Degeneracy and networked buffering: principles for supporting emergent evolvability in agile manufacturing systems

This article introduces new principles for improving upon the design and implementation of agile manufacturing and assembly systems. It focuses particularly on challenges that arise when dealing with novel conditions and the associated requirements of system evolvability, e.g. seamless reconfigurability to cope with changing production orders, robustness to failures and disturbances, and modifiable user-centric interfaces. Because novelty in manufacturing or the marketplace is only predictable to a limited degree, the flexible mechanisms that will permit a system to adequately respond to novelty cannot be entirely pre-specified. As a solution to this challenge, we propose how evolvability can become a pervasive property of the assembly system that, while constrained by the system’s historical development and domain-specific requirements, can emerge and re-emerge without foresight or planning. We first describe an important mechanism by which biological systems can cope with uncertainty through properties described as degeneracy and networked buffering. We discuss what degeneracy means, how it supports a system facing unexpected challenges, and we review evidence from simulations using evolutionary algorithms that support some of our conjectures in models with similarities to several assembly system contexts. Finally, we discuss potential design strategies for encouraging emergent changeability in assembly systems. We also discuss practical challenges to the realization of these concepts within a systems engineering context, especially issues related to system transparency, design costs, and efficiency. We discuss how some of these difficulties can be overcome while also elaborating on those factors that are likely to limit the applicability of these principles.

[1]  Mauro Onori,et al.  Evolvable assembly systems: coping with variations through evolution , 2008 .

[2]  Franz Rothlauf,et al.  Redundant Representations in Evolutionary Computation , 2003, Evolutionary Computation.

[3]  Dirk Malthan,et al.  Building a mini‐assembly system from a technology construction kit , 2004 .

[4]  F. Musharavati RECONFIGURABLE MANUFACTURING SYSTEMS , 2010 .

[5]  Kanji Ueda Emergent Synthesis Approaches To Biological Manufacturing Systems , 2007 .

[6]  Mauro Onori,et al.  Evolvable Assembly Systems : A New Paradigm? , 2002 .

[7]  Ralph L. Hollis,et al.  TOWARD A SECOND-GENERATION MINIFACTORY FOR PRECISION ASSEMBLY , 2003 .

[8]  G. Edelman,et al.  Degeneracy and complexity in biological systems , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Viktor Mikhaĭlovich Glushkov,et al.  An Introduction to Cybernetics , 1957, The Mathematical Gazette.

[10]  Franz Rothlauf,et al.  Representations for genetic and evolutionary algorithms , 2002, Studies in Fuzziness and Soft Computing.

[11]  박홍석 Holonic Manufacturing 개념하의 자주ㆍ협동적인 시스템 , 1996 .

[12]  Paulo Leitão A Bio-Inspired Solution for Manufacturing Control Systems , 2008, BASYS.

[13]  Alfred A. Rizzi,et al.  Programming in the architecture for agile assembly , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[14]  Paul Valckenaers,et al.  Holonic Manufacturing Execution Systems , 2005 .

[15]  Pavel Vrba MAST: manufacturing agent simulation tool , 2003, EFTA 2003. 2003 IEEE Conference on Emerging Technologies and Factory Automation. Proceedings (Cat. No.03TH8696).

[16]  Mihaela Ulieru,et al.  A Holonic Self-Organization Approach to the Design of Emergent e-Logistics Infrastructures , 2003, Engineering Self-Organising Systems.

[17]  James M. Whitacre,et al.  Degenerate Neutrality Creates Evolvable Fitness Landscapes , 2009, GEM.

[18]  Giovanna Di Marzo Serugendo,et al.  Concepts in complexity engineering , 2011, Int. J. Bio Inspired Comput..

[19]  A. G. U Lso,et al.  Reconfigurable manufacturing systems: Key to future manufacturing , 2000 .

[20]  Alexei Kurakin,et al.  Scale-free Flow of Life: On the Biology, Economics, and Physics of the Cell , 2009 .

[21]  Giovanna Di Marzo Serugendo,et al.  A complexity theory approach to evolvable production systems , 2007 .

[22]  Richard A. Watson,et al.  On the Utility of Redundant Encodings in Mutation-Based Evolutionary Search , 2002, PPSN.

[23]  James M. Whitacre Evolution-Inspired Approaches for Engineering Emergent Robustness in an Uncertain Dynamic World , 2010, ALIFE.

[24]  Mihaela Ulieru,et al.  Emergent e-Logistics Infrastructure for Timely Emergency Response Management by Collaborative Problem-Solving with Optimized Resource ( Re ) Allocation , 2003 .

[25]  Thomas Y. Choi,et al.  Supply networks and complex adaptive systems: Control versus emergence , 2001 .

[26]  A Koestler,et al.  Ghost in the Machine , 1970 .

[27]  Hermann Kaindl,et al.  An automation agent architecture with a reflective world model in manufacturing systems , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[28]  José Barata,et al.  Distributed systems - from natural to engineered: three phases of inspiration by nature , 2010, Int. J. Bio Inspired Comput..

[29]  Giovanna Di Marzo Serugendo,et al.  Ambient intelligence in self-organising assembly systems using the chemical reaction model , 2010, J. Ambient Intell. Humaniz. Comput..

[30]  James M. Whitacre,et al.  Degeneracy: a link between evolvability, robustness and complexity in biological systems , 2009, Theoretical Biology and Medical Modelling.

[31]  Jeffrey O. Kephart,et al.  The Vision of Autonomic Computing , 2003, Computer.

[32]  R. L. Hollis,et al.  Vision Guided Pick and Place in a Minifactory Environment , .

[33]  Christoph Hanisch,et al.  Evolvability and the intangibles , 2008 .

[34]  Giovanna Di Marzo Serugendo,et al.  Advances in complexity engineering , 2011, Int. J. Bio Inspired Comput..

[35]  Eberhard Abele,et al.  Design principles for reconfigurable machine tools , 2007 .

[36]  Wolfgang Banzhaf,et al.  Genotype-Phenotype-Mapping and Neutral Variation - A Case Study in Genetic Programming , 1994, PPSN.

[37]  Weiming Shen,et al.  Applications of agent-based systems in intelligent manufacturing: An updated review , 2006, Adv. Eng. Informatics.

[38]  J. A. Buzacott,et al.  Models for Understanding Flexible Manufacturing Systems , 1980 .

[39]  Stuart A. Kauffman,et al.  The origins of order , 1993 .

[40]  Xin Yao,et al.  Evolutionary mechanics: new engineering principles for the emergence of flexibility in a dynamic and uncertain world , 2011, Natural Computing.

[41]  Mauro Onori,et al.  MARK III, A New Approach to High-Variant, Medium-Volume Flexible Automatic Assembly Cells , 1998, Robotica.

[42]  Yaochu Jin,et al.  A fitness-independent evolvability measure for evolutionary developmental systems , 2010, 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

[43]  Hamideh Afsarmanesh,et al.  A multi-agent based infrastructure to support virtual communities in elderly care , 2004, Int. J. Netw. Virtual Organisations.

[44]  Gérard Berry,et al.  The chemical abstract machine , 1989, POPL '90.

[45]  Bernhard Sendhoff,et al.  Evolutionary multi-objective optimization of robustness and innovation in redundant genetic representations , 2009, 2009 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making(MCDM).

[46]  Alfred A. Rizzi,et al.  A high-performance network infrastructure and protocols for distributed automation , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[47]  Axel Bender,et al.  Degeneracy: a design principle for achieving robustness and evolvability. , 2009, Journal of theoretical biology.

[48]  Paulo Leitão,et al.  Holonic and Multi-Agent Systems for Manufacturing , 2011, Lecture Notes in Computer Science.

[49]  Giovanna Di Marzo Serugendo,et al.  Self-Organizing Assembly Systems , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[50]  Paulo Leitão,et al.  An agile and adaptive holonic architecture for manufacturing control , 2004 .

[51]  Giacomo Cabri,et al.  A method fragments approach to methodologies for engineering self-organizing systems , 2012, TAAS.

[52]  J. Whitacre Genetic and environment-induced pathways to innovation: on the possibility of a universal relationship between robustness and adaptation in complex biological systems , 2011, Evolutionary Ecology.

[53]  A. Wagner,et al.  Innovation and robustness in complex regulatory gene networks , 2007, Proceedings of the National Academy of Sciences.

[54]  Ralph L. Hollis,et al.  Agile assembly architecture: an agent based approach to modular precision assembly systems , 1997, Proceedings of International Conference on Robotics and Automation.

[55]  Paulo Leitão,et al.  Implementation of a Holonic Control System in a Flexible Manufacturing System , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[56]  Axel Bender,et al.  Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems , 2009, Theoretical Biology and Medical Modelling.

[57]  Giovanna Di Marzo Serugendo,et al.  Designing Self-Organization for Evolvable Assembly Systems , 2008, 2008 Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems.

[58]  Valeriy Vyatkin,et al.  Ontology-based reconfiguration agent for intelligent mechatronic systems in flexible manufacturing , 2010 .

[59]  Sven A. Brueckner,et al.  RETURN FROM THE ANT SYNTHETIC ECOSYSTEMS FOR MANUFACTURING CONTROL , 2000 .

[60]  Rajeev Kaula,et al.  A modular approach toward flexible manufacturing , 1998 .

[61]  Hoda A. ElMaraghy,et al.  Flexible and reconfigurable manufacturing systems paradigms , 2005 .

[62]  James M. Whitacre Genetic and Environment-Induced Innovation - Complementary Pathways to Adaptive Change that are Facilitated by Degeneracy in Multi-Agent Systems , 2010, ALIFE.

[63]  Julian Francis Miller,et al.  Neutrality and the Evolvability of Boolean Function Landscape , 2001, EuroGP.

[64]  Ahmed Azab,et al.  Modelling evolution in manufacturing: A biological analogy , 2008 .

[65]  Stefan Bussmann,et al.  Self-organizing manufacturing control: an industrial application of agent technology , 2000, Proceedings Fourth International Conference on MultiAgent Systems.

[66]  M. Onori,et al.  A multiagent based control approach for evolvable assembly systems , 2005, INDIN '05. 2005 3rd IEEE International Conference on Industrial Informatics, 2005..

[67]  Regina Frei,et al.  Self-organisation in evolvable assembly systems , 2010 .

[68]  Arantxa Etxeverria The Origins of Order , 1993 .

[69]  Rolf P. Wrtz Organic Computing - Understanding Complex Systems , 2008 .

[70]  Xin Yao,et al.  The Role of Degenerate Robustness in the Evolvability of Multi-agent Systems in Dynamic Environments , 2010, PPSN.