Effective management of mining assets is critical for long term success. Today’s mining industry demands better strategies and tools to overcome maintenance challenges. AMT4SAP is designed to complement a miner’s existing SAP solution. It provides enhanced maintenance cost budgeting and life cycle decision support with logical business connections to SAP.
Providing powerful forecasting - in real time.
Create and analyse multiple scenarios, forecasts and budgets utilising historical, real-time and forecast data.
Optimise upcoming activities to understand the impact on inventory, labour, availability and cost without the need for work orders.
AMT enables a comparison of strategy approach from both a cost and reliability perspective.
AMT keeps a live zero-based budget for all assets to a component level.
Accurately forecast long-lead-time components to reduce downtime, optimise working capital and align processes.
Identify the optimal economic life of an asset, evaluate options for future asset purchases, and perform feasibilities studies.
Accurately benchmark assets across sites, company and industry while normalising localised differences.
AMT4SAP provides Zero-Based Budgeting that is continuously live, to a component level including all planned and unplanned events. Users can create & analyse multiple scenarios, forecasts & budgets utilising historical, real-time and forecast data. All of which is seamlessly integrated with SAP.
Through the long term planning functionality users can optimise upcoming activities and understand the impact on inventory, labour, availability, and cost. The user can accurately forecast long-lead-time components with component forecasting to optimise working capital and align processes. All of this can be done before a work order is created to understand the impact on the asset.
Historical data is often structured inconsistently across assets and sites, making benchmarking difficult. However, AMT accurately benchmarks assets across sites, company and industry while considering differences in operating environments, maintenance strategies and manufacturers.
The holistic view of the assets encompasses both history and future planned and unplanned activities. This allows analysis of causes of variance across historical, future and predicted “whole of life” data to identify problems. The data structures provide a natural data framework and the necessary flexibility to benchmark assets across sites and companies.
AMT can hold multiple versions of an asset’s maintenance strategy to support scenario (‘what-if’) analysis without impacting the asset’s current live strategy. Most systems can hold only one current strategy for an asset, encompassing the maintenance plans and tasks. AMT users can perform sensitivity analyses on maintenance strategies by evaluating drivers that can affect each asset, e.g. application severity, mine plan, production targets, utilisation, etc. This enables comparison and selection of the best strategic option from both a cost and reliability perspective.