Predictive Maintenance: The Business Impact of IoE for Mining Companies
What if an industrial vehicle or piece of equipment could tell you to change a part or warn you before it breaks? The impact for mining and other industrial companies would be tremendous in terms of reduced downtime and maintenance costs. As I spent time with mining executives at the recent SAP Mining Forum, many interesting discussions were around the impact of the Internet of Things (IoT) in their operations. In fact, Cisco and SAP have been working on using (or ‘mining’) the wealth of data from sensors and machines in new and innovative ways.
The most immediate impact of IoT on mining is in the improvements to maintenance of mining heavy machinery and assets. Based on the many conversations I have had with industry experts, it is apparent that many in the mining industry are using a ‘break to fix’ mentality on their assets. They ‘push’ the asset to a point that it breaks. The issue here is that this approach is unpredictable and incredibly costly to the operations of the business. Waiting until a machine breaks leads to downtime which leads to lost revenue.
However, innovative companies are implementing a preventative maintenance program. They proactively use the information within their devices (PLC’s, SCADA, etc) to start to understand if and when a component may fail. An example of this is using a temperature sensor that monitors the temperature in and around a component and if it detects a sharp increase or decrease outside of a known ‘norm’ operators someone are alerted immediately so they can intercede before the device fails. This allows the mining company to have a planned downtime window, meaning (1) the downtime isn’t a surprise and (2) the impact on revenue is lessened.
With predictive maintenance, Cisco and SAP are taking existing equipment or asset servicing information and adding more information and more dependencies to make informed decisions. For example, with a proactive maintenance strategy, companies can take information such as Human Resource scheduling for technicians or mechanics then layer those with order information plans, supply chain and logistics and other maintenance information (such as parts availability) to reduce overall capital expenditures. Another benefit to proactive planning is allowing operators to be able to see 3-4 machines that are up for maintenance so they can start to plan a unified scheduled downtime to fix all the machines at once. As a result, mining companies can be more strategic in scheduling and plan to do maintenance, after completing an order for a key customer that has to ship on time. Take a look at additional mining use cases here:
At the Internet of Things World Forum (IoTWF) in Chicago, one of our large mining customers, Rio Tinto and their Head of Innovation, John McGagh described their journey of going from little visibility into their machines’ maintenance needs to enhanced controls in their operations. The crowd was wowed with the capabilities that Rio Tinto has implemented, including improved monitoring and controls (over 200 sensors on a typical truck for example) through their ‘Mine of the Future’ project.