Abstract
CITATION: Coetzer, E. O. & Vlok, P. J. 2019. A standardised model to quantify the financial impact of poor engineering information quality in the oil and gas industry. South African Journal of Industrial Engineering, 30(4):131-142, doi:10.7166/30-4-2080.
Highlights
Industrial assets rely on engineering information to run safely and to be environmentally responsible and profitable
If a defensible business case could be made, it would enable managers to weigh the benefits of a quality improvement investment against other opportunities
This paper reports on a research project to develop a defensible model to quantify the financial effects of poor engineering information quality, deconstructed into the classifications that follow from the research design
Summary
But digital formats increase the risk of lost data quality, implying huge risk. The elements are productivity and production loss, and increased cost and risk. A Monte Carlo method was field tested. The results were presented in graphical and Pareto form to facilitate funding and prioritisation. Die energie-industrie benodig hoë gehalte data, maar digitale formate verhoog die moontlikheid van gehalteverlies, wat groot risiko tot gevolg mag hê. Die voordele van data gehalte is moeilik berekenbaar en dus so ook die regverdiging van uitgawes verbonde aan verbeteringsprojekte. Die elemente is verlies aan produksie en produktiwiteit en verhoogde koste en risiko. ʼn Monte-Carlo simulasiemodel is gebou en getoets. Die resultate is grafies en in Pareto-formaat aangebied om befondsing en prioritisering te vergemaklik. Die resultate bewys dat die kostes noemenswaardig is. Geleenthede bestaan vir meer gesofistikeerde modelle enn ondersoek na die oorsake moet van stapel gestuur word
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