Mining is a mechanically intensive process with many pieces of rotating equipment. Vibration is inevitably a problem, but if it is detected and analyzed it can be used to predict impending operational issues. Mine processing equipment consists of high capital expenditure (CAPEX) and operational expenditure (OPEX) items. Tracking key process indicators (KPIs) – such as overall equipment effectiveness (OEE), equipment availability, and mean time between failure (MTBF) – empowers operators to proactively manage maintenance and sustain production levels.
Equipment such as conveyors, crushers, stacker reclaimers, shiploaders and mills are prone to failure due to vibration. At the machine automation level, it is possible to collect a huge amount of data at a high frequency to measure vibration, temperature and noise via sensors and instrumentation. The raw data itself is too excessive for transmission to the cloud due to costs and bandwidth issues. A better option is to relay this large volume of machine data to an edge controller, which can then use the raw data inputs to complete some preconfigured computations and send summarized time-series data to a supervisory system. This concentrated information is much more suitable for transmitting via low-bandwidth serial, Ethernet, cellular or other networks.
Edge controllers are a modern automation platform for enabling digital transformation and effectively applying IIoT concepts. Because mining operations are most often remotely located, any useful technologies must be suitable for these conditions and provide extensive communication options. Edge controllers are built for this rugged environment, and have the latest and most secure IT computing and networking features. Edge controllers are especially compelling for this service because they can gather and store data locally, process and analyze it, directly inform operational logic of optimal settings, and relay the most essential information to higher level systems.
The operations team, which can be located centrally or throughout the world, can apply analytics to this time-series data to establish baseline equipment profiles and assess if any part of the system is becoming mechanically compromised from a processing or hardware standpoint. With this information, the team can safely bring systems offline before an adverse breakdown occurs. This early warning system can be used in conjunction with a proactive maintenance strategy to plan shutdowns and reduce downtime. Here, the edge controller, together with embedded algorithms, will give plantwide visibility into mechanical integrity, ensuring greater OEE. For instance, a hydrocyclone is used to separate material based on size. This particle size classification is critical to the efficiency of flotation cells downstream and overall metal recovery. Roping and plugging are the most common operational issues. The former occurs when too many solids are discharged out the cyclone overflow, which looks like a rope is being discharged from the underflow. Plugging, on the other hand, is a situation where something is stuck inside processing equipment and there is no separation taking place. This is the worst-case scenario because all the material within the cyclone is sent along to flotation. If undetected for too long, plugging will require flotation cell shutdown to physically remove accumulated material. Measuring vibration of hydrocyclones is an effective way to detect the onset of roping or plugging events. Two-wired vibration sensors attached externally on each of the cyclones transmit process real-time vibrational data to an edge controller, where it can undergo local analytical processing to identify problem conditions.
How do you detect the impact of vibration in mining operations?
For more information on the use of edge technology in metals and mining, check out this Emerson White Paper.
And find out more about Emerson's industrial automation & controls solutions for the mining & metals industries here.