A data and modelling framework for strategic supply chain decision-making in the petro-chemical industry.

Van Schalkwyk, Willem Tobias (2006-12)

Thesis (MScEng)--Stellenbosch University, 2006.

Thesis

ENGLISH ABSTRACT: The research was initiated by an opportunity within the petro-chemical company Sasol to explore, improve and integrate various analytical techniques used in the modelling, design and optimisation of supply chains. Although there is already a strong focus on the use of analytical applications in this environment, the lack of both modelling integration and analytical data availability has led to less than optimal results. This document presents an exploration into the supply chain planning landscape, and in particular strategic planning in the petro-chemical environment. Various modelling methodologies and techniques that support strategic supply chain decision-making are identified, followed by an in-depth analysis of the data requirements for effectively constructing each of these models. Perhaps the biggest hurdle in the continual use of modelling techniques that support strategic supply chain decision-making, remains the extent of the data gathering phase in any such project. Supply chain models are usually developed on an ad hoc project basis, each time requiring extensive data gathering and analysis from transactional data systems. The reason for this is twofold: 1) transactional data are not configured to meet the analytical data requirements of supply chain models, and 2) projects are often done in isolation, resulting in supply chain data that end up in spreadsheets and point solutions. This research proposes an integrated data and modelling framework, that aspires to the sustainable use of supply chain data, and continual use of modelling techniques to support strategic supply chain decision-making. The intent of the framework is twofold: 1) to enable the design of new supply chains, and 2) to ensure a structured approach for capturing historical supply chain activities for continued review and optimisation. At the heart of the framework is the supply chain analytical data repository (SCADR), a database that maintains supply chain structural and managerial information in a controlled data model. The motivation behind developing a database structure for storing supply chain data is that a standard encoding method encourages data sharing among different modelling applications and analysts. In the globalised environment of the 21•t century, companies can no longer ensure its market position solely by its own functional excellence ... in the new economy, whole business ecosystems compete against each other for global survival (Moore, 1996). This motivates the ever-increasing importance of supply chain management, which necessitates the use of advanced analytical tools to assist business leaders in making ever more complex supply chain decisions. It is believed that the integration of information requirements for multiple optimisation/ modelling initiatives in a structured framework (as presented in this research) will enable sustainability and improved strategic decision-making for the petro-chemical supply chain.

AFRIKAANSE OPSOMMING: Hierdie navorsing het ontstaan uit die geleentheid binne die petro-chemiese maatskappy Sasol, om die gebruik van verskeie analitiese tegnieke in die modellering, ontwerp en optimisering van voorsienings-kettings te ondersoek, te verbeter en te integreer. Alhoewel daar reeds 'n sterk fokus is op die gebruik van analitiese toepassings in hierdie omgewing, lei die gebrek aan modellerings integrasie en die onbeskikbaarheid van analitiese data, tot sub-optimale resultate. Hierdie dokument ondersoek die geleenthede en uitdagings van beplanning in voorsienings-ketting bestuur, en fokus spesifiek op strategiese beplanning in die petrochemiese omgewing. Verskeie modellerings metodologiee en tegnieke word ondersoek, gevolg deur 'n in-diepte analise van die data behoeftes vir effektiewe gebruik van elk van hierdie modelle. Moontlik die grootste uitdaging vir die volhoubare gebruik van modellerings tegnieke om strategiese voorsienings-ketting besluitneming te ondersteun, is die omvang van die data versameling fase in enige s6 projek. V oorsienings-ketting modelle word gewoonlik op 'n ad hoc projek basis ontwikkel, wat telkens 'n intensiewe data versameling en analise van transaksionele stelsels vereis. Die rede hiervoor is tweevoudig: 1) transaksionele stelsels word nie gekonfigureer om die analitiese data behoeftes van voorsienings-ketting modelle aan te spreek nie, en 2) projekte word dikwels in isolasie gedoen, wat tot gevolg het dat voorsienings-ketting inligting in sprei-bladsye en punt oplossings verlore raak. Hierdie navorsing stel 'n gemtegreerde data en modellerings raamwerk voor, wat streef na die volhoubare gebruik van voorsienings-ketting inligting, en die volgehoue toepassing van modellerings tegnieke om strategiese besluitneming te ondersteun. Die bedoeling is tweeledig: 1) om die ontwerp van nuwe voorsienings-kettings moontlik te maak, en 2) om 'n gestruktureerde manier daar te stel vir die stoor van historiese voorsienings-ketting aktiwiteite, wat gebruik kan word vir voortdurende hersiening en optimering. In die hart van die raamwerk le die voorsienings-ketting analitiese databasis (SCADR), 'n databasis wat strukturele- en bestuurs- inliging van die maatskappy se voorsieningskettings bevat in 'n gekontroleerde data model. Die motivering vir die ontwerp van hierdie databasis struktuur is dat 'n standaard manier van data enkodering die deel van data tussen verskillende modellerings toepassings en analiste aanmoedig. In die era van globalisering waarin ons tans leef, kan maatskappye nie meer hul mark posisie verseker deur slegs op hul eie funksionele uitnemendheid staat te maak nie ... in die nuwe ekonomie gaan besigheids-ekosisteme met mekaar meeding vir globale oorlewing (Moore, 19%). Dit motiveer die belangrikheid van voorsienings-ketting bestuur, wat die gebruik van gevorderde analitiese- en modellerings tegnieke impliseer. Die voordeel wat hierdie tegnieke bied is dat dit besigheidsleiers help om steeds meer komplekse voorsienings-ketting besluite te neem. Die student glo dat die integrasie van inligtings behoeftes vir verskeie optimiserings / modellerings inisiatiewe, in 'n gestruktureerde raamwerk soos aangebied in hierdie navorsing, volhoubaarheid en verbeterde strategiese besluitneming in die petro-chemiese voorsienings-ketting sal verseker.

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