Automated sorting systems specialist TOMRA Mining has published a new e-book to help mines enhance efficiencies and profitability by using information gathered by sorting machines.

The “easy-to-read”, 21-page booklet, titled ‘When Sorters Become Data Generating Machines’, explains how businesses can “connect to possibilities” with the TOMRA Insight data platform, and the competitive advantages this gives.
 
The e-book begins by reminding readers that sensors in sorting machines can do more than identify whether products or materials on a line should be accepted or rejected.

As the book says: “They collect and store every piece of information about what they see. And this information can tell you a lot about how your machine is performing, about the products that pass through it, and your process.”

The e-book makes the encouraging point that turning TOMRA’s sorters into connected devices is not difficult, and businesses can benefit from digital sorting data with minimal impact – elaborating that businesses need wiring and a stable Internet connection to do so.

The data solution’s software stores and processes the data coming from sorters and presents this in near real time in a dashboard-style monitoring and reporting system. This is compatible with supervisory control and data acquisition (Scada) systems –  but whereas Scada controls the process and visualises related alarms, performances and control parameters, the digital sorting dashboard enables advanced analytics based on much larger data sets and time series.

Two types of data can be generated by sorters, namely Data at Rest and Data in Motion.

Data at Rest contains non-real-time information about machines, such as service reports, spare parts history, and manuals. Data in Motion contains a continuous flow of dynamic data originating from the sorting activity, including alarms, sorting throughput and statistics. Data in Motion can become a powerful reporting and decision-making tool for businesses.

The e-book identifies four categories of process data, namely feed composition statistics, material distribution statistics, sorting statistics and machine health data.

Feed composition statistics visualise what the machine sees, giving a good view of the nature and quality of the products or materials in the infeed stream. Material distribution statistics visualise the distribution of material on the machine over time, monitoring whether machines and processes are running optimally.

Sorting statistics visualise the sorting fractions, serving as a powerful tool for quality management and helping to match product characteristics to customer requirements. Lastly, machine health data provides information about the machine’s operational status and condition, preventing unnecessary downtime.

This deep mine of information is accessible and actionable through TOMRA Insight, the cloud-based data platform available to TOMRA machine users as a subscription-based service. The e-book explains how digital sorting data gathered by TOMRA Insight is secure – and how, by putting this data to good use, sorting can be transformed from an operational process into a valuable strategic management tool.

Click here to download TOMRA Insight's Mining Ebook "When Sorters Become Data Generating Machines".