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Spare parts optimisation – A maintenance modelling approach using MAROS

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John Spouge

John Spouge

Senior Principal Consultant

The availability of spare parts has a crucial role on the continuing operation of an asset; the lack of spare parts has the potential to cause significant production loss due to extended repair time. On the other hand, holding unnecessary spare parts ties up capital and may add to operating costs.

Published: 27 February, 2018

An optimal spare part holding strategy will help maximise asset production availability at a minimum cost. Lai Tran and Guy Cozon explain how RAM analysis and maintenance modelling can help.

A spare part optimisation process is key to achieving a good spare part holding strategy. The optimisation process can provide recommendations on the quantity and location of capital spares as well as operational spares to achieve the required production availability. We recommend to perform the spare part optimisation process using a RAM methodology and maintenance modelling approach as early as FEED phase but ideally in EPC phase, where requirements for spare parts are being established.

Maintenance modelling
MAROS, a DNV proprietary simulation tool for RAM analysis, offers extensive maintenance modelling features to simulate maintenance logistic delays, including delay in obtaining the required spare parts. Modelling maintenance logistics involves determining the repair delay or ‘Mobilisation & preparation delay’ portion of the failure sequence below.

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Failure sequence

This is achieved by defining the location, quantity and constraints of the various resources involved in the repair process: maintenance crew, tools and spare parts. This then allows the simulator to determine the repair delay for each failure, depending upon the foregoing and the instantaneous workload and conditions at the time of the failure.

Key questions
When an equipment item fails, there are a number of important logistical and strategical issues involved in dealing with the ensuing repair task, typically:

  • Where is the job to be performed (location)?
  • What spare parts are required?
  • What manpower requirements are required?
  • What other support resources are required (utility vessels, lifting gear, etc.)?
  • How important is the job (with respect to production downtime)?
  • How are the resources going to get to the job location (transport, travel times, weather conditions)?
  • Are there any opportunities to conduct other maintenance activities at this time (opportunity strategies, bringing forward PMRs etc.)?

DNV maintenance modelling approach deals with the above questions and allows an optimum balance to be struck between the costs of equipment upkeep and the impact of lost revenues due to their failures.

20180227_Spare Parts Optimisation – A Maintenance Modelling Approach Using MAROS 343x661pxlSpare part modelling
Delay in obtaining spare parts is a significant cause to production loss of the asset. For this reason, spare parts, especially capital/ insurance spare parts for critical machineries, which fail more often than static equipment, should always be included in a RAM model.

We do not usually consider routine spare parts or spare parts for static equipment  in RAM modelling. However, if certain pieces of static equipment rank high in the list of critical equipment items, their spare requirements, especially for those frequently failed components such as instruments and control valves, might be considered.

There is usually no need for a comprehensive spare parts inventory analysis when comparing alternative concepts in the early stages of a study.

Modelling the impact of spare parts involves consideration of the following main attributes. Most of them are only available late in EPC phase or early Operational phase:

  • Number in stock: the maximum amount of the spare that can be held. This is also used as the initial number available for this equipment item.
  • Mobilisation time: Time taken when spare is drawn out of stock and put into use.
  • Restocking level: The level at which a restocking activity is invoked.
  • Restocking time: Time taken for restocking.
  • Refurbishment time: Time taken to refurbish the failed item.
  • Cost data: cost of item and mobilisation/demobilisation cost.

Sample results

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Operational spares
During EPC phase, in addition to capital spares, operational spares for the top 5 (or top 10) critical equipment items could be considered.

These equipment items will have their failure modes broken down to component or maintainable item level (e.g. actuating device, anti-surge valve, bearing, casing etc. for a centrifugal compressor). This further level of modelling will allow capital and operational spare parts for these maintainable items to be included and optimized.

We usually consider spare parts holding for these maintainable items under 3 levels/locations. Each level/location requires different lead time for the spare parts, hence different impact on the production availability:

  • Held at site (i.e. always available)
  • Held in-country warehouse (a few days mobilisation required)
  • Procurement on demand, subject to long lead time.

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Case study: Optimisation of operational spares

Critical issues:

  • An offshore development project progressed well into the EPC phase. The owner and EPC contractor did not expect major design changes with significant CAPEX implications.
  • To improve production availability, improvement measures were evaluated with optimisation of spare parts inventory being key.
  • Limited space available on the platform for storing spare parts.
20180227_Spare Parts Optimisation – A Maintenance Modelling Approach Using MAROS 770x535pxlSolutions:
  • We built a RAM model using MAROS for the development to calculate the production availability and rank the most critical equipment items.
  • In order to achieve the required production availability, we investigated a number of improvement measures. Central to these measures were the availability and location of spares for critical equipment.
  • For critical equipment, modelling at maintainable item level instead of equipment level, was adopted in order to include the impact of spare part availability and mobilisation of spare part for each component/maintainable item’s failure.
  • We then adjusted the availability and location of spare parts for these components/maintainable items to achieve the optimum production availability with minimum changes to the design.
  • 3 alternative cases were examined to evaluate and optimise the impact of spares holding for maintainable items on the production availability.
    • Spares held offshore for top 10 critical equipment
    • Spares held onshore for top 10 critical equipment
    • Best assumption for location of spares for top 10 critical equipment

Value delivered:

  • The study helped understand the impact and value of the availability and location of spares on the performance of the development. 
  • Spare parts optimisation for a targeted group of equipment was performed to help achieve the production availability target without the need of major design changes. 

Recommendation extracted from the study: 

  • Instruments and control valves for Glycol Contactor, Still and Stripping Columns should be should be held in offshore warehouse if possible as they are responsible for the majority of these columns’ losses. If these spare parts were to be held in onshore warehouse instead, which requires 24-36 hours to obtain and transport to site, this may reduce the production availability by 0.22%. This is equivalent to a production reduction of 1.1 MMSCF per day or roughly $1.2 million a year.

Contact us:

John Spouge

John Spouge

Senior Principal Consultant