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Towards Integration of Knowledge Extraction from Process Interoperability in Future Internet Enterprise Systems
Proceedings of the 14th IFAC Symposium on Information Control Problems in Manufacturing Bucharest, Romania, May 23-25, 2012
Towards Integration of Knowledge Extraction from Process Interoperability in Future Internet Enterprise Systems Mihnea Alexandru Moisescu*, Ioan Stefan Sacala*, Aurelian Mihai Stanescu*, Cristina Serbanescu*.
*8QLYHUVLW\³3ROLWHKQLFD´RI%XFKDUHVW, Faculty of Automatic Control and Computers, Bucharest Romania (e-mail: [email protected], [email protected], [email protected]). Abstract: Current R&D directions sustained by the European Commission, by FP7 and in the near future by FP8 research programs, are focusing on the development and standardization of new technologies to VXVWDLQ WKH ³)XWXUH ,QWHUQHW´ ,Q WKLV FRQWH[W WKH GHYHORSPHQW RI QHZ ,QWHUQHW UHODWHG FRQFHSWV DQG technologies oriented towards providing positive benefits for economy has been included in a broad FRQFHSW RI ³)XWXUH ,QWHUQHW %DVHG (QWHUSULVH 6\VWHPV´ 7KH ,QWHOOLJHQW 0DQXIDFWXULQJ 6\VWHPV ,06 paradigms, are leading our Information Society towards New Economy-driven Knowledge Society copying with Global e-Markets new list of System of Systems requirements. Efficient interoperability, both horizontal and vertical, is a basic requirement towards the aim of Enterprise System Integration within Collaborative Concurrent Competitive Enterprises. In this context, the authors will propose a framework for web service composition and knowledge extraction form process execution based on process description embedded in Internet of Things compliant intelligent objects. Keywords: Knowledge Management, Interoperability, Future Internet Enterprise Systems
1. INTRODUCTION Today¶V society has to face great challenges due, ironically, to its own development capacity and speed, that resulted in phenomena like globalization and competition, in a more and more rapidly changing environment. The development of Information & Communication Technologies (ICT), which was intent to solve usual problems, became actually a driver for the increased complexity of socio-economical advance. Considering the concept of Open Enterprise Innovation which will extend the boundaries of collaboration and knowledge exchange to other enterprises, research institutes and academic research groups, new technologies have to be taken into consideration in order to be able to sustain then paradigm shift. The authors have taken into account researches in the fields of manufacturing system, as well as from the area of knowledge management, control systems, enterprise architecture and future internet systems, in order to develop a model for the imbricate development of manufacturing and knowledge. The present paper will discuss the future of the manufacturing oriented knowledge management that use the concept of Internet of Things. Emerging intelligence could be obtained by a future enterprise from the information detained by each of its components, contextualized for reflecting a given situation. The next section will present the respective compliant evolution of manufacturing systems and knowledge management, underlining their mutual relationship. A brief survey of manufacturing concepts and paradigm shifts that have radically influenced the enterprise architectures in the
978-3-902661-98-2/12/$20.00 © 2012 IFAC
past years will be used in order to emphasize the importance of other domains (control theory, communications, artificial intelligence) evolution in the process. Section III will introduce the paradigm of Internet of Things (IoT), that will be used in section IV for shaping a possible evolution of manufacturing systems using this concept. 2. PARADIGM SHIFTS TOWARDS FUTURE ENTERPRISE SYSTEMS One of the most important moments in the evolution of manufacturing systems was the development of the CIMOSA (Computer Integrated Manufacturing ± Open System Architecture) concepts. The CIM-OSA approach and the paradigms derived from the integrationist theory in manufacturing insisted on very precise and detailed organization of the enterprise as a key factor of success. However, research exploring the influence of organizational structure on the enterprise performance in dynamic environments, already indicated that there is a fundamental tension between possessing too much and too little structure. As a general result, organizations that have too little structure do not possess the capability of generating appropriate behaviors, though lacking efficiency, as those using too much structure are deficient in flexibility. New manufacturing paradigm like: Concurrent Engineering, Virtual Organizations, Intelligent Manufacturing Systems, and Networked Enterprises, have tried to make use of collaborative autonomous structures, and provided simple enough, versatile architectures based on elaborated communication infrastructure in order to ensure efficient behavior patterns. (Dumitrache, 2008)
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To manage the recent kind of complex systems, a new approach has to be developed, integrating Computer and Communications in order to reinforce the analytical power of control structures, giving way to new concepts, from Virtual Organizations to Intelligent Manufacturing Systems. We will further review these concepts as important steps towards the development of Future Enterprise Systems. A manufacturing enterprise system can be defined in the context of the Knowledge Economy as a n-tuple involving: E: f[Mp, Mo, Ma, Mr, Mk, MA, G] (1) where: Mp: a set of various technical and economical processes (manufacturing, design , business, management, a.s.o.) Mo: a set of "computational objects" Ma: a set of both artificial and human agents Mk: a set of both tacit and social knowledge MA: a set of activities (integrated by flow-work management) G: a business goal that is based on a decomposition roll (objective/ activities/ tasks). (Stanescu et all, 2008) A Virtual Organization (VO) is, according to a widely DFFHSWHG GHILQLWLRQ ³D IOH[LEOH QHWZRUN RI LQGHSHQGHQW entities linked by information technology to share skills, knowledge and access to others' expertise in non-traditional ZD\V´ $ 92 FDQ DOVR EH FKDUDFWHUL]HG DV D IRUP RI cooperation involving companies, institutions and/or individuals delivering a product or service on the basis of a common business understanding. The units participate in the collaboration and present themselves as a unified organization. A potential definition which should be improved by dealing with the sound issues, could offer a merging systemic (complex adaptive system) formulation: A virtual enterprise is an open geographically dispersed metasystem which has a formal support within a 3Dimenssions "Universe of discourse" U (Discrete Event Dynamic Systems/ Information Systems/ Knowledge based Systems), generating a set of "fabrications" F in terms of Mview set of various multi-view (perspective) representations, such as the b common business goal is achievable optimally or suboptimal (Stanescu et all, 2008): 9( ^8 ) 0view *` i) Mv; a set of specific models (functional model, organizational model, information model, data/metadata model, economic model, a.s.o.) ii) F: a set of "fabricators" (autonomous system) supporting a specific role within a planned scenario, such as a nominal state trajectory of the System of Systems (Sos should be explicitly governed) In the framework of increasing effectiveness and Quality of Service (QoS) in a global e-economy, networked, collaborative manufacturing paradigm includes: design, programming, operation and diagnosis of automation behaviour in distributed environments, system integration models, configuration and parameterization for communication connected devices, heterogeneous networks for automation-based quality of services, life-cycle aspects for distributed automation systems and remote maintenance.
The enterprise itself is regarded as a network integrating advanced technologies, computers, communication systems, control strategies as well as cognitive agents (both humans and/or advanced intelligent systems) able not only to manage processes and products, but also to generate new behaviours for adapting themselves to a dynamic market. Collaborative networked organizations (CNO) represent a new dynamic world, based on cooperation, competitiveness, world-excellence and agility. They are complex production structures ± scaling from machine tools, robots, conveyors, etc., to knowledge networks, including humans ± and should normally be designed as hives of autonomous but cooperative/ collaborative entities. Intelligent Manufacturing Systems (IMS) can be viewed as large pools of human and software agents, with different levels of expertise and different local goals, which have to act together, in variable configurations of temporary communities in order to react to dynamically changing inputs and to accomplish dynamically changing objectives. As systems acting in unpredictable and turbulent environments, IMS have to solve problems as: - Integrated production planning and scheduling (mathematical models and combinations of operation research, estimation of solution appropriateness, parametric scalable modules for production optimization, integration of intelligent technologies as hybrid intelligent systems) - Real-time production control (recognition situations and related problem solving, decision support, reactive and proactive rescheduling algorithms and production control support systems). - Management of distributed, cooperative systems (multiagent systems in hierarchical and heterarchical architecture, models for describing production networks, behaviour networks analysis and negotiation mechanisms and communication protocols for efficient behavioral patterns involving inter-related spatial and temporal effects) (Dumitrache, 2008) Manufacturing enterprise intelligence should then encompass features as: - Adaptivity ± as a primary intelligence level, implying the capacity of acting on UXOHV³LI-then-HOVH´ - Reasoning ± as a higher level that includes preparation of new possible scenarios DQGVWUDWHJLHV³ZKDWLI´ - Knowledge representation and processing (including focusing, feature identification and organization in connectionist structures) Considering the chalanging and the structure of Intelligent Manufacturing it became obvious that it corresponds to at least some definitions of Complex Adaptive Systems as complex systems that include:
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x
reactive units, i.e., units capable of exhibiting systematically different attributes in reaction to changed environmental conditions. goal-directed units, i.e., units that are reactive and that direct at least some of their reactions towards the achievement of built-in (or evolved) goals.
INCOM 2012, May 23-25, 2012 Bucharest, Romania
x
planner units, i.e., units that are goal-directed and that attempt to exert some degree of control over their environment to facilitate achievement of these goals.
The balance between control and emergence is a real challenge for designing CAS involving non-linear phenomena, incomplete data and knowledge - a combinatorial explosion of states, dynamic changes in environment.
x x x x x x x
Resource planning towards efficient use Green manufacturing Enterprise social networking Business partners collaboration Customer relationships Tacit and implicit Enterprise Knowledge Management Business transparency and corporate governance.
The introduction of a new concept: Quality of Being, (FInES, 2009) becomes a necessity in regard to the evolution of enterprise quality issues. QoB will have to mediate between the enterprise quality management and the evolution of enterprise operational dimension: Invent, Plan, Build, Operate, Monitor and Manage and Dismiss. (FInES, 2012) In order to achieve such characteristics a new concept has been introduced: Internet Enterprise Resource (FInER) as describing a digitalization of enterprise entities regardless of their properties like: tangible or intangible, simple or complex. These representation of such entities is related to identification, computational power, storage and communication and characterized by different functions. This concept will support the evolution of FInES as a network of different FInERs. The integration of the social emerging Internet of people with the enterprise oriented Internet of Knowledge represents another important step in enterprise business process reengineering. The current knowledge management tools and knowledge repositories will have to be replaced by a flow of knowledge from distributed FInER collections accessible via internet infrastructure and with a meta-knowledge infrastructure represented with the help of ontologies and linked at semantic level.
Fig1. Successive paradigm shifts that influenced Enterprise Systems 3. FUTURE INTERNET ENTERPRISE SYSTEMS The integration of new concepts in the area of enterprise collaboration and interoperability like: Collaborative Networks and Digital Business Ecosystem, the large scale utilization of the Software as a Service (SaaS) using the new infrastructure provided by Cloud Computing technologies and the ongoing demand for communication and collaboration is stressing to the limits the current internet technologies and infrastructure.
A set of QoB predications have been defined in order to unify approaches towards the integration of FI technologies (FInES, 2012): x Inventive Enterprise x Humanistic Enterprise x Cognitive Enterprise x Community-oriented Enterprise x Agile Enterprise x Glocal Enterprise x Sensing Enterprise A few technological paradigms that can sustain the future researches on FInES are presented below: x x x x x x x
In this context the development of new Internet related technologies oriented towards providing positive benefits for individuals, society, economy, culture and environment has been included in a broad concept of Future Internet Systems. A updated set of business values is emerging in relation to the transformation of Internet into a universal business environment (FInES, 2009): x Revenue and profit x Reputation and level of trust
Applications with proactive behavior IaaS or PaaS (Infrastructure/Platform as a Service) Interoperability Service Utility (ISU) Knowledge Representation and Semantic Modeling Federated, Open and Trusted Platforms (FOT) Software as a Service (SaaS) Automated Service Discovery and Configuration
This will include the integration and federation of heterogeneous service-based systems (SBS). A paradigm shift regarding the traditional 3 layer reference architecture:
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Functional, Logical and Technical will allow for the integration of new trends such as: pattern based approach. (Stricker et all, 2010) An important aspect of FInES is the integration of the new approaches to the Future Internet: Internet of Service, Internet of Things, 3D and Media Internet, Internet of Knowledge, Internet of People. Two main benefits have been emphasized within the Internet of Things research area, with regard to enterprise systems ³WKLQJV RQ WKH PRYH´ XELTXLWRXV intelligent devices". (Santucci, 2009) 7KH ³WKLQJV RQ WKH PRYH´ FRQFHSW ZLOO DOORZ EHWWHU identification and transport efficiency of food products along the Supply Chain from the producer to the distributer, the shop floor, cashier and check-out leading to the intelligent logistic management. This will also prevent counterfeiting and assure consumers of controlled origin of the food product. The "ubiquitous intelligent devices" concept will allow the possibility of information exchange between any intelligent object. Another capability is the implementation of reactive behaviours according to a predetermined set of actions. With the advent of globalization, enterprises have been pushed to operate at an international level in terms of sourcing, production and markets, as well as finance and technologies. This process has promoted a number of improvements for the economy of the planet, allowing for new business scenarios, with new players entering the scene. But at the same time, especially where the enterprises do not show transparency and social quality (see above), globalization is producing hardship and difficulties for part of the populations in both advanced and developing countries. Globalization is with us, and it will remain. Thus rather than fighting against it, a number of corrections to limit its downsides must be introduced. One of the most significant is the possibility of conjugating two apparently contradicting dimensions, i.e., local and global, merging them into a virtuous blend referred WR DV ³glocal´ $ Glocal Enterprise will be able to understand and think at a global level, while being aware of the local levels in which it operates, acting in harmony with its geo-social surroundings. To achieve this, it is necessary to show a specific kind of flexibility, necessary for instance to adapt products and production processes to the culture and needs of a given geographic area. (FInES, 2009) Integrating devices and everyday objects to a smart environment is the first step towards the Internet of Things. Technical, extensible standards and protocols suited for ³,QWHUQHW RI 7KLQJV´ DUH UHTXLUHG in order to integrate all types of devices, including robots. Several standards have been proposed in order to identify and track objects based on RFID tags. The most successful have been of them are the MIT AutoID Lab standards that include: EPC (Electronic Product Code) ± analogous to IP address x ONS(Object Name Service) ± analogous with DNS x PML(Physical Markup Language) ± analogous with XML and the Uid Center: Ubiquitous Identification Code. x
Fig. 2. Representation of FInER object building blocks. A framework for modeling the tag data, assigned to a real object has been provided in fig 2. The framework adds to the a data describing the object: data that allows for the virtualization of the object information UHJDUGLQJ WKH REMHFW¶V RZQ EHKDYLRU RU LW¶s functionality LQIRUPDWLRQ UHJDUGLQJ RWKHU REMHFW¶V EHKDYLRUV WRZDUGV WKLV object.
Fig3. Dimensions of Enterprise Systems $V WKH REMHFW¶V SURSHUWLHV DQG GHVFULSWLRQ KDV DOUHDG\ EHHQ implemented in RFID tags, the focus of this research group is to e[WHQG WKH REMHFW¶V GHVFULSWLRQ E\ GHILQLQJ DQG implementing object behaviors. All of these data and LQIRUPDWLRQ FDQ EH VWRUHG LQ WKH WDJ¶V PHPRU\ $ SUREOHP would be to find a wide used tool to describe this data and information. As discussed, a suitable and largely available way for data transfer is the Extended Markup Language. As PML (based on XML) has been widely adopted by the users of the EPC standard, we chose PML for the object proprieties description within the framework. PML also allows for the description of object shape and color but we consider that a PRUH DSSURSULDWH ZD\ WR GHVFULEH WKH REMHFW¶V YLVXDO properties would be to use standard 3D web oriented language: X3D. X3D language is considered to be the next step after VRML (Virtual Reality Markup Language) aiming at communicating 3D on the web, between applications and across distributed networks and web services. In order to describe the behavior of the object and the behavior towards the object, XTND - XML Transition Network Definition Language has been chosen. We can model behaviors using
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transition networks. These kinds of networks are used to describe a set of states and the transitions that are possible between them.
operational level which is defined as the level where different stakeholders (individuals, departments), with diverse skills, store and share knowledge.
7KH LQWHJUDWLRQ RI REMHFWV ZLWKLQ WKH ³,QWHUQHW RI 7KLQJV´ offers great perspectives, but it is not easy to implement at this point, taking into consideration the following aspects:
To cope with such cases the construction of a knowledge module is proposed. In this case "knowledge module" will refer to a sequence of primitive activities with assigned resources that are necessary to fulfill a given objective. It will be also considered that by an activity is denoted the implementation of knowledge at a lower level of granularity, by a task, the implementation of a primitive action.
x x x x x x
different or no interoperability standards different service descriptions and capability declaration different radio interfaces and media access different resources management different encryption different publication and subscription of devices
4. INTEGRATION OF KNOWLEDGE EXTRACTION WITH INTERNET OF THINGS ORIENTED SYSTEMS Recent studies regarding the balance between organizational structure and enterprise efficiency for different kind of enterprises and environments has provided the following conclusions (Davis et al, 2007): - There is an inverted U-shaped relationship between structure and performance, that is asymmetric: too little structure leads to a catastrophic performance decline while too much structure leads to only a gradual decay - The key dimension of the market dynamism is unpredictability that underlines the tension between too much and too little structure. The range of optimal structures varies inversely with unpredictability: in unpredictable environments, there is only a very narrow range of optimal structures with catastrophic drops on either side that are likely to be difficult to manage. - Other dimensions of market dynamism (i.e. velocity, complexity, and ambiguity) have their own unique effects on performance Extracting knowledge in order to allow for market triggered business process re-engineering can provide the key to balance structure and performance within the enterprise environment. Knowledge management is recognizing and taking into account two main kind of knowledge co-existing in an organization (Dalkir, 2005): explicit knowledge, which is the only form of knowledge possessed by non-human agents, and which has been codified and structured and tacit knowledge, which is the intangible knowledge that only human agents can have. Organizational knowledge management approach focuses especially on procedures to transform tacit knowledge into explicit. Consider the following scenario: a new problem is raised, eventually by the strategic level of a manufacturing enterprise after analyzing supply chain processes. At this level, problem specification is made taking into account very general knowledge, as enterprise purpose, technologies and theories that are available a.s.o. Problem specification is made in terms of initial conditions and final results. The SUREOHP¶V VROXWLRQ ZLOO EH KDQGOHG DQG LPSOHPHQWHG DW WKH
A few characteristics are important to be discussed: - the definition of a "knowledge module" is iterative (it can include other knowledge modules); - it is always important for solving a problem to define primarily a list (part of a common dictionary) of primitive actions ± implying, at the organizational level, an important focus on generating, articulating, categorizing and systematically leveraging organizational knowledge assets. Internet of Future oriented Enterprise Systems will allow for the implementation of such new concepts and technologies aiming at improving enterprise efficiency. The research in the area of intelligent objects capable of unrestricted communication and interoperability with other similar objects as well as with any service within the entire enterprise system is focused on supporting that goal. In this context the development of methods used to transform common objects involved in the enterprise business processes into intelligent objects is regarded as a highly benefic. The first step for such an approach is to be able to identify the object and to distinguish it from the environment. The recent progress of the RFID technology has boosted the capability of object identification and allowed for the development of new identification technologies as EPC code and ucode as discussed in the previous section. These technologies require that the information suitable for the identification of an object should be accessed from a remote database. With the development of new and more powerful data storage devices we can focus on a different approach: storing the data on the tag attached to the object and accessing that data when ether necessary. A data representation schema has been proposed in figure 2. Business Process Modeling Notation standard offers a comprehensive way for description and representation. Interoperability frameworks should be taken into consideration and the following tiers have to be included: organizational interoperability that focuses on the interoperability of business processes and information architectures beyond the borders of different administrations and semantic interoperability that aims to establish a common meaning of the exchanged data, process models or used procedures. Ontology basically provides the semantics and has a twofold role in this context: can describe both the semantics of the modelling language constructs as well as the semantics of model instances. In the context of business processes this means that ontologies can be used for the explication of both
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the semantics of activities in general as well as for describing the semantics of a specific activity in that, for instance, the used resources or the application context are described by a domain ontology. The second step is to integrate such objects with the enterprise systems the information attached to the tag should be not exclusively divided in the following categories: object proprieties, object functionality or in a broader meaning object behavior, description of the planned processes (at task level) which involve the object, and the description of the DFWXDOSURFHVVHVDV³H[SHULHQFHG´E\WKHREMHFW The defined process attached to the object is associated with the process models as described in the Process Modeling level of the Enterprise Architecture. This approach will allow for the creation of a map of the processes that the object will be subjected to and for a better integration with the services included in the Enterprise Systems. In such a case any enterprise system or production cell will be able to read the process map and proceed with the object accordingly. An example can be represented by a product that is going to be shipped. The shipping service will be able to read the process map, identify the shipping sub-process and act according to the predefined tasks. By extracting process information from the object, service choreography can be achieved within the enterprise system service layer.
Fig 4. Intelligent objects represented as FInER within the FInES Knowledge Management System As the predefined processes may differ to the actual processes completed by the object, a record to register the changes can be defined. An example in this area can be identified at the level of an adaptive supply chain. Such a record can provide valuable feedback related to the insight of the sub-processes and tasks. This information can be further processed in order to produce valuable knowledge within the Enterprise Management System.
Knowledge management in particular, owing to its evolution that parallels that of manufacturing paradigms, is expected to issue new methods allowing humans to both benefit from and increase the value of ± technological advances. A hybrid knowledge structure can be foreseen, where the interaction between human and non-human knowledge stakeholders will became transparent and will allow creation and use of metaknowledge. REFERENCES Dalkir, K. (2005). Knowledge Management in Theory and Practice. Elsevier, ISBN-13: 978-0- 7506-7864-3, ISBN10: 0-7506-7864-X Davis,J. P.; Eisenhardt K & Bingham B.C. (2007) Complexity Theory, Market Dynamism and the Strategy of Simple Rules, Proceedings of DRUID Summer Conference 2007 on Appropriability, Proximity Routines and Innovation, Copenhagen, CBS, Denmark, June 18 20, 2007 Dumitrache, I., Stanescu, A.M., Caramihai, S.I., Voinescu, M., Moisescu, M.A., Sacala, I.S., (2009) Knowledge Management Based Supply Chain In Learning Organization, In: 13th IFAC Symposium on Information Control Problems in Manufacturing (Incom 2009), 3-5 Jun 2009, Moscow, Russian federation Goncalves R., Sarraipa J. and SteigeræGarcao A., Semantic harmonization for seamless networked supply chain planning in the future of internet, , IFIP International Conference Network of the Future, IFIP AICT 326, pp. 78ææ89. IFIP International Federation for Information Processing, 2010, Australia. (IFIP) FInES Research Roadmap Task Force, (2009). Future Internet Enterprise Systems (FInES) Cluster, Research Roadmap, Version 1.3, 9 november 2009, http://cordis.europa.eu/fp7/ict/enet/ FInES Research Roadmap Task Force, (2012). Future Internet Enterprise Systems (FInES) Cluster, Research Roadmap, Version 2.0, march 2012, http://cordis.europa.eu/fp7/ict/enet/ Santucci G., (2009). From Internet of Data to Internet of Things, Available from: http://ec.europa.eu/ information_society/ policy/rfid/ Stanescu A.M., Dumitrache I., Pouly M., Caramihai S. I., Moisescu, M. (2007) Towards a General Systems Theory approach to design the future of Concurrent Engineering Science, In Geilson Loureiro and Richard Curran (ed.) Complex Systems Concurrent Engineering Collaboration Technology Innovation and Sustainability, pp 3-10, Springer Verlag Stricker V., Lauenroth K., Corte P., Gittler F., De Panfilis S., Pohl K., (2010) Creating a Reference Architecture for Service-Based Systems- A Pattern-Based Approach, In Georgios Tselentis et all (eds.) Towards the Future Internet, Emerging Trends from European Research. 161-173, IOS Press
5. CONCLUSIONS The concepts, proposed within the Internet of Things, paradigm are becoming a reality due to the research efforts leading towards the development of new devices and services.
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Towards Integration of Knowledge Extraction from Process Interoperability in Future Internet Enterprise Systems Mihnea Alexandru Moisescu*, Ioan Stefan Sacala*, Aurelian Mihai Stanescu*, Cristina Serbanescu*.
*8QLYHUVLW\³3ROLWHKQLFD´RI%XFKDUHVW, Faculty of Automatic Control and Computers, Bucharest Romania (e-mail: [email protected], [email protected], [email protected]). Abstract: Current R&D directions sustained by the European Commission, by FP7 and in the near future by FP8 research programs, are focusing on the development and standardization of new technologies to VXVWDLQ WKH ³)XWXUH ,QWHUQHW´ ,Q WKLV FRQWH[W WKH GHYHORSPHQW RI QHZ ,QWHUQHW UHODWHG FRQFHSWV DQG technologies oriented towards providing positive benefits for economy has been included in a broad FRQFHSW RI ³)XWXUH ,QWHUQHW %DVHG (QWHUSULVH 6\VWHPV´ 7KH ,QWHOOLJHQW 0DQXIDFWXULQJ 6\VWHPV ,06 paradigms, are leading our Information Society towards New Economy-driven Knowledge Society copying with Global e-Markets new list of System of Systems requirements. Efficient interoperability, both horizontal and vertical, is a basic requirement towards the aim of Enterprise System Integration within Collaborative Concurrent Competitive Enterprises. In this context, the authors will propose a framework for web service composition and knowledge extraction form process execution based on process description embedded in Internet of Things compliant intelligent objects. Keywords: Knowledge Management, Interoperability, Future Internet Enterprise Systems
1. INTRODUCTION Today¶V society has to face great challenges due, ironically, to its own development capacity and speed, that resulted in phenomena like globalization and competition, in a more and more rapidly changing environment. The development of Information & Communication Technologies (ICT), which was intent to solve usual problems, became actually a driver for the increased complexity of socio-economical advance. Considering the concept of Open Enterprise Innovation which will extend the boundaries of collaboration and knowledge exchange to other enterprises, research institutes and academic research groups, new technologies have to be taken into consideration in order to be able to sustain then paradigm shift. The authors have taken into account researches in the fields of manufacturing system, as well as from the area of knowledge management, control systems, enterprise architecture and future internet systems, in order to develop a model for the imbricate development of manufacturing and knowledge. The present paper will discuss the future of the manufacturing oriented knowledge management that use the concept of Internet of Things. Emerging intelligence could be obtained by a future enterprise from the information detained by each of its components, contextualized for reflecting a given situation. The next section will present the respective compliant evolution of manufacturing systems and knowledge management, underlining their mutual relationship. A brief survey of manufacturing concepts and paradigm shifts that have radically influenced the enterprise architectures in the
978-3-902661-98-2/12/$20.00 © 2012 IFAC
past years will be used in order to emphasize the importance of other domains (control theory, communications, artificial intelligence) evolution in the process. Section III will introduce the paradigm of Internet of Things (IoT), that will be used in section IV for shaping a possible evolution of manufacturing systems using this concept. 2. PARADIGM SHIFTS TOWARDS FUTURE ENTERPRISE SYSTEMS One of the most important moments in the evolution of manufacturing systems was the development of the CIMOSA (Computer Integrated Manufacturing ± Open System Architecture) concepts. The CIM-OSA approach and the paradigms derived from the integrationist theory in manufacturing insisted on very precise and detailed organization of the enterprise as a key factor of success. However, research exploring the influence of organizational structure on the enterprise performance in dynamic environments, already indicated that there is a fundamental tension between possessing too much and too little structure. As a general result, organizations that have too little structure do not possess the capability of generating appropriate behaviors, though lacking efficiency, as those using too much structure are deficient in flexibility. New manufacturing paradigm like: Concurrent Engineering, Virtual Organizations, Intelligent Manufacturing Systems, and Networked Enterprises, have tried to make use of collaborative autonomous structures, and provided simple enough, versatile architectures based on elaborated communication infrastructure in order to ensure efficient behavior patterns. (Dumitrache, 2008)
1458
10.3182/20120523-3-RO-2023.00395
INCOM 2012, May 23-25, 2012 Bucharest, Romania
To manage the recent kind of complex systems, a new approach has to be developed, integrating Computer and Communications in order to reinforce the analytical power of control structures, giving way to new concepts, from Virtual Organizations to Intelligent Manufacturing Systems. We will further review these concepts as important steps towards the development of Future Enterprise Systems. A manufacturing enterprise system can be defined in the context of the Knowledge Economy as a n-tuple involving: E: f[Mp, Mo, Ma, Mr, Mk, MA, G] (1) where: Mp: a set of various technical and economical processes (manufacturing, design , business, management, a.s.o.) Mo: a set of "computational objects" Ma: a set of both artificial and human agents Mk: a set of both tacit and social knowledge MA: a set of activities (integrated by flow-work management) G: a business goal that is based on a decomposition roll (objective/ activities/ tasks). (Stanescu et all, 2008) A Virtual Organization (VO) is, according to a widely DFFHSWHG GHILQLWLRQ ³D IOH[LEOH QHWZRUN RI LQGHSHQGHQW entities linked by information technology to share skills, knowledge and access to others' expertise in non-traditional ZD\V´ $ 92 FDQ DOVR EH FKDUDFWHUL]HG DV D IRUP RI cooperation involving companies, institutions and/or individuals delivering a product or service on the basis of a common business understanding. The units participate in the collaboration and present themselves as a unified organization. A potential definition which should be improved by dealing with the sound issues, could offer a merging systemic (complex adaptive system) formulation: A virtual enterprise is an open geographically dispersed metasystem which has a formal support within a 3Dimenssions "Universe of discourse" U (Discrete Event Dynamic Systems/ Information Systems/ Knowledge based Systems), generating a set of "fabrications" F in terms of Mview set of various multi-view (perspective) representations, such as the b common business goal is achievable optimally or suboptimal (Stanescu et all, 2008): 9( ^8 ) 0view *` i) Mv; a set of specific models (functional model, organizational model, information model, data/metadata model, economic model, a.s.o.) ii) F: a set of "fabricators" (autonomous system) supporting a specific role within a planned scenario, such as a nominal state trajectory of the System of Systems (Sos should be explicitly governed) In the framework of increasing effectiveness and Quality of Service (QoS) in a global e-economy, networked, collaborative manufacturing paradigm includes: design, programming, operation and diagnosis of automation behaviour in distributed environments, system integration models, configuration and parameterization for communication connected devices, heterogeneous networks for automation-based quality of services, life-cycle aspects for distributed automation systems and remote maintenance.
The enterprise itself is regarded as a network integrating advanced technologies, computers, communication systems, control strategies as well as cognitive agents (both humans and/or advanced intelligent systems) able not only to manage processes and products, but also to generate new behaviours for adapting themselves to a dynamic market. Collaborative networked organizations (CNO) represent a new dynamic world, based on cooperation, competitiveness, world-excellence and agility. They are complex production structures ± scaling from machine tools, robots, conveyors, etc., to knowledge networks, including humans ± and should normally be designed as hives of autonomous but cooperative/ collaborative entities. Intelligent Manufacturing Systems (IMS) can be viewed as large pools of human and software agents, with different levels of expertise and different local goals, which have to act together, in variable configurations of temporary communities in order to react to dynamically changing inputs and to accomplish dynamically changing objectives. As systems acting in unpredictable and turbulent environments, IMS have to solve problems as: - Integrated production planning and scheduling (mathematical models and combinations of operation research, estimation of solution appropriateness, parametric scalable modules for production optimization, integration of intelligent technologies as hybrid intelligent systems) - Real-time production control (recognition situations and related problem solving, decision support, reactive and proactive rescheduling algorithms and production control support systems). - Management of distributed, cooperative systems (multiagent systems in hierarchical and heterarchical architecture, models for describing production networks, behaviour networks analysis and negotiation mechanisms and communication protocols for efficient behavioral patterns involving inter-related spatial and temporal effects) (Dumitrache, 2008) Manufacturing enterprise intelligence should then encompass features as: - Adaptivity ± as a primary intelligence level, implying the capacity of acting on UXOHV³LI-then-HOVH´ - Reasoning ± as a higher level that includes preparation of new possible scenarios DQGVWUDWHJLHV³ZKDWLI´ - Knowledge representation and processing (including focusing, feature identification and organization in connectionist structures) Considering the chalanging and the structure of Intelligent Manufacturing it became obvious that it corresponds to at least some definitions of Complex Adaptive Systems as complex systems that include:
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reactive units, i.e., units capable of exhibiting systematically different attributes in reaction to changed environmental conditions. goal-directed units, i.e., units that are reactive and that direct at least some of their reactions towards the achievement of built-in (or evolved) goals.
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x
planner units, i.e., units that are goal-directed and that attempt to exert some degree of control over their environment to facilitate achievement of these goals.
The balance between control and emergence is a real challenge for designing CAS involving non-linear phenomena, incomplete data and knowledge - a combinatorial explosion of states, dynamic changes in environment.
x x x x x x x
Resource planning towards efficient use Green manufacturing Enterprise social networking Business partners collaboration Customer relationships Tacit and implicit Enterprise Knowledge Management Business transparency and corporate governance.
The introduction of a new concept: Quality of Being, (FInES, 2009) becomes a necessity in regard to the evolution of enterprise quality issues. QoB will have to mediate between the enterprise quality management and the evolution of enterprise operational dimension: Invent, Plan, Build, Operate, Monitor and Manage and Dismiss. (FInES, 2012) In order to achieve such characteristics a new concept has been introduced: Internet Enterprise Resource (FInER) as describing a digitalization of enterprise entities regardless of their properties like: tangible or intangible, simple or complex. These representation of such entities is related to identification, computational power, storage and communication and characterized by different functions. This concept will support the evolution of FInES as a network of different FInERs. The integration of the social emerging Internet of people with the enterprise oriented Internet of Knowledge represents another important step in enterprise business process reengineering. The current knowledge management tools and knowledge repositories will have to be replaced by a flow of knowledge from distributed FInER collections accessible via internet infrastructure and with a meta-knowledge infrastructure represented with the help of ontologies and linked at semantic level.
Fig1. Successive paradigm shifts that influenced Enterprise Systems 3. FUTURE INTERNET ENTERPRISE SYSTEMS The integration of new concepts in the area of enterprise collaboration and interoperability like: Collaborative Networks and Digital Business Ecosystem, the large scale utilization of the Software as a Service (SaaS) using the new infrastructure provided by Cloud Computing technologies and the ongoing demand for communication and collaboration is stressing to the limits the current internet technologies and infrastructure.
A set of QoB predications have been defined in order to unify approaches towards the integration of FI technologies (FInES, 2012): x Inventive Enterprise x Humanistic Enterprise x Cognitive Enterprise x Community-oriented Enterprise x Agile Enterprise x Glocal Enterprise x Sensing Enterprise A few technological paradigms that can sustain the future researches on FInES are presented below: x x x x x x x
In this context the development of new Internet related technologies oriented towards providing positive benefits for individuals, society, economy, culture and environment has been included in a broad concept of Future Internet Systems. A updated set of business values is emerging in relation to the transformation of Internet into a universal business environment (FInES, 2009): x Revenue and profit x Reputation and level of trust
Applications with proactive behavior IaaS or PaaS (Infrastructure/Platform as a Service) Interoperability Service Utility (ISU) Knowledge Representation and Semantic Modeling Federated, Open and Trusted Platforms (FOT) Software as a Service (SaaS) Automated Service Discovery and Configuration
This will include the integration and federation of heterogeneous service-based systems (SBS). A paradigm shift regarding the traditional 3 layer reference architecture:
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Functional, Logical and Technical will allow for the integration of new trends such as: pattern based approach. (Stricker et all, 2010) An important aspect of FInES is the integration of the new approaches to the Future Internet: Internet of Service, Internet of Things, 3D and Media Internet, Internet of Knowledge, Internet of People. Two main benefits have been emphasized within the Internet of Things research area, with regard to enterprise systems ³WKLQJV RQ WKH PRYH´ XELTXLWRXV intelligent devices". (Santucci, 2009) 7KH ³WKLQJV RQ WKH PRYH´ FRQFHSW ZLOO DOORZ EHWWHU identification and transport efficiency of food products along the Supply Chain from the producer to the distributer, the shop floor, cashier and check-out leading to the intelligent logistic management. This will also prevent counterfeiting and assure consumers of controlled origin of the food product. The "ubiquitous intelligent devices" concept will allow the possibility of information exchange between any intelligent object. Another capability is the implementation of reactive behaviours according to a predetermined set of actions. With the advent of globalization, enterprises have been pushed to operate at an international level in terms of sourcing, production and markets, as well as finance and technologies. This process has promoted a number of improvements for the economy of the planet, allowing for new business scenarios, with new players entering the scene. But at the same time, especially where the enterprises do not show transparency and social quality (see above), globalization is producing hardship and difficulties for part of the populations in both advanced and developing countries. Globalization is with us, and it will remain. Thus rather than fighting against it, a number of corrections to limit its downsides must be introduced. One of the most significant is the possibility of conjugating two apparently contradicting dimensions, i.e., local and global, merging them into a virtuous blend referred WR DV ³glocal´ $ Glocal Enterprise will be able to understand and think at a global level, while being aware of the local levels in which it operates, acting in harmony with its geo-social surroundings. To achieve this, it is necessary to show a specific kind of flexibility, necessary for instance to adapt products and production processes to the culture and needs of a given geographic area. (FInES, 2009) Integrating devices and everyday objects to a smart environment is the first step towards the Internet of Things. Technical, extensible standards and protocols suited for ³,QWHUQHW RI 7KLQJV´ DUH UHTXLUHG in order to integrate all types of devices, including robots. Several standards have been proposed in order to identify and track objects based on RFID tags. The most successful have been of them are the MIT AutoID Lab standards that include: EPC (Electronic Product Code) ± analogous to IP address x ONS(Object Name Service) ± analogous with DNS x PML(Physical Markup Language) ± analogous with XML and the Uid Center: Ubiquitous Identification Code. x
Fig. 2. Representation of FInER object building blocks. A framework for modeling the tag data, assigned to a real object has been provided in fig 2. The framework adds to the a data describing the object: data that allows for the virtualization of the object information UHJDUGLQJ WKH REMHFW¶V RZQ EHKDYLRU RU LW¶s functionality LQIRUPDWLRQ UHJDUGLQJ RWKHU REMHFW¶V EHKDYLRUV WRZDUGV WKLV object.
Fig3. Dimensions of Enterprise Systems $V WKH REMHFW¶V SURSHUWLHV DQG GHVFULSWLRQ KDV DOUHDG\ EHHQ implemented in RFID tags, the focus of this research group is to e[WHQG WKH REMHFW¶V GHVFULSWLRQ E\ GHILQLQJ DQG implementing object behaviors. All of these data and LQIRUPDWLRQ FDQ EH VWRUHG LQ WKH WDJ¶V PHPRU\ $ SUREOHP would be to find a wide used tool to describe this data and information. As discussed, a suitable and largely available way for data transfer is the Extended Markup Language. As PML (based on XML) has been widely adopted by the users of the EPC standard, we chose PML for the object proprieties description within the framework. PML also allows for the description of object shape and color but we consider that a PRUH DSSURSULDWH ZD\ WR GHVFULEH WKH REMHFW¶V YLVXDO properties would be to use standard 3D web oriented language: X3D. X3D language is considered to be the next step after VRML (Virtual Reality Markup Language) aiming at communicating 3D on the web, between applications and across distributed networks and web services. In order to describe the behavior of the object and the behavior towards the object, XTND - XML Transition Network Definition Language has been chosen. We can model behaviors using
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transition networks. These kinds of networks are used to describe a set of states and the transitions that are possible between them.
operational level which is defined as the level where different stakeholders (individuals, departments), with diverse skills, store and share knowledge.
7KH LQWHJUDWLRQ RI REMHFWV ZLWKLQ WKH ³,QWHUQHW RI 7KLQJV´ offers great perspectives, but it is not easy to implement at this point, taking into consideration the following aspects:
To cope with such cases the construction of a knowledge module is proposed. In this case "knowledge module" will refer to a sequence of primitive activities with assigned resources that are necessary to fulfill a given objective. It will be also considered that by an activity is denoted the implementation of knowledge at a lower level of granularity, by a task, the implementation of a primitive action.
x x x x x x
different or no interoperability standards different service descriptions and capability declaration different radio interfaces and media access different resources management different encryption different publication and subscription of devices
4. INTEGRATION OF KNOWLEDGE EXTRACTION WITH INTERNET OF THINGS ORIENTED SYSTEMS Recent studies regarding the balance between organizational structure and enterprise efficiency for different kind of enterprises and environments has provided the following conclusions (Davis et al, 2007): - There is an inverted U-shaped relationship between structure and performance, that is asymmetric: too little structure leads to a catastrophic performance decline while too much structure leads to only a gradual decay - The key dimension of the market dynamism is unpredictability that underlines the tension between too much and too little structure. The range of optimal structures varies inversely with unpredictability: in unpredictable environments, there is only a very narrow range of optimal structures with catastrophic drops on either side that are likely to be difficult to manage. - Other dimensions of market dynamism (i.e. velocity, complexity, and ambiguity) have their own unique effects on performance Extracting knowledge in order to allow for market triggered business process re-engineering can provide the key to balance structure and performance within the enterprise environment. Knowledge management is recognizing and taking into account two main kind of knowledge co-existing in an organization (Dalkir, 2005): explicit knowledge, which is the only form of knowledge possessed by non-human agents, and which has been codified and structured and tacit knowledge, which is the intangible knowledge that only human agents can have. Organizational knowledge management approach focuses especially on procedures to transform tacit knowledge into explicit. Consider the following scenario: a new problem is raised, eventually by the strategic level of a manufacturing enterprise after analyzing supply chain processes. At this level, problem specification is made taking into account very general knowledge, as enterprise purpose, technologies and theories that are available a.s.o. Problem specification is made in terms of initial conditions and final results. The SUREOHP¶V VROXWLRQ ZLOO EH KDQGOHG DQG LPSOHPHQWHG DW WKH
A few characteristics are important to be discussed: - the definition of a "knowledge module" is iterative (it can include other knowledge modules); - it is always important for solving a problem to define primarily a list (part of a common dictionary) of primitive actions ± implying, at the organizational level, an important focus on generating, articulating, categorizing and systematically leveraging organizational knowledge assets. Internet of Future oriented Enterprise Systems will allow for the implementation of such new concepts and technologies aiming at improving enterprise efficiency. The research in the area of intelligent objects capable of unrestricted communication and interoperability with other similar objects as well as with any service within the entire enterprise system is focused on supporting that goal. In this context the development of methods used to transform common objects involved in the enterprise business processes into intelligent objects is regarded as a highly benefic. The first step for such an approach is to be able to identify the object and to distinguish it from the environment. The recent progress of the RFID technology has boosted the capability of object identification and allowed for the development of new identification technologies as EPC code and ucode as discussed in the previous section. These technologies require that the information suitable for the identification of an object should be accessed from a remote database. With the development of new and more powerful data storage devices we can focus on a different approach: storing the data on the tag attached to the object and accessing that data when ether necessary. A data representation schema has been proposed in figure 2. Business Process Modeling Notation standard offers a comprehensive way for description and representation. Interoperability frameworks should be taken into consideration and the following tiers have to be included: organizational interoperability that focuses on the interoperability of business processes and information architectures beyond the borders of different administrations and semantic interoperability that aims to establish a common meaning of the exchanged data, process models or used procedures. Ontology basically provides the semantics and has a twofold role in this context: can describe both the semantics of the modelling language constructs as well as the semantics of model instances. In the context of business processes this means that ontologies can be used for the explication of both
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the semantics of activities in general as well as for describing the semantics of a specific activity in that, for instance, the used resources or the application context are described by a domain ontology. The second step is to integrate such objects with the enterprise systems the information attached to the tag should be not exclusively divided in the following categories: object proprieties, object functionality or in a broader meaning object behavior, description of the planned processes (at task level) which involve the object, and the description of the DFWXDOSURFHVVHVDV³H[SHULHQFHG´E\WKHREMHFW The defined process attached to the object is associated with the process models as described in the Process Modeling level of the Enterprise Architecture. This approach will allow for the creation of a map of the processes that the object will be subjected to and for a better integration with the services included in the Enterprise Systems. In such a case any enterprise system or production cell will be able to read the process map and proceed with the object accordingly. An example can be represented by a product that is going to be shipped. The shipping service will be able to read the process map, identify the shipping sub-process and act according to the predefined tasks. By extracting process information from the object, service choreography can be achieved within the enterprise system service layer.
Fig 4. Intelligent objects represented as FInER within the FInES Knowledge Management System As the predefined processes may differ to the actual processes completed by the object, a record to register the changes can be defined. An example in this area can be identified at the level of an adaptive supply chain. Such a record can provide valuable feedback related to the insight of the sub-processes and tasks. This information can be further processed in order to produce valuable knowledge within the Enterprise Management System.
Knowledge management in particular, owing to its evolution that parallels that of manufacturing paradigms, is expected to issue new methods allowing humans to both benefit from and increase the value of ± technological advances. A hybrid knowledge structure can be foreseen, where the interaction between human and non-human knowledge stakeholders will became transparent and will allow creation and use of metaknowledge. REFERENCES Dalkir, K. (2005). Knowledge Management in Theory and Practice. Elsevier, ISBN-13: 978-0- 7506-7864-3, ISBN10: 0-7506-7864-X Davis,J. P.; Eisenhardt K & Bingham B.C. (2007) Complexity Theory, Market Dynamism and the Strategy of Simple Rules, Proceedings of DRUID Summer Conference 2007 on Appropriability, Proximity Routines and Innovation, Copenhagen, CBS, Denmark, June 18 20, 2007 Dumitrache, I., Stanescu, A.M., Caramihai, S.I., Voinescu, M., Moisescu, M.A., Sacala, I.S., (2009) Knowledge Management Based Supply Chain In Learning Organization, In: 13th IFAC Symposium on Information Control Problems in Manufacturing (Incom 2009), 3-5 Jun 2009, Moscow, Russian federation Goncalves R., Sarraipa J. and SteigeræGarcao A., Semantic harmonization for seamless networked supply chain planning in the future of internet, , IFIP International Conference Network of the Future, IFIP AICT 326, pp. 78ææ89. IFIP International Federation for Information Processing, 2010, Australia. (IFIP) FInES Research Roadmap Task Force, (2009). Future Internet Enterprise Systems (FInES) Cluster, Research Roadmap, Version 1.3, 9 november 2009, http://cordis.europa.eu/fp7/ict/enet/ FInES Research Roadmap Task Force, (2012). Future Internet Enterprise Systems (FInES) Cluster, Research Roadmap, Version 2.0, march 2012, http://cordis.europa.eu/fp7/ict/enet/ Santucci G., (2009). From Internet of Data to Internet of Things, Available from: http://ec.europa.eu/ information_society/ policy/rfid/ Stanescu A.M., Dumitrache I., Pouly M., Caramihai S. I., Moisescu, M. (2007) Towards a General Systems Theory approach to design the future of Concurrent Engineering Science, In Geilson Loureiro and Richard Curran (ed.) Complex Systems Concurrent Engineering Collaboration Technology Innovation and Sustainability, pp 3-10, Springer Verlag Stricker V., Lauenroth K., Corte P., Gittler F., De Panfilis S., Pohl K., (2010) Creating a Reference Architecture for Service-Based Systems- A Pattern-Based Approach, In Georgios Tselentis et all (eds.) Towards the Future Internet, Emerging Trends from European Research. 161-173, IOS Press
5. CONCLUSIONS The concepts, proposed within the Internet of Things, paradigm are becoming a reality due to the research efforts leading towards the development of new devices and services.
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