Project life cycle support using RAM analysis

Article extract from DNV GL blog, part of ReliablePlant newsletter:
http://blogs.dnvgl.com/software/2014/11/project-life-cycle-support-using-ram-analysis/

RAM (Reliability, Availability and Maintainability) analysis are commonly used to support the decision making process. The analysis can be used throughout the project life cycle to support the decisions that have to be made at each of the various stages:

Conceptual Design

The Conceptual Design is a preliminary stage where a description of the proposed system in terms of a set of integrated ideas and concepts are made. The result is the generation of many Design Concepts which are supported to  evaluate the feasibility of each conceptual alternative. Advanced RAM analysis allows quick screening of various development options to assess suitability (from a functional & commercial perspective) of the proposed designs.

Front End Engineering Design stage

Once a number of options have been selected, a more detailed analysis can be carried out to choose major equipment types and maintenance philosophies. At this stage, the most important decisions in regards to concept and plans for the project are made. Some of the questions that you might want to answer at this stage are:

• How does equipment/unit reliability impact production?
• What happens if equipment performance is worse than expected?
• What size storage tanks (equipment) should I have?
• What is the impact of unit over-design (catch-up) margins?
• What is the optimum unit configuration in order to maximise production/availability and maintenance reduction?
• Will it be possible to meet the customers’ demands for products?
• What is supply efficiency to each customer?

Advanced RAM analysis helps you to decide what is the best configuration for your assets and aids you in answering these and many more questions.

Detailed engineering

The Front End Engineering Design (FEED) stage leads to the creation of primary design documents such as process flow diagrams (PFDs), Process & Instrumentation Diagrams (P&IDs), equipment lists and equipment datasheets. Once the FEED has been finalised, a much more detailed design for the system is specified. At this stage, the questions are much more specific:

• What happens if I improve equipment reliability?
• What is the financial impact of investing in more reliable equipment?
• Should I spare equipment to increase reliability?
• How many spares do I need to have and how would it increase system reliability?

Advanced RAM analysis ensure that the system design meets your required performance targets.

Execute

By identifying the critical elements and the bottlenecks in the system, the results from an Advanced RAM study can be used to feed in to other methodologies, such as Risk Based Inspection (RBI) and Reliability Centred Maintenance (RCM). Subsequently, the output from the RBI and RCM processcan then be fed back into the model to provide a final picture of system performance.

Operational Stage

During the Operational phase, it is not very cost-effective to make decisions in regards to the design. However, Advanced RAM analysis can also be used to assess impact of planned modifications. The most common evaluation carried out during the Operational stage is related to the maintenance philosophy which, basically, refers to number of spares, re-stock time and available personnel. There is always a trade-off between the cost of lost production versus the cost of maintenance.

Rejuvenate

For mature systems, as we keep asking more of our ageing assets, the Advanced RAM methodology allows you to find potential areas for rejuvenation or facilities life extension. Many sensitivity cases can be applied to a mature system model, which will indicate to various rejuvenation options and the potential gains quantified.

A platform at the end of its lifecycle must be assessed to extend their production. Many parameters must be evaluated:

• Ageing systems and old technology – what is critical when it comes to production loss?
• Decommission of problematic systems – which system should be turned off?
• Where should I focus main preventive maintenance?

Decommission

Sometimes, due the high number of variables in an oil and gas development, it is not easy to identify at where the operational expenditure exceeds the revenue, making the system no longer economically viable. By modelling all the transient behaviours of a system, Advanced RAM analysis helps you to  evaluate decommissioning strategies viability.

Reliability Modelling

I have been working full on until New Year building component library for a consultancy and running reliability modelling. I have run into a lot of issues with the model and would like to share them to promote an understanding.

The very first thing you do as an engineer is always question the validity of those data you acquire. In summary, I would not recommend doing reliability modelling. My personal opinion is, it is a waste of time, effort and money. If you are looking at doing reliability modelling, chances are, your existing plant reliability is not great and your reliability knowledge is not comprehensive. For the accuracy you get, you are better off with a 0.9 factor of industry average reliability figure. No modelling out there I have seen is accurate enough for any good use. If you are doubtful on the quality of people you are able to hire into the maintenance team, use a factor of 0.7 and you should have a somewhat conservative availability figure. Yes it looks ugly, yes it looks unrealistically low, but I'm sorry to say, that is reality of the availability and reliability figure you should expect for saving cost hiring cheap people. I could not emphasize enough, good asset management and reliability starts with good people.

Back onto the topic I was suppose to be writing about - Limitations of reliability model. Firstly, ALL reliability model I have seen is designed in series. It is all well and good if your process is in series like a simple production line of a simple mine site, if you have a complicated processing plant, your reliability model will not do. In fact, there's so much work trying to design the model to fit your plant, it is just not worth the effort. Unless there's a free template already setup similar to your plant and takes just a little bit of effort to patch up, there's no point going down this path.

Secondly, in a complex process plant, you will have varying equipment MTBF and MTTR. Every plant's figure is unique. For the model to be accurate enough to be of any use, it has to be from your plant, your production forecast, you historical availability, and reliability. This is because as the errors build up in the reliability model, the final result is again of not much use to you as the owner.

Thirdly, a complex equipment in a complex plant will have a long list of failure modes to prevent. Some of these failure modes will be attended to in one work task and reset their likelihood of occurrence and budgeted life. None of the reliability model I seen cater for this.

With this three fundamental issues in modelling unresolved, I would not recommend any company looking at carrying out the modelling without understanding the limitations of it.