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Time-driven activity-based costing related to digital twinning in additive manufacturing

dc.contributor.authorAnderson, Anje Marjorieen_ZA
dc.contributor.authorVan der Merwe, Andreen_ZA
dc.date.accessioned2021-06-01T11:56:59Z
dc.date.available2021-06-01T11:56:59Z
dc.date.issued2021-05
dc.identifier.citationAnderson, A. M. & Van Der Merwe, A. 2021. Time-driven activity-based costing related to digital twinning in additive manufacturing. South African Journal of Industrial Engineering, 32(1):37-43, doi:10.7166/32-1-2271
dc.identifier.issn2224-7890 (online)
dc.identifier.issn1012-277X (print)
dc.identifier.otherdoi:10.7166/32-1-2271
dc.identifier.urihttp://hdl.handle.net/10019.1/110527
dc.descriptionCITATION: Anderson, A. M. & Van Der Merwe, A. 2021. Time-driven activity-based costing related to digital twinning in additive manufacturing. South African Journal of Industrial Engineering, 32(1):37-43, doi:10.7166/32-1-2271.
dc.descriptionThe original publication is available at http://sajie.journals.ac.za
dc.description.abstractENGLISH ABSTRACT: Many businesses in the additive manufacturing industry have limited equipment capacity. This method of using time-driven activity-based costing in collaboration with digital twinning will be advantageous to optimise their use of time and their capacity. Optimising the use of time is essential to ensure efficient process flow and to waste less time and money. To optimise, we need to analyse system dynamics and model system responses, to enable us to consider various scenarios iteratively. This paper first considers activity-based costing, driven by its most precious resource, time. Standard time is defined as the base parameter by which cost is calculated. Charge-out rates of elements are based on the actual cost of equipment apportioned to activities, based on the time spent using such equipment. The process chain is broken into elements, each of which incurs full cost when started. The value chain develops accordingly, enabling us to predict the actual cost of production. Second, the use of digital twinning to model standard time is considered. Stochastic variation is evident, but standard time can be allocated to each element in the process chain, given a certain confidence level. Together, a cause—effect prediction model can be developed. The model would predict the time that a process chain, consisting of known elements, would take. However, in the event of an occurrence out of the norm, the updated expected time can be predicted. Using the same rates, the new cost can be determined immediately. We propose that the digital twin can predict production cost, based on a statistically measurable stochastic variation of element duration and the time-varying charge-out rate.en_ZA
dc.description.abstractAFRIKAANSE OPSOMMING: Talle besighede in die toevoegingsvervaardiging bedryf het beperkte toerustingskapasiteit. In hierdie artikelword daar eerstens gekyk na aktiwiteitsgebaseerdekoste, met die hoof fokus op tyd. Tweedens word die gebruik van ʼn digitale tweeling oorweeg om standaardtyd te modelleer. Die model voorspel die tyd wat ʼn prosesketting, bestaande uit bekende elemente,salneem. In die geval van ʼn abnormale voorval, kan die opgedateerde verwagte tyd ookvoorspel word. Met dieselfde tariewe kan die koste onmiddellik bepaal word. Die artikel stel voor dat die digitale tweeling die produksiekoste kan voorspel, gebaseer op staties meetbare stogastiese variasie van die duur van die element, en die tydsveranderende heffingstariefaf_ZA
dc.description.urihttp://sajie.journals.ac.za/pub/article/view/2271
dc.format.extent7 pagesen_ZA
dc.language.isoen_ZAen_ZA
dc.publisherSouthern African Institute for Industrial Engineeringen_ZA
dc.subjectAdditive manufacturingen_ZA
dc.subjectDigital twinningen_ZA
dc.subjectActivity-based costingen_ZA
dc.titleTime-driven activity-based costing related to digital twinning in additive manufacturingen_ZA
dc.typeArticleen_ZA
dc.description.versionPublisher's version
dc.rights.holderAuthors retain copyrighten_ZA


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