Thesis (MBA)--Stellenbosch University, 2008. / ENGLISH ABSTRACT: Volkswagen of South Africa (Pty) Ltd. (VWSA) is part of the Volkswagen Group, which originated in Germany. VWSA’s production plant is situated in Uitenhage in the Eastern Cape and produces ± 100 000 cars per year with ± 5 800 employees. At the time of writing this report, VWSA had three platforms on which it produced the Citi Golf, Polo/Polo Classic and Golf 5/Jetta 5.
It takes on average four days to produce a vehicle, but up to 17 weeks lead time is required before production can start. This lead time is needed to procure, transport and receive the single parts from suppliers in South Africa, Europe and other countries. The time window required in order to manufacture a vehicle is therefore relatively long. For this reason it is important that VWSA’s production schedule is firstly planned properly and secondly optimised continuously and timely, as circumstances change and unforeseen conditions arise.
VWSA assemble vehicles “to stock” and not “to order”. This means that a production schedule is planned and executed, based on forecasted volumes and not on actual customer orders. The monthly production offline demand is received from marketing, which includes both the volume requirements for domestic and export units. Currently the production scheduling process of VWSA is performed manually in an Excel spreadsheet. This is a time consuming process that could be exposed to mistakes. Much iteration is performed manually in order to achieve the best solution.
The aim of this research report was to develop an optimisation model for production after the fixed lead time period in order to ensure finished products on time as per the local and export demand. VWSA requires a 52 week rolling production schedule, which should take all the various constraints into account. The objective of the production schedule is to determine shift patterns and production units per shift that will provide some consistency, by avoiding short time, overtime, plant closures, variations in production rates, etc. as far as possible. More importantly, the production schedule must optimise the use of resources and minimise costs.
A scheduling model was developed for each of the three model lines, making use of Mixed Integer Programming. The constraints and applicable costs were built into each individual model. Each model was solved with the use of Premium Solver Platform software, due to the fact that it has advance capabilities and includes a Nonlinear GRG Solver. Optimal solutions were found, satisfying all the various constraints, within seconds compared to the hours and days required for the current manual scheduling process.
A summary sheet was developed, combining the individual model line schedules for distribution and presentation purposes. This summarises the required production units per day, week and cumulative. In addition it includes the required export units that are first priority to be produced per week. To improve decision making, a column was included to indicate the quantity of units of each model type that must be produced during overtime. This model provides management with the information required to make decisions regarding detailed production scheduling. / AFRIKAANSE OPSOMMING: Volkswagen van Suid-Afrika (Pty) Ltd. (VWSA) is deel van die Volkswagen Groep, wat onstaan het in Duitsland. VWSA se produksie aanleg is geleë in Uitenhage in die Oos-Kaap en vervaardig ± 100 000 voertuie per jaar deur gebruik te maak van ± 5 800 werknemers. Ten tyde van die skryf van hierdie verslag het VWSA drie platforms gehad waarop dit die Citi Golf, Polo/Polo Classic en Golf 5/Jetta 5 vervaardig het.
Dit neem gemiddeld vier dae om ’n voertuig te vervaardig, maar kan tot 17 weke leityd benodig voordat produksie kan begin. Die leityd is nodig om enkel komponente van verskaffers in Suid-Afrika, Europa en ander lande te bestel, vervoer en te ontvang. Die tydperk wat benodig word om ’n voertuig te vervaardig is dus relatief lank. As gevolg van hierdie rede is dit belangrik dat VWSA se produksie skedule eerstens deeglik beplan word en tweedens aanhoudend en betyds ge-optimeer word soos omstandighede verander.
VWSA vervaardig voertuie vir voorraad en nie op bestellings nie. Dit beteken dat ’n produksieskedule beplan en uitgevoer word, gebasseer op vooruitgeskatte volumes en nie op konkrete bestellings van kliënte nie. Die maandlikse produksie aanvraag word ontvang vanaf die Bemarkings-departement en sluit beide binnelandse en uitvoer aanvraag in. Die produksie skedulering van VWSA word tans in ’n Excel sigblad verrig. Dit is ’n tydrowende proses wat blootgestel is aan moontlike foute. Baie iterasies word benodig om uiteindelik die mees gepaste oplossing te vind.
Die doel van hierdie navorsingsverslag was om ’n optimeringsmodel vir produksie na die vaste leityd tydperk te ontwikkel, met die doel om te verseker dat klaarprodukte betyds volgens die binnelandse en uitvoer aanvraag gelewer word. VWSA benodig ‘n 52 week rollende produksieskedule wat al die verskeie beperkings in ag neem. Die doel van die produksieskedule is om skofpatrone en volumes per skof te bepaal wat uiteindelik konsekwentheid verskaf deur korttyd, oortyd, aanlegsluitings, variasies in lynspoed, ens. te beperk. Meer belangrik, die produksieskedule moet die gebruik van bronne optimeer en kostes minimeer.
’n Skeduleringsmodel is ontwerp vir elkeen van die drie modellyne, deur gebruik te maak van Gemengde Heeltal Programmering. Die toepaslike beperkings en kostes is by elke individuële model ingebou. Elke model is opgelos deur gebruik te maak van “Premium Solver Platform” sagteware, as gevolg van die feit dat dit gevorderde vermoëens het asook “Nonlinear GRG Solver” insluit. Binne sekondes is optimale oplossings gevind, wat ook die beperkings bevredig, in teenstelling met die ure en dae wat benodig word vir die huidige skeduleringsproses.
‘n Opsommende blad is ontwikkel wat die individuële skedules saamvat vir verspreidings- en voordrag doeleindes. Dit bevat die beplande produksievolumes per dag, week en kumulatief. Addisioneel bevat dit ook die vereiste uitvoervolumes per week wat eerste prioriteit geniet. Om besluitneming te verbeter is ‘n kolom ingesluit wat aandui hoeveel eenhede van elke model tipe word benodig gedurende oortydproduksie. Die model verskaf aan bestuur die inligting wat benodig word om detail besluite oor produksieskedulerings te neem.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/80788 |
| Date | 12 1900 |
| Creators | Miller, Anthonette |
| Contributors | Gevers, Wim, Stellenbosch University. Faculty of Economic and Management Sciences. Graduate School of Business. |
| Publisher | Stellenbosch : Stellenbosch University |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | Unknown |
| Type | Thesis |
| Format | xiii, 93 p. : ill. |
| Rights | Stellenbosch University |
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