Spare Parts Management for Nuclear Power Generation Facilities

With deregulation, utilities in the power sector face a much more urgent imperative to emphasize cost efficiencies as compared to the days of regulation. One major opportunity for cost savings is through reductions in spare parts inventory. Most utilities are accustomed to carrying large volumes of expensive, relatively slow-moving units because of a high degree of risk-averseness. This attitude towards risk is rooted in the days of regulation. Under regulation, companies recovered capital inventory costs by incorporating them into the base rate charged to its customers. In a deregulated environment, cost recovery is no longer guaranteed. Companies must therefore reexamine their risk profile and develop policies for spare parts inventory that are appropriate for a competitive business environment.This research studies the spare parts inventory management problem in the context of electric utilities, with a focus on nuclear power. It addresses three issues related to this problem: criticality, risk, and policy. With respect to criticality and risk, a methodology is presented that incorporates the use of influence diagrams and the Analytic Hierarchy Process (AHP). A new method is developed for group aggregation in the AHP when Saaty and Vargas' (2007) dispersion test fails and decision makers are unwilling or unable to revise their judgments. With respect to policy, a quantitative model that ranks the importance of keeping a part in inventory and recommends a corresponding stocking policy through the use of numerical simulation is developed. This methodology and its corresponding models will enable utilities that have transitioned from a regulated to a deregulated environment become more competitive in their operations while maintaining safety and reliability standards. Furthermore, the methodology developed is general enough so that other utility plants, especially those in the nuclear sector, will be able to use this approach. In addition to regulated utilities, other industries, such as aerospace and the military, can also benefit from extensions to these models, as risk profiles and subsequent policies can be adjusted to align with the business environment in which each industry or company operates

Creating a climate for food security: the business, people & landscapes in food production

AbstractBalancing human and environmental needs is urgent where food security and sustainability are under pressure from population increases and changing climates. Requirements of food security, social justice and environmental justice exacerbate the impact of agriculture on the supporting ecological environment. Viability of the Australian rural economy is intrinsically linked to food production and food security requiring systematic evaluation of climate change adaptation strategies for agricultural productivity.This food-systems research drew on global climate change literature to identify risks and adaptation. The transdisciplinary team applied specialist experience through collaboration in social science, economics and land-management to provide comprehensive methods to engage researchers and decision-makers making decisions across the food-system. Research focus on the dairy and horticulture sectors in the SW-WA and SEQld provided a comparative context in food-systems and regional economies. Expert knowledge was engaged through a series of panel meetings to test and challenge existing practice applying conceptual and empirical approaches in Structural Equation, Value-Chain, Supply-Chain modelling and Analytical Hierarchy modelling. This iterative action-research process provided immediate generation and transfer of expert knowledge across the involved sectors. The scenarios and adaptive strategies provide evidence-based pathways to strengthen food-systems; account for climate change mitigation and adaptation; and weather-proof regional economies in the face of climate change. Balancing human and environmental needs is urgent where food security and sustainability are under pressure from population increases and changing climates. Requirements of food security, social justice and environmental justice exacerbate the impact of agriculture on the supporting ecological environment. Viability of the Australian rural economy is intrinsically linked to food production and food security requiring systematic evaluation of climate change adaptation strategies for agricultural productivity.This food-systems research drew on global climate change literature to identify risks and adaptation. The transdisciplinary team applied specialist experience through collaboration in social science, economics and land-management to provide comprehensive methods to engage researchers and decision-makers making decisions across the food-system. Research focus on the dairy and horticulture sectors in the SW-WA and SEQld provided a comparative context in food-systems and regional economies. Expert knowledge was engaged through a series of panel meetings to test and challenge existing practice applying conceptual and empirical approaches in Structural Equation, Value-Chain, Supply-Chain modelling and Analytical Hierarchy modelling. This iterative action-research process provided immediate generation and transfer of expert knowledge across the involved sectors. The scenarios and adaptive strategies provide evidence-based pathways to strengthen food-systems; account for climate change mitigation and adaptation; and weather-proof regional economies in the face of climate change. The triple-bottom-line provided a comprehensive means of addressing social, economic and ecological requirements, and the modelling showed the interacting dynamics between these dimensions. In response to climate change, the agricultural sector must now optimise practices to address the interaction between economic, social and environmental investment. Differences in positions between the industry sector, the government and research sectors demonstrate the need for closer relationships between industry and government if climate change interventions are to be effectively targeted. Modelling shows that capacity for adaptation has a significant bearing on the success of implementing intervention strategies. Without intervention strategies to build viability and support, farm businesses are more likely to fail as a consequence of climate change. A framework of capitals that includes social components - cultural, human and social capital-, economic components -economic and physical capital - and ecological components -ecological and environmental capital - should be applied to address capacities. A priority assessment of climate change intervention strategies shows that strategies categorised as ‘Technology & Extension’ are most important in minimising risk from climate change impacts. To implement interventions to achieve ‘Food Business Resilience’, ‘Business Development’ strategies and alternative business models are most effective. ‘Research and Development’ interventions are essential to achieve enhanced ‘Adaptive Capacity’.The individual components of TBL Adaptive Capacity can be achieved through ‘Policy and Governance’ interventions for building ‘Social Capital’ capacity, ‘Research and Development’ will develop ‘Economic Capital’, and ‘Business Development’ strategies will build ‘Ecological Capital’.These strategic interventions will promote food security and maintain resilience in local food systems, agricultural production communities and markets, global industrial systems, and developing world food systems. Climate change mitigation and adaptation interventions reflect a rich conceptualisation drawing from the Australian context, but also acknowledging the moral context of global association.Please cite this report as:Wardell-Johnson, A, Uddin, N, Islam, N, Nath, T, Stockwell, B, Slade, C 2013 Creating a climate for food security: the businesses, people and landscapes in food production, National Climate Change Adaptation Research Facility, Gold Coast, pp. 144.Balancing human and environmental needs is urgent where food security and sustainability are under pressure from population increases and changing climates. Requirements of food security, social justice and environmental justice exacerbate the impact of agriculture on the supporting ecological environment. Viability of the Australian rural economy is intrinsically linked to food production and food security requiring systematic evaluation of climate change adaptation strategies for agricultural productivity.This food-systems research drew on global climate change literature to identify risks and adaptation. The transdisciplinary team applied specialist experience through collaboration in social science, economics and land-management to provide comprehensive methods to engage researchers and decision-makers making decisions across the food-system. Research focus on the dairy and horticulture sectors in the SW-WA and SEQld provided a comparative context in food-systems and regional economies. Expert knowledge was engaged through a series of panel meetings to test and challenge existing practice applying conceptual and empirical approaches in Structural Equation, Value-Chain, Supply-Chain modelling and Analytical Hierarchy modelling. This iterative action-research process provided immediate generation and transfer of expert knowledge across the involved sectors. The scenarios and adaptive strategies provide evidence-based pathways to strengthen food-systems; account for climate change mitigation and adaptation; and weather-proof regional economies in the face of climate change. The triple-bottom-line provided a comprehensive means of addressing social, economic and ecological requirements, and the modelling showed the interacting dynamics between these dimensions. In response to climate change, the agricultural sector must now optimise practices to address the interaction between economic, social and environmental investment. Differences in positions between the industry sector, the government and research sectors demonstrate the need for closer relationships between industry and government if climate change interventions are to be effectively targeted. Modelling shows that capacity for adaptation has a significant bearing on the success of implementing intervention strategies. Without intervention strategies to build viability and support, farm businesses are more likely to fail as a consequence of climate change. A framework of capitals that includes social components - cultural, human and social capital-, economic components -economic and physical capital - and ecological components -ecological and environmental capital - should be applied to address capacities. A priority assessment of climate change intervention strategies shows that strategies categorised as ‘Technology & Extension’ are most important in minimising risk from climate change impacts. To implement interventions to achieve ‘Food Business Resilience’, ‘Business Development’ strategies and alternative business models are most effective. ‘Research and Development’ interventions are essential to achieve enhanced ‘Adaptive Capacity’.The individual components of TBL Adaptive Capacity can be achieved through ‘Policy and Governance’ interventions for building ‘Social Capital’ capacity, ‘Research and Development’ will develop ‘Economic Capital’, and ‘Business Development’ strategies will build ‘Ecological Capital’.These strategic interventions will promote food security and maintain resilience in local food systems, agricultural production communities and markets, global industrial systems, and developing world food systems. Climate change mitigation and adaptation interventions reflect a rich conceptualisation drawing from the Australian context, but also acknowledging the moral context of global association

Opposites Attract: An Approach to Collaborative Supply Chain Management between Semiconductor and Automotive Companies

This article illustrates the differences between the semiconductor and the automotive industry and the subsequent challenges to their common supply chain. The weak points at the interfaces between the two supply chains will systematically be identified and assessed. Based on this analysis, a toolkit for collaborative supply chain planning and execution between the automotive and the semiconductor industry is presented. A fit/gap analysis assesses the measures and their potential to solve the supply chain challenges in a systematic manner. The model is built upon existing supply chain management frameworks and defines a set of specific optimization measures for the problem at hand. These are designed to ensure a better alignment of planning and control processes between the automotive and the semiconductor industry

Strategic supplier performance evaluation::a case-based action research of a UK manufacturing organisation

The main aim of this research is to demonstrate strategic supplier performance evaluation of a UK-based manufacturing organisation using an integrated analytical framework. Developing long term relationship with strategic suppliers is common in today׳s industry. However, monitoring suppliers׳ performance all through the contractual period is important in order to ensure overall supply chain performance. Therefore, client organisations need to measure suppliers׳ performance dynamically and inform them on improvement measures. Although there are many studies introducing innovative supplier performance evaluation frameworks and empirical researches on identifying criteria for supplier evaluation, little has been reported on detailed application of strategic supplier performance evaluation and its implication on overall performance of organisation. Additionally, majority of the prior studies emphasise on lagging factors (quality, delivery schedule and value/cost) for supplier selection and evaluation. This research proposes both leading (organisational practices, risk management, environmental and social practices) and lagging factors for supplier evaluation and demonstrates a systematic method for identifying those factors with the involvement of relevant stakeholders and process mapping. The contribution of this article is a real-life case-based action research utilising an integrated analytical model that combines quality function deployment and the analytic hierarchy process method for suppliers׳ performance evaluation. The effectiveness of the method has been demonstrated through number of validations (e.g. focus group, business results, and statistical analysis). Additionally, the study reveals that enhanced supplier performance results positive impact on operational and business performance of client organisation

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

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

Multiple criteria approach applied to digital transformation in fashion stores: the case of physical retailers in Spain

This research is funded by the Spanish State Research Agency, as part of the project PID2019103880RB-I00/AEI/10.13039/501100011033, and by the Andalusian Government, as part of the project P20_00673.In a very open competitive context where pure online players are consistently gaining market share, the use of digital devices is a steady trend which is penetrating physical retail stores as a tool for retailers to improve customer experience and increase engagement. This need has increased with the COVID-19 pandemic as electronic devices in physical stores reduce the contact between people providing a greater sense of health safety, hence improving the customer experience. This work develops a multiple-criteria decision-making model for retailers who want to digitize their physical stores, providing a systematic approach to manage investment priorities in the organization. Important decisions should involve all different areas of the organization: Finance, Clients, Internal Processes and Learning & Growth departments. This strategic decision can be made hierarchically to obtain consistent decisions, also the use of the Order Weighted Average operator allows for alternative scenarios to be presented and agreed among the different areas of the business. The authors develop a use case for a Spanish fashion retailer. In the most widely agreed scenario the preferred devices were more technologically complex and expensive, while in the scenarios where the head of Finance is more predominant, cheaper and simpler devices were selected.Spanish Government PID2019103880RB-I00/AEI/10.13039/501100011033Andalusian Government P20_0067

OVID-BV : optimising value in decision making for best value in the UK social housing sector

The Governments’ promotion and support of Best Value within the Social Housing Sector has been a prime catalyst in the move by Registered Social Landlord’s [RSL’s] away from the traditional culture of acceptance of the lowest bid towards consideration of both price and quality criteria as a basis for contractor selection. Manifestly this radical change in the way the sector procures its construction services has forced many of its stakeholders to undergo significant cultural and organisational changes within a relatively short period of time, and problems have developed during this transitional period that have affected the efficiency of the best value process. This research traced the root causes of these problems and its overarching aim was to develop an approach which will enable RSL’s and their stakeholders to streamline the best value tender analysis procedure thereby allowing tenders to be dealt with effectively and efficiently whilst also creating a transparent and auditable decision making process. The approach has been established using a mixed methods research methodology utilising; case studies, surveys, rational decision analysis and system evaluation. The main output of the research is the development of a support tool known by the acronym OVID-BV which aids the multi objective decision making process. The underlying rationale for the support tool is based on the innovative use of uncertainty in decision making and the functionality of the tool uses a combination of the analytical hierarchy process (AHP), multi attribute utility theory (MAUT) and whole life costing (WLC)

An information model for lean, agile, resilient and green supply chain management

Dissertação para a obtenção de Grau de Mestre em Engenharia e Gestão IndustrialIn modern business environments, an effective Supply Chain Management (SCM) is crucial to business continuity. In this context, Lean, Agile, Resilient and Green (LARG), are advocated as the fundamental paradigm for a competitive Supply Chain (SC) as a whole. In fact, competition between supply chains (SC) has replaced the traditional competition between companies. To make a supply chain more competitive, capable of responding to the demands of customers with agility, and capable of responding effectively to unexpected disturbance, in conjugation with environmental responsibilities, and the necessity to eliminate processes that add no value, companies must implement a set of LARG SCM practices and Key Performance Indicators (KPI) to measure their influence on the SC performance. However, the selection of the best LARG SCM practices and KPIs is a complex decision-making problem, involving dependencies and feedbacks. Still, any decision-making must be supported by real and transparent data. This dissertation intends to provide two integrated models to assist the information management and decision-making. The first is an information model to support a LARG SCM, allowing the exchange and storage of data/information through a single information platform. In this model three types of diagrams are developed, Business Process Diagram (BPD), Use Cases Diagram and Class Diagram to assist the information platform design. The second is a decision-making model, designated LARG Analytical Network Process (ANP) to select the best LARG SCM practices/KPI to be implemented in SCs. Both models are developed and validated within the automotive SC, namely in Volkswagen Autoeuropa