Industry 4.0 roll-out strategy for dynamic mine heat load management

Deep-level mining is under severe financial pressure from several unique challenges. One of these is maintaining acceptable underground temperatures for humans to work in while achieving demanding production targets. As mines regularly reach new depths, additional heat is added to the system, contributing to this problem. Accurate mine heat load studies are therefore required to ensure that heat sources are actively evaluated, managed, and mitigated through adequate cooling practices. However, present heat load models are based on design parameters that cater for worst-case scenarios. Most of these models are also based on outdated empirical data taken at a time when mining differed from the present. Industry 4.0 technologies provide potential optimisation benefits when integrated with new heat load models to ensure effective monitoring, and consequently dynamic management, of heat sources. The roll-out strategy presented in this article will serve as a real alternative to earlier and outdated heat load prediction modelsDiepvlak-mynbou is onder hewige finansiële druk weens verskeie unieke uitdagings. Een van die uitdagings is die handhawing van ondergrondse temperature wat geskik is vir mense om in te werk. Soos wat myne gereeld nuwe dieptes bereik word addisionele hitte tot die stelsel toegevoeg wat die probleem vererger. Akkurate myn hittelas studies is dus nodig om te verseker dat hittebronne deurlopend evalueer, bestuur en getemper word deur voldoende verkoelingspraktyke. Bestaande hittelas modelle is egter gebaseer op ontwerpsparameters wat voorsienning maak vir ergste scenario’s. Die meeste van hierdie modelle is ook gebaseer op verouderde empiriese datastelle. Industrie 4.0 tegnologieë bied potensiële optimiseringsvoordele wanneer dit met nuwe hittelas modelle geïntegreer word en kan moontlik doeltreffende monitering, en gevolglik dinamiese bestuur, van hittebronne as gevolg hê. Die implementeringstrategie in hierdie artikel kan as ’n werklike alternatief vir vroeër, verouderde hittelasvoorspelling modelle die