The increased adoption of unmanned aerial vehicles (UAVs) may improve the productivity and cost-effectiveness of remote sensing in the mining industry. This review's objective is to enable stakeholders to identify possible application adoption, improvement, and innovation opportunities. The review merges a building block strategy and practical screening criteria to identify possible avenues of research to answer the review questions. After the screening process, 72 documents were included in the review. Papers were classified into four categories: exploration, development, exploitation, and reclamation. Fifteen applications were identified, the majority of which were in the exploration phase. The most often researched applications were topographic surveys, reclamation monitoring, and slope management. From the two UAV types identified, multi-rotor vehicles were the most favoured for all applications. From the eight remote sensing techniques identified, photogrammetry was the one most often used. Other techniques were limited because of complexity, cost, or the incompatibility of sensors and UAVs. The review was limited to published papers in academic journals. Future studies could aim to include empirical data on the latest UAV applications used in the mining industry.

Asset and maintenance managers are often confronted with difficult decisions related to asset replacement or repair. Various analytical models, such as decision analysis and simulation, can assist a manager in making better decisions. This paper proposes that by combining renewal theory with decision analysis methods, the expected value (EV) of information for non-repairable components can be calculated. Subsequently, it is proposed that this method can be used to determine the expected replacement cost per unit time of predictive maintenance. It is argued that this predicted cost will give the maintenance decision-maker the ability to compare it to the cost of alternative maintenance strategies when choosing between strategies. Although this paper is limited to non-repairable components, the theory and methodology can also be applied to repairable systems. OPSOMMINGBate-en instandhoudingsbestuurders word dikwels gekonfronteer met moeilike besluite rakende die vervanging of herstel van fisiese bates. Verskeie analitiese modelle, soos besluitsanalise en simulasie, kan die bestuurder help om beter besluite te neem. Hierdie artikel stel voor dat deur hernubare teorieë te kombineer met besluitnemingsmetodes, die verwagte waarde van inligting vir nie-herstelbare komponente bereken kan word. Gevolglik word dit voorgestel dat hierdie metode gebruik kan word om die verwagte koste per tyd eenheid van voorspelbare instandhouding te bereken. Daar word geargumenteer dat hierdie beraamde koste die instandhoudings-besluitnemer die vermoë sal gee om die koste van verskeie instandhoudingstrategieë te vergelyk wanneer daar gekies word tussen strategieë. Hierdie artikel sal beperk word tot nie-herstelbare komponente, maar deur soortgelyke prosesse te volg, kan die teorie uitgebrei word na herstelbare stelsels.

There are many factors to be considered in risk management that influence the effective control of risk either beneficially or detrimentally. An improvement in the quality of risk analysis will enable risk managers and decision-makers to make more accurate decisions that would benefit all stakeholders. The aim of this research was to determine the effectiveness of the most commonly employed risk analysis methods. Two decision problems and two hypothetical risk analysis problems were presented to groups of respondents who were asked to choose a correct answer from the given options. The results showed no significant association between a person's age or experience and their choice or decision about risk management. The only association was found between a higher level of professional qualification and the correct choice, when a decision problem was given without providing a decision tree. OPSOMMINGVerskeie faktore moet in ag geneem word in risikobestuur wat die effektiewe beheer van risikos voordelig of nadelig beïnvloed. 'n Verbetering in die kwaliteit van risiko analise kan risikobestuurders en besluitnemers help om meer akkurate besluite te neem tot voordeel van alle belanghebbers. Die doel van hierdie studie was om die effektiwiteit van die mees algemene risiko bepaling metodes te evalueer. Twee besluitnemingsprobleme en twee risiko-analise probleme is vir groepe respondente voorgehou, en respondente is versoek om 'n korrekte keuse te maak uit 'n lys moontlike oplossings. Die resultate toon dat ouderdom of ervaring nie 'n betekenisvolle invloed op 'n effektiewe besluit of keuse met betrekking tot risikobestuur het nie. 'n Betekenisvolle assosiasie is wel waargeneem tussen 'n hoër vlak van professionele kwalifikasie en die korrekte keuse, wanneer 'n besluitnemingsprobleem sonder dat 'n besluitboom verskaf is.

Heritage buildings have evolved into development catalysts that, when properly maintained, can improve their surrounding area’s liveability while sustaining productivity in an ever-changing global context. Unfortunately, the high uncertainty involved in preserving heritage buildings frequently leads to over-budget projects. This article evaluates the factors that contribute to projects being over budget and the methods used to develop project budgets. History-based budgeting methods, value-oriented budgeting methods, analytical budgeting methods, and budgeting by condition description are frequently used, while new artificial intelligence models are also emerging. In addition, the review considers the Monte Carlo method and compares it with artificial intelligence models. Considering the high uncertainty involved when maintaining heritage buildings, it is concluded that the Monte Carlo method could be a very effective tool. For this reason, it is recommended that its use be tested on heritage building projects. Keywords heritage buildings; budget; maintenance; conservation projects; Monte Carlo simulation

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