Challenge

Codelco

Innovations to predict behavoir of Conveyor Belts

Challenge

Innovations to predict behavoir of Conveyor Belts

CODELCO has asked Expande to prospect the local and international ecosystem to identify technological solutions that respond to the technical challenge “Digital Twin for Conveyor Belts”.

General aspects

At the end of 2019, Codelco Chuquicamata Division started up one of the largest and most sophisticated conveyor belt systems in the world. It consists of 14 kilometers of belts that carry the ore from the subway part of the deposit to the surface, and from there to the concentrator plant. This definitive transport system will allow it to transport 140 thousand tons per day, with a useful life of 40 to 50 years.

These belts, classified within the high-tension range of operation, represent one of the most critical systems for the operations of this deposit, therefore they require a constant and rigorous monitoring of operation and maintenance variables. In this context, it is considered necessary to incorporate, among others, digital twin technology that allows predicting the behavior of conveyor belts through modeling and simulation, creating a virtual and parallel system of these equipment. With this tool, it will be possible to anticipate eventual deterioration of these assets and proactively manage actions aimed at optimizing their utilization.

Objectives of this prospection
Identify technological solutions that allow the implementation of technologies, such as digital twins, for high-tension ore conveyors, focusing on an integral optimization from operation to maintenance.

Technological Solutions requirements

  • Proven experience in development of tools for monitoring and simulating conditions for high-tension conveyor belts.
  • Maturity level ≥ 7 (demonstration in operational environment).
  • Agnostic system, compatible with different existing monitoring and information management platforms (e.g.: SMAP, PI System and PI Vision).
  • Tools for modeling, simulation, event prediction, reporting and traceability.
  • Storage in standardized and auditable database.