A Multi-Criteria Classification Framework for Spare Parts Management: A case study

The offshore petroleum industry can be described as a capital-intensive industry. Capital intensive refers to a heavy and high-value asset structure with long lifetimes that demands considerable effort to maintain. Large investments are required to produce goods and services, and the consequences of downtime, shortage and production loss are extensive. Efficient and reliable maintenance operations are essential to secure safe, productive and reliable production, creating a great incentive to stock up on all kinds of spare parts to reduce the consequences of the above-mentioned. However, there are great costs and inefficiencies related to spare parts inventories. Holding costs are high, turnover ratios are low, and inconsistent demand patterns make demand difficult to predict. Therefore, the trade-off between availability and efficiency is a fundamental principle in inventory management of spare parts. The industry puts a lot of effort into optimising spare parts inventories and spends resources on developing efficient and reliable spare parts operations. Among these efforts is spare parts classification. This is the process of classifying spare parts into distinct groups and is crucial to control the enormous number of parts with different characteristics. The decisions on which characteristics to use in classification practices is not straightforward and has been subject to research and debate for many decades. In current classification practices, most spare parts of an equipment are assigned the same criticality rank as the equipment itself, which is not necessarily the case. Therefore, Moreld Apply AS are interested in developing a method for spare parts classification that further evaluates criticality and consequence analysis on a spare parts level. This study presents a way to classify spare parts using a multi-criteria framework to establish precise criticality classes for each part. The findings in this thesis have ultimately led to the conclusion that multi-criteria approaches have great potential in the classification practices in the industry. We also see that the framework is already implementable for single case scenarios, such as the one analysed in this thesis, and provide reliable results. The results indicate that, in almost all instances, the criticality level of spares is reduced compared to the main equipment. The main contributions of this thesis is a framework with several steps guiding the user through the process of setting up the evaluation, preparing the analysis, as well as doing the analysis. Important aspects will be the selection of the most appropriate classification criteria, data collection processes and preparation activities. These topics form the main body of research.The offshore petroleum industry can be described as a capital-intensive industry. Capital intensive refers to a heavy and high-value asset structure with long lifetimes that demands considerable effort to maintain. Large investments are required to produce goods and services, and the consequences of downtime, shortage and production loss are extensive. Efficient and reliable maintenance operations are essential to secure safe, productive and reliable production, creating a great incentive to stock up on all kinds of spare parts to reduce the consequences of the above-mentioned. However, there are great costs and inefficiencies related to spare parts inventories. Holding costs are high, turnover ratios are low, and inconsistent demand patterns make demand difficult to predict. Therefore, the trade-off between availability and efficiency is a fundamental principle in inventory management of spare parts. The industry puts a lot of effort into optimising spare parts inventories and spends resources on developing efficient and reliable spare parts operations. Among these efforts is spare parts classification. This is the process of classifying spare parts into distinct groups and is crucial to control the enormous number of parts with different characteristics. The decisions on which characteristics to use in classification practices is not straightforward and has been subject to research and debate for many decades. In current classification practices, most spare parts of an equipment are assigned the same criticality rank as the equipment itself, which is not necessarily the case. Therefore, Moreld Apply AS are interested in developing a method for spare parts classification that further evaluates criticality and consequence analysis on a spare parts level. This study presents a way to classify spare parts using a multi-criteria framework to establish precise criticality classes for each part. The findings in this thesis have ultimately led to the conclusion that multi-criteria approaches have great potential in the classification practices in the industry. We also see that the framework is already implementable for single case scenarios, such as the one analysed in this thesis, and provide reliable results. The results indicate that, in almost all instances, the criticality level of spares is reduced compared to the main equipment. The main contributions of this thesis is a framework with several steps guiding the user through the process of setting up the evaluation, preparing the analysis, as well as doing the analysis. Important aspects will be the selection of the most appropriate classification criteria, data collection processes and preparation activities. These topics form the main body of research

A Multi-Criteria Classification Framework for Spare Parts Management: A case study

The offshore petroleum industry can be described as a capital-intensive industry. Capital intensive refers to a heavy and high-value asset structure with long lifetimes that demands considerable effort to maintain. Large investments are required to produce goods and services, and the consequences of downtime, shortage and production loss are extensive. Efficient and reliable maintenance operations are essential to secure safe, productive and reliable production, creating a great incentive to stock up on all kinds of spare parts to reduce the consequences of the above-mentioned. However, there are great costs and inefficiencies related to spare parts inventories. Holding costs are high, turnover ratios are low, and inconsistent demand patterns make demand difficult to predict. Therefore, the trade-off between availability and efficiency is a fundamental principle in inventory management of spare parts. The industry puts a lot of effort into optimising spare parts inventories and spends resources on developing efficient and reliable spare parts operations. Among these efforts is spare parts classification. This is the process of classifying spare parts into distinct groups and is crucial to control the enormous number of parts with different characteristics. The decisions on which characteristics to use in classification practices is not straightforward and has been subject to research and debate for many decades. In current classification practices, most spare parts of an equipment are assigned the same criticality rank as the equipment itself, which is not necessarily the case. Therefore, Moreld Apply AS are interested in developing a method for spare parts classification that further evaluates criticality and consequence analysis on a spare parts level. This study presents a way to classify spare parts using a multi-criteria framework to establish precise criticality classes for each part. The findings in this thesis have ultimately led to the conclusion that multi-criteria approaches have great potential in the classification practices in the industry. We also see that the framework is already implementable for single case scenarios, such as the one analysed in this thesis, and provide reliable results. The results indicate that, in almost all instances, the criticality level of spares is reduced compared to the main equipment. The main contributions of this thesis is a framework with several steps guiding the user through the process of setting up the evaluation, preparing the analysis, as well as doing the analysis. Important aspects will be the selection of the most appropriate classification criteria, data collection processes and preparation activities. These topics form the main body of research

Shared Spare Parts Management in Offshore Remote Locations: A Model to Improve Logistics and Reduce Carbon Emissions.

The management of spare parts poses significant challenges, particularly in offshore remote locations. The combination of the remoteness of these locations and harsh environmental conditions adds complexity to the process of timely delivery of spare parts. As a result, lead times are prolonged and operational downtime is increased, leading to substantial financial losses for companies. The lack of simulation models limits the practical application of sharing spare parts strategy, hindering understanding of their potential benefits, costs, and challenges. This gap hinders the implementation of the concept of sharing spare parts management and prevents their adoption in real-world scenarios To address this gap, a simulation model was developed to manage spare parts across three offshore locations in the Barents Sea. The focus lies in exploring the benefits of sharing spare parts strategy among platforms, particularly regarding lead times, CO2 emissions, carbon tax costs, and reuse of spare parts among these platforms. The study follows a quantitative approach using AnyLogic software for simulation. Various factors, including storage capacities, vessel speed, carbon emissions, and carbon tax costs, were incorporated into the model. The research design consists of four stages: conceptualization, model structuring, parameterization, and validation. A case study approach is used, with data from three common equipment types across three criticality classes. Through a comparison between the baseline scenario and the solution scenario, the results demonstrate the effectiveness of the proposed concept of sharing spare parts. It reduced trips to the onshore warehouse by 42%, decreased total traveling time, CO2 emissions, and carbon tax costs by 48.6% each, and optimized lead times and inventory management. These results underscore the potential benefits of sharing spare parts systems, providing a pathway for more efficient and sustainable spare parts management in offshore operations

A Roadmap for Acquisition of Legacy Parts Through an On-demand Solution Aimed at the Energy Sector on the Norwegian Continental Shelf - A Case Implementation

\section{Abstract} Equinor has initiated a Field Life Extension (FLX) project to prolong the end-life operational capabilities of their installations by innovative methods, including Stafjord A. One of these innovative methods is to implement an on-demand solution for re-supplying the installation with spare parts manufactured through alternative methods, such as additive manufacturing (AM) and rapid casting. However, due to the age of specific components, the documentation for design, material specification, and manufacturing may be missing, i.e., legacy parts. The main aim of this thesis is to map the path from notification of a potential failure of a legacy part to the installation of a near-identical part. The life extension implies that mechanical equipment, such as valve bodies for the fire deluge systems must maintain their integrity throughout the expanded life cycle. Unfortunately, this component has exceeded its life expectancy by twice. Hence, increased degradation and risk for potential accidents introduce the need for acquiring new valve bodies. A literature review investigated the challenges and requirements for implementing the on-demand solution for legacy parts. Standards and manufacturing methods have been studied and compared. An Analytical Hierarchy Process was used to analyze the input from experts within AM and rapid casting. Finally, a case review processed the valve body through the Reverse Engineering Process (REP) activities. A roadmap is proposed based on regulations governing the manufacturing of mechanical components used on the Norwegian Continental Shelf (NCS). Furthermore, requirements for implementing the on-demand solution for legacy parts are described, including a proposition for an explicit criticality assessment for metal AM. A recommendation for operational part-monitoring and identification linked with a digital warehouse of the corresponding part is made to finalize the proposed roadmap for acquiring legacy parts on the NCS. The Analytical hierarchy process (AHP) reveals that rapid casting outperforms metal AM for valve body manufacturing. In addition, metal AM and rapid casting are benchmarked regarding realistic cost and lead time procurement limitations. The results include the AHP output and indicate that the cost of ordering the valve body favour rapid casting, but the lead time for metal AM is lower than rapid casting. The total cost for metal AM per part is nearly equal to the cost of the initial requested batch of 26 valve bodies produced by rapid casting

Optimization of maintenance performance for offshore production facilities

Master's thesis in Offshore technologyNew technologies are becoming advanced and complex for offshore production facilities. However this advancement and complexity in technology creates a more complicated and time consuming forensic processes for finding causes of failure, or diagnostic processes to identify events that reduce performance. As a result, micro-sensors, efficient signaling and communication technologies for collecting data efficiently, advanced software tools (such as fuzzy logic, neural networks, and simulation based optimization) have been developed, in parallel, to manage such complex assets. Given the nature and scale of ongoing changes on complexities, there are emerging concerns that increasing complexities, ill-defined interfaces, unforeseen events can easily lead to serious performance failures and major risks. To avoid such undesirable circumstances, „just-in-time‟ measures of performance to ensure fully functional is absolutely necessary. The increasing trend in complexity creates a motivation to develop an integrated maintenance management framework to get real-time information to solve problems quickly and hence to increase functional performance (help the asset to perform its required function effectively and efficiently while safeguarding life and the environment). Establishing “just-in-time” maintenance and repairs based on true machine condition maximizes critical asset useful life and eliminates premature replacement of functional components. This thesis focuses on developing an integrated maintenance management framework to establish „just-in-time‟ maintenance and to ensure continuous improvements based on maintenance domain experts as well as operational and historic data. To do this, true degradation of components must be identified. True level of degradation often cannot be inferred by the mere trending of condition indicator‟s level (CBM), because condition indicator levels are modulated under the influence of the diverse operating context. Besides, the maintenance domain expert does not have a precise knowledge about the correlation of the diverse operating context and level of degradation for a given level of condition indicator on specific equipment. Efforts have been made in here to identify the true degradation pattern of a component by analyzing these vagueness and imprecise knowledge. Key words: effective and efficient maintenance strategy, ‘just-in-time’ maintenance, condition based maintenance, P-F interval

Development of risk assessment model for equipment within the petroleum industry

Maintenance department within petroleum industry seek to increase equipment safety by means of reducing the occurrence of the failure and its undesirable consequences. In this study, a risk assessment model is proposed, which includes the likelihood of the risk and the consequences of failure. A new mathematical equation is proposed to assess the likelihood of risk and identify the optimum inspection interval. In addition, modified mathematical equation to evaluate consequences of risk which allow more generalization and accuracy of weighing the possible losses (performance, financial, ecology and human) is developed. The results demonstrate an improvement at the assessment of the probability of risk and provide better understanding of the impact of the risk on the major identified areas within the petroleum industry

Risk based life management of offshore structures and equipment

Risk based approaches are gaining currency as industry looks for rational, efficient and flexible approaches to managing their structures and equipment. When applied to inspection and maintenance of industrial assets, risk based approaches differ from other approaches mainly in their assessment of failure in its wider context and ramifications. These advanced techniques provide more insight into the causes and avoidance of structural failure and competing risks, as well as the resources needed to manage them. Measuring risk is a challenge that is being met with state of the art technology, skills, knowledge and experience. The thesis presents risk based approaches to solving two specific types of problem in the management of offshore structures and equipments. The first type is finding the optimum timing of an asset life management action such that financial benefit is maximised, considering the cost of the action and the risk (quantified in monetary terms) of not undertaking that action. The approach presented here is applied to managing remedial action in offshore wind farms and specifically to corroded wind turbine tower structures. The second type of problem is how to optimise resources using risk based criteria for managing competing demands. The approach presented here is applied to stocking spares in the shipping sector, where the cost of holding spares is balanced against the risk of failing to meet demands for spares. Risk is the leitmotiv running through this thesis. The approaches discussed here will find application in a variety of situations where competing risks are being managed within constraints

Maintenance Concept Study for Deep Subsea Tunnels: Rogfast Tunnel as a Case

Today, Norway has 1259 road tunnels, 1185 are categorized as inland tunnels and 41 are categorized as subsea tunnels. In fact, the number of subsea tunnels has doubled in the last 20 years and entering a more challenging era as deeper and longer underwater tunnels are either already built, in progress, or planned. Keeping such complex assets available at minimal operations and maintenance cost requires effective maintenance engineering analysis to be considered during the early design and project phase. Therefore, the purpose of this thesis is to explore the state of the practice of maintenance engineering for deep underwater tunnels, specifically in Norway. To explore that, a case study method has been applied where the Rogfast tunnel is purposefully selected and analysed. Rogfast will be the deepest and longest underwater tunnel in the whole world and it is currently in the middle of the project phase. The case study has focused on the five main aspects of maintenance engineering: technical hierarchy, consequence classification, failure mode analysis, maintenance data exchange, and reliability and availability analysis. The case study has utilized data from existing tunnels, e.g., Ryfylke tunnel, Mastrafjord tunnel and Karmoy tunnel, to extract failure modes, failure rate, mean time to repair. The findings indicate a lack in the current practice of maintenance engineering at the project phase, due to the domination of safety over other consequences like availability, operating cost, and environmental impact. Considering availability, operating cost, and environmental issues provide a more realistic image of the potential operating expenditures. It will also enable the need to collect specific data categories according to standardized technical hierarchy and data exchange framework and initiate analysis regarding potential failure modes, system reliability and availability, prioritizing maintenance concepts and tasks. Therefore, this thesis proposes and demonstrates a more customised technical hierarchy and consequence classification matrix to enable maintenance engineering analysis and maintenance data exchange. It is found that the Rogfast tunnel has a unique configuration due to the roundabout at Kvitsoy that might be utilized to gain a higher level of tunnel availability. It is also demonstrated how new trends and maintenance programs like condition-based, predictive and perspective maintenance can be explored. The methodology applied in this thesis complies with NORSOK Z-008 and is well known for oil and gas sector. However, it is customised in this thesis to fit the tunnel industry