Search results for "smart"

showing 10 items of 938 documents

Internal model-based feedback control design for inversion-free feedforward rate-dependent hysteresis compensation of piezoelectric cantilever actuat…

2018

Abstract This study proposes a new rate-dependent feedforward compensator for compensation of hysteresis nonlinearities in smart materials-based actuators without considering the analytical inverse model. The proposed rate-dependent compensator is constructed with the inverse multiplicative structure of the rate-dependent Prandtl–Ishlinskii (RDPI) model. The study also presents an investigation for the compensation error when the proposed compensator is applied in an open-loop feedforward manner. Then, an internal model-based feedback control design is applied with the proposed feedforward compensator to a piezoelectric cantilever actuator. The experimental results illustrate that the propo…

0209 industrial biotechnologyComputer scienceApplied MathematicsFeedback controlInternal modelFeed forwardInverseInversion (meteorology)02 engineering and technology021001 nanoscience & nanotechnologyMotion controlSmart materialComputer Science::OtherComputer Science Applications020901 industrial engineering & automationControl and Systems EngineeringControl theoryElectrical and Electronic Engineering0210 nano-technologyActuatorControl Engineering Practice
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Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments — a case study

2019

Traditional industry is seeing an increasing demand for more autonomous and flexible manufacturing in unstructured settings, a shift away from the fixed, isolated workspaces where robots perform predefined actions repetitively. This work presents a case study in which a robotic manipulator, namely a KUKA KR90 R3100, is provided with smart sensing capabilities such as vision and adaptive reasoning for real-time collision avoidance and online path planning in dynamically-changing environments. A machine vision module based on low-cost cameras and color detection in the hue, saturation, value (HSV) space is developed to make the robot aware of its changing environment. Therefore, this vision a…

0209 industrial biotechnologyComputer scienceMachine visionTKReal-time computingRobot manipulator02 engineering and technologyWorkspaceAdaptive Reasoninglcsh:Chemical technologyBiochemistryHuman–robot interactionArticleAnalytical ChemistrySettore ING-IND/14 - Progettazione Meccanica E Costruzione Di Macchinehuman-robot interaction020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineeringlcsh:TP1-1185Motion planningElectrical and Electronic EngineeringInstrumentationpath planningCollision avoidancerobot controlsmart sensingAdaptive reasoningdynamic environmentsAtomic and Molecular Physics and OpticsRobot control:Engineering::Mechanical engineering [DRNTU]ObstacleDynamic EnvironmentsRobot020201 artificial intelligence & image processingadaptive reasoning
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Experimental results on the economic management of a smart microgrid

2020

The aim of this paper is to assess economic benefits deriving from the adoption of a smart microgrid. To this end, a case study consisting of 250 houses connected to the distribution network through a MV/LV transformer substation has been investigated and implemented in the experimental microgrid built at the Polytechnic University of Bari, Italy. The analysis has been performed by comparing three different energy providers: the utility grid, the utility grid with the inclusion of non-programmable renewables generators, and the inclusion of such residential loads into a smart microgrid. The obtained results demonstrated that with the adoption of a smart microgrid significant costs savings c…

0209 industrial biotechnologyComputer sciencemicrogrids020209 energyeconomic analysi02 engineering and technologylaw.invention020901 industrial engineering & automationgrid-connected operationlaw0202 electrical engineering electronic engineering information engineeringTransformerbusiness.industryEconomic analysis; economic dispatch; grid-connected operation; microgridseconomic dispatchEconomic dispatchEconomic analysisGridEconomic benefitsRenewable energyReliability engineeringSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiamicrogridSmart microgridEconomic managementMicrogridbusiness
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Propulsion monitoring system for digitized ship management: Preliminary results from a case study

2020

Abstract The paradigm of Industry 4.0 a fundamental driver of innovation in marine industry, where the new digital era will see the development of smart cyber-ships equipped with advanced automation systems that will progressively evolve towards fully autonomous vessels. Although the journey towards such technological frontier has started, most companies operating in the maritime sector still appear un-prepared to face the future scenario. In the maritime sector, in fact, empirical models and oversimplified approaches are still largely employed for the management of fleet operations. There is thus the necessity of developing and providing operative models for digitized ship management, whic…

0209 industrial biotechnologyDecision support systemShip managementcontinuous engine monitoring systemsmart shipbusiness.industryDigital eraComputer scienceMonitoring systemContext (language use)02 engineering and technologyPropulsionIndustry 4.0AutomationGeneralLiterature_MISCELLANEOUSIndustrial and Manufacturing Engineering020303 mechanical engineering & transports020901 industrial engineering & automation0203 mechanical engineeringRisk analysis (engineering)Artificial IntelligenceOrder (exchange)Settore ING-IND/17 - Impianti Industriali Meccanicibusiness
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Industry 4.0 Technologies for Manufacturing Sustainability: A Systematic Review and Future Research Directions

2021

Recent developments in manufacturing processes and automation have led to the new industrial revolution termed “Industry 4.0”. Industry 4.0 can be considered as a broad domain which includes: data management, manufacturing competitiveness, production processes and efficiency. The term Industry 4.0 includes a variety of key enabling technologies i.e., cyber physical systems, Internet of Things, artificial intelligence, big data analytics and digital twins which can be considered as the major contributors to automated and digital manufacturing environments. Sustainability can be considered as the core of business strategy which is highlighted in the United Nations (UN) Sustainability 2030 age…

0209 industrial biotechnologyEngineeringTechnologyIndustry 4.0QH301-705.5QC1-999Big dataInternet of Things02 engineering and technology020901 industrial engineering & automationSustainable businessSettore ING-IND/17 - Impianti Industriali Meccanici0502 economics and businessGeneral Materials Sciencesmart manufacturingCloud manufacturingBiology (General)InstrumentationQD1-999cloud manufacturingFluid Flow and Transfer Processesbusiness.industryProcess Chemistry and TechnologyTPhysics05 social sciencesGeneral EngineeringCyber-physical systemartificial intelligenceIndustry 4.0sustainabilityEngineering (General). Civil engineering (General)sustainable manufacturingComputer Science ApplicationsEngineering managementmanufacturingChemistrySustainabilityStrategic managementDigital manufacturingInternet of ThingTA1-2040business050203 business & managementApplied Sciences
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Smart factory in the context of 4th industrial revolution: challenges and opportunities for Romania

2017

Manufacturing companies, independent of operation sector and size, must be able to produce lot size one products, just-in-time at a competitive cost. Coping with this high adaptability and short reaction times proves to be very challenging. New approaches must be taken into consideration for designing modular, intelligent and cooperative production systems which are easy to integrate with the entire factory. The coined term for this network of intelligent interacting artefacts system is cyber-physical systems (CPS). CPS is often used in the context of Industry 4.0 – or what many consider the forth industrial revolution. The paper presents an overview of key technological and social requirem…

0209 industrial biotechnologyEngineeringbusiness.industrymedia_common.quotation_subjectSmart factory02 engineering and technologyModular designAdaptabilityEngineering management020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingOperations managementbusinessIndustrial Revolutionmedia_commonIOP Conference Series: Materials Science and Engineering
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Interdisciplinary design methodology for systems of mechatronic systems focus on highly dynamic environmental applications

2017

This paper discusses a series of research challenges in the design of systems of mechatronic systems. A focus is given to environmental mechatronic applications within the chain “Renewable energy production — Smart grids — Electric vehicles”. For the considered mechatronic systems, the main design targets are formulated, the relations to state and parameter estimation, disturbance observation and rejection as well as control algorithms are highlighted. Finally, the study introduces an interdisciplinary design approach based on the intersectoral transfer of knowledge and collaborative experimental activities.

0209 industrial biotechnologyFocus (computing)Computer science020208 electrical & electronic engineering02 engineering and technologyMechatronics7. Clean energy020901 industrial engineering & automationSmart gridInterdisciplinary design13. Climate actionControl system0202 electrical engineering electronic engineering information engineeringSystems engineeringIECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
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Patented intelligence: Cloning human decision models for Industry 4.0

2018

Industry 4.0 is a trend related to smart factories, which are cyber-physical spaces populated and controlled by the collective intelligence for the autonomous and highly flexible manufacturing purposes. Artificial Intelligence (AI) embedded into various planning, production, and management processes in Industry 4.0 must take the initiative and responsibility for making necessary real-time decisions in many cases. In this paper, we suggest the Pi-Mind technology as a compromise between completely human-expert-driven decision-making and AI-driven decision-making. Pi-Mind enables capturing, cloning and patenting essential parameters of the decision models from a particular human expert making …

0209 industrial biotechnologyKnowledge managementIndustry 4.0Computer sciencecognitive modelsCompromisemedia_common.quotation_subjectpäätöksentekoCognitive computingRationality02 engineering and technologyIndustrial and Manufacturing Engineeringcyber-physical system020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineeringontologyindustry 4.0preferencevalue systemmedia_commonta113cloneta214Cloning (programming)business.industryCollective intelligencecollective intelligencedecision-makingPi-Mindsmart decisiontietämysjärjestelmätpatented intelligenceHardware and ArchitectureControl and Systems Engineeringteollisuusautomaatioälytekniikkavalmistustekniikka020201 artificial intelligence & image processingjoukkoälyHuman cloningbusinessDecision modelSoftwareJournal of Manufacturing Systems
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Engineering multi-agent systems using feedback loops and holarchies

2016

This paper presents a methodological approach for the engineering of Multi-Agent Systems using feedback loops as a first class concept in order to identify organizations. Feedback loops are a way for modeling complex systems that expose emergent behavior by means of a cause-effect loop between two levels called micro and macro levels of the system. The proposed approach principles consist in defining an abstract feedback loop pattern and providing activities and guidelines in order to identify and refine possible candidates for feedback loops during the analysis phase of the Aspecs methodology. This approach is illustrated by using an example drawn from the smart grid field.

0209 industrial biotechnologyLoop (graph theory)Computer scienceMulti-agent systemMulti-agent systemsMethodologyControl engineering02 engineering and technologyFeedback loopFeedback loopsField (computer science)020901 industrial engineering & automationSmart gridHolarchiesMulti-agent systemArtificial IntelligenceControl and Systems Engineering0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingFeedback loopElectrical and Electronic EngineeringHolarchie
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Conceptual Key Competency Model for Smart Factories in Production Processes

2020

Abstract Background and Purpose: The aim of the study is to develop a conceptual key competency model for smart factories in production processes, focused on the automotive industry, as innovation and continuous development in this industry are at the forefront and represent the key to its long-term success. Methodology: For the purpose of the research, we used a semi-structured interview as a method of data collection. Participants were segmented into three homogeneous groups, which are industry experts, university professors and secondary education teachers, and government experts. In order to analyse the qualitative data, we used the method of content analysis. Results: Based on the anal…

0209 industrial biotechnologyOrganizational Behavior and Human Resource ManagementKnowledge managementIndustry 4.0Strategy and Managementcompetencies conceptual key competency model smart factory Industry 4.0 automotive industryAutomotive industryQualitative property02 engineering and technologylcsh:BusinessManagement Information Systems020901 industrial engineering & automationEmpirical research0502 economics and businessBusiness and International Managementindustry 4.0CurriculumMarketingcompetenciesconceptual key competency modelbusiness.industry05 social sciencesSoft skillssmart factoryautomotive industryContent analysisTourism Leisure and Hospitality ManagementStructured interviewbusinesslcsh:HF5001-6182Settore SECS-P/08 - Economia E Gestione Delle Imprese050203 business & management
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