Quoted fromMiningGlobal, speak with Ashley Bosworth, Director of Analytics andInnovation at Pulse Mining on the year ahead for the mining industry:
What do youthink will be the biggest change in the mining industry in 2017?
With expandingproduction of certain major commodities over the past decade, and a collapse inmining profitability over the past three years, areas such as efficiency andproductivity are now considered a major priority. This means more concentrationon the impact of decisions and more use of data across the production cycle.
In mining,data-driven decisions reach all areas under management: from invested capital,equipment and materials, to labour, the production processes for operating themine, and the spending on goods and services.
What do you seehappening in the Internet of Things, and how will this affect the miningsector?
The miningsector has already used sensors on devices and assets to provide updates onstatus. The opportunity here is to bring this data into a wider context. TheInternet of Things pushes this concept further, providing more insight into howthose devices perform over time. This can then be used for predictivemaintenance and to reduce problems like downtime.
For example,companies like Pulse Mining create applications that target specific miningpain points based on Birst. Using data from 300 sensors that capture andtransmit information every second, this application helps monitor mineoperations in real-time, enabling firms to drive millions worth of additionalproduction. In one instance, there has seen a 3.2 percent increase in operatingrate and an increase from $2.5 million to $3 million per year in the value oftonnes produced.
What role willanalytics play in companies during 2017?
Looking at theErnst and Young report on the mining sector for 2016-2017, cash optimization,capital access, and productivity are the most important areas for companiesglobally.
Linking up datafrom finance, with the production and operations departments will therefore beimportant to boost operational cash flow for long-term profitability. Thisincludes using data to identify areas of cost reduction such as supplierconsolidation across different regions or countries. The same goes for usingdata to increase the life of working capital. Predictive maintenance canidentify the lifetime and sustainability of assets and move companies towardsreplacing their equipment on a need-base instead of a calendar-base routine, extractingmore value from existing assets to present opportunities of savings.
To make thishappen, mining companies will have to network their different teams ofoperations, finance, repair, production, and supply chain together to promoteinformation sharing and impact analysis.
Will moreemployees in the mining sector start using data in their daily lives?
I think so. Whenmargins are tight, it’s more important that each decision made is based onrelative data. Providing more context around the decision is a good first step,followed by greater decision support and automation of recommendations based ondata.
Additionally,the use of analytics supports companies where there has been a loss ofexperience out of the industry. Many experienced professionals have retired,and their knowledge has gone with them. While they might have naturallyunderstood the best approaches to a particular environment, their successorsdon’t have those nuances. Using data analytics, that expertise and productionefficiency can be embedded into everyday processes for the business to benefitfrom.
How close to the“coal face” will data get, and how much difference will it make to day-to-dayactivities?
Pretty close. Wehave seen this uptake with leading mining companies. Analytics for the miningindustry has potential that is already being realised in other market sectors.The efficiency of resources, staffing, time, material and production processescan have a direct impact on profitability. Using big data, and networkedanalytics, it’s possible to make decisions that lead to higher profitabilityand better business performance.