Development of an autonomous control system for target-optimised use of intralogistics means of transport in a production system for individualised products

dc.contributor.advisorVon Leipzig, Konraden_ZA
dc.contributor.advisorHummel, Veraen_ZA
dc.contributor.authorGrosse Erdmann, Julianen_ZA
dc.contributor.otherStellenbosch University. Faculty of Industrial Engineering. Dept. of Industrial Engineering. .en_ZA
dc.date.accessioned2020-02-19T12:03:13Z
dc.date.accessioned2020-04-28T12:13:37Z
dc.date.available2020-02-19T12:03:13Z
dc.date.available2020-04-28T12:13:37Z
dc.date.issued2020-03
dc.descriptionThesis (MEng)--Stellenbosch University, 2020.en_ZA
dc.description.abstractENGLISH ABSTRACT: Rapidly changing market conditions and global competition result in higher expectations from customers, and in turn, require increased efficiencies from companies. This, coupled with the increasing complexity of logistics systems, requires innovative approaches concerning the organisation and control of these logistics systems. In scientific research, concepts of autonomously controlled logistics systems show a promising approach to meeting the increasing requirements for flexible and efficient order processing. In this context, this work aims to develop a system that is able to dynamically adjust order processing, and optimise intralogistics transportation with regard to various generic intralogistics target criteria in a flexible flow production. In this paper, the logistics system under consideration consists of various means of transport for autonomous decision-making and fulfilment of transport orders with defined source-sink relationships. The framework of this work is set by the development of a conceptual understanding of autonomous control and optimisation of several target figures in intralogistics. The two main target figures are costs and performance. The core idea of the system’s logic is to solve the problem of an order allocation to a specific means of transport by linking a Genetic Algorithm with a Multi-agent System. The Genetic Algorithm provides a global optimised solution to the problem, which is partially evaluated by a Multi-agent System, and then optimised based on local knowledge by monitoring and adjusting the appropriate decision variables in terms of problem-specific criteria. The developed model is based on the existing production system at the Werk 150, the factory of the ESB Business School on the Reutlingen University campus. The behaviour of the system is first examined with the help of a simulation study. The results obtained from the simulation are tested with common verification and validation techniques in production and logistics to confirm the credibility of the system. The work shows that the developed system leads to a higher logistical target achievement than conventional central planning and control concepts.en_ZA
dc.description.abstractAFRIKAANSE OPSOMMING: Vinnig veranderende marktoestande en wêreldwye kompetisie lei tot hoër verwagtinge van kliënte, en dus verg meer doeltreffendheid van ondernemings. Dit, tesame met die toenemende kompleksiteit van logistieke stelsels, verg innoverende benaderings rakende die organisering en beheer van hierdie logistieke stelsels. In wetenskaplike navorsing word konsepte getoon van outonome beheerde logistieke stelsels met 'n belowende benadering om aan die toenemende vereistes vir buigsame en doeltreffende bestelling verwerking te voldoen. Die doel van hierdie werk is om 'n stelsel te ontwikkel wat in staat is om bestelling verwerking dinamies aan te pas en om intra-logistiese vervoer te optimeer met betrekking tot verskillende generiese intra-logistiese teiken kriteria in 'n buigsame vloei produksie. In hierdie navorsing word ‘n logistieke stelsel oorweeg wat bestaan uit verskillende vervoermiddele vir outonome besluitneming en die uitvoering van vervoer bestellings met gedefinieerde afhaal en aflewerings verhoudinge. Die raamwerk van hierdie werk word bepaal deur die ontwikkeling van 'n konseptuele begrip van outonome beheer en die optimalisering van verskillende teiken syfers in intra-logistiek. Die twee belangrikste teiken syfers is koste en prestasie. Die kerngedagte agter die logika van die stelsel is om die probleem van 'n bestellings toewysing aan 'n spesifieke vervoermiddel op te los deur 'n genetiese algoritme met 'n “Multi-agent” stelsel te koppel. Die genetiese algoritme bied 'n wêreldwye geoptimaliseerde oplossing vir die probleem aan. Dit word gedeeltelik deur 'n “Multi-agent” stelsel geëvalueer en daarna geoptimaliseer op grond van plaaslike kennis deur die toepaslike besluitnemings veranderlikes te monitor en aan te pas in terme van probleem spesifieke kriteria. Die ontwikkelde model is gebaseer op die bestaande produksie stelsel van die Werk 150 van Reutlingen Universiteit. Die gedrag van die stelsel word eers ondersoek met behulp van ‘n gesimuleerde studie. Die resultate van die simulasie word getoets met algemene bevestiging- en validasie tegnieke in produksie en logistiek om die geloofwaardigheid van die stelsel te bevestig. Hierdie navorsing toon aan dat die ontwikkelde stelsel lei tot 'n hoër logistiese doelwitbereikings vlak teenoor huidige konvensionele sentrale beplanning en beheer konsepte.af_ZA
dc.description.versionMasters
dc.format.extentxv, 196 leaves : illustrations (some color)
dc.identifier.urihttp://hdl.handle.net/10019.1/107998
dc.language.isoenen_ZA
dc.publisherStellenbosch : Stellenbosch Universityen_ZA
dc.rights.holderStellenbosch Universityen_ZA
dc.subjectAutonomous control systemen_ZA
dc.subjectIntralogisticsen_ZA
dc.subjectTransportationen_ZA
dc.subjectUCTDen_ZA
dc.subjectIndustrial procurement -- Technological innovationsen_ZA
dc.subjectBusiness logisticsen_ZA
dc.titleDevelopment of an autonomous control system for target-optimised use of intralogistics means of transport in a production system for individualised productsen_ZA
dc.typeThesisen_ZA
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
grosseerdmann_autonomous_2020.pdf
Size:
15.36 MB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Plain Text
Description: