What if your mine could raise productivity and optimize its processes by analysing data from every aspect of the mine site?
THERE is a crucial need across the global mining industry to substantially increase efficiency and raise productivity. Mining productivity has declined by as much as 28% in the past 10 years (McKinsey) and while the decline is beginning to slow, innovations and intuitive solutions must be found to return the industry to its peak.
Pitram’s Cycle Optimization functionality, used to manage truck-loader allocations in the shift.
Mine control is a complex interaction between people, material, equipment and infrastructure. Inefficiencies can be a result of a plethora of factors, from mismanagement of a heading blast, to network failure or human error. It is crucial to collect and analyse shift and operational data from all elements of the mine site - from truck payloads and maintenance, to geology and human resources. Analysis and reporting of this data provides the opportunity to identify the specific trends requiring adjustment.
McKinsey & Company recently created a new metric (MineLens Productivity Index) to measure a mine’s productivity. On the results of the metric, McKinsey stated: “…mining companies should use advanced analytics to harness the potential of the vast amounts of data generated in typical modern mining operations in order to boost productivity-improvement initiatives.”
When operational trends have been identified, these elements should be tweaked to increase productivity and optimize mining performance. Data analysis software packages such as MICROMINE’s Pitram provide the opportunity to find and act on trends and inefficiencies in the entire mining process. Pitram collects essential mining data in a centralized database using a variety of data collection methods, such as data logs, payload monitors and tagging systems.
With a centralized reporting source, Pitram analyses and displays data in the form of reports, dashboards, and graphs. The reporting choices are vast - over the past 25 years, MICROMINE has developed countless reporting templates for grade control, material movements and measures, maintenance, SMUs, budgets and more.
The possibilities for data extraction are extensive - data can be collected from equipment, maintenance personnel, human resources, geological findings and more. Pitram’s RESTful Integration Services (PRIS) uses Hypertext Transfer Protocol (HTTP) to collect data from (and provide data to) third parties such as weighbridge systems and underground positioning. While many data analysis packages are limited in data collection methods or sources, Pitram can be configured depending on the size, technological maturity and budget of the minesite.
MICROMINE’s chief operations officer Michael Layng says Pitram has been designed to take into consideration all angles of the mining process in order to provide a true picture of productivity and state. “The power and flexibility of Pitram’s data collection means that progress of all activities can be taken into account in the optimization, not just those related to equipment units or equipment fitted with network capabilities.”
An example of this is the analysis of time to operating; specifically first and last dumps. By analysing the progress of truck movements, a mine site is able to make better decisions in allocating trucks at the end of the shift. In order to increase production, trucks can be allocated efficiently and avoid parking up early due to lack of time in the final truck cycle. The mine can also improve shift start and re-entry procedures to reduce the time between the start of the shift, and equipment commencing operation, including the first load.
“Pitram records each discrete activity that occurs in the advance of a development heading. Not only can the total time to advance be reported, but the performance of each activity, equipment unit and person involved. Activities falling outside of acceptable parameters can be analysed and steps taken to improve the process,” Michael Layng says.
Pitram in the Asia Pacific
Newcrest is deploying Pitram Shift Planner at Gosowong mine in Indonesia. It is utilizing Pitram to facilitate production activities and the in-shift, short-interval-control management of development.
Pitram’s Shift Planner application is used to organize and monitor mining tasks. Mine controllers are able to track and delegate equipment, personnel, consumables and locations. When efficiency and productivity trends are identified during data analysis, the Shift Planner application enables mine managers to adjust the activity parameters of future shifts.
The way forward in the mining industry’s turnaround is to embrace innovative and proven approaches to the mining process. While the global decrease in productivity is alarming, it can be countered by increased consciousness and rapid response to inefficiencies.
Practical data capture and analysis software such as MICROMINE’s Pitram provide mine sites with the potential to not only respond to real-time inefficiencies but to discover trends in collected data that have the potential to maximize productivity and optimize the entire mining process.
Reference: McKinsey & Company, ‘Productivity in mining operations: Reversing the downward trend’