Learn what's new and what's news in today's digital landscape

What companies use to power their decisions, and how it can impact your business

International Mining


International mining detailed insight into Accenture’s capabilities in helping shape the future of mineral processing. The company sees the value of a connected mine in digging deep into the wealth of data available to provide integrated, end-to-end situational awareness and systemic management, and it has been one of the leading companies helping mines progress from structuring through to implementing data-led transformation with AI.



Data analytics paired with predictive maintenance can be a virtual goldmine for mining operations, with initial cost reduction and productivity gains amounting 10% to 20%. This article outlines the strategy adopted by miners such as Barrick Gold to save millions of dollars due to their newfound ability to detect and address failures early on, as well as reduce the number of failures from engine, brake or suspension by 30%.

PWE Magazine


The reliability of brake systems for key mining components is crucial to maintain peak productivity and throughput. Svendborg shares how clients can upgrade their systems to reduce the time and cost associated with on-site inspections and maintenance activities. Their solution combines IIoT and data analytics technologies to offer remote, real-time monitoring and predictive maintenance to their braking systems.



Plantservice editor shares six case studies illustrating some of the numerous ways predictive maintenance and Prescriptive maintenance are transformative. Clear benefits in preventing costly unplanned downtime and lower costs have improved financial justification and driven adoption in a wide range of industries.

Reliability Connect


A great example of one of the world’s largest gold miner integrating an asset optimization system with IIOT wireless sensors to monitor critical assets throughout their operations. The wireless Predictive Maintenance program paid for itself within six months and demonstrated increases in asset reliability, personnel efficiency and production. Discover how asset data is automatically collected and analysed with machine learning algorithms to predict equipment problems.