Additive manufacturing costing parameter sensitivity

Date
2019-12
Journal Title
Journal ISSN
Volume Title
Publisher
Stellenbosch : Stellenbosch University
Abstract
ENGLISH ABSTRACT: Additive manufacturing (AM) offers a perfect solution for the development and manufacturing of many products, but the burning issue is to determine which products should be manufactured in such a way? Also, of extreme importance, is to understand the economy of scale for the use of AM competitively. The latter requires knowledge-based decision-making systems based on product geometry, complexity, size, tolerance, material requirements, and mechanical properties, parallel with AM machine or process capabilities. Although directly involved in the material research and platform development from the onset, the Massachusetts Institute of Technology (MIT) classified AM as only one of ten breakthrough technologies in 2013. Forbes depicts AM as the technology that will equip manufacturers with the ability to turn product development into their competitive advantage. With the advancement in computer and software capabilities, it will rapidly dominate 40% of the market share (Gartner 2015). Capability alone will not suffice, however. To increase market share, focus should be placed on the analysis of AM costing. The thesis aims to determine if a more simplistic but accurate cost determination method can be developed to augment online costing opportunities that are fully integrated with the Enterprise Resource Planning (ERP) system. Costing is one of the critical business functions of any advanced manufacturing operation. This critical business function is also known as enterprise resource planning application components. Examples of these are aspects that allow an AM unit to use a system of integrated applications to manage the business and automate various back-office functions related to technology. It also allows for services and human resources to develop the data capturing, manipulations, calculation, and validation for a unique enterprise resource-planning model that is founded in a fail-safe quality management system (QMS).
AFRIKAANSE OPSOMMING: Laagvervaardiging (LV) beklee tans ʼn unieke posisie. Die vraag wat indringend beantwoord moet word, is of produkte en komponente op hierdie metode vervaardig behoort te word? Alhoewel die Massachusetts Institute of Technology (MIT) van meet af direk by die wesenlike navorsing en platformontwikkeling betrokke was, klassifiseer die Massachusetts Institute of Technology (MIT) LV in 2013 as een van slegs tien deurbraak-tegnologieë. Forbes beeld LV uit as dié tegnologie wat vervaardigers met die vermoë sal toerus om produkontwikkeling tot ʼn mededingende voordeel te vernuwe. Vooruitgang in rekenaartegnologie, rekenaarvaardigheid en die vermoë van ondersteuningsagteware, sal verseker dat LV in die nabye toekoms 40% van die vervaardigingsmarkaandeel kan oorneem (Gartner, 2015). Dit is dus nodig dat behoorlike fokus op die ontleding van LV-kostes geplaas word. Die doel van die tesis is om te bepaal of ʼn vereenvoudigde maar akkurate kostebepalingsmetode ontwikkel kan word om aanlynkoste-geleenthede ten volle met die ondernemingsstelsel te integreer. As deel van die sake-prosesbestuursaspekte, is LV-kostes een van die kritieke besigheidsfunksies van enige gevorderde vervaardigingsonderneming. Hierdie kritieke besigheidsfunksie staan ook as die ondernemingshulpbron-beplanning-toepassing-komponent bekend. Voorbeelde hiervan is aspekte wat 'n LV-eenheid toelaat om 'n stelsel van geïntegreerde toepassings te gebruik om die besigheid en verskeie steundienstefunksies verwant aan die tegnologie te outomatiseer en te bestuur. Dit stel ook dienste en menslike hulpbronne in staat om die data-vaslegging, -manipulasies, -berekening en -validering vir 'n unieke onderneming-hulpbronbeplanningsmodel wat in 'n onfeilbare gehaltebestuurstelsel gevestig is, te ontwikkel.
Description
Thesis (MEng)--Stellenbosch University, 2019.
Keywords
Automatic control, UCTD, Additives -- Manufacturing, Geometry, Enterprise Resource Planning, Decision making -- Systems
Citation