Our client had a high throughput plant with significant subject matter expertise constraints on site. They were focused on identifying productivity improvement opportunities with low or zero implementation costs.
Engaging Interlate for a value assessment, advanced analytics of 12 months of historical data from across the whole value chain was performed. Site machine learning, subject matter expertise and unique licensed technology were leveraged. Combing a value assessment with services provided by our data visualisation consultants, enabled the creation of simple visual tools for site operators and processing engineers to use to improve yield under a wide variety of circumstances. This value assessment is conducted over an intensive time period and recommendations provided within a 4-6 week period. In addition, online decision support is provided to assist site team to implement and verify improvements.
Whole plant was analysed and focus areas were prioritised based on value improvement potential and being practical (both implementable and sustainable). Analyses highlighted advanced analytical capability providing significant productivity improvement. An additional ~290kT p.a. of in-specification coal product over the data set that is not discernible using conventional data analysis methods was dientified and an additional ~7% production for Operations. Product yield improvement of $30M annualised per annum were identified.