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001439435 019__ $$a1266359670
001439435 020__ $$a9783030858742$$q(electronic bk.)
001439435 020__ $$a303085874X$$q(electronic bk.)
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001439435 0247_ $$a10.1007/978-3-030-85874-2$$2doi
001439435 035__ $$aSP(OCoLC)1266904855
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001439435 049__ $$aISEA
001439435 050_4 $$aTS155.6$$b.I475 2021
001439435 08204 $$a658.500285$$223
001439435 1112_ $$aIFIP TC5/WG5.7 International Conference on Advances in Production Management Systems$$d(2021 :$$cOnline)
001439435 24510 $$aAdvances in production management systems :$$bartificial intelligence for sustainable and resilient production systems : IFIP WG 5.7 international conference, APMS 2021, Nantes, France, September 5-9, 2021 : proceedings.$$nPart I /$$cAlexandre Dolgui, Alain Bernard, David Lemoine, Gregor von Cieminski, David Romero (eds.).
001439435 24630 $$aAPMS 2021
001439435 264_1 $$aCham :$$bSpringer,$$c[2021]
001439435 264_4 $$c©2021
001439435 300__ $$a1 online resource (779 pages) :$$billustrations (some color)
001439435 336__ $$atext$$btxt$$2rdacontent
001439435 337__ $$acomputer$$bc$$2rdamedia
001439435 338__ $$aonline resource$$bcr$$2rdacarrier
001439435 4901_ $$aIFIP advances in information and communication technology ;$$v630
001439435 500__ $$aInternational conference proceedings.
001439435 500__ $$aIncludes author index.
001439435 5050_ $$aArtificial Intelligence Based Optimization Techniques for Demand-Driven Manufacturing -- Goods and Activities Tracking Through Supply Chain Network Using Machine Learning Models -- Long term demand forecasting system for demand driven manufacturing -- FBD_Bmodel Digital Platform: a web-based application for demand driven fashion supply chain -- Data-driven approach for Credit Card FraudDetection with Autoencoder and One-ClassClassification techniques -- A model for a multi-level disassembly system under random disassembly lead times-. Hybrid Approaches for Production Planning and Scheduling -- Scheduling of parallel 3D-printing machines with incompatible job families: A Matheuristic algorithm -- An Iterated Greedy Matheuristic for Scheduling in Steelmaking-Continuous Casting Process -- Hybridization of mixed-integer linear program and discrete event systems for robust scheduling on parallel machines -- An unrelated parallel machines rescheduling problem: an industrial case study -- Tactical planning and predictive maintenance: towards an integrated model based on epsilon-reliability -- Intelligent Systems for Manufacturing Planning and Control in the Industry 4.0 -- Comparison between product and process oriented Zero-Defect Manufacturing (ZDM) approaches -- Industry 4.0: An Indian perspective -- Opportunities of Blockchain Traceability Data for Environmental Impact Assessment in a Context of Sustainable Production -- Demand forecasting for an automotive company with neural network and ensemble classifiers approaches -- A deep learning algorithm for the throughput estimation of a CONWIP line -- Dynamic scheduling in a flow shop using Deep Reinforcement Learning -- A Text Understandability Approach for Improving Reliability-Centered Maintenance in Manufacturing Enterprises -- Manufacturing strategy dimensions as I4.0 performance antecedents in developing economies -- Exploring Interdependency Effects of Production Orders as Central Impact Factors of Logistics Performance in Manufacturing Systems -- Design of a Li-Fi Transceiver for Distributed Factory Planning Applications -- Metamodeling of Deteriorating Reusable Articles in a Closed Loop Supply Chain -- Risk Assessment and Mitigation for Industry 4.0: Implementation of a Digital Risk Quick Check -- Digital Twin Framework for Machine-Learning Enabled Integrated Production and Logistics Processes -- A smart contracts and tokenization enabled permissioned blockchain framework for the Food Supply Chain -- Learning and Robust Decision Support Systems for Agile Manufacturing Environments -- Due date-related Order Prioritization for Scheduling with Decision Support in Dynamic Environments -- Knowledge graphs in digital twins for AI in production -- Smart short term capacity planning: A reinforcement learning approach -- Reactive Scheduling by Intelligent DSS -- Worker in the loop: a framework for enabling Human-Robot collaborative assembly -- Decision Support on the Shop Floor Using Digital Twins: Architecture and Functional Components for Simulation-Based Assistance -- A taxonomy for resistance concepts in manufacturing networks -- Real-time machine learning automation applied to failure prediction in automakers supplier manufacturing system -- Resilient Project Scheduling Using Artificial Intelligence: a Conceptual Framework -- A digital twin-driven methodology for material resource planning under uncertainties -- Low-Code and Model-Driven Engineering for Production System -- Towards Development Platforms for Digital Twins: A Model-Driven Low-Code Approach -- A Low-Code Development Environment to Orchestrate Model Management Services -- Towards Twin-Driven Engineering: Overview of the State-of-the-Art and Research Directions -- Developing a bi-objective model to configure a scalable manufacturing line considering energy consumption -- Single machine Order Acceptance Scheduling with periodic energy consumption limits -- A MILP Model for Energy-Efficient Job Shop Scheduling Problem and Transport Resources -- Designing Bioenergy Supply Chains under Social Sustainability Constraints -- Meta-Heuristics and Optimization Techniques for Energy-Oriented Manufacturing Systems -- Developing a bi-objective model to configure a scalable manufacturing line considering energy consumption -- Single machine Order Acceptance Scheduling with periodic energy consumption limits -- A MILP Model for Energy-Efficient Job Shop Scheduling Problem and Transport Resources -- Designing Bioenergy Supply Chains under Social Sustainability Constraints -- Metaheuristics for Production Systems -- Multi-objective genetic algorithm to reduce setup waste in a single machine with coupled-tasks scheduling problem -- Tabu search algorithm for single and multi-model line Balancing problems -- A Distributed Model for Manufacturing Scheduling: Approaching the EDGE -- Scheduling jobs on unrelated machines with job splitting and setup resource constraints for weaving in textile manufacturing -- Comparison of metaheuristics and exact method for the dynamic line rebalancing problem -- Modern Analytics and New AI-Based Smart Techniques for Replenishment and Production Planning Under Uncertainty -- A Probabilistic Estimation of Perfect Order Parameters -- Inventory and Commitment Decisions for On-demand Warehousing System -- Effect of Informed Demand Lead Time under Imperfect Advance Demand Information -- Tool for nervousness analysis in a rolling planning environment via historical data -- A Preliminary Overview of Ramp-up Management Practices in Crisis Context -- Optimization of a Periodic Review Joint Replenishment Policy for a Stochastic Inventory System -- CGA-Based Optimal (r, Q) Policy Tuning in Goods Distribution Systems with Complex Topologies -- Multi-period Multi-sourcing Supply Planning with Stochastic Lead-times, Quantity-dependent Pricing, and Delivery Flexibility Costs -- System Identification for Manufacturing Control Applications -- Multi-Step Problem of Inventory Control with Returns -- Expert-Classification Methods for Estimation of the Structure and Parameters of Controlled Queueing Systems -- Simulation Experiment in a Virtual Laboratory Environment as a Ground for Production Competencies Acquiring -- Identification of Nonlinear Dynamic Systems Structured by Expanded Wiener Model -- Data Analysis and Production Process Control -- Management Projects for Digital Ecosystems of Automotive Enterprises: Truck Sharing -- Formation of work plans and schedules at enterprises with conveyor assembly -- Resolution Estimates for Selected Coordinate Descent: Identification of Seismic Structure in the Area of Geothermal Plants -- Product Quality Improvement based on Process Capability Analysis -- Software Architecture for an Active Device Driver in Reconfigurable Manufacturing Systems -- Price-to-Quality Ratio Dependent Demand: Keeping the Intensity of Demand Constant -- Identification of Integrated Rating Mechanisms on Complete Data Sets -- Application of Linear Random Processes to Construction of Diagnostic System for Power Engineering Equipment -- Construction of multi-step price forecasts in commodity markets based on qualitative and quantitative data analysis methods -- The Future of Lean Thinking and Practice -- More checks for less waste in the lamination process of a shipbuilding company pursuing Lean Thinking -- Implementation of 5S+S for knowledge work in engineering projects -- A Lean approach for multi-criteria decision-making in public services strategy deployment -- Lean Six Sigma in knowledge work: A case study from policing and prosecution services -- Industry and Services: different Organizational Cultures, same Openness to Lean Implementation? -- An Enhanced Data-Driven Algorithm for Shifting Bottleneck Detection -- Practical Estimation of the Impact of a Reduction of the Number of Kanban Cards on the Delivery Performance -- Lean Production and industry 4.0 Technologies: Link and interactions -- Heijunka 4.0 Key Enabling Technologies for Production Levelling in the Process Industry -- Towards an Economic Theory of Lean -- Reshaping the concepts of Job Enrichment and Job Enlargement: the impacts of Lean and Industry 4.0 -- Managing Variability in Production -- Realizing value opportunities for a Circular Economy: Integrating Extended Value Stream Mapping and Value Uncaptured Framework -- Exploring the link between lean practices and sources of uncertainty in Supply Chain -- Transition towards Circular 
001439435 5050_ $$aEconomy: An intraorganizational perspective identifying knowledge wastes.
001439435 506__ $$aAccess limited to authorized users.
001439435 520__ $$aThe five-volume set IFIP AICT 630, 631, 632, 633, and 634 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2021, held in Nantes, France, in September 2021.* The 378 papers presented were carefully reviewed and selected from 529 submissions. They discuss artificial intelligence techniques, decision aid and new and renewed paradigms for sustainable and resilient production systems at four-wall factory and value chain levels. The papers are organized in the following topical sections: Part I: artificial intelligence based optimization techniques for demand-driven manufacturing; hybrid approaches for production planning and scheduling; intelligent systems for manufacturing planning and control in the industry 4.0; learning and robust decision support systems for agile manufacturing environments; low-code and model-driven engineering for production system; meta-heuristics and optimization techniques for energy-oriented manufacturing systems; metaheuristics for production systems; modern analytics and new AI-based smart techniques for replenishment and production planning under uncertainty; system identification for manufacturing control applications; and the future of lean thinking and practice Part II: digital transformation of SME manufacturers: the crucial role of standard; digital transformations towards supply chain resiliency; engineering of smart-product-service-systems of the future; lean and Six Sigma in services healthcare; new trends and challenges in reconfigurable, flexible or agile production system; production management in food supply chains; and sustainability in production planning and lot-sizing Part III: autonomous robots in delivery logistics; digital transformation approaches in production management; finance-driven supply chain; gastronomic service system design; modern scheduling and applications in industry 4.0; recent advances in sustainable manufacturing; regular session: green production and circularity concepts; regular session: improvement models and methods for green and innovative systems; regular session: supply chain and routing management; regular session: robotics and human aspects; regular session: classification and data management methods; smart supply chain and production in society 5.0 era; and supply chain risk management under coronavirus Part IV: AI for resilience in global supply chain networks in the context of pandemic disruptions; blockchain in the operations and supply chain management; data-based services as key enablers for smart products, manufacturing and assembly; data-driven methods for supply chain optimization; digital twins based on systems engineering and semantic modeling; digital twins in companies first developments and future challenges; human-centered artificial intelligence in smart manufacturing for the operator 4.0; operations management in engineer-to-order manufacturing; product and asset life cycle management for smart and sustainable manufacturing systems; robotics technologies for control, smart manufacturing and logistics; serious games analytics: improving games and learning support; smart and sustainable production and supply chains; smart methods and techniques for sustainable supply chain management; the new digital lean manufacturing paradigm; and the role of emerging technologies in disaster relief operations: lessons from COVID-19 Part V: data-driven platforms and applications in production and logistics: digital twins and AI for sustainability; regular session: new approaches for routing problem solving; regular session: improvement of design and operation of manufacturing systems; regular session: crossdock and transportation issues; regular session: maintenance improvement and lifecycle management; regular session: additive manufacturing and mass customization; regular session: frameworks and conceptual modelling for systems and services efficiency; regular session: optimization of production and transportation systems; regular session: optimization of supply chain agility and reconfigurability; regular session: advanced modelling approaches; regular session: simulation and optimization of systems performances; regular session: AI-based approaches for quality and performance improvement of production systems; and regular session: risk and performance management of supply chains *The conference was held online.
001439435 588__ $$aDescription based on print version record.
001439435 650_0 $$aProduction management$$xData processing$$vCongresses.
001439435 650_0 $$aArtificial intelligence$$xIndustrial applications$$vCongresses.
001439435 650_0 $$aBusiness logistics$$xData processing$$vCongresses.
001439435 650_6 $$aProduction$$xGestion$$xInformatique$$vCongrès.
001439435 650_6 $$aIntelligence artificielle$$xApplications industrielles$$vCongrès.
001439435 650_6 $$aLogistique (Organisation)$$xInformatique$$vCongrès.
001439435 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001439435 655_7 $$aConference papers and proceedings.$$2lcgft
001439435 655_7 $$aActes de congrès.$$2rvmgf
001439435 655_0 $$aElectronic books.
001439435 7001_ $$aDolgui, A.$$q(Alexandre),$$eeditor.
001439435 7001_ $$aBernard, Alain$$c(Researcher in telecommunication),$$eeditor.
001439435 7001_ $$aLemoine, David,$$eeditor.
001439435 7001_ $$aVon Cieminski, Gregor,$$eeditor.
001439435 7001_ $$aRomero, David,$$eeditor.
001439435 77608 $$iPrint version:$$aDolgui, Alexandre.$$tAdvances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems.$$dCham : Springer International Publishing AG, ©2021$$z9783030858735
001439435 830_0 $$aIFIP advances in information and communication technology ;$$v630.
001439435 852__ $$bebk
001439435 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-85874-2$$zOnline Access$$91397441.1
001439435 909CO $$ooai:library.usi.edu:1439435$$pGLOBAL_SET
001439435 980__ $$aBIB
001439435 980__ $$aEBOOK
001439435 982__ $$aEbook
001439435 983__ $$aOnline
001439435 994__ $$a92$$bISE