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Intelligent Cyber Enterprise in the Production Context
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19th IFAC World Congress,Cape Town South Africa August 24 29 2014. to market and socio environmental challenges could qualify it towards Flexible Manufacturing Systems viewed as. as intelligent a set of Flexible Manufacturing Cells interlinked by. a common transport system and respectively by a,By merging the virtual and the physical world of. common information flow the physical location of, manufacturing through CPS and considering all aspects. the cells is important rather from the organizational. connected with real life we have to create the enterprise of. and technological point of view not from the, future as an Intelligent Cyber Enterprise with main facilities. conceptual one, as adaptivity self organization cognition and sustainability.
At organizational levels though every stage in, In this new type of enterprise we are finding the agility. shop floor manufacturing was considered from the, adaptability autonomy and flexibility in production systems. point of view of resource optimization reducing,to face succesfully high dynamics and uncertain. costs integrating the information flow ensuring the. environments, constant and measurable quality of products in any. Integration of cognitive objects into a hierarchical condition developing concepts as Total Quality. architecture of enterprise management and control Management Computer Integrated Manufacturing. coordinating shop floor production creates a knowledge Concurrent Engineering Extended Enterprise. based environment which allows self configuring self Virtual Manufacturing Lean manufacturing. healing self optimizing and self protecting capabilities Workflow Management Business Process. Modelling a s o Applying different combinations of. By self configuring capabilities a production system adapts. these approaches in different conditions resulted in. itself to unpredictable conditions by automatically changing. different types of enterprises whose success, its configuration adding or removing new resources or depended rather on the adequacy of means to their.
creating new tasks specific operating conditions than to the intrinsic. By self optimizing capabilities a production system tunes value of every paradigm. itself pro actively to improve its performances by goal. Control architectures used the available, directed control as a response to environmental changes. technologies in order to solve in optimal conditions. These capabilities are developped by using cognitive agents cost and reliability being the main factors. with attributes as perception analyse learning planning manufacturing challenges They have basically. evolved from centralized hierarchical architectures. This paper aims to present a framework for the design of an towards agent oriented structures with different. Intelligent Cyber Enterprise as an emerging model for degrees of hierarchy embedded as a compromise. today s challenges faced by manufacturing industry based on between flexibility robustness and efficiency. the most recent developments in the field smart and predictability Resource planning and scheduling. cognitive factories use of SOA and Internet of Things smart supply chain management and real time monitoring. sensors networks a s o and on a CPS approach with respect evolved in parallel as support for control. to Knowledge Management KM,Information flow management has known the most. Next section will present a short overwiev of the intelligent spectacular evolution in the last years since the. manufacturing concept development underlining some basic microprocessor development and between the. approaches in Smart Factories and Cognitive Enterprise continuous increase of computer availability in. paradigms in a view based on the CPS concept industrial purposes and the increased software. Section III will present the concept derived from these interoperability and standardisation information. approaches of the intelligent Cyber Enterprise based on a management has influenced both enterprise. knowledge driven agent based CPS oriented view organization and control approaches Manufacturing. enterprises have gradually increased the importance. 2 NEW APPROACHES IN INTELLIGENT allotted to information and knowledge until they. MANUFACTURING understood that these represent one of their most. important asset Knowledge Management KM,2 1 Evolution of manufacturing concept. evolved as a discipline from which it is expected, There are many ways in which evolution of manufacturing today to solve many of the challenges enterprises are. concepts can be presented especially because it is not linear facing but especially to fully use all their. there is a very strong interconnection between basic shop capabilities and to pro actively act on the market. floor manufacturing methodology production organization Technologies had usually answered to demands. control architectures technologies and mostly information expressed by industry some of them as. management microprocessor Internet or RFID allowed real. Until recently manufacturing paradigms were focused on one paradigm shifts at control information flow. aspect at a time management and organizational levels. At shop floor level manufacturing evolved from The problem is that all these aspects are inter related when. disparate machines to production lines and then generating an emergent behaviour of the enterprise and any. change made in one of them will affect not only the global. 19th IFAC World Congress,Cape Town South Africa August 24 29 2014.
performances of the enterprise but also the functioning of In figure 1 is presented a CPS oriented view of the Smart. others and not always for the best Factory, This is the reason for which in the last decade there were. developed several holistic strategic approaches related to the. enterprise as a whole Some of the most interesting which. will be shortly referred to in the following sub sections are. the Cognitive Factory and the Smart Factory,2 2 The Cognitive Factory. The Cognitive Factory is a relatively recent research trend. where artificial cognitive capabilities were used for the. control of production systems In Bannat et al 2011 are. presented in detail the problems that this approach has to. solve as well as some of the work lines, This solution is typically conceived Rungger et al 2008 for. manufacturing enterprises dealing with low volume and high. diversity production where efficiency is drastically limited. by the capacity of adaptation of the production system. The solution is to introduce the so called cognition into Fig 1 Smart Factory in a CPS oriented view. technical systems cognitive technical systems are understood. as entities showing abilities of perceiving momentary A smart factory should be typically working into a global. situations classifying and interpreting them and executing environment with different physical locations each one with. appropriate actions and strategies in order to accomplish its particular competencies and functionalities costs and. varying production tasks availability, In the context of production it signifies that there should be The optimal use of such a Global Facility requests a so called. conceived means to convert data in information and then in Border Dissipation approach the planning of production and. knowledge in order to construct models reflecting the actual production capacities extensions should take into account a. state of production Based on them it is foreseen to generate situation based global planning for local production and. on line appropriate production plans and control programs development. In Brecher et al 2012 is given an example of the work It would request for each sub system of the enterprise both. developed within the Cluster of Excellence Integrative the capacity of independent action under planning defined. Production Technology for High Wage Countries for a specifications and the capacity of communication allowing. robotized production unit the transfer of meta data information and knowledge. between components in order to offer reliable context. The idea of this approach is to integrate or rather emulate. oriented behaviour, human reasoning capabilities at machine plant level and to.
perform modelling planning and control into a highly 3 KNOWLEDGE DRIVEN INTELLIGENT. integrative way adapted to the real context MANUFACTURING ENTERPRISE. We believe that this goal may be achieved also by an The most important common points in Cognitive and Smart. integrating CPS modelling approach where real humans are Manufacturing approaches are. part of CPS giving high efficiency to communication. Enterprise is a network of autonomous entities, context interpretation and knowledge integration with. which differ in nature human and artificial,implicit learning capabilities. physical structure functionalities and local, 2 3 The Smart Factory purposes but which should generate by their inter. connection an intelligent emergent behaviour with a. The smart factory is designed according to sustainable and common goal. service oriented business practices by converging technical Enterprise is a complex highly dynamic system. and business processes into CPS models facing an unpredictable environment to which it. Using a flexible network of CPS based production systems should adapt by re active and pro active behaviour. the high level of automation of all processes creates the smart The link between enterprise entities is information. factory flow any modern enterprise should have an, Flexible production systems which are able to respond in all integrative information system. real time conditions allow the in house production processes Knowledge is one of the most important asset of an. to be optimized and integrated into a global network of enterprise. adaptive and self organizing production units,19th IFAC World Congress.
Cape Town South Africa August 24 29 2014, Humans may be considered as intelligent agents that sources Data mining and data warehousing together. are acting in close interconnection with other enable the synthesis of diverse information from. resources giving them superior goals and multiple sources ERP Workflow Management and. capabilities Business Intelligence Systems are good examples of. IT capabilities in information aggregation, From those considerations it is this paper view that the. concept of the Intelligent Manufacturing Enterprise of the In connection with the CPS modelling of enterprise. future should be based on three pillars resources structures and processes the integrative IT system. should be finally capable to link together all drivers and. I A CPS oriented enterprise model a CPS is a structure. resources related to a certain product to be executed. which possess a set of internal characteristics which. including the customer and the optimal resources according. determine its functionality autonomy purpose etc and the. to user requirements and to the enterprise capabilities and. communication capability,cost issues, By its inherent autonomy it allows considering when. III A holistic knowledge management system KMS if the. strategically planning activities only from the point of view. CPS oriented modelling represents the back bone of the. of functionalities competencies knowledge and behaviour. enterprise the knowledge management system should, represent its nervous system and mind It is the support for. By its communication capabilities it may change purpose enterprise intelligent and adaptive behaviour and for its auto. and improve functionalities thus evolving and adapting to configuration capabilities The integration is made through. new environments and situations allowing dynamical the IT system at two conceptual levels. reconfiguration for the system it belongs,At CPS module level Fig 2 As an autonomous system.
CPS oriented modelling encompass all the advantages of every CPS module has its own information and knowledge. agent oriented approach and embedded system resources They may have different semantics depending on. implementation but is adding a supplementary degree of their structure functionalities and origin encompassing. flexibility in communication and sensing and allows an models goals and functionalities Some of these are internal. increased level of intelligence by connecting to a knowledge and inherent to the CPS physical structure and they are. management system determining the structure of information they are using for. fulfilling them, II An integrative IT system The IT infrastructure should. include data processing storage and communication, technologies and the entire spectrum of the organization s. information systems including transaction processing. systems management information systems enterprise,resource planning systems databases DB and data. warehouses,One possible way of systematically viewing the IT. infrastructure is to consider the capabilities it provides in four. important aspects Fernandez and Sabherval 2010,Reach within the context of a network reach.
reflects the number and geographical locations of, the nodes that can be efficiently accessed Today s. development of the concepts of IoT and SOA will,allow IT infrastructures to connect every entity. represented by a service,Depth focuses on the detail and amount of. Fig 2 Knowledge management cycle at CPS module level. information that can be effectively communicated, over a medium it corresponds to the technological They should not be available for communication with other. aspects of bandwidth and customization modules and are usually structurally stable Knowledge. representing them could be considered as explicit and. The richness of a medium is based on its ability to. a provide multiple meanings simultaneously b, provide quick feedback c personalize messages But the real flexible dimension of a CPS resides in its.
and d use natural language The evolution of IT communication and information gathering capabilities It. allowed a significant increase in its ability to support allows a CPS module to define global oriented goals and new. rich communication capabilities It may be connected not only to a sensorial. network allowing it to react to the environment but also to. Aggregation refers to the capability of IT, the enterprise KMS from which it will be informed about. infrastructure to store and quickly process, global enterprise goals and requests concerning the use of its. information This enables the aggregation of large,capabilities. volumes of information drawn from multiple,19th IFAC World Congress. Cape Town South Africa August 24 29 2014, Moreover by the KMS may also be transmitted operational level workflow management supply.
supplementary knowledge acquired by other CPS modules chain management production scheduling and. which can allow updating of the internal knowledge planning order management. Information and data from the sensorial network is. strategic level goal setting product and process, considered by the CPS module as explicit it is used after. design enterprise development planning, appropriate checking and filtering for feeding its internal. models and for fulfilling its goals, On the other hand information obtained from KMS is used. differently it may contain either requirements orders or. problems to be solved by the CPS triggering a cycle which. implies information contextualization with respect to CPS. competencies and actual state simulation on internal models. activity planning decisions based on internal knowledge and. communication with other modules or new pieces of,knowledge acquired by some other CPS modules with. similar functionalities, This alternative requires a similar cycle but with different.
consequences first of all new pieces of information or Fig 3 Knowledge agent dynamics. knowledge may have different semantics as the source may These levels may be interpreted from the point of view of. have different structure and purposes Even if it should be necessary knowledge. represented by the integrative IT infrastructure in a. comprehensible format information should be checked by at the shop floor level the necessary knowledge is. running different internal models and simulation generally explicit and public it consists in process. contextualized in the local semantics and stored as new models as workflows machine programs. knowledge or rejected Knowledge storing implies also the procedures for humans problems have algorithmic. association of a reliability degree which may increase or decidable reliable solutions the solving time should. decrease based on subsequent results of knowledge be short and results predictable and deterministic. integration Much of the performance of a KMS relies on an Usually CPS agents acting at this level are either. appropriate use of the reliability degree based on source on representing resources or products and their. extrapolations on application results interactions are based on standard communication. procedures Gathering new knowledge is rarely, Knowledge integration implies application of different requested at this level especially because its. knowledge in solving actual problems and updating of integration takes time and may imply trial and error. internal models and reliability degree When the reliability scenarios which are not desirable precision being. degree of knowledge reaches a certain threshold the result of one of the most important agent success criteria. its application becomes a new competence of the CPS. module It may be shared with the KMS closing the cycle at the operational level problems to be solved are. more diversified and the systems that should be, Finally information obtained from internal models is a result managed are more dynamic inter connected and. of simulations which may be used for value judgement complex in nature models and procedures are less. allowing decisions and activity planning and it usually precise and they usually should be adapted at an. impacts as it is on knowledge storing and knowledge environment that should be firstly identified by. integration steps inter agent communication and intelligence. At enterprise level Fig 3 a hierarchical dynamic structure exchange Knowledge used here is partly explicit. of agents combining and migrating between levels and may be found in the common KMS but most of. according to their competencies and the enterprise goals it is what could be called proprietary knowledge. as it is gathered and integrated for use by specific. There are several ways in which knowledge may be agents knowledge stakeholders that have to deal. necessary and used in a manufacturing enterprise with with specific problems It may be explicit in the. respect to the time solving horizon for a given problem internal knowledge base of an agent but it has to. degree of precision and repeatability of results process gain a certain reliability degree and integration level. models and methodologies that should be used a s o in order to be made explicit for the KMS. Traditionally there are three control levels considered for a Integration is made by trial and error scenarios. manufacturing enterprise with respect to the above which are generally elaborated by every knowledge. mentioned criteria stakeholder At this level the knowledge necessary. for solving the same type of problem may be, shop floor level real time control of material detained by several agents which could act. flows machine programming and monitoring shop differently in same circumstances They have to. floor transport systems repository management exchange information in order to converge towards. 19th IFAC World Congress,Cape Town South Africa August 24 29 2014. reliable knowledge and to construct correct models 6 CONCLUSIONS. for problem solving, The paper is introducing new concepts with respect to the.
At the strategic level the most important capacity of Enterprise of the Future considered as a complex intelligent. an agent is pro activity The problem solving system Performances of production systems are reconsidered. environment is the most dynamic and uncertain and in the context of IoT and IoS paradigm implementation as. the agents should define not only their methods for ways of improving M2M H2M object to object O2O. solving new problems which they may do by communication based on the cognitive character of the. decomposing them in similar operational problems production chain modelled as a CPS dynamic network. but also the success criteria by which they have to aiming to a sustainable adaptive behaviour. appreciate the solutions Here is needed what is, In the future the aspect of the sustainable engineering will be. called expert knowledge as it is tacit in nature and. explicitly taken into account by mechanisms encompassed at. depends extensively on the internal model of the, the level of the cognitive agents and validating the decisions. agent Choosing correct success criteria impacts, taken at the expert wisdom level of the enterprise KMS. greatly on the enterprise survival and progress and. Sustainable Engineering is based on four pillars economy. such behaviour may be accordingly considered as, society technology and environment the Intelligent Cyber. agent wisdom, Enterprise must then consider technical economical social.
The system is dynamic in nature not only because agents and ecological performance to create a real sustainable Eco. should always interact and their communication patterns are System. changing the overall behaviour of the system but also. Manufacturing must be sustainable in terms of performance. because at every level there are some problems which have. of products and processes quality of products services and. different characteristics When a resource is breaking down at. processes and safety of people facilities and, a shop floor level a local re scheduling problem has to be. infrastructures, solved So some of the agents usually CPS modules that. include human intelligence have to test trial and error We have to create intelligent products based on embedded. scenarios based on the concrete data they have and on devices allowing innovative operation and new materials. eventual appeal to proprietary knowledge These agents learn allowing easy disassembly recovery recycling with lower. and may become knowledge stakeholders as well as some of impact on the environment. operational agents should comply with real time problem. The Intelligent Cyber Enterprise may solve these aspects but. solving time horizon thus acting at shop floor level. the transition of actual enterprises towards such structures. New models developed at the operational level may include necessitates special efforts and investments in processes and. knowledge useful for the strategic level and by interaction services re organization and re design and especially the. an operational knowledge stakeholder may became an expert formation of a human resource able to integrate the above. There is much research to be done in order to develop reliable mentioned concepts. methods providing agents the possibility of learning and. REFERENCES, evolution a promising approach is working with motivated. knowledge agents Bannat A et al 2011 Artificial Cognition in Production. Systems In IEEE Transactions on Automation Science. But the most reliable way used today is based on the human. resource integration in CPS modules as H2M and Engineering vol 8 no 1. communication is developing allowing exchanges in explicit Brecher C Breitbach Th Muller S Mayer Odenthal B. Schlick C Herfs W 2012 3D Assembly Group, and tacit knowledge and H2H communication remains the. Analysis for Cognitive Automation In Journal of, best way in exchanging and integrating tacit knowledge.
Robotics DOI 10 1155 2012 375642, In this way the enterprise may be considered to have an Dumitrache I Caramihai S I 2010 The Intelligent. organic growth each part continuously influencing the Manufacturing Paradigm in Knowledge Society In Pasi. others based on a combination of local and global goals The Virtanen and Nina Helander ed Knowledge. CPS modelling approach ensures for sub systems the Management InTech Publishing. possibility to locally comply with a part of environmental Dumitrache I Caramihai S I 2013 The Enterprise of. dynamics relying at the same time on the cooperation with Future As a Cyber Physical System In 7th IFAC. other modules for the rest Conference on Manufacturing Modelling Management. and Control Saint Petersburg http www ifac, The equilibrium maintained through a KMS allowing the. papersonline net DOI 10 3182 20130619 3 RU, compliance between local and global goals sustained by an. 3018 00418, integrative IT system will ensure an optimum development of. Fernandez I B Sabherwal R 2010 Knowledge, the enterprise and allow for its adaptive intelligent.
management systems and processes M E Sharpe Inc,Rungger M Ding H Paschedag T Stursberg O 2008. Hierarchical Hybrid Modeling and Control of Cognitive. Manufacturing Systems Proc of the 1st Int Workshop.

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