EN - LIGM - Linha de Investigação em Gestão da Manutenção
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- Advanced Methodologies Applied in a Dynamic Maintenance ContextPublication . Lampreia, S.; Lobo, Victor; Vairinhos, V.Maintaining military systems in a dynamic context presents unique challenges that require advanced methodologies to ensure the operational readiness and effectiveness of the Armed Forces. This article analyses and discusses advanced methodologies applied in the maintenance of military technology, highlighting their contributions to the optimization of the maintenance process in constantly evolving operational environments. Initially, we address the importance of predictive maintenance, which uses techniques such as real-time data analysis, condition monitoring and machine learning algorithms to predict failures and proactively schedule maintenance interventions. This approach minimizes downtime, and costs associated with corrective maintenance, significantly increasing the availability of military systems. Additionally, we explore the application of emerging technologies, databases and the use of smart sensors integrated into military equipment. These technologies enable the continuous collection of performance and condition data, enabling a more comprehensive understanding of the state of each component and system. This not only facilitates early detection of anomalies, but also supports data driven decision making, resulting in more efficient and accurate maintenance. The use of condition-based maintenance approaches is also discussed in this article. These methodologies consider not only the age or time of use of the equipment, but also its actual state of operation. By continuously monitoring operating conditions, it is possible to extend the life of systs, reduce unnecessary wear and tear, and plan maintenance interventions more effectively. Finally, we highlight the importance of integrating computer-aided maintenance management systems and decision support systems. The combination of these tools provides a comprehensive environment for planning, executing and analysing maintenance activities, enabling more efficient resource management and a more agile response to operational demands. In short, this article demonstrates how the adoption of advanced methodologies in the maintenance of military technology is fundamental to ensuring the operational readiness and effectiveness of the Armed Forces in a dynamic and constantly evolving context.
- Comparative Analysis on Country Reputation through Patterns of Intellectual Capital: The case Portugal Versus Romania.Publication . Vairinhos, Valter MartinsIn the last decade the world economy has undergone numerous transformations that have changed the way we evaluate the assets of organizations, cities and countries. In this context, Intellectual Capital (IC) and Knowledge Management (KM), based on the management of intangible assets, became a factor of differentiation and competitiveness. The way countries are dealing with IC and knowledge management is a decisive factor in their international reputation, which in turn acts as country branding. Country branding is the image of a nation-state and from the link between this image and the success of its economy, corresponding to its competitiveness, its richness, the efficiency of the state and the quality of life of its citizens, among others. Reputable countries usually attract more investment and, consequently, are more innovative. While some decision makers argue that economic development should focus on investment and the creation of jobs, many studies have shown that this growth should be underpinned by the proper management of IC in all its dimensions. Assuming that is proved a cause-effect relationship between IC management and innovation - the most innovative countries are those with a better IC management and vice versa - the purpose of this study is to search for empirical evidence of a possible relationship between these indicators and the reputation of the countries. If it is possible to identify a connection between the variables that compose each index, we can design patterns that can guide the management of international branding strategy of each country. This paper uses multivariate data analyses techniques, including biplots methodology, in its attempt to study the case of Portugal versus Romania. These countries have different indicators, but both have problems in reputation management. In terms of originality, this empirical study aims to create discussions about the factors that determine the reputation of these countries.
- Control Charts Limits Flexibility Based on the Equipment ConditionsPublication . Lampreia, Suzana Paula Gomes Fernando da Silva; Vairinhos, Valter Martins; Lobo, Victor J. A. S.; Parreira, Rui; Requeijo, José GomesCondition Based Maintenance became an important development in industrial and transport equipment maintenance efforts. Many statistical methodologies have been applied in this area. These methodologies are usually applied off-line: after the data is collected. We propose an online, real-time condition monitoring system based on a modified control chart, applied to engine parameters. These charts should be flexible enough and its control limits should reflect the equipment state, the manufacturer specifications and onboard meteorological conditions. In this study we will develop a methodology to specify flexible chart control limits. The experimental equipment is a combined diesel or gas propulsion system. Two phases will be assumed. In phase 1 the equipment and historical data are analyzed, studying historical data, which leads to the definition of equipment parameters. In phase 2, new data is obtained by simulation, and the Exponentially Weighted Moving Average charts are applied considering flexible limits.
- Diesel Engine Condition Monitoring Due to Different Operation AreasPublication . Lampreia, Suzana Paula Gomes Fernando da Silva; Lobo, Victor J. A. S.; Requeijo, José GomesWhen a ship design is developed, its engines are installed accordingly the owner requisites and the environment conditions in the designated operation area. Usually they are not adapted to sail all over the world. This implies that in some cases the power output cannot be the same for the safety of the engine, If a engine was conceived to operate on 16ºC of ocean sea, when it navigates on a 36ºC ocean, the engine power must be limited in order to not provoke major damage. Due to the fact, in this study two diesel engines will be monitor with online data collection and statistical treatment. The statistic treatment will be with the univariate control charts. With the engines operating on a range of ocean temperatures form 16ºC to 36ºC, the power limitatiom and the systems must be flexible due the use of the engines and consequently the use of ships over sea.
- Dynamic Maintenance Based on Fuzzy LogicPublication . Lampreia Suzana; Mestre, Inês; Morgado T. & Navas H.Currently, certain maritime assets are confronted with the challenge of optimizing their performance, even when resources are limited. They strive to minimize intervention actions on equipment while upholding safety standards and acceptable performance levels. Ships, which are not yet autonomous, serve as maritime assets responsible for transporting personnel and systems. Maintaining these ships with high performance is imperative to ensuring the safety of both material and personnel. This not only prevents damage to the ships themselves but also mitigates the potential for personnel injuries and sea pollution. Organizations, scientific community, and stakeholders have been actively developing advanced systems to monitor data from ship equipment within the scope of maintenance management. This helps in preventing breakdowns and ensures real time knowledge about the equipment's condition. These systems employ various techniques for condition control using algorithms, statistical equations, and other methodologies on the collected data. In this investigation Fuzzy Logic will be applied to data from a selected equipment. For the case study, an air compressor from an ocean patrol vessel has been selected. This air compressor plays a crucial role on Navy ships and has been chosen by the Organization's Maintenance Management Centre for monitoring working hours and operational status.
- Implementation of MEWMA Control Chart in Equipment Condition MonitoringPublication . Lampreia, Suzana Paula Gomes Fernando da Silva; Vairinhos, Valter Martins; Requeijo, José Gomes; Dias, J. M.The progressive degradation of presently operating electro-mechanical systems is a certain future fact. To minimize losses, maintenance costs and eventual replacements, condition monitoring should be applied to critical equipment (Condition Based Maintenance – CBM). The state of equipment can be predicted at any moment using statistical methods to analyze condition monitoring data. In this paper, collected data are vibration values, obtained at p points (p = 4 for instance) of an experimental equipment, forming p variables. When independence condition does not hold, it is suggested modeling data with Auto-Regressive Integrated Moving Average (ARIMA) models, and using the residues of the estimated model for Phase I. In Phase I, the estimation of parameters is achieved using the Hotelling T control chart; only after applying the defined ARIMA model, the p variables are treated. In Phase II, equipment state is artificially degraded through induced failures and failure prediction obtained using special multivariate control charts for data statistical treatment. Assuming data independence and normality, Multivariate Exponentially Weighted Moving Average Modified (MEWMAM) control charts are applied in Phase II to data collected from an electric pump, controlling the behavior of data using this procedure. In Phase II, for non-independent data the prediction errors from the adjusted model are used instead of original data. To show that the suggested methodology can be applied to propulsion systems, simulated data from a gas turbine are used. Using these methodologies it is possible to run online condition monitoring, and act in time, to minimize maintenance costs and maximize equipment performance.
- Leveraging intellectual capital through Lewin’s force field analysis (the case of software development companies)Publication . Vairinhos, Valter MartinsThis article outlines an original conceptual framework for the strategic management of intellectual capital assets in software development companies, interconnected with force field analysis approach. The framework allows assessing the opinions of the managers from software companies about the impact of both driving and restraining forces on the pillars of intellectual capital. Considering the capacity to adapt to change as one of the most relevant for the companies from knowledge intensive industries, this research uses a sample of 74 software development companies located in Romania to offer valuable insights on foresight capabilities to enable change benefits by managing the driving forces, respectively the restraining forces, at the level of IC pillars (human, structural and relational). The findings, represented by the average scores per each item embedded in the conceptual framework, show that the driving forces’ effects, quantified by means of PathMaker software’s Force Field Tool, are more significant than the restraining forces to change, in the case of each IC pillar. This paper’s original contribution consists of the explanatory power of the proposed framework to managers’ needs to find answers in the scientific research community to their challenging responsibility to drive change in their organizations through effective IC management. Furthermore, the article describes how the validation of the results encourages the implementation of change that aim to create value for the software development companies.
- Machine Learning applied to LCA of mechanical components obtained by SLMPublication . Alves, J.; Morgado, Pereira M.; Lampreia, S.Over time, industries are starting to be concern about their impact on the environment, and therefore new technologies, have arrived with the capability of improving the sustainability of the industrial paradigm. Machine Learning (ML) and Artificial Intelligence (AI) are taking over the global industry, by offering new data drive solutions capable of optimizing decision-making and operation. Meanwhile, new advanced manufacturing technologies such as Selective Laser Melting (SLM), also known as 3D printing, are spreading through the market, due to the new doors unlocked by the possibility of manufacturing high for a minimal time and use of material. Together, these new technologies of industry 4.0, promise to bring an all-new future, sustainable and resilient. The aim of this work is to analyze how can ML and AI expand each phase of the LCA of a light alloy, produced by SLM, in order to improve the sustainability of this new advanced manufacturing technologies.
- Mapping the intellectual capital of cities and regionsPublication . Vairinhos, Valter MartinsContemporary cities or regions have complex challenges that require ongoing monitoring enabling intelligent answers in an appropriate period of time. There are many studies that indicate that this monitoring should take into account not only the tangible assets, but also the assets of intellectual capital. Several authors consider that these are the assets that are crucial either in sustainable innovation processes either in the process of developing the necessary reputation for building strong brands, able to attract talented people and investments. Based on the literature review and preliminary studies that compare the metrics for evaluating the intellectual capital of companies with the intellectual capital of the countries, this paper presents a theoretical model supporting the auditing and the mapping of intellectual capital management of cities and regions. This process is based on the creation of sensors for monitoring the intellectual capital and on the evaluation of how these are managed so as to support the decision making of the decision-makers and economic policy-makers. With this paper we intend to broaden the discussion on the importance of the decision makers of the strategies of cities or regions to support their choices on criteria that take into account the assets of intellectual capital.
- Navy Ship Dynamic MaintenancePublication . Lampreia, S.; Vairinhos, V.; Lobo, V.A maintenance system complemented with condition monitoring is suggest being implemented in Navy Ships to allow its patrol on the large maritime territory of Portugal with high performance and operationality. To that an advanced maintenance system is required oriented towards Condition Monitoring. That must be done while maximizing system performance, as well as improved high level of ship availability and minimal oil consumption in the form e.g. lubricants or refrigerant gases but also marine gasoil reducing the environment impact. To meet these objectives, we propose the development of a Dynamic Maintenance Management System (DMMS) based on dynamic prioritization process for technical interventions. That is where Failure Modes, Effects and Criticality Analysis (FMECA) comes in - a structured risk analysis framework to mitigate the propensity of failures occurring with consequences on ship systems and persons. With FMECA, maintenance priorities can be changed somewhat dynamically due to components and failure modes that are most critical based on actual performance.