Thesis (PhD)--University of Stellenbosch, 2004. / ENGLISH ABSTRACT: The importance of waste management is growing rapidly for several reasons. These
reasons include the escalating cost of wastewater treatment and cleaning chemicals, an
emerging trend of onerous regulatory regime regarding e uent disposal from governments,
rising public awareness on the adverse e ects of industrial waste as well as drastic reduc-
tion in water resources in the winegrowing regions. In addition, owing to the large energy
demand for refrigeration purposes for high quality wine production and rapidly increasing
energy costs, the challenges of energy management in the wine industry were also inves-
tigated.
In order to address these challenges adequately, the solutions were derived via the
integration of two disciplines: environmental science (waste and energy management)
and computer science (applications of arti cial intelligence). Therefore, the ndings re-
ported from this study seek to advance knowledge through the construction of decision
support systems for waste and energy management in circumstances where conventional
mathematical formalisms are inadequate. In that sense, the dissertation constitutes in-
terdisciplinary research on the application of integrated arti cial intelligence technologies
(expert systems and fuzzy logic) in designing and developing decision tools for waste and
energy management in the wine industry.
The dissertation rst presents the domain of interest, where the scope and breadth of
the problems it addresses are clearly de ned. Critical examination of the domain data-
bases revealed that data, information, and knowledge for waste and energy management
in the wine industry are generally incomplete and lack structure overall. Owing to these
characteristics, a hybrid system approach was proposed for the development of decision
support systems based on fuzzy logic. The integrated decision support systems were de-
veloped based on an object-oriented architecture. This approach facilitated the
exible
design required for waste and energy management-related complex problem-solving.
To illustrate the applicability of the o -line decision tools developed, several case stud-
ies mirroring on actual industrial practices were considered. These systems were found to
be robust and yielded results that were in accordance with actual industrial practices inthe wine industry. Furthermore, they provided intelligent suggestions in scenarios where
there was minimal information, and under certain instances they o ered feasible sugges-
tions in circumstances where a human novice could have problems in making the right
decisions. / AFRIKAANSE OPSOMMING: Die belangrikheid van afvalbestuur neem om verskeie redes vinnig toe. Die redes sluit
in die eskalerende koste van afvalwaterbehandeling en skoonmaakmiddels, streng regula-
toriese vereistes van regeringskant met betrekking tot die verwydering van uitvloeisels,
toenemende openbare bewustheid van die nadelinge e ekte van nywerheidsafval, sowel
as die drastiese afname in waterbronne in wynproduserende omgewings. Daarby, a.g.v.
die groot energieverbruik wat deur die verkoeling van hokwaliteitwyn vereis word en die
snelgroeiende energiekoste, is die uitdagings van energiebestuur in die wynbedryf ook on-
dersoek.
Ten einde die uitdagings die hoof te kon bied, is oplossings gevind deur die integrasie
van twee disciplines: omgewingswetenskap (afval- en energiebestuur) en rekenaarweten-
skap (toepassings van kunsmatige intelligensie). Gevolglik is daar deur die bevindinge
van die studie gepoog om kennis te bevorder deur die konstruksie van besluitnemingson-
dersteuningstelsels vir afval- en energiebestuur onder omstandighede waar konvensionele
wiskundige algoritmes ontoereikend sou wees. In die opsig verteenwoordig die proefskrif
interdissiplinre navorsing in die toepassing van gentegreerde kunsmatige intelligensieteg-
nologie (kundige stelsels en wasige logika) in die ontwerp en ontwikkeling van besluitne-
mingshulpmiddels vir afval- en energiebestuur in die wynindustrie.
Die proefskrif baken eers die probleemgebied af, waarna die bestek en omvang van die
probleme waarop die werk gemik is duidelik gede nieer word. Kritiese ondersoek van
die databasisse in die domein het getoon dat die data, informasie en kennis oor afval- en
energiebestuur in die wynbedryf in die algemeen onvolledig en gebrekkig gestruktureer is.
A.g.v. di eienskappe, is 'n hibriede stelselbeandering voorgestel vir die ontwikkeling van
besluitnemingstelsels gegrond op wasige logika. Die gentegreerde besluitnemingsonders-
teuningstelsels is ontwikkel op 'n objek-georinteerde argitektuur. Die benadering het die
daarstelling van 'n buigsame ontwerp wat benodig word vir komplekse probleemoplossing
in afval- en energiebestuur vergemaklik.
Om die toepaslikheid van die a
ynige besluitnemingshulpmiddels wat ontwerp is, te
illustreer, is verskeie gevallestudies wat werklike industrile praktyk uitbeeld beskou. Diestelsels was robuust en het resultate gelewer wat in ooreenstemming was met werklike
industrile praktyke in die wynnywerheid. Die kundige stelsels het verder intelligente
voorstelle gemaak in scenarios waar daar minimale informasie beskikbaar was, en onder
sekere omstandighede het hulle realistiese oplossings voorgestel waar 'n onkundige persoon
probleme sou gehad he tom die regte besluite te kon neem.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/16067 |
| Date | 12 1900 |
| Creators | Musee, Ndeke |
| Contributors | Lorenzen, L., Aldrich, C., University of Stellenbosch. Faculty of Engineering. Dept. of Process Engineering. |
| Publisher | Stellenbosch : University of Stellenbosch |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | Unknown |
| Type | Thesis |
| Format | xxii, 270 leaves : ill. |
| Rights | University of Stellenbosch |
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