Sustainable Manufacturing for Industry 4.0:An Augmented Approach


Concept of Industry 4.0Introduction and Evolution of Industry 4.0IntroductionWhat Is Industry 4.0?Components of Industry 4.0Benefits of Industry 4.0ConclusionReferencesCharacteristics and Design Principles of Industry 4.0IntroductionCharacteristics of Industry 4.0Horizontal and Vertical IntegrationDemand and MarketingDigital Supply Chain and ProductionDigital Products and ServicesDigital Customer ExperienceDesign PrinciplesInteroperabilityVirtualisationDecentralisationReal-Time CapabilityService-OrientationModularityChallenges Involved in Executing Industry 4.0 FrameworkConclusionsReferencesSustainable Manufacturing and Industry 4.0Design for Sustainability and Its FrameworkIntroductionAmong the Industrial RevolutionsSystematic Changes While Adopting I.4.0Speculative Stochastic Process of I.4.0Applying Sustainability to the Supply ChainI.o.T. Empowered Production for SustainabilityRobot Interaction for Human SustainabilityCorrelation of I.4.0 and SustainabilityConcluding RemarksReferencesOrientation of Sustainable Product DevelopmentIntroductionCyber-Physical SystemsInternet of ThingsI.o.T. Employed within Production ManagementCloud ComputingConclusionReferencesEnd of Life Disposal and Sustainable Industrial Waste Management in Industry 4.0IntroductionEffect of End of Life Disposal on EconomyBrief Introduction of Industry 4.0End of Life (E.O.L.) DisposalEnd of Life Disposal for Biodegradable WasteFootwear IndustryEnd of Life Disposal of Non-biodegradable WasteSustainable Waste Management – A Necessity for Industry 4.0Smart IndustriesNecessity of Industry 4.0Sustainable Manufacturing in Industry 4.0Advantages of Sustainable ManufacturingConclusionReferencesInnovation for Smart FactoriesRole of Industrial Internet of Things (I.I.o.T.) ManufacturingIntroduction to the Role of the Industrial Internet of Things (I.I.o.T.) ManufacturingEvolution of I.I.o.T. in IndustryI.o.T. Manufacturing OperationsIntelligent ManufacturingAsset ManagementPlanningMonitoringTypes of Condition MonitoringImportance of Data in I.o.T. ManufacturingBenefits of I.o.T. in ManufacturingConclusionReferencesBig Data and Its Importance in ManufacturingIntroductionChallenges in Manufacturing IndustriesWhat Is Big Data?Impact of Big Data in ManufacturingHow to Adopt Big Data Analytics?ConclusionReferencesNetworking for Industry 4.0Introduction to Networking for Industry 4.0Mass CommunicationFlexibilityFactory VisibilityConnected Supply ChainEnergy ManagementCreating ValuesRemote MonitoringProactive Industry MaintainsExternal Communication for Devices through Gateway S.D.N.Connection and Management of Data in the CloudDynamic Management of Smart DevicesFeed of Data and Automatic Decision-MakingOptimisation of Customers Directly with Industry 4.0History of Networking in IndustryNeed for Networking in IndustryVision for Networking in IndustryInitialisation of and Basic Matters about Networking in IndustryRequirement, Assessment and Methodology of Networking in IndustryMethodologyAdvantages, Disadvantages and LimitationsAdvantages of Industry 4.0Difficulties Confronting Industry 4.0LimitationsConclusion and Future ScopeConclusionFuture ScopeBibliographyAnalysis of Drivers for Cloud Manufacturing and Its Integration with Industry 4.0 Using the MCDM TechniqueIntroductionLiterature ReviewMethodologyCase StudyAnalysis Using A.H.P. MethodologyNormalisation CalculationResults and DiscussionConclusionReferencesDecision-Making to Achieve Sustainability in FactoriesArtificial Intelligence (A.I.) and Industry 4.0Elements in Artificial Intelligence: ABCDEChallenges of Artificial IntelligenceIntroduction to A.I.History of A.I.Explanation of Artificial IntelligenceTypical A.I. ProblemsAdvantages and Disadvantages of A.I.A.I. ModelsApplication of A.I.Image Processing through Artificial IntelligenceArtificial Intelligence in the Clothing IndustryImpact of A.I. on Some Other IndustriesIndustry 4.0Defining Industry 4.0Why Industry 4.0?Introduction to the Smart FactoryAdvantages of Industry 4.0Disadvantages of Industry 4.0ApplicationsConclusionBibliographyRole of Machine Learning in Industry 4.0IntroductionHistory of Machine LearningMachine LearningBroad Classification of Machine LearningSupervised LearningUnsupervised LearningMethods of LearningConcept LearningDecision Tree LearningPerceptron LearningBayesian LearningReinforcement LearningArtificial Neural Network and Deep LearningArtificial Neural NetworkDeep LearningWhat Can Machine Learning do?Data MiningQuality ManagementPredictive MaintenanceSupply Chain ManagementProcess PlanningOperation Selection and PlanningTool Condition MonitoringProcess ModellingApplications of Machine LearningManufacturing IndustryFinance SectorProcess AutomationSecurityGuaranteeing and Credit ScoringRobo-AdvisorsHealthcare IndustriesCancer DiagnosisDetection of HaemorrhageRobo-Assisted SurgeryRetail IndustryFuture Scope of Machine LearningConclusionsReferencesSoftware Development for Industry 4.0IntroductionHistory of Software in Manufacturing IndustriesNeed for Software Development in Industries?Vision for Software Development for IndustriesComparison of Past and Present Scenario of Software in IndustriesExpecting Future Software Development in Industries 2050Method Used for Selection Software in IndustryWaterfall Development MethodologyRapid Application Development MethodologyAgile Development MethodologyDevOps Deployment MethodologyAvailable Software for Different Areas in IndustriesIndustrial Design SoftwareInformation Technology IndustrySummaryConclusionReferencesMonitoring Manufacturing Process Parameters for Negative Environmental Impacts: Case Study from ColombiaIntroductionEnvironmental Impact MeasurementFunctions and Characteristics of Composite Indicators of Environmental PerformanceEnvironmental Performance Indicators ClassificationColombian Case StudyPressures Facing the Colombian Manufacturing Sector at National and Regional LevelIndustry 4.0 Sector in ColombiaConclusions and RecommendationsReferencesERP Systems and SCM in Industry 4.0IntroductionChallenges in the Supply ChainPhases of Product Value ChainCapitalising on Industry 4.0 Technologies in Supply ChainInfluence of Industry 4.0 in Supply ChainThe Digital Transformation of Supply Chain in Industry 4.0Raw Materials and Raw Materials ProcessingDesignManufacturingDistributionSalesUse PhaseExtended Life of the Product – Make a Sustainable ImpactConclusionReferencesThe Importance of Additive Manufacturing – Factories of the FutureIntroductionMaterials for A.M.PolymersMetalsCeramicsCompositesSmart Materials for Industry 4.0AM for Rapid ToolingConclusionsReferencesGuidelines for Ensuring Sustainability in Industry 4.0IntroductionSustainability in Industry 4.0Guidelines for Ensuring Sustainability in Industry 4.0Impact of Sustainability in Industry 4.0ConclusionReferencesCase studies – Sustaining Global Competitiveness with Industry 4.0IntroductionChallenges and Issues of Industry 4.0Technologies of Industry 4.0Internet of Things (I.o.T.)Cyber-Physical Systems (C.P.S.)Cloud ManufacturingBig Data AnalyticsCase Studies Based on Industry 4.0 TechnologiesCases on Neural Network TechnologiesCase Studies on I.o.T. TechnologiesCases on Big Data TechnologiesCases on Industrial Wireless Network (I.W.N.) TechnologiesIndustrial Internet of Things (I.I.o.T.) TechnologiesLogistics Optimisation TechnologiesSummary and Final RemarksReferencesModelling the Interrelationship of Factors EnablingAgile-Industry 4.0: A DEMATEL ApproachIntroductionLiterature ReviewDecision-Making Trial and Evaluation LaboratoryDEMATEL ApproachApplication of DEMATELResults and DiscussionConclusionReferencesDevelopment of a Novel Framework for a Distributed Manufacturing System Process for Industry 4.0IntroductionLiterature ReviewA Proposed Novel Framework for Telefacturing Distributed Process for Industry 4.0Discussion on Processing of Telefacturing-Based Distributed SystemUser Service LevelControl Service LevelApplication Service LevelConclusionsReferences
 
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