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Träfflista för sökning "WFRF:(Sharma Pankaj) ;pers:(Campos Jaime)"

Sökning: WFRF:(Sharma Pankaj) > Campos Jaime

  • Resultat 1-10 av 16
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1.
  • Albano, Michele, et al. (författare)
  • Energy Saving by Blockchaining Maintenance.
  • 2018
  • Ingår i: Journal of Industrial Engineering and Management Science. - : River Publishers. - 2446-1822. ; 2018:1, s. 63-88
  • Tidskriftsartikel (refereegranskat)abstract
    • The development and interest in Industry 4.0 together with rapid development of Cyber Physical Systems has created magnificent opportunities to develop maintenance to a totally new level. The Maintenance 4.0 vision considers massive exploitation of information regarding factories and machines to improve maintenance efficiency and efficacy, for example by facilitating logistics of spare parts, but on the other hand this creates other logistics issues on the data itself, which only exacerbate data management issues that emerge when distributed maintenance platforms scale up. In fact, factories can be delocalized with respect to the data centers, where data has to be transferred to be processed. Moreover, any transaction needs communication, be it related to purchase of spare parts, sales contract, and decisions making in general, and it has to be verified by remote parties. Keeping in mind the current average level of Overall Equipment Efficiency (50%) i.e. there is a hidden factory behind every factory, the potential is huge. It is expected that most of this potential can be realised based on the use of the above named technologies, and relying on a new approach called blockchain technology, the latter aimed at facilitating data and transactions management. Blockchain supports logistics by a distributed ledger to record transactions in a verifiable and permanent way, thus removing the need for multiple remote parties to verify and store every transaction made, in agreement with the first “r” of maintenance (reduce, repair, reuse, recycle). Keeping in mind the total industrial influence on the consumption of natural resources, such as energy, the new technology advancements can allow for dramatic savings, and can deliver important contributions to the green economy that Europe aims for. The paper introduces the novel technologies that can support sustainability of manufacturing and industry at large, and proposes an architecture to bind together said technologies to realise the vision of Maintenance 4.0.
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2.
  • Baglee, David, et al. (författare)
  • How can SMEs adopt a new method to advanced maintenance strategies : A Case study approach
  • 2018
  • Ingår i: Conference Proceedings: 30th International Conference on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2017). - : University of Central Lancashire. - 9781909755154 ; , s. 155-162
  • Konferensbidrag (refereegranskat)abstract
    • Maintenance is crucial to manufacturing operations. In many organisations, the production equipmentrepresents the majority of invested capital, and deterioration of these facilities and equipment increasesproduction costs, reduces product quality. Over recent years the importance of maintenance, and thereforemaintenance management, within manufacturing organisations has grown. The maintenance function hasbecome an increasingly important and complex activity, particularly as automation increases. Theopportunity exists for many organisations to benefit substantially through improvements to theircompetitiveness and profitability by adopting a new approach to maintenance management. Several toolsand technologies including Condition Based Maintenance (CBM), Reliability Centred Maintenance (RCM)and more recently e-maintenance have developed under the heading of Advanced Maintenance Strategies.However, the adoption of advanced maintenance strategies and their potential benefits are usuallydemonstrated in large organisations. Unfortunately, the majority of organisations are constrained by thelack of knowledge and understanding on the requirements, which need to be in place before adopting anadvanced maintenance strategy. These are usually classified as Small and Medium Sized Enterprises(SMEs).The research strategy is based on ‘empirical iterations’ using survey secondary data, experts’ interviewsinformation and multiple case studies. The results show that there is a set of recommendations, whichstrongly influence the implementation of an Advanced Maintenance Strategy (AMS) with a Small toMedium Enterprise (SME). Organisations require a structured and integrative approach in order to takeadvantage of a new approach to maintenance management. This paper will propose recommendations forintegrating an AMS into the organisation and provide evidence of a successful implementation.
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3.
  • Baglee, David, et al. (författare)
  • How Does CBM Function in the Real World?
  • 2016
  • Ingår i: MFPT 2015 and ISA’s 61st International Instrumentation Symposium, At Dayton. Ohio.
  • Konferensbidrag (refereegranskat)abstract
    • Manufacturing organizations are under increasing pressure to meet customer and corporate demands by implementing improved maintenance initiatives to reduce costs, improve equipment availability, and protect against failure of critical equipment. Condition Based Maintenance (CBM) is widely accepted and used as a financially effective maintenance strategy which is used to anticipate equipment or component failure. Recent technological advances in component sensitivities, size reductions, and most importantly, cost has opened up an entirely new area of diagnostics. The economic benefit of CBM is achieved if the approach to maintenance is applied to the right equipment and through appropriate tools. In particular the degradation behavior of the equipment needs to be understood to correctly deploy a CBM approach and specific actions to specific equipment or components. Failure modes can be applied to support and optimise the decision making process. Using failure modes can be an efficient low-risk tool process for the prevention of problems, and is referred to as a deductive technique that consists of failure identification in each component. However, the literature is limited regarding the importance and the role of various failure models in different industrial sectors. Thus, if failure models are not known, understood and utilised correctly the use of CBM will not lead to financial benefits. The paper examines the relationship between the failure patterns observed in industrial maintenance practice and the corresponding impact on adoption and potential benefits of Condition-Based Maintenance (CBM). The paper will explain the need for accurate and up to date equipment information to support the correct maintenance approach. The paper suggests the importance of further supporting such investments by appropriately addressing the need to collect relevant data as a basis upon which to make the right decisions.
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4.
  • Baglee, David, et al. (författare)
  • Optimizing Condition Monitoring of Big Data Systems
  • 2017
  • Ingår i: Proceedings of the 2017 International Conference on Data Mining. - : CSREA Press. - 1601324537 ; , s. 127-131
  • Konferensbidrag (refereegranskat)abstract
    • Industrial communication networks are common in a number of manufacturing organisations. The high availability of these networks is crucial for smooth plant operations. Therefore local and remote diagnostics of these networks is of primary importance in determining issues relating to plant reliability and availability. Condition Monitoring (CM) techniques when connected to a network provide a diagnostic system for remote monitoring of manufacturing equipment. The system monitors the health of the network and the equipment and is therefore able to predict performance. However, this leads to the collection, storage and analyses of large amounts of data, which must provide value. These large data sets are commonly referred to as Big Data. This paper presents a general concept of the use of condition monitoring and big data systems to show how they complement each other to provide valuable data to enhance manufacturing competiveness.
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5.
  • Campos, Jaime, et al. (författare)
  • A big data analytical architecture for the Asset Management
  • 2017
  • Ingår i: Industrial Product/Service-Systems (IPSS) Conference. - : Elsevier. ; , s. 369-374
  • Konferensbidrag (refereegranskat)abstract
    • The paper highlights the characteristics of data and big data analytics in manufacturing, more specifically for the industrial asset management. The authors highlight important aspects of the analytical system architecture for purposes of asset management. The authors cover the data and big data technology aspects of the domain of interest. This is followed by application of the big data analytics and technologies, such as machine learning and data mining for asset management. The paper also presents the aspects of visualisation of the results of data analytics. In conclusion, the architecture provides a holistic view of the aspects and requirements of a big data technology application system for purposes of asset management. The issues addressed in the paper, namely equipment health, reliability, effects of unplanned breakdown, etc., are extremely important for today's manufacturing companies. Moreover, the customer's opinion and preferences of the product/services are crucial as it gives an insight into the ways to improve in order to stay competitive in the market. Finally, a successful asset management function plays an important role in the manufacturing industry, which is dependent on the support of proper ICTs for its further success. (C) 2017 The Authors Published by Elsevier B.V.
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6.
  • Campos, Jaime, et al. (författare)
  • An Open Source Framework Approach to Support Condition Monitoring and Maintenance
  • 2020
  • Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 10:18, s. 1-17
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper discusses the integration of emergent ICTs, such as the Internet of Things (IoT), the Arrowhead Framework, and the best practices from the area of condition monitoring and maintenance. These technologies are applied, for instance, for roller element bearing fault diagnostics and analysis by simulating faults. The authors first undertook the leading industry standards for condition-based maintenance (CBM), i.e., open system architecture–condition-based maintenance (OSA–CBM) and Machinery Information Management Open System Alliance (MIMOSA), which has been working towards standardizing the integration and interchangeability between systems. In addition, this paper highlights the predictive health monitoring methods that are needed for an effective CBM approach. The monitoring of industrial machines is discussed as well as the necessary details are provided regarding a demonstrator built on a metal sheet bending machine of the Greenbender family. Lastly, the authors discuss the benefits of the integration of the developed prototypes into a service-oriented platform, namely the Arrowhead Framework, which can be instrumental for the remotization of maintenance activities, such as the analysis of various equipment that are geographically distributed, to push forward the grand vision of the servitization of predictive health monitoring methods for large-scale interoperability.
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7.
  • Campos, Jaime, et al. (författare)
  • Arrowhead Framework services for condition monitoring and maintenance based on the open source approach
  • 2019
  • Ingår i: 6th International Conference on Control Decision Information Technologies (CoDIT 2019). - : IEEE. - 9781728105215 - 9781728105208 - 9781728105222 ; , s. 697-702
  • Konferensbidrag (refereegranskat)abstract
    • The emergence of new Information and Communication Technologies, such as the Internet of Things and big data and data analytics provides opportunities as well as challenges for the domain of interest, and this paper discusses their importance in condition monitoring and maintenance. In addition, the Open system architecture for condition-based maintenance (OSA-CBM), and the Predictive Health Monitoring methods are gone through. Thereafter, the paper uses bearing fault data from a simulation model with the aim to produce vibration signals where different parameters of the model can be controlled. In connection to the former mentioned a prototype was developed and tested for purposes of simulated rolling element bearing fault systems signals with appropriate fault diagnostic and analytics. The prototype was developed taking into consideration recommended standards (e.g., the OSA-CBM). In addition, the authors discuss the possibilities to incorporate the developed prototype into the Arrowhead framework, which would bring possibilities to: analyze various equipment geographically dispersed, especially in this case its rolling element bearing; support servitization of Predictive Health Monitoring methods and large-scale interoperability; and, to facilitate the appearance of novel actors in the area and thus competition.
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8.
  • Campos, Jaime, et al. (författare)
  • Business Performance Measurements in Asset Management with the Support of Big Data Technologies
  • 2017
  • Ingår i: Management Systems in Production Engineering. - : De Gruyter Open. - 2299-0461 .- 2450-5781. ; 25:3, s. 143-149
  • Tidskriftsartikel (refereegranskat)abstract
    • The paper reviews the performance measurement in the domain of interest. Important data in asset management are further, discussed. The importance and the characteristics of today’s ICTs capabilities are also mentioned in the paper. The role of new concepts such as big data and data mining analytical technologies in managing the performance measurements in asset management are discussed in detail. The authors consequently suggest the use of the modified Balanced Scorecard methodology highlighting both quantitative and qualitative aspects, which is crucial for optimal use of the big data approach and technologies.
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9.
  • Campos, Jaime, et al. (författare)
  • Business performance measurements in asset management with the support of big data technologies
  • 2016
  • Ingår i: Proceedings of MPMM 2016. - : Luleå tekniska universitet. - 9789175838410 ; , s. 89-95
  • Konferensbidrag (refereegranskat)abstract
    • The paper reviews the performancemeasurement in the domain of interest. Important data in assetmanagement are further, discussed. The importance and thecharacteristics of today’s ICTs capabilities are also mentionedin the paper. The role of new concepts such as big data anddata mining analytical technologies in managing theperformance measurements in asset management are discussedin detail. The authors consequently suggest the use of themodified Balanced Scorecard methodology highlighting bothquantitative and qualitative aspects, which is crucial foroptimal use of the big data approach and technologies.
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10.
  • Campos, Jaime, et al. (författare)
  • The challenges of cybersecurity frameworks to protect data required for the development of advanced maintenance
  • 2016
  • Ingår i: Product-Service Systems Across Life Cycle. - : Elsevier. ; , s. 222-227
  • Konferensbidrag (refereegranskat)abstract
    • The main objective of the paper is to highlight the important aspects of the data management in condition monitoring and maintenance, especially when the emergent technologies, such as the cloud computing and big data, are to be considered in the maintenance department. In addition, one of the main data management elements highlighted in the current work are the cybersecurity issues which might be one of the biggest obstacles hindering the development of cloud based big data for condition-based maintenance (CBM) purposes. Further, the benefits and current risks of storing a company's data in the cloud are highlighted. The authors discuss as well different data needs in various processes in the area of asset management. In addition, the challenges and issues to be addressed for the optimal use of the company data at the cloud together with the big data approach are addressed. This is seen as an important part in an effort to achieve sustainable information and communication technologies for the industry.
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