Actionable Asset Intelligence

Fast results with low investment

Actionable Asset Intelligence

Fast results with low investment

Actionable Asset Intelligence

Fast results with low investment

who we are

Convergência is an applied research and development company that creates and operates truly innovative prescriptive maintenance models to enhance mobile asset performance. Operating for over a decade at the cutting edge of applied data science, we have delivered unprecedented results in the mining industry, such as an increase in both asset availability (3-10 p.p.) and lifespan (30-50%) together with a reduction in both costs (25-35%) and operational risk.

What we do

Convergência delivers concrete results through actionable asset intelligence. We empower clients to create and manage their own centres of excellence for asset health. Our solutions, the engine powering these centers of excellence, enable clients to benefit from cutting edge applied data science and build up state-of-the-art competences, taking their capability to manage asset health to a whole new level. Clients achieve outstanding results whilst keeping a high degree of control over the end-to-end process.

how we do it

Site assessment

Identify the potential value to be created and unlocked at the specific client site by the deployment of Convergência's solutions

Extending the lifespan of each asset through prescriptive work orders based on its specific condition

Asset Health

Extending the lifespan of each asset through prescriptive work orders based on its specific condition

Making the most out of component lifecycle through an optimised replacement plan across the full fleet

component lifecycle

Making the most out of component lifecycle through an optimised replacement plan across the full fleet

why we are different

agile digital transformation

Our approach delivers fast results and learnings whilst requiring low investment.

ACTIONABLE DELIVERABLES

Our output is in the form of work orders integrated in the client’s process rather than only decision support dashboards.

ROBUST ANALYTIC MODELS

Our decision models are based on algorithms developed through machine learning and already fed with millions of hours of operation.

Proven deployment methods

Our implementation plans are based on extensive field experience and purpose-developed best practices.

concrete results

copper mine with a new fleet

  • Costs of parts and components 29% below budget.
  • Average engine lifespan 50% above manufacturer’s estimate.

iron mine with a mixed fleet 

  • Costs of parts and components 31% below budget.
  • Availability stabilized after initial increase of 2 p.p.

iron mine with a mixed fleet

  • Availability increase of 10 p.p.
  • Effect comparable to previous equipment replacements in the past.

a glimpse of our work