Phase I. Introduction, theoretical review and research methodology Introduction
CHAPTER 6 LEVEL OF REPAIR ANALYSIS (LORA) MODEL
6.3 A CASE STUDY
6.3.1 DESCRIPTION
SONATRACH, the Algerian National Oil & Gas Company, owns and operates oil & gas fields, refineries, LNG plants and oil & gas transmission network in Algeria. This network ensures the flow of hydrocarbons (crude oil, natural gas, LPG and condensate) from the Algerian desert to the exporting ports in the north and to the south of Europe. Algeria's Petroleum Transmission System consists of 16 200 km of pipelines of different designation and capacity, and 79 pumping and compressor stations equipped with over 290 main machines with a total capacity of over 02 millions horse-power. The efficiency of this transmission system relies heavily on the availability of the installed gas turbines. This equipment converts the thermal energy produced by fuel combustion into mechanical energy to revolve the compressor’s shaft.
Fig. (6.2): Gas turbine
A real gas turbine system is considered in this research. The selection of this class of petroleum equipment is intentional for a number of reasons; first, this equipment is installed in a spread area along with pipeline routes; secondly, its repair is undertaken in hierarchy structure which consists of local and intermediate bases. These two reasons fit perfectly the process of LORA and spare part models. Figure (6.3) represents a material breakdown structure of gas turbine used in boosting station like PGT10, PGT16, PGT25 and ALSTOM. These systems, which comprise various repairable and consumable parts, play a key role in the operation of the Transmission System. For large companies, such as a petroleum company, enhancing operation performances of such asset at reduced costs related to repair and maintenance tasks are one of the major of management concerns. In
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relation to this, the case studies conducted in this research mostly concern maintenance supply with spare parts of gas turbines, such as blades, shaft, gears, compressor and some other parts. In response to these concerns, the case studies were carried out for identifying the optimal number of spare parts with regard to the operating requirement.
Based on ILS standard and guidelines, the first step of LORA and spare part analysis is to generate or adopt a system breakdown structure that categorises all relevant components in hierarchical format. In a typical LORA analysis, a system is defined as a collection of components. These components are usually the items, parts, equipment or subsystems of the system. The proposed system breakdown structure is divided into three levels (Figure 6.1). This engine modules are maintained based on fixed operating time (8 000 hours, 16 000 hours and 32 000 hours), on corrective reactions and on condition using. As an engine undergoes maintenance tasks at the repair shop, different subsystems and components are replaced by new or restored ones. The failed items are scrapped, or repaired then tested at three local repair bases or at three intermediate bases.
6.3.2 DATA COLLECTION
Three main sources of ILS data should be identified: manufacturers’ and suppliers’ data, organisation data, historical data and predictive model data. In LORA analysis, this data will be split furthermore into two principal categories: data related to the system itself and data related to the repair shops. The first category includes the following information: turbine ID, list of material, item procurement cost, dates of maintenance events, repair interval, downtime and maintenance comments. The above gas turbines are similar in type, structure and functionality and each of them consists of the following subsystems, namely, turbine, compressor, combustion system, air inlet system, start-up system and turnion support.
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System related data is collected through the maintenance work orders and the maintenance reporting system at the company. In these archives, the available information is; the work order starting date, the work order finishing date, system ID, failed subsystem or subsystems, replaced item or items, type of system downtime (total, partial or minor downtime) and the reasons for failures. Unfortunately, all these data sources do not contain cost information such as: repair cost, spare part cost, etc.
The relevant data for LORA analysis consists of the following three characteristics: (a) the number of stops; (b) failed item (s) and (c) stop time. The intent behind the LORA analysis is to check whether the repair actions are optimally designed or not. The table 6.1 summarises the LORA data of the different turbine subsystems. The last two columns give the mean time between failure of the selected components and their repair demand. Due to confidentiality reasons, it has not been allowed to present the real data of the case study used to evaluate LORA model. Consequently, all cost values in the table 6.1 are presented in modified monetary unit symbolised by MU.
The second LORA required data is the costs for repair actions. For gas turbine example, these costs are repair facility cost, support and test equipment cost and labour cost. In order to evaluate the economic consequences of repair actions it is essential to distinguish between fixed costs and variable costs. The fixed costs class is characterised by installed capacity which does not increase with the failure rate up to a certain limit. These costs are normally defined for each echelon of maintenance and they may include the following subclasses:
Repair shops building Support and test equipment Manpower cost
Documentation
Another issue arises when considering the fixed costs is that all above subclasses is devoted to a set of operational systems such: turbines, compressors, pumps, etc. In order to allocate costs to each system, repair capacity is firstly split into direct and indirect costs then indirect cost are allocated to system by means of repair demands. Besides, variable costs are continuous functions which vary with the failure rate such as: spare part costs and labour costs. Following WLC mathematical expression, repair cost for the
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whole life of the turbine, presented by the present value PV, is given by (as described in chapter 3):
∑
= + + + = N k k k repair repair repair repair i d VC FC NPV 1 (1 ) ) 1 ( * * λ (6.7)∑
= + + + = N k k k discard discard discard discard i d VC FC NPV 1 (1 ) ) 1 ( * * λ (6.8)∑
= + + + = N k k k move move move move i d VC FC NPV 1 (1 ) ) 1 ( * * λ (6.9) Where:λrepair, λdiscard and λmove denote the annual demand for repair, discard and move
respectively.
FC and VC are fixed and variable costs.
i and d are the discount rate and the inflation rate respectively.
Since every system has a predefined useful life based on technological considerations, operation requirements and physical characteristics (FAA Life Cycle Cost Estimating Handbook, 2002), gas turbines usually operate over 25 years. In case of SONATRACH, some gas turbines have been in operation since the 70s; therefore, 30 years will refer to study period in this LORA model. In addition, SONATRACH uses discount rate of 10% and 1.5% as the inflation rate for all financial analysis. Using this information, the cost data for LORA model is evaluated and presented in table 6.1.