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Levels of control for autonomous trucks in . open-pit mining
KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.), Industrial Management.
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Kontrollnivåer för autonoma lastbilar i  dagbrott (English)
Abstract [en]

The development of autonomous trucks has been moving forward in a fast pace during the last couple of years and is seen as a suitable alternative to be used in open-pit mining environments.

This thesis presents the underlying KPIs that need to be considered when developing a management system for autonomous trucks in open-pit mining. These KPIs are then linked to control levels exemplified by real mining situations.

In order to establish the KPIs, observations in form of a field study was conducted in Aitik mine outside of Gällivare in northern Sweden. In addition, five semi-structured interviews were performed with people who were experts in their respective field. After the empirical data was gathered three different types of analyses were conducted in order to establish the KPIs. A framework by Hollnagel & Woods (2005) called the Extended Control Model (ECOM)  as used to link the KPIs to levels of control. The analysis led to a better understanding of the interaction between autonomous trucks and the mine and can act as guidance in the design phase of both the management system and the autonomous truck. With the introduction of an autonomous haulage system more KPIs will be linked to the truck and consequently the truck will be given a higher authority. The role of the mine dispatcher will change into a more analytical role interacting with the system solely at the highest level of control

Abstract [en]

Utvecklingen av autonoma lastbilar har gått framåt i snabb takt under de senaste åren och de ses som ett lämpligt alternativ till att användas i gruvindustrins dagbrott.

I denna uppsats presenteras de underliggande KPIer som måste beaktas när man utvecklar ett ledningssystem för autonoma lastbilar i dagbrott. Dessa nyckeltal är sedan kopplade till kontrollnivåer som exemplifieras av verkliga gruvsituationer.

För att fastställa KPIer genomfördes iakttagelser i form av en fältstudie i Aitikgruvan utanför Gällivare i norra Sverige. Dessutom har fem semistrukturerade intervjuer genomförts med experter inom de relevanta områdena. Efter att empirisk data samlats in genomfördes tre olika typer av analyser för att fastställa de underliggande KPIerna. Ett ramverk av Hollnagel & Woods (2005) kallad Extended Control Model (ECOM) användes för att koppla KPIer till kontrollnivåer. Analysen ledde till en bättre förståelse för samspelet mellan autonoma lastbilar och gruvan och kan fungera som vägledning i designfasen av både ledningssystemet och den autonoma lastbilen. Med införandet av ett autonomt system kommer fler nyckeltal att kopplas till lastbilen och därmed får lastbilen en högre befogenhet. Rollen som dispatcher  gruvan kommer att förändras till en mer analytisk roll som interagerar med systemet enbart på den högsta kontrollnivån.

Place, publisher, year, edition, pages
2015. , 49 p.
Keyword [en]
open-pit mining, key performance indicators, autonomous trucks, automation
National Category
Economics and Business
Identifiers
URN: urn:nbn:se:kth:diva-189617OAI: oai:DiVA.org:kth-189617DiVA: diva2:947406
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Available from: 2016-07-11 Created: 2016-07-08 Last updated: 2016-07-11Bibliographically approved

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