operator interfaces actually appear to be simple in terms of the number of controls; by moving the spreader quickly and accurately, with or without a container, it requires an exceptional sense of its dynamics, including how to effectively stop the moving mass. The need of a new solution for crane visual tension problems is emerging. In this frame the aim of the SPRINCE project is to improve the performance of industrial cranes with innovative real-time computer-aided visual feedback control and estimate new&emerging risks with early warning indicators tools.

Keywords: operator support

Scientific disciplines: ergonomics

Expected outputs

The main goal is to reduce the number of incidents due to situations that can be prevented by promoting a real-time computer-aided visual feedback, based on the following observations:

typical crane operator interfaces are simple in terms of the number of controls, thus an exceptional sense of its dynamics is needed, including how to effectively stop the moving mass
there is the necessity to reduce the productivity drop due to human-machine interface problems, the large financial losses due to the cost of accidents, the costs for frequent repairs, the disturbance in material handling schedules and the increased work-load on other equipment and their consequent quicker downtime and break down
there is a need to manage emerging risks, derived by the increased use of integrated operations/remote operations in process industry and transport of hazardous materials, by means of an improved virtualization technology.

The outputs expected include:

a platform that allows improvement of the positioning performance of industrial cranes (high execution speed, ease of integration, low cost, low power consumption, less computer memory and good support with precise position visual guidance)
scalability information, related to the display configuration and the ergonomics, by using and testing different screen types in crane cabins through case studies
risk indicators which are context specific (derived through the analysis of Italian and Serbian case studies) and operator-specific (account for organizational and human factors by means of the response of operators to the questionnaire)

Workplan

The project comprises five work packages:

WP1: the implementation of a real-time object detection solution to industrial cranes
WP2: the development of a risk indicator tool for the implemented solution
WP3: the application of the risk indicator tool
WP4: the economic appraisal
WP5: project management

Associated deliverables

D1: Visual guidance system development
Intermediate report CC BY-SA published on 2016-09-15

This deliverable describes a real-time computer-aided visual guidance application that has been developed to avoid crane accidents where an obstructed view is a contributory factor. The system allows predicting whether a dangerous event is going to occur and promptly alerting the crane-operator in order to let her/him taking corrective actions during the execution of crane-assisted shifting duties.

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Video showing operation of the visual guidance system
Illustrative video CC BY-SA published on 2016-09-15

This video illustrates content presented in deliverable D1.

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Participating researchers

Aleksandar Brkic (Faculty of Mechanical Engineering, University of Belgrade, Serbia)

Maria Francesca Milazzo (epartment of Electronic Engineering, Industrial Chemistry and Engineering, University of Messina, Italy) — project coordinator

Vesna Spasojevic Brkic (Faculty of Mechanical Engineering, University of Belgrade, Serbia)

Nikola Dondur (Faculty of Mechanical Engineering, University of Belgrade, Serbia)

David Valis (Faculty of Military Technologies, Brno University of Defence, Czech Republic)

Funding organizations

CZ-TPIS (Czech Republic)

MESTD (Serbia)

INAIL (Italy)

More details

Duration	2015-04 to 2017-04
Contact email	`mfmilazzo@unime.it`
More information

Information last updated on 2016-09-15.

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