A browser-based Maros alternative
DNV Maros is the established oil & gas production-availability tool. Ramly brings the same core idea — Monte Carlo simulation of a system to a production-availability number — to the browser, with no install and subscription pricing.
DNV Marosis the long-established production-assurance tool in oil & gas: a Windows desktop application that simulates production systems as flow networks, with multi-state partial-capacity equipment, buffers and contractual terms, and a sister tool (Taro) for the operational phase. For deep production-network modelling it is purpose-built.
Ramly overlaps on the core: a RAM study of a reliability block diagram with throughput capacities, producing production availability and lost production in real units — by Monte Carlo simulation or an exact analytical solver, including multi-state, partial-capacitycomponents. Where Maros goes further is full production-flow networks — routing, blending, storage and contractual terms. Ramly’s bet is the common production-availability study — in the browser, fast, at a price that doesn’t need a purchase order.
Feature comparison
| Ramly | DNV Maros | |
|---|---|---|
| Deployment | Runs in any modern browser — nothing to install, on macOS, Windows or Linux. | Windows desktop application, installed per machine. |
| Getting started | Sign up and open a worked example model in minutes. | Per-seat license, typically quoted and procured. |
| Core method | Monte Carlo simulation and an exact analytical (Markov) solver of a reliability block diagram with throughput capacity. | Monte Carlo simulation of production systems — the established oil & gas production-assurance tool. |
| Production availability | Real-unit throughput capacity → production availability and lost production in t/h. | Production availability is its core output. |
| Partial-capacity / multi-state | Multi-state components with per-state capacity (e.g. running at reduced rate), solved by the analytical solver for production availability. | Multi-state, partial-capacity production modelling within a detailed flow network. |
| System structure | Reliability block diagram: series, parallel (k-of-n), standby and arbitrary nesting. | Detailed production flow networks with routing, blending and contractual terms. |
| Maintenance realism | Preventive maintenance, logistics delay, shared crews with queuing, spare pools with stock-outs. | Maintenance, spares and logistics modelling. |
| Redundancy & standby | k-of-n parallel; cold/warm standby with a separate dormant failure rate. | Redundancy and sparing configurations. |
| Importance & loss contributors | Birnbaum, RAW and RRW importance, plus ±20% MTTF/MTTR sensitivity. | Criticality / loss-contributor ranking. |
| Lifecycle | Design and operational questions from one browser model. | Maros for design-phase studies; sister tool Taro for the operational phase. |
| Automation | Python API (libram.so) for scripted, repeatable runs. | Automation via its platform tooling. |
| Reproducibility | Fix the random seed and any reviewer re-runs to an identical result. | Seedable simulation. |
| Pricing | Subscription, published pricing — below most corporate card thresholds. | Per-seat license, quote-based. |
Which one should you use?
Choose Ramly when…
- ▸You want a production-availability study in the browser, started today — no install or PO.
- ▸Your system fits a reliability block diagram with throughput capacities.
- ▸You want production availability and lost production in real units, fast.
- ▸You value reproducible seeded runs, a Python API and subscription pricing.
- ▸Your team is on mixed operating systems.
Choose Maros when…
- ▸You model complex production-flow networks with routing, blending, storage and contracts.
- ▸Your partial-capacity modelling needs a full flow network, not component-level states.
- ▸You want the long-established oil & gas production-assurance tool, with Taro for operations.
- ▸Your study is contractually tied to Maros outputs.
Try a real RAM study in your browser
No install, no procurement. Open a worked example model, run a Monte Carlo simulation and read the availability results in minutes.
Comparison reflects DNV Maros’s publicly published materials as of June 2026 and has not been independently benchmarked. DNV Maros and all other product names are trademarks of their respective owners and are used here only for identification and comparison. Capabilities and licensing of third-party products change — verify current details with the vendor.