Reliability Availability Maintainability (RAM) study

Reliability, Availability & Maintainability modelling assesses production system’s capabilities, whether it is in operation or still in the design phase. The results from a RAM modeling will identify possible causes of production losses and can examine possible system alternatives, such as design modifications and maintenance and spare part philosophy adjustments.

Typically, RAM analysis results in:  

  • Identification of bottlenecks in the production
  • Ranking of critical systems and components contributing the most to production losses
  • Understanding of the impact of varying design, operations and maintenance priorities on failure
  • Comparison of design alternatives based on production availability in order to meet contract production requirements
  • Guidance for future OPEX allocations in the form of likelihood and duration of unplanned maintenance requirements
  • Optimization of maintenance schedules
  • Increase of logistics effectiveness

The RAM study is thus a tool for decision-making with help for costs versus benefits analysis in view to achieve the installation availability optimization.

Tecnitas generally uses Bureau Veritas proprietary RAM simulator Optimise©, to assess production system’s capability and performance, but can use other modelling tools depending on the customer request and requirements, such as Reliability Block Diagrams (RBD).

With Optimise©, Tecnitas is able to model almost any type of installation whatever the complexity is, while considering:

  • Production profile,
  • Multi-Branch type of production flow line
  • Maintenance logistics (number of teams, repair prioritization, time of mobilization, lead time of spare parts…)
  • Logic features to simulate installation and production characteristics like ramp-up production, failure sequencing,
  • Availability calculated based on the production capability
  • Buffers and Storage
  • Ship Modeling (routes, ports, ships…)

Once a base case model is established and modelled, sensitivity cases can be used to improve and add value to the design and do so cost effectively in a controlled manner without costly changes to design.