Cover image for Networks Of Interacting Machines : Production Organization In Complex Industrial Systems And Biological Cells.
Networks Of Interacting Machines : Production Organization In Complex Industrial Systems And Biological Cells.
Title:
Networks Of Interacting Machines : Production Organization In Complex Industrial Systems And Biological Cells.
Author:
Armbruster, Dieter.
ISBN:
9789812703248
Personal Author:
Physical Description:
1 online resource (280 pages)
Contents:
CONTENTS -- Preface -- 1 Continuum Models for Interacting Machines Dieter Armbruster, Pierre Degond, Christian Ringhofer -- 1.1 Introduction -- 1.2 Heuristic Models -- 1.2.1 Quasistatic Models -- 1.2.2 Advection-Diffusion Equations -- 1.2.3 Policies and Bottlenecks -- 1.2.3.1 Dispatch Rules -- 1.2.3.2 Bottlenecks and Maximal Capacities -- 1.3 First Principle Models -- 1.3.1 Kinetic Models -- 1.3.2 Deterministic Kinetic Models -- Models with capacity constraints: -- The multi - phase model -- An example with bottlenecks: -- 1.3.3 Stochasticity and Diffusion -- Random velocity updates -- Asymptotics for many stage processes: -- A numerical comparison -- 1.4 Conclusions -- Acknowledgements -- References -- 2 Supply and Production Networks: From the Bullwhip Effect to Business Cycles Dirk Helbing, Stefan Lammer -- 2.1 Introduction -- 2.2 Input-Output Model of Supply Networks -- 2.2.1 Adaptation of Production Speeds -- 2.2.2 Modelling Sequential Supply Chains -- 2.2.3 More Detailed Derivation of the Production Dynamics -- 2.2.4 Dynamic Solution and Resonance Effects -- 2.2.5 The Bullwhip Effect -- 2.3 Network Effects -- 2.3.1 General Methods of Solution -- 2.3.2 Examples of Supply Networks -- 2.4 Network-Induced Business Cycles -- 2.4.1 Treating Producers Analogous to Consumers -- 2.5 Reproduction of Some Empirically Observed Features of Business Cycles -- 2.5.1 Dynamic Behaviors and Stability Thresholds -- 2.6 Summary -- 2.7 Future Research Directions -- 2.7.1 Network Engineering -- 2.7.2 Cyclic Dynamics in Biological Systems -- 2.7.3 Heterogeneity in Production Networks -- 2.7.4 Multi-Goal Control -- 2.7.5 Non-Linear Dynamics and Scarcity of Resources -- Acknowledgements -- Appendix A -- 2.8 Boundary between Damped and Growing Oscillations -- 2.9 Boundary between Damped Oscillations and Overdamped Behavior -- References.

3 Managing Supply-Demand Networks in Semiconductor Manufacturing Karl Kempf -- 3.1 Introduction to Supply-Demand Networks -- 3.2 Examples from the Semiconductor Manufacturing -- 3.2.1 A Product-Centric Perspective -- 3.2.2 A Facilities-Centric Perspective -- 3.2.3 Repetitive Decisions -- 3.2.4 Combinatorial Complexity -- 3.2.5 Complexity from Supply Stochasticity -- 3.2.6 Complexity from Demand Stochasticity -- 3.2.7 Complexity from Nonlinearity -- 3.2.8 Financial Complexity -- 3.3 Managing Supply-Demand Networks -- 3.3.1 A Capacity Planning Formulation -- 3.3.2 An Inventory Planning Formulation -- 3.3.3 Integrating Capacity and Inventory Planning -- 3.3.4 A Tactical Execution Formulation -- 3.3.5 Simulation Support -- 3.4 Conclusions -- Acknowledgments -- References -- 4 Modelling Manufacturing Systems for Control: A Validation Study Erjen Lefeber, Roel van den Berg, J.E. Rooda -- 4.1 Introduction -- 4.2 Preliminaries -- 4.3 Effective Process Times (EPT's) -- 4.4 Control Framework -- 4.4.1 Approximation Model -- 4.4.2 Model Predictive Control (MPC) -- 4.4.3 Control Framework (revisited) -- 4.5 Modelling Manufacturing Systems -- 4.6 Validation of PDE-Models -- 4.6.1 Manufacturing Systems -- 4.6.2 PDE-Models -- 4.6.3 Validation Study -- 4.7 Concluding Remarks -- References -- 5 Adaptive Networks of Production Processes Adam Ponzi -- 5.1 Introduction -- 5.2 Review of von-Neumann Model -- 5.3 Dynamical Production Model -- 5.4 Model Behaviour -- 5.4.1 Single Process in Fixed Environment -- 5.4.2 Multiple Timescales -- 5.4.3 Complex Dynamics -- 5.4.4 Network Structure -- 5.5 Discussion -- Acknowledgments -- References -- 6 Universal Statistics of Cells with Recursive Production Kunihiko Kanelco, Chikara Furusaura -- 6.1 Question to be Addressed -- 6.2 Logic -- 6.3 Model -- 6.4 Zipf Law -- 6.5 Log-Normal Distribution -- 6.6 Experiment.

6.6.1 Confirmation of Zipf Law -- 6.6.1.1 Confirmation of Laws on Fluctuations -- 6.7 Discussion -- References -- 7 Intracellular Networks of Interacting Molecular Machines Alexander S . Mikhailov -- 7.1 Introdution -- 7.2 Networks of Protein Machines -- 7.3 Coherent Molecular Dynamics -- 7.4 Mean-Field Approximation -- 7.5 Further Theoretical Developments -- 7.6 Coherence in Cross-Coupled Dynamical Networks -- 7.7 Discussion -- References -- 8 Cell is Noisy Tatsuo Shibata -- 8.1 Introduction -- 8.2 Origin of Molecular Noise -- 8.3 Stochastic Gene Expression -- 8.3.1 Noise in Single Gene Expression -- 8.3.2 Attenuating Gene Expression Noise by Autoregulation -- 8.4 Noisy Signal Amplification in Signal Transduction Reactions -- 8.5 Propagation of Noise in Reaction Networks -- 8.6 Outlook -- Acknowledgments -- References -- 9 An Intelligent Slime Mold: A Self-organizing System of Cell Shape and Information Tetsuo Ueda -- 9.1 Introduction -- 9.1.1 The True Slime Molds, Like Nothing on Earth -- 9.2 Cell Motility and Cell Behavior by the Plasmodium -- 9.2.1 Cell Motility -- 9.2.2 Chemotaxis -- 9.2.3 Sensing and Transduction -- 9.2.4 Search for Second Messengers -- 9.3 Integration of Sensed Information in Chemotaxis -- 9.3.1 A Model for Integration -- 9.4 Collective Dynamics of Coupled Oscillators in Cell Behavior -- 9.4.1 The Response to External Stimulation -- 9.4.2 Alteration of the Judgment by Oscillatory Stimulation through Entrainment -- 9.4.3 Correspondence of Tactic Behavior with Contractility -- 9.4.4 Bifurcation of Dynamic States in the Feeding Behavior by the Placozoan -- 9.5 Chemical Oscillations as a Basis for the Rhythmic Contraction -- 9.6 Transition of Chemical Patterns Accompanying the Selection of Cell Behavior -- 9.6.1 Theory of Cell Behavior in Terms of Dissipative Structure.

9.6.2 Link to the Organization of Cytoskeleton and Chemical Pattern -- 9.7 Computing by Changing Cell Shape -- 9.7.1 Solving a Maze Problem -- 9.7.2 Solving the Steiner Problem -- 9.7.3 Formation of Veins by External Oscillation -- 9.8 Fragmentation of the Plasmodium: Control of Cell Size -- 9.8.1 Thermo-Fragmentation -- 9.8.2 Photofragmentation and its Photosystem -- 9.9 Memory Effects and Morphogen: Phytochrome as Morphogen in the Fragmentation -- 9.10 Locomotion -- 9.10.1 Allometry in Locomotion Velocity -- 9.10.2 Correlation of Oscillations During Directional Movement -- 9.11 The Emergence of the Rhythmic Streaming -- 9.12 Time Order Among Multiple Rhythms in the Plasmodium -- 9.12.1 Long-Term Changes in Cell Shape of the Plasmodium -- 9.12.2 Multiple Oscillations -- 9.13 Concluding Remarks as Future Prospects -- Acknowledgments -- References -- 10 Communication and Structure within Networks Kim Sneppen, Martin Rosvall, Ala Trusina -- 10.1 Introduction -- 10.2 An Economy for Exchange of Social Contacts -- 10.3 Limited Information Horizons in Complex Networks -- 10.4 Conclusion -- Acknowledgments -- References.
Abstract:
This review volume is devoted to a discussion of analogies and differences of complex production systems — natural, as in biological cells, or man-made, as in economic systems or industrial production. Taking this unified look at production is based on two observations: Cells and many biological networks are complex production units that have evolved to solve production problems in a reliable and optimal way in a highly stochastic environment. On the other hand, industrial production is becoming increasingly complex and often hard to predict. As a result, modeling and control of such production networks involve many different spatial and temporal scales and decision policies for many different structures. The common themes of industrial and biological production include evolution and optimization, synchronization and self-organization, robust operation despite high stochasticity, and hierarchical dynamics. The mathematical techniques used come from dynamical systems theory, transport equations, control theory, pattern formation, graph theory, discrete event simulations, stochastic processes, and others. The application areas range from semiconductor production to supply chains, protein networks, slime molds, social networks, and whole economies.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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