Real-time Simulation for Sustainable Production: Enhancing User Experience and Creating Business Val

Creating Value with Sustainable Production Based on Real-Time SimulationReflections on Sustainable Production Based on real-Time SimulationOrigins of the BookFuture Research DirectionsConclusionReferencesI Industrial Needs of Sustainable ProductionIdentifying Industrial Needs for Real-Time Simulation and Digital TwinsReal-Time Simulation and Digital Twins Over the Product LifecycleReal-Time Simulation and Digital TwinsProduct-Service System and Product Lifecycle ManagementMethodologyResults – Identified Industrial Needs For Real-Time Simulation and Digital TwinsConclusionsAcknowledgmentsReferencesCompany Capabilities and Implementing Real-Time ActivitiesTheoretical Framework and Research ModelTheoretical FrameworkDigital Business StrategyDigital CapabilitiesDigital Business Strategy and Real-Time ActivitiesDigital Capabilities and Real-Time ActivitiesResearch ModelEmpirical Examination of Real-Time SimulationData Collection and SampleDescriptive ResultsStatistical Analysis ResultsConclusionsTheoretical ImplicationsManagerial ImplicationsLimitations and Further ResearchReferencesReal-Time Simulation Strategies: Implications For Operational Excellence and Sustainability PerformanceReal-Time Simulation For SustainabilityCharacteristics of Real-Time Simulation ModelsThe Concept of Sustainability PerformanceEmpirical Examination of Real-Time Simulation StrategiesData CollectionCluster Analysis ResultsCharacteristics of the Real-Time Simulation StrategiesThe “Data Wisdom” StrategyThe “in the Game” StrategyThe “Bystander” StrategyConclusions: Sustainable Strategies For Real-Time SimulationTheoretical ImplicationsManagerial ImplicationsLimitations and Further Research DirectionsReferencesSelling Digital Twins in Business-To-Business MarketsTheoretical BackgroundDigital Twins in Manufacturing IndustrySelling Data-Based Solutions in Data-Based-Business-To-Business MarketsResearch MethodologyResultsModel Illustrating the Level of Customer and Digital-Twin understanding Needed From the Sales PerspectiveChallenges in Selling Digital TwinsConclusionsAcknowledgmentsReferencesII Game-Like Virtual EnvironmentsAccelerating Design Processes Using Data-Driven ModelsConcept of a Data-Driven ModelSystem ModelingNeural-Networks-Based Data Models and Other MethodsData-Driven Models in the Multibody FrameworkApplications of Data-Driven ModelsResearch and Product DevelopmentEnhanced OperationMaintenance and ServiceNew Business OpportunitiesSupporting Sales and PurchaseConclusionsNotesReferencesGamification and the Marketing of Agricultural MachineryModeling An Agricultural MachineDesign process for parameterizationEnvironment ModelingGamificationElements of a GameMethods of Data ExtractionCase Example of a Farm TractorGamification of the Farm Tractor ModelProduct Development OpportunityMarketing OpportunityConclusionAcknowledgment(s)ReferencesAdded Value From Virtual SensorsVirtual Sensors: Context and BackgroundVirtual Sensors As a Part of the Product OfferingTechnical Methods Enabling Virtual SensingAnalytical MethodsNumerical MethodsOpportunities/benefits and Challenges of Virtual MeasurementsOffline Virtual Measurement – Slower Than Real TimeOnline Virtual Measurement – Faster Than Real TimeBusiness Opportunities Introduced By Virtual SensorsConclusionsReferencesThe Technical-Business Aspects of Two Technical-Business-Mid-Sized Manufacturing Companies Implementing a Joint Simulation ModelMethodology: Assembling the Joint Simulation ModelsDeveloping Customer-Oriented B2B ProductsPreparation of B2B Parameterized Real-Time Joint Simulation ModelCombining Parameterized Models and the Optimized ModelJoint Simulation of Industrial Mobile MachinesTechnical-Business Challenges of Joint Simulation/Joint simulation ChallengesReal-Time Joint Simulation SolutionsSelection of Optimal ParametersOptimal Range of ParametersJoint-Model StabilityFeasibilities of Joint Simulation CombinationsUser Selection of Parameterized Model/User Designing and Testing of Simulation ModelCollaboration Benefits and Issues On the AllianceConclusionsReferencesIII Capturing Customer Value and User ExperienceImplementing Digital Twins to Enhance Digitally Extended Product-Service SystemsRelated ResearchResearch MethodologyResultsDiscussion and ConclusionsAcknowledgmentsReferencesThe Expected Benefits of Utilizing Simulation in Manufacturing Companies: Insights From a Delphi StudySimulation Modeling Motives in ManufacturingResearch Method and Data Gathering ProcessSimulation Modeling in Manufacturing Companies: Insights From the Expert PanelBenefits of Using Simulation in the Long Term For the Customer and Other StakeholdersThe Business-Activity Related Effects of SimulationConclusionsReferencesIntegrating the User Experience Throughout the Product Lifecycle With Real-Time Real-Time-Simulation-Based Digital TwinsRelated ResearchMultibody Definition of a Digital TwinProduct LifecycleThe User ExperienceCo-Creating Product Value With the UX and Co-Creating-Multibody-Based digital TwinsEnabling User Experiences in the Product Lifecycle With An Immersive Multibody-Based Multibody-Based-Digital-Twin ApproachDeveloping a User-Centered Virtual Space of a Physical ModelUser Selection of Component Design DataImmersive Methods For Generating User InputSimulator Or Motion Feedback PlatformVR, AR, Mixed Reality Glasses, Leap Controllers and HapticsManufacturing of the Physical ProductReal-Time Communication Between the Physical and Virtual Spaces of the Digital TwinProduct Life Management DataEnhancement of Measured DataIndustrial Case Study: the UX in Different Phases of the Product Lifecycle With a Multibody Digital TwinNew Product Development Approach: User Co-Creation of a New Forklift Mast System in the Virtual SpaceCommercialization: User Testing of the Parameterized Model in Different EnvironmentsManufacturing: Utilizing the User-Based Multibody Model in ProductionUser-Related Product Services in the Operation Phase: Updating the Virtual Space of the Digital Twin With User-Related-Real-World InformationEnd of Product Life: Retiring the Product Based On User Data generated in the Digital TwinConclusionAcknowledgmentsReferencesIV Value for BusinessThe Digital Twin Combined With Real-Time Performance Measurement in Lean ManufacturingContext and BackgroundLean Approach and Performance MeasurementDigital Twins and Performance MeasurementMethodologyAdvantages of the Digital Twin and Real-Time Performance MeasurementAdvantages to StakeholdersManagementWorkerCustomerAdvantages By Process PerspectiveConclusionReferencesUsing Real-Time Simulation in Company Value Chains and Business Models For Value CreationThe Effect of Digitalization On the MarketReal-Time Simulation Models and How They Create Value For CustomersBusiness Model Canvas As a Tool to Analyze the Value ChainApplying Real-Time Simulation to Different Alue Chain ActivitiesApplying Real-Time Simulators in R&d and Product DevelopmentApplying Real-Time Simulators in TrainingApplying Real-Time Simulators to Predict FaultsApplying Real-Time Simulators in ServicesApplying Real-Time Simulators in Sales and MarketingThe Effect of Real-Time Simulation On Business ModelsDiscussion and ConclusionsNotesReferencesSustainable Competitive Advantage Through the Implementation of a Digital TwinA Multidimensional Model For the Implementation of a Digital TwinTheoretical UnderpinningsDefining a Digital TwinDescription of the ModelFirm CompetenciesStrategic DirectionSustainability PerformanceExternal EnvironmentRequisite Competencies and Research PropositionsLinking Competencies to the Strategic Direction of a Digital TwinLinking Strategic Direction of a Digital Twin to Sustainability performanceExternal Environment As ModeratorConclusionsTheoretical ImplicationsManagerial ImplicationsLimitations and Further Research DirectionsReferencesManaging Digital-Twin lifecycle – Recognition and handling of Business RisksTheoretical BackgroundDigital TwinsDigital Twin LifecycleLifecycle Risks of Digital TwinsResearch MethodologyResultsConcluding RemarksAcknowledgmentsReferences
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