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INTEROPERABILITY PROBLEMS IN SUPPLY CHAINS CONTEXT
INCOM'2006: 12th IFAC/IFIP/IFORS/IEEE/IMS Symposium Information Control Problems in Manufacturing May 17-19 2006, Saint-Etienne, France
INTEROPERABILITY PROBLEMS IN SUPPLY CHAINS CONTEXT 1
1
1
Séverine BLANC , Yves DUCQ , Bruno VALLESPIR 1
Laboratoire d'Automatique, Productique et Signal, LAPS/GRAI, UMR 5131 CNRS, Université Bordeaux 1, ENSEIRB, 351 cours de la Libération, 33405 Talence Cedex, France. Tel.: +33 5 40 00 24 09; fax: +33 5 40 00 66 44 E-Mail: {first name}.{last name}@laps.u-bordeaux1.fr
Abstract: Today, the enterprises must cooperate to survive in a context increasingly competing. This cooperation is carried out using organization in network through supply chain. In order to do so, the enterprises must be interoperable. For this, the system must eradicate the heterogeneity. In a first part, the paper exposes the problems of heterogeneity. In a second part is presented the synchronisation and standardisation of practices of business processes in order to solve a part of the problem of organisational heterogeneity. Then, the last part presents a method to solve heterogeneity problems by using an evolution management method: GEM. In parallel, two performance measurement systems are used. Copyright © 2006 IFAC Keywords: Communication environment, Enterprise modelling, Semantic problems, System management.
The interest of using EM techniques is to represent completely the operating of the enterprise from several points of view: functional, decisional, information system and business process. Based on the EM representation, it is possible to extract the interoperability nodes. This allows to improve the achievement of interoperability. The identification of heterogeneity points constitutes the "AS IS" i.e. the existing system. The target allows to determine the "SHOULD BE". Between both, the evolution of the system is elaborated by using an evolution model. The management of evolution can be represented by the Fig. 1, and is composed of three different parts: the semantic heterogeneity, which is the representation of the non-interoperability. It can be eradicated to allow the semantic interoperability, the performance indicators, which are the guardians of evolution follow up. They allow to validate each step described in the project of evolution, the modifications of organisations and ways of work, which are the result of enterprise modelling. It allows the organisational interoperability.
1. INTRODUCTION Today, the enterprises must cooperate to survive in a context increasingly competing. This cooperation is carried out using organization in network through supply chain. In order to do so, the enterprises must be interoperable. The general problematic is the interoperability in the context of supply chain. In order to solve the problem it is necessary to define precisely the interoperability. The interoperability is defined as “the ability of two or more systems or components to exchange information and to use the information that has been exchanged” (IEEE, 1990) (ATHENA, 2003). The noninteroperability will be named into this paper "heterogeneity". In fact, the interoperability is the final goal that the system must reach. For this, the system must eradicate the heterogeneity. This notion of heterogeneity can be considered and then solved thanks to three different domains: Ontology for good comprehension during the exchange of information between enterprises, Enterprise Modelling (EM) for the organisation of each enterprise, synchronisation and harmonisation of practices, Architecture and platform for problems of data compatibility, of presence of software or not and which type.
The input of the management of evolution is enterprises which want to work together although they are heterogeneous. At this level, these enterprises are not interoperable. The semantic heterogeneity allows the enterprises to exchange in using the same language and the same means.
653
Management of evolution
Semantic Heterogeneity
Interoperability Specialists
Performance Indicators
Enterprises Members
Enterprises after the evolution (interoperable)
Modifications of organisations and way of work
2.1. Representation of complex
Enterprises Managers
Fig. 1. Developed approach for interoperability achievement
SC1
SC2
E1
E2 Product 2
Product 2
Product 3
Product 3
Product 2
Product 1
The performance indicators allow to measure the performance of the supply chain as a whole or just by parts. The modifications of organisations and ways of work allow to get organisations that allow the interoperability. The management of evolution allow to make the enterprises evolve regards to the modifications imposed by the three previous domains.
E4
E3 Product 4
Enterprises before the evolution (noninteroperable)
the heterogeneity. Firstly, the concepts can be expressed within the meaning of description logics. The main advantage of this representation is that it is easily computerizable. Secondly, they can be expressed under the form of lexical concepts graph. Thirdly, we can express them under the form of concepts expressed in algebraic topology which can be represented by the complex for collaboration between enterprises or by the graph for collaboration between people or services.
Result of Benchmarking
Product 3
Directives of enterprises managers
Product 4 Product 3
Fig. 2 Multiple supply chain example The following example (Fig. 2) allows to have a better view of the applications with the representation of complex. This example shows two different supply chains: SC1 and SC2, with four different enterprises: E1, E2, E3 and E4, and four different products: P1, P2, P3 and P4. The SC1 create the products P1, P2 and P3, using the enterprises E1, E2 and E3. The enterprise E3 works for SC1 and SC2. The SC2 create the product P4 with the enterprise E3 and E4. With the complex representation, it is possible to translate this situation in the Fig. 3.
So, in a first time, a detailed definition of heterogeneity is presented. Then, a progressive method which manages the enterprises' evolution is presented. Finally, two performance measurement systems (for the supply chain and for each individual enterprise) is described. 2. HETEROGENEITY
P1
E1
E1
SC1 SC2
As partially presented in (Sansonnet, 2004), three different cases of heterogeneity can be differentiated: semantic heterogeneity (as a part of the ontology research domain, semantics studies the meaning of a speech, i.e. the meaning of words and sentences), material heterogeneity (information technology related) and also organisational heterogeneity (enterprise modelling related).
E3 E2
(a)
E3
E4 P2
(b)
E1
E1 P2
(d)
E3
P3
P4 E3
E2
P3
(c)
E4
(e)
E4 E2
(f)
E3
Fig. 3 Representation with the "simplicial complex"
Semantic heterogeneity, is due to the fact that the applications and organisations have often been defined and built by different people, in different places at different times, with different aims, with different vocabularies...
The main advantage of this representation is to allow a synthetic view of the studied supply chain part. Indeed, in order to identify quickly the relations between several entities, it is possible to represent different points of view: network ((a), (b)), enterprises (f), products ((c), (d), (e)), etc. contributing on a same product. This representation allows to put the potential heterogeneity problems in obvious: by product, by enterprises or by supply chain. For example, here, the product P3 is represented by a volume between the points: E1, E2, E3 and E4. It is possible to represent more complex examples with this representation.
Organisational heterogeneity exists because different enterprises are growing and prospering one isolated to each others. Each enterprise has developed its own organisation independently to the others. Consequently, the same task will maybe not be executed by the same way in two different enterprises and then the result of one will probably not be compatible by the following. Material heterogeneity consists, for the distributed systems, in using few-interoperable machines. Today, to reduce the question of information transport, in an independent way of the material conditions i.e. machines and/or subjacent operating systems, it is possible to use software applications.
2.2. Representation of graphs An other representation, using graphs, can be applied to our domain. A concrete example is given in this paragraph. The Fig. 4 represents the exchange of decision frames between different peoples of an enterprise. A line between two nodes represents a decision frame, each point represents a person.
The semantic heterogeneity can be confronted by the resolution of the individual problems. In this perspective, three strategies can be defined to confront 654
Jim
Andrew
Brian
Jennifer
Katherine Nicholas
Jonah
Susan
Alex
Tony
Lynn
John Georges Dennis Rich
Fig. 4 Simplicial graph representation applied to the GRAI grid example The simplicial graph representation allows an easily view of communication between people. In representing only the transmission of decisional frame, the interoperability nodes appear clearly. Indeed, Jennifer does not need to be interoperable with Andrew, she does just need to be interoperable with Jim and Alex.
AS IS E1
STEP 1 E1
STEP 2 E1
TARGET 0 E1 TARGET 1 E1
TARGET 2 E1
Evolution Model toward Interopera bility
After putting the interoperability nodes in a prominent place, heterogeneity problems must be solved. Following section proposed a method to reach this objective.
Performance Measurement System for Evolution Management
Effective Collaboration E1 - E2
TARGET 2 E2
TARGET 1 E2
AS IS E2
3. HOW TO SOLVE THE HETEROGENEITY PROBLEM TO REACH INTEROPERABILITY?
STEP 1 E2
STEP 2 E2
Refe renc e Mo Supp del of ly Ch ain
nce orma Perf rement su a e M m of Syste Chain ly Supp cution Exe
TARGET 0 E2
Fig. 5 Method to solve the heterogeneity problem The PMSE is readapted at the end of each step and is transformed in PMSSC when the collaboration becomes effective. The final goal is an effective collaboration between the two (or more) enterprises concerned E1 and E2. The main objectives for the future Supply Chain (SC) are described from the beginning of the evolution project. They result from a Supply Chain Reference Model and are validated by the PMSSC.
3.1. A Progressive Method This method (Fig. 5) is based on the Grai Evolution Method (GEM) (Malhene, 2000) to allow isolated enterprises to evolve towards the interoperability and the collaboration through the supply chain. The principle of this method is to build system evolution like continuous processes. In practice, the evolution process is made of a sequence of steps representing the evolution of the system status. Here, we consider two different enterprises, the enterprise 1 (E1) and enterprise 2 (E2). Before the beginning of the evolution they don't collaborate because they cannot.
It is possible to focus on the management evolution process (fig. 6Erreur ! Source du renvoi introuvable.). Here, there is not only the AS IS, the STEP and the TARGET, but also a set of complementary steps to define the AS IS, the STEP and the TARGET.
The AS IS represents the model of existing system. The components of the system are here described and formalised: it is possible to better understand how the system is running and also to detect the points to improve. The TARGET corresponds to the strategic objectives of the system. The final TARGET is the "Effective Collaboration" between E1 and E2. The STEP is an intermediate stage between the AS IS and the TARGET. It corresponds to the future system which should be implemented.
GEM allows evolution of the whole enterprise. In this paper, evolution is limited at different parts that improve the interoperability. When the model of existing system (AS IS) is defined, points of interoperability can be identified thanks to semantic heterogeneity representation. The Users Specifications result from the comparison between the current models and the target. This comparison must be made for the functional, physical, decisional and informational models. The Users Specifications described flows, functions and activities, which are modified and added to the system. However, this orientation should not eclipse the essential concept of integration. This is the objective of software and material physical architectures and enterprises' organisations. .
To validate each step, a performance indicators system is established. In fact, in this method, there are two different measurement systems: a Performance Measurement System to manage the Evolution (PMSE), a Performance Measurement System to manage the Supply Chain (PMSSC).
655
Performance Measurement System Definition for Evolution Management
Performance Measurement System Definition for Evolution Management
Performance Measurement System Definition for Evolution Management
Target 2
Establishment Establishment
AS IS 1
Establishment
S''
S'
Identification of Interoperability Nodes Elaboration of Users Specifications
Step 1
Realization
Elaboration of Technical Specifications
Target 1
Realization
Elaborations of Technical Specifications
Realization Elaborations of Technical Specifications
Definition of Architectures Definition of Action Plan Coherence Analysis of Objectives for Each Level
Fig. 6: GEM use to solve interoperability problems The three previous representations of the heterogeneity supply the "AS IS" situation of the method that is described in the second part of this paper.
They must indicate the technical solutions up to what point can come to be integrated into the existing system. In a large majority of cases, technical solutions refer to existing tools on the market. These tools have the advantage of being standard and of offering periodic updates. However, the greatest interest comes from the fact that their establishment is more easily controllable in term of time and cost. An intermediate step is characterized by the implementation of a project of change or an action allowing to establish a technical solution. It is possible to identify various types of actions according to their priority of establishment: strong, average and weak priority. This concept of priority is relative because the system evolution, from the AS IS towards the Step, implies the implementation of the whole of the projects defined by the model of this Step. The model of the Step presented through a decisional model behaves like an integrating model in which several projects of low amplitude take place. The definition of the priorities associated with the intermediate states is done through the definition of an Action plan. Once the action plan is realized, it is necessary to valid the coherence of objectives at each level in order to avoid implementing contradictory actions between the local and the global objectives. Performance measurement system must be defined, just before establishment of the action plan, in order to validate it thanks to the indicators of performance.
3.2. Performance Measurement System 3.2.1. Supply Chain Performance Measurement System In the domain of supply chain performance measurement system (PMS), lots of methods exist. We chose to extend the research work of (Chalmeta and Grangel, 2005) in order to adapt it at our problem. This method is composed of three phases that are divided by different activities, as shown in fig. 7. The "phase 1" treats of the SC design including the Performance Measurement System (PMS). The "phase 2" is similar than the phase 1, but at an individual enterprise level. The "phase 3" is the exploitation phase of the SC. To apply this method at our work, we had to adapt it (fig. 7). Indeed, some parts have been suppressed to keep only those in which we are interested. The starting point of this method is defined by the evolution model, which begins by the definition of strategic objectives for the concerned step. Then, it determines actions plans for the SC for the concerned step.
656
Phase 1
Deployment and follow-up of the SC and each individual enterprise indicators system
GRAI Evolution Perf Model
Revisions Define SC stratégic objectives for the step concerned Determine actions plans for the SC for the step concerned Validation for each individual enterprise indicators system
Establish indicators of the SC for the step concerned
Phase 3
ECOGRAI Deploy each individual enterprise strategic indicators in indicators for people and equipment
Validation of the SC indicators system
Deploy each individual enterprise strategic indicators in indicators for areas and processes
Consolidate the SC indicators system
Determine criteria for the goal setting
Define strategic objectives for each individual enterprise Identifie actions plans pour for each individual enterprise
Establish strategic indicators for each individual enterprise
GIM
Phase 2
GRAI Strategy
Fig. 7 Supply Chain Performance Measurement System Finally, it is possible to deduce the global performance measurement system applied at the supply chain level as a whole.
3.2.2. Evolution Performance Measurement System Here, the principle is almost the same as for the "Supply Chain Performance Measurement System" above. The phase 1 is reduced at the three last steps, the phase 2 is unchanged and the phase 3 is limited at the validation, deployment and revision of performance indicators.
The beginning of the second phase is similar to the first one, but applies at the local level. Then, the validation of the performance indicators coherence at a global level compared to a local level is a necessity before the deployment in the phase 3. The third phase is the exploitation phase. More particularly, it aims to validate, to implement, to follow-up and to revise the PMS. It is possible to identify the GRAI modules of the GRAI methodology which composed the method: • GIM (GRAI Integrated Modelling) (Doumeingts et Ducq, 2001) for the design of the targeted system. It can be used at a local level (individual enterprise level). It allows the modelling of existing system and, from its diagnosis (determination of strong points and points to improve) and from the objectives of the project, to design the model of the new system. • ECOGRAI (Ducq and Vallespir, 2005) for the definition and the implementation of performance indicators system. This module allows to define and to implement Performance Indicators System in the considered system. The number of Performance Indicators is limited, relevancy distributed in the structure with a coherent way at each decisional level, from the strategic to the operational level. • GRAI Strategy (Kleinhans, 1999) for the Industrial strategic planning. It is a module supporting the elaboration, the improvement and the implementation of a business plan.
For each step, the strategic objectives are extracted and analysed to deduce the most appropriate global performance indicators system to validate the step concerned. From these global indicators, it is possible to determine the strategic objectives for each individual enterprise, the actions plans and the strategic indicators. After a validation of the coherence, the indicator system is deployed and followed. This indicators system is reviewed for each change of step. 4. CONCLUSION In this paper, the problems of interoperability and heterogeneity have been presented and some solutions have been detailed. These solutions are mainly based on enterprises modelling and semantic heterogeneity techniques. By using Performance Measurement System appropriate for the evolution management and exploitation of the systems, the enterprises of supply chains can evolve towards interoperability. In the future, the research works will be about the characterization of the interoperability and the definition of the interoperability of an enterprise compared to another i.e. what enables us to say that an enterprise is interoperable with another or not?
657
Kleinhans S., 1999, Intégration de la modélisation d'entreprise dans une démarche de stratégie industrielle, Thèse de l'Université Bordeaux 1, October 29th, 1999. Malhene N., 2000, Gestion du processus d'évolution des systèmes industriels – Conduite et méthode, GEM, thèse de l'Université Bordeaux 1, Janvier 2000. Sansonnet J-P., 2004, Approches de l'hétérogénéité sémantique entre agents informationnels, http://www.limsi.fr/Individu/jps/research/weakalie ns/weakaliens.htm, 2004. Valencia E., 2000, Hétérogénéité Sémantique entre Agents modélisés en Logique de Descriptions, Thèse de doctorat de l'Université de Paris XI, December 8, 2000. Valencia E. and J.-P. Sansonnet, Simplicial Representation for Description Logics Databases, International Conference on Description Logic DL 2000, Aachen Germany, august 2000
REFERENCES ATHENA, 2003, Annex I – “Description of work”, sixth framework program, European Integrated Project ATHENA, 11 november 2003. Chalmeta R. and R. Grangel, 2005, Performance measurement systems for virtual enterprise integration, Computer Integrated Manufacturing, Vol. 18, N°1, January – February 2005, 73-84. Doumeingts G. and Y. Ducq, 2001, Enterprise modelling techniques to improve efficiency of enterprises, Production Planning & Control, 2001, Vol. 12, N°2, 146 – 163. Ducq Y. and B. Vallespir, 2005, Definition and aggregation of performance measurement system in three aeronautical workshops using the ECOGRAI method, Production Planning & Control, 2005, Vol. 16, N°2, 163 – 177. IEEE, (1990), "IEEE standard computer dictionary: a compilation of IEEE standard computer glossaries."
658
INTEROPERABILITY PROBLEMS IN SUPPLY CHAINS CONTEXT 1
1
1
Séverine BLANC , Yves DUCQ , Bruno VALLESPIR 1
Laboratoire d'Automatique, Productique et Signal, LAPS/GRAI, UMR 5131 CNRS, Université Bordeaux 1, ENSEIRB, 351 cours de la Libération, 33405 Talence Cedex, France. Tel.: +33 5 40 00 24 09; fax: +33 5 40 00 66 44 E-Mail: {first name}.{last name}@laps.u-bordeaux1.fr
Abstract: Today, the enterprises must cooperate to survive in a context increasingly competing. This cooperation is carried out using organization in network through supply chain. In order to do so, the enterprises must be interoperable. For this, the system must eradicate the heterogeneity. In a first part, the paper exposes the problems of heterogeneity. In a second part is presented the synchronisation and standardisation of practices of business processes in order to solve a part of the problem of organisational heterogeneity. Then, the last part presents a method to solve heterogeneity problems by using an evolution management method: GEM. In parallel, two performance measurement systems are used. Copyright © 2006 IFAC Keywords: Communication environment, Enterprise modelling, Semantic problems, System management.
The interest of using EM techniques is to represent completely the operating of the enterprise from several points of view: functional, decisional, information system and business process. Based on the EM representation, it is possible to extract the interoperability nodes. This allows to improve the achievement of interoperability. The identification of heterogeneity points constitutes the "AS IS" i.e. the existing system. The target allows to determine the "SHOULD BE". Between both, the evolution of the system is elaborated by using an evolution model. The management of evolution can be represented by the Fig. 1, and is composed of three different parts: the semantic heterogeneity, which is the representation of the non-interoperability. It can be eradicated to allow the semantic interoperability, the performance indicators, which are the guardians of evolution follow up. They allow to validate each step described in the project of evolution, the modifications of organisations and ways of work, which are the result of enterprise modelling. It allows the organisational interoperability.
1. INTRODUCTION Today, the enterprises must cooperate to survive in a context increasingly competing. This cooperation is carried out using organization in network through supply chain. In order to do so, the enterprises must be interoperable. The general problematic is the interoperability in the context of supply chain. In order to solve the problem it is necessary to define precisely the interoperability. The interoperability is defined as “the ability of two or more systems or components to exchange information and to use the information that has been exchanged” (IEEE, 1990) (ATHENA, 2003). The noninteroperability will be named into this paper "heterogeneity". In fact, the interoperability is the final goal that the system must reach. For this, the system must eradicate the heterogeneity. This notion of heterogeneity can be considered and then solved thanks to three different domains: Ontology for good comprehension during the exchange of information between enterprises, Enterprise Modelling (EM) for the organisation of each enterprise, synchronisation and harmonisation of practices, Architecture and platform for problems of data compatibility, of presence of software or not and which type.
The input of the management of evolution is enterprises which want to work together although they are heterogeneous. At this level, these enterprises are not interoperable. The semantic heterogeneity allows the enterprises to exchange in using the same language and the same means.
653
Management of evolution
Semantic Heterogeneity
Interoperability Specialists
Performance Indicators
Enterprises Members
Enterprises after the evolution (interoperable)
Modifications of organisations and way of work
2.1. Representation of complex
Enterprises Managers
Fig. 1. Developed approach for interoperability achievement
SC1
SC2
E1
E2 Product 2
Product 2
Product 3
Product 3
Product 2
Product 1
The performance indicators allow to measure the performance of the supply chain as a whole or just by parts. The modifications of organisations and ways of work allow to get organisations that allow the interoperability. The management of evolution allow to make the enterprises evolve regards to the modifications imposed by the three previous domains.
E4
E3 Product 4
Enterprises before the evolution (noninteroperable)
the heterogeneity. Firstly, the concepts can be expressed within the meaning of description logics. The main advantage of this representation is that it is easily computerizable. Secondly, they can be expressed under the form of lexical concepts graph. Thirdly, we can express them under the form of concepts expressed in algebraic topology which can be represented by the complex for collaboration between enterprises or by the graph for collaboration between people or services.
Result of Benchmarking
Product 3
Directives of enterprises managers
Product 4 Product 3
Fig. 2 Multiple supply chain example The following example (Fig. 2) allows to have a better view of the applications with the representation of complex. This example shows two different supply chains: SC1 and SC2, with four different enterprises: E1, E2, E3 and E4, and four different products: P1, P2, P3 and P4. The SC1 create the products P1, P2 and P3, using the enterprises E1, E2 and E3. The enterprise E3 works for SC1 and SC2. The SC2 create the product P4 with the enterprise E3 and E4. With the complex representation, it is possible to translate this situation in the Fig. 3.
So, in a first time, a detailed definition of heterogeneity is presented. Then, a progressive method which manages the enterprises' evolution is presented. Finally, two performance measurement systems (for the supply chain and for each individual enterprise) is described. 2. HETEROGENEITY
P1
E1
E1
SC1 SC2
As partially presented in (Sansonnet, 2004), three different cases of heterogeneity can be differentiated: semantic heterogeneity (as a part of the ontology research domain, semantics studies the meaning of a speech, i.e. the meaning of words and sentences), material heterogeneity (information technology related) and also organisational heterogeneity (enterprise modelling related).
E3 E2
(a)
E3
E4 P2
(b)
E1
E1 P2
(d)
E3
P3
P4 E3
E2
P3
(c)
E4
(e)
E4 E2
(f)
E3
Fig. 3 Representation with the "simplicial complex"
Semantic heterogeneity, is due to the fact that the applications and organisations have often been defined and built by different people, in different places at different times, with different aims, with different vocabularies...
The main advantage of this representation is to allow a synthetic view of the studied supply chain part. Indeed, in order to identify quickly the relations between several entities, it is possible to represent different points of view: network ((a), (b)), enterprises (f), products ((c), (d), (e)), etc. contributing on a same product. This representation allows to put the potential heterogeneity problems in obvious: by product, by enterprises or by supply chain. For example, here, the product P3 is represented by a volume between the points: E1, E2, E3 and E4. It is possible to represent more complex examples with this representation.
Organisational heterogeneity exists because different enterprises are growing and prospering one isolated to each others. Each enterprise has developed its own organisation independently to the others. Consequently, the same task will maybe not be executed by the same way in two different enterprises and then the result of one will probably not be compatible by the following. Material heterogeneity consists, for the distributed systems, in using few-interoperable machines. Today, to reduce the question of information transport, in an independent way of the material conditions i.e. machines and/or subjacent operating systems, it is possible to use software applications.
2.2. Representation of graphs An other representation, using graphs, can be applied to our domain. A concrete example is given in this paragraph. The Fig. 4 represents the exchange of decision frames between different peoples of an enterprise. A line between two nodes represents a decision frame, each point represents a person.
The semantic heterogeneity can be confronted by the resolution of the individual problems. In this perspective, three strategies can be defined to confront 654
Jim
Andrew
Brian
Jennifer
Katherine Nicholas
Jonah
Susan
Alex
Tony
Lynn
John Georges Dennis Rich
Fig. 4 Simplicial graph representation applied to the GRAI grid example The simplicial graph representation allows an easily view of communication between people. In representing only the transmission of decisional frame, the interoperability nodes appear clearly. Indeed, Jennifer does not need to be interoperable with Andrew, she does just need to be interoperable with Jim and Alex.
AS IS E1
STEP 1 E1
STEP 2 E1
TARGET 0 E1 TARGET 1 E1
TARGET 2 E1
Evolution Model toward Interopera bility
After putting the interoperability nodes in a prominent place, heterogeneity problems must be solved. Following section proposed a method to reach this objective.
Performance Measurement System for Evolution Management
Effective Collaboration E1 - E2
TARGET 2 E2
TARGET 1 E2
AS IS E2
3. HOW TO SOLVE THE HETEROGENEITY PROBLEM TO REACH INTEROPERABILITY?
STEP 1 E2
STEP 2 E2
Refe renc e Mo Supp del of ly Ch ain
nce orma Perf rement su a e M m of Syste Chain ly Supp cution Exe
TARGET 0 E2
Fig. 5 Method to solve the heterogeneity problem The PMSE is readapted at the end of each step and is transformed in PMSSC when the collaboration becomes effective. The final goal is an effective collaboration between the two (or more) enterprises concerned E1 and E2. The main objectives for the future Supply Chain (SC) are described from the beginning of the evolution project. They result from a Supply Chain Reference Model and are validated by the PMSSC.
3.1. A Progressive Method This method (Fig. 5) is based on the Grai Evolution Method (GEM) (Malhene, 2000) to allow isolated enterprises to evolve towards the interoperability and the collaboration through the supply chain. The principle of this method is to build system evolution like continuous processes. In practice, the evolution process is made of a sequence of steps representing the evolution of the system status. Here, we consider two different enterprises, the enterprise 1 (E1) and enterprise 2 (E2). Before the beginning of the evolution they don't collaborate because they cannot.
It is possible to focus on the management evolution process (fig. 6Erreur ! Source du renvoi introuvable.). Here, there is not only the AS IS, the STEP and the TARGET, but also a set of complementary steps to define the AS IS, the STEP and the TARGET.
The AS IS represents the model of existing system. The components of the system are here described and formalised: it is possible to better understand how the system is running and also to detect the points to improve. The TARGET corresponds to the strategic objectives of the system. The final TARGET is the "Effective Collaboration" between E1 and E2. The STEP is an intermediate stage between the AS IS and the TARGET. It corresponds to the future system which should be implemented.
GEM allows evolution of the whole enterprise. In this paper, evolution is limited at different parts that improve the interoperability. When the model of existing system (AS IS) is defined, points of interoperability can be identified thanks to semantic heterogeneity representation. The Users Specifications result from the comparison between the current models and the target. This comparison must be made for the functional, physical, decisional and informational models. The Users Specifications described flows, functions and activities, which are modified and added to the system. However, this orientation should not eclipse the essential concept of integration. This is the objective of software and material physical architectures and enterprises' organisations. .
To validate each step, a performance indicators system is established. In fact, in this method, there are two different measurement systems: a Performance Measurement System to manage the Evolution (PMSE), a Performance Measurement System to manage the Supply Chain (PMSSC).
655
Performance Measurement System Definition for Evolution Management
Performance Measurement System Definition for Evolution Management
Performance Measurement System Definition for Evolution Management
Target 2
Establishment Establishment
AS IS 1
Establishment
S''
S'
Identification of Interoperability Nodes Elaboration of Users Specifications
Step 1
Realization
Elaboration of Technical Specifications
Target 1
Realization
Elaborations of Technical Specifications
Realization Elaborations of Technical Specifications
Definition of Architectures Definition of Action Plan Coherence Analysis of Objectives for Each Level
Fig. 6: GEM use to solve interoperability problems The three previous representations of the heterogeneity supply the "AS IS" situation of the method that is described in the second part of this paper.
They must indicate the technical solutions up to what point can come to be integrated into the existing system. In a large majority of cases, technical solutions refer to existing tools on the market. These tools have the advantage of being standard and of offering periodic updates. However, the greatest interest comes from the fact that their establishment is more easily controllable in term of time and cost. An intermediate step is characterized by the implementation of a project of change or an action allowing to establish a technical solution. It is possible to identify various types of actions according to their priority of establishment: strong, average and weak priority. This concept of priority is relative because the system evolution, from the AS IS towards the Step, implies the implementation of the whole of the projects defined by the model of this Step. The model of the Step presented through a decisional model behaves like an integrating model in which several projects of low amplitude take place. The definition of the priorities associated with the intermediate states is done through the definition of an Action plan. Once the action plan is realized, it is necessary to valid the coherence of objectives at each level in order to avoid implementing contradictory actions between the local and the global objectives. Performance measurement system must be defined, just before establishment of the action plan, in order to validate it thanks to the indicators of performance.
3.2. Performance Measurement System 3.2.1. Supply Chain Performance Measurement System In the domain of supply chain performance measurement system (PMS), lots of methods exist. We chose to extend the research work of (Chalmeta and Grangel, 2005) in order to adapt it at our problem. This method is composed of three phases that are divided by different activities, as shown in fig. 7. The "phase 1" treats of the SC design including the Performance Measurement System (PMS). The "phase 2" is similar than the phase 1, but at an individual enterprise level. The "phase 3" is the exploitation phase of the SC. To apply this method at our work, we had to adapt it (fig. 7). Indeed, some parts have been suppressed to keep only those in which we are interested. The starting point of this method is defined by the evolution model, which begins by the definition of strategic objectives for the concerned step. Then, it determines actions plans for the SC for the concerned step.
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Phase 1
Deployment and follow-up of the SC and each individual enterprise indicators system
GRAI Evolution Perf Model
Revisions Define SC stratégic objectives for the step concerned Determine actions plans for the SC for the step concerned Validation for each individual enterprise indicators system
Establish indicators of the SC for the step concerned
Phase 3
ECOGRAI Deploy each individual enterprise strategic indicators in indicators for people and equipment
Validation of the SC indicators system
Deploy each individual enterprise strategic indicators in indicators for areas and processes
Consolidate the SC indicators system
Determine criteria for the goal setting
Define strategic objectives for each individual enterprise Identifie actions plans pour for each individual enterprise
Establish strategic indicators for each individual enterprise
GIM
Phase 2
GRAI Strategy
Fig. 7 Supply Chain Performance Measurement System Finally, it is possible to deduce the global performance measurement system applied at the supply chain level as a whole.
3.2.2. Evolution Performance Measurement System Here, the principle is almost the same as for the "Supply Chain Performance Measurement System" above. The phase 1 is reduced at the three last steps, the phase 2 is unchanged and the phase 3 is limited at the validation, deployment and revision of performance indicators.
The beginning of the second phase is similar to the first one, but applies at the local level. Then, the validation of the performance indicators coherence at a global level compared to a local level is a necessity before the deployment in the phase 3. The third phase is the exploitation phase. More particularly, it aims to validate, to implement, to follow-up and to revise the PMS. It is possible to identify the GRAI modules of the GRAI methodology which composed the method: • GIM (GRAI Integrated Modelling) (Doumeingts et Ducq, 2001) for the design of the targeted system. It can be used at a local level (individual enterprise level). It allows the modelling of existing system and, from its diagnosis (determination of strong points and points to improve) and from the objectives of the project, to design the model of the new system. • ECOGRAI (Ducq and Vallespir, 2005) for the definition and the implementation of performance indicators system. This module allows to define and to implement Performance Indicators System in the considered system. The number of Performance Indicators is limited, relevancy distributed in the structure with a coherent way at each decisional level, from the strategic to the operational level. • GRAI Strategy (Kleinhans, 1999) for the Industrial strategic planning. It is a module supporting the elaboration, the improvement and the implementation of a business plan.
For each step, the strategic objectives are extracted and analysed to deduce the most appropriate global performance indicators system to validate the step concerned. From these global indicators, it is possible to determine the strategic objectives for each individual enterprise, the actions plans and the strategic indicators. After a validation of the coherence, the indicator system is deployed and followed. This indicators system is reviewed for each change of step. 4. CONCLUSION In this paper, the problems of interoperability and heterogeneity have been presented and some solutions have been detailed. These solutions are mainly based on enterprises modelling and semantic heterogeneity techniques. By using Performance Measurement System appropriate for the evolution management and exploitation of the systems, the enterprises of supply chains can evolve towards interoperability. In the future, the research works will be about the characterization of the interoperability and the definition of the interoperability of an enterprise compared to another i.e. what enables us to say that an enterprise is interoperable with another or not?
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Kleinhans S., 1999, Intégration de la modélisation d'entreprise dans une démarche de stratégie industrielle, Thèse de l'Université Bordeaux 1, October 29th, 1999. Malhene N., 2000, Gestion du processus d'évolution des systèmes industriels – Conduite et méthode, GEM, thèse de l'Université Bordeaux 1, Janvier 2000. Sansonnet J-P., 2004, Approches de l'hétérogénéité sémantique entre agents informationnels, http://www.limsi.fr/Individu/jps/research/weakalie ns/weakaliens.htm, 2004. Valencia E., 2000, Hétérogénéité Sémantique entre Agents modélisés en Logique de Descriptions, Thèse de doctorat de l'Université de Paris XI, December 8, 2000. Valencia E. and J.-P. Sansonnet, Simplicial Representation for Description Logics Databases, International Conference on Description Logic DL 2000, Aachen Germany, august 2000
REFERENCES ATHENA, 2003, Annex I – “Description of work”, sixth framework program, European Integrated Project ATHENA, 11 november 2003. Chalmeta R. and R. Grangel, 2005, Performance measurement systems for virtual enterprise integration, Computer Integrated Manufacturing, Vol. 18, N°1, January – February 2005, 73-84. Doumeingts G. and Y. Ducq, 2001, Enterprise modelling techniques to improve efficiency of enterprises, Production Planning & Control, 2001, Vol. 12, N°2, 146 – 163. Ducq Y. and B. Vallespir, 2005, Definition and aggregation of performance measurement system in three aeronautical workshops using the ECOGRAI method, Production Planning & Control, 2005, Vol. 16, N°2, 163 – 177. IEEE, (1990), "IEEE standard computer dictionary: a compilation of IEEE standard computer glossaries."
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