Validate system design, achieve reliability and availability targets, while balancing capital and maintenance expense.
A RAM analysis is a proven approach and effective tool for assessing system reliability, availability and maintainability. It is crucial to support the through-life viability of a project. The aim of a RAM analysis is to identify any significant causes of loss of operational availability or issues that may limit the production throughput and then propose improvements to the design or maintenance program to enable RAM targets and project requirements to be met.
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Balancing design optimization with cost constraints
Operations and engineering teams must ensure that systems, processes, and equipment meet reliability and availability requirements without exceeding budget limits. Achieving this balance requires accurate analysis to minimize costs without compromising performance.
Developing high-quality maintenance plans efficiently
Creating effective maintenance plans and generating accurate master data can be costly and time-consuming. Reliability and Maintenance Managers need streamlined tools that support the rapid development of maintenance strategies to optimize asset performance within budget.
Providing reliable forecasts for availability and capacity
To ensure smooth operations, it's critical to develop accurate forecasts of equipment availability and capacity based on current maintenance plans. These insights are essential for planning resources, justifying budgets, and achieving operational targets without unexpected shortfalls.
Comprehensive RAM Analysis throughout the project lifecycle
We utilize a variety of RAM analysis tools for each project phase to enable asset management plans to be created in a streamlined way and to be consistent with the operational objectives of the project.
Ideally, a RAM analysis, supported by a Failure Mode, Effects and Criticality Analysis (FMECA), would be conducted in the design stages of a project. As design moves through the various FEED stages from concept, pre-feasibility, feasibility, detailed design, commissioning and handover, the RAM model also matures from high-level assumptions to specific failure mode models.
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Identifying critical reliability issues early in design helps avoid costly changes later in the project. A Reliability Block Diagram (RBD) visually maps equipment interconnections and failure logic, showing dependencies across equipment, spares, and resources. This approach highlights bottlenecks, ranks equipment criticality, and enables evaluation of design parameters like redundancy and equipment sizing for optimal outcomes.
Make every decision with confidence on what maintenance to perform, whether it is off line or online, spares required, refurbishment effectiveness, and warning signs and time required to respond. These are all important in the determination of the capacity of the system to deliver, to be available and to avoid interruptions between planned outages.
Understanding the availability of a plant and its capacity to produce enables decision making throughout the FEED process and when designing new projects. There are many options to be considered, including equipment sizing, multiple parallel streams, intermediate stockpiles and buffers, catch up capacity, work-arounds, standby arrangements. By modelling all the variables, such as power supply, steam and utilities, relief systems, material transport, load in stations, load out stations, cleaning processes, regeneration requirements, and statutory regulations for inspection, you will be able to validate the system capacity and identify bottlenecks and critical areas.
Developing maintenance strategies, plans and work instructions produces thousands of documents. Implement work processes to define the master data standard and ensure all uploads meet the standard before uploading. Standardize tasks across the enterprise for same work on the same equipment or similar equipment.
As the design matures from concept to detailed design, reliability assumptions keep pace with procurement decisions, maintenance reviews, operator input, commissioning performance. Data records are kept for operational teams to update models, understand strategy requirements and build out detailed plans and work instructions. Quickly find the underlying assumptions for equipment reliability, likely failure rates, failure modes, production capacity, redundancy, spares availability and maintenance outages.
Forecast accurate spare holding levels for planned work to ensure an economical balance between procurement and holding costs. For unplanned work and breakdowns, ensure holding levels are optimized against the holding cost and cost of an outage. Model the spares supply chain and factor in logistical delays and usage rate that may impact availability and ultimately system downtime.
As the project phase matures to detailed design, a detailed system model ensures all elements of the design are aligned to the project objective: procurement, equipment vendors, maintenance strategy and plan definition, redundancy, type of equipment, infrastructure, instrumentation and protection systems, resourcing. The detailed system model provides the basis for defining master data, establishing detailed maintenance plans, work instructions, Bills of Material, Spares levels. In many projects, these steps are duplicated by the O&M team, often without alignment to the project objectives. Use of the Systems model streamlines ramp up, reduces the commissioning phase and provides the base for managing further improvements, without reinventing the wheel.