Marcius Fabius Carvalho
email: marcius.carvalho@cti.gov.br

Ralph Santos

Evaluation of Enterprise Cooperation through Information Exchange

Keywords: Supply Chain, Enterprise Cooperation, Information Exchange, automotive industry

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

It is recognized that supply chain management requires the inter-and intraorganizational integration relationships and coordination of different types of flows as material, founds and information. Information technology to improve supply chain performance as point of sale scanner and electronic data interchange are available, nonetheless the performance of the supply chain has never been worse [START_REF] Barut | Measuring Supply Chain Coupling: An Information System Perspective[END_REF].

The true supply chain excellence will only come from making a digital business transformation and wWhen done effectively, it enables companies to share information that can dramatically shorten processing time, eliminate value-depleting activities, and improve quality, all of which are fundamental to long-term success [START_REF] Bowersox | R The Digital Transformation -Technology and Beyond[END_REF]. The importance of strategic collaboration and definition of supply chain integration as the degree to which a manufacturer collaborates with its supply chain partners and collaboratively manages intra-and inter-organization processes was highlighted by [START_REF] Fisher | What is the right supply chain for your Product Harvard Business Review[END_REF].

Despite of the importance of information flow, little attention has been given in the literature to measure the magnitude and the effectiveness of information exchange for the coordination of enterprises with their supply chain. This is a paradox since the integration and coordination, through information technology can be largely utilized in an accessible cost.

In one of the few papers in the literature addressing the issue of information exchange among enterprises examine the relationship between the information availability and successful implementation of integrated logistics systems inside of an individual company [START_REF] Flynn | The impact of supply chain integration on performance: A contingency and configuration approach[END_REF]. Scales for measuring supply chain integration and five different strategies were identified was developed by [START_REF] Frohlich | Arcs of integration: an International Study of Supply Chain Strategies[END_REF]. Each of these strategies is characterized by a different "arc of integration", representing the direction (towards suppliers and/or customers) and degree of integration activity. There was consistent evidence that the widest degree of arc of integration with both suppliers and customer shad the strongest association with enterprise performance improvement. A Research [START_REF] Gustin | The effects of Information availability on logistics integration[END_REF] extended the work of [START_REF] Flynn | The impact of supply chain integration on performance: A contingency and configuration approach[END_REF] by providing a general tool that can be used for both the macro and micro levels to evaluate the relative performance of a given information flow structure. The measure, a single 2-tuple index, was derived from information about a firm's relationship with suppliers and customers. The measure encompasses both the depths of information exchanges, that is how far up or down in the supply chain a firm exchanges information as well as the intensity of the information that is exchanged and used in logistics planning. Intensity is measured by gauging the degree to which demand, inventory, and production planning is shared and used by the firms in both directions of the supply chain.

This study takes the work [START_REF] Gustin | The effects of Information availability on logistics integration[END_REF] to answer the question: What is the actual level of integration of auto parts industry sited in Campinas region? The next section presents the method to evaluate the information exchange. In the following the methodology defines the sample specification and questionnaire composition. In the section four the results are analyzed and finally in the section five the conclusion and limitation of the research are presented.

Supply Chain Coupling Index

The method for describing the degree to which a firm is "coupled" within its supply chain, called Supply Chain Coupling Index SCCI based on two indicators [START_REF] Gustin | The effects of Information availability on logistics integration[END_REF]: Information Extent (IE) and Information Intensity (II). IE describes how deep into the network (in either direction of customers or suppliers) the information is exchanged, whereas II describes the richness, and amount of the information used (either in the direction of customers or suppliers). Then SCCI is defined as:

SCCI = EI + II (1)
The enterprise will be less coupled within its supply chain as the value of both indexes (IE and II) approaches zero. On the other hand, the enterprise becomes more coupled as SCCI approaches unity. The ideal situation, EI = II = 1, means all relevant information from all members of the supply chain (customers, suppliers) are shared.

Information extent (IE)

The EI index describes how deep the information can be seen and used into the network (in either direction of customers and suppliers). It is defined as the weighted average of two indexes: the IE toward customers (IE d ) and the IE toward suppliers (IE u ). Thus, the degree of IE is defined as:

I E= k 1 . IE c + k 2 . IE s ( 2
)
Where IEc is the information extent toward customers, IEs is the information extent toward suppliers, k1 and k2 are weights toward customer and suppliers respectively. k1, k2 are between 0 and 1 and sum one.

Information Intensity (II)

The II index describes the richness, and amount of the information used (either in the customer and supplier direction)and, similarly, is composed of two indexes Eq.3.

II = l 1 . II c + l 2 . II s (3)
The IIc and IIs indicate the intensity of information exchange of the firm with its customer and supplier respectively and l1,l2 are weights that sum equal 1. To be coordinated in an effective way a supply chain must consider at minimum the exchange of information of: demand (D), inventory (I), capacity (C), and production scheduling (P). Assuming Dc for demand information from the customer and so on, the information intensity index related to the customer can be written as:

II c = w 1 c D c + w 2 c I c + w 3 c C c + w 4 c P c (4)
Where w1c, w2c, w3c and w4c are weights that sum equal one. And, also assuming Ds for demand information toward suppliers and so on, the customer information intensity index related to customer can be written as:

II s = w 1 s D s + w 2 s I s + w 3 s C s + w 4 s P s (5)

Methodology

The supply chain coupling evaluation was composed of three main activities: sample definition, questionnaire composition, application and analysis of results.

Sample Definition

Taking the theoretical referential it was structured and conducted a field research involving medium and large size auto parts enterprises of Campinas region, Brazil with the objective to answer the question: What is the actual level of integration of auto parts industry sited in Campinas region? This area has been chosen due to a significant number of auto parts firms in the region to be an area on vanguard in the utilization of advanced technology and methodology mainly associated to information exchange. The automotive sector has been chosen since it is one of those dependents of information exchange for the success of its supply chain. Also the automotive sector in Brazil has contributed with 18% of the Gross Domestic Product (GDP). Eighteen enterprises, representing suppliers of first and second level of final assembly plant were participating in the research and fifteen questionnaires were considered valid. Medium and large enterprises were chosen since they are those with perspective of best information technology utilization with their partners. Particularly, assembly plants were neglected since they are not accessible as auto part enterprises are.

Questionnaire composition

The questionnaire was structured in four parts. The two initial parts was focused on qualitative and quantitative measures to identify the size, the position of the participant enterprise in the supply chain, its main suppliers and customers, and internal importance attributed to the information technology. The two last parts were dedicated to determine the Supply Chain Coupling -SCCI as a result of upstream and downstream information coupling. Part 3 Four questions directed to the supplier, to the supplier of the direct supplier, to the direct customer and to the customer of the customer were defined to identify the Information extent Index (IE) as shown in Table 1.

Part 4

This part of the questionnaire was designed for identifying the intensity of firm information exchange from and to both customers and suppliers and type of information used. In general are Demand (D), Production planning (P), Capacity(C) and Storage (S), as shown in Table 2.

Discussion of Results

The Information Extent (IE) for the fifteen enterprises is presented in the Table 1 through as binary form. "1" means information exchange while "0" means no significant information exchange between coupled enterprises. This work considers enterprises sited until two levels upstream to the reference enterprise and two levels downstream to the reference enterprise. Also, weights factors were associated to each level (K = 0,35 to the first level and K = 0,15 for the second level), to express the relative importance of the information. The columns 3 and 4 present the respondent perception related with the cooperation by information exchange with the first level partners up and downstream of the reference enterprise. The second level IE ss index is less relevant than the first level IE s index then its weight is lower.

According to the respondent the information exchange is more intensive with first and second order customers than with the suppliers. It can be confirmed by the dendogram generated from Table 1 and presented in Fig. 1. It also shows the group of enterprises with same behavior regarding to information exchange. The Enterprise (E5), it is totally uncoupled from its upstream neighbor, that is a steel partner, large and strong enough to negotiate with its clients. Table 2 shows the Information Intensity index (II) regarding to the Demand, Storage, Capacity and Production data. Also, the binary representation was assumed (1 information exchange; 0 no information exchange) and the same weight was attributed to the upstream and downstream information exchange, although any other value should be used to consider different way to exchange information. The results demonstrate that actual information exchange practice of the enterprises is inferior to the perception of the respondent expressed in Table 1. Although the respondent recognizes the importance of information exchange as an element for enterprise competitiveness, the individual measures indicate low level of information exchange than they believe. Second, is observed more information exchange with suppliers than with clients. Most of these enterprises are first level supplier of car manufacturers. To confirm this unexpected result an unstructured interview with some enterprises was developed. They say to appeal to secondary data to plan its production. Example, new car sale variation can indicate tendencies in future car maker orders. This tendency influences the enterprise production planning and must be considered although not pointed out by the car makers. This finding shows the importance of second level information and the low cooperation among enterprises participants of the research. A resume of Supply Chain Coupling Index is presented in Table 3. The E16 presents the best coupling index and E05 one enterprise with the worst coupling index. These indexes represent the point of view of the respondent about cooperation of its enterprise with the supply chain. Also it allows to compare one enterprise against its partners or competitors.

Table 1 Information Extent Enterprise Supplier of supplier K ss = 0,15 Immediate supplier K s = 0,35 Immediate Customer K c = 0,35 Customer of Customer K cc = 0,15 Index IE E2 1 1 1 1 1,0 E3 0 1 1 0 0,7 E4 1 1 1 1 1,0 E5 0 0 1 0 0,35 E6 0 1 1 0 0,7 E8 1 1 1 1 1,0 E9 0 1 1 0 0,7 E10 0 1 1 0 0,7 E11 0 1 1 0 0,7 E12 0 1 1 0 0,7 E14 1 1 1 1 1,0 E15 0 1 1 1 0,85 E16 1 1 1 1 1,0 E17 0 0 1 1 0,5 E18 0 0 1 1 0,
,25 E16 1 1 1 1 1 1 1 1 1 1 1 E17 1 0 1 1 0,75 1

Conclusion and Limitation

An analysis of cooperation through information exchange of the Campinas auto parts sector was proposed based in a sample of 15 questionnaires applied to in medium and large size enterprises directly coupled to the car makers or enterprises coupled to the first level suppliers. The main conclusions are:

1) All the respondent enterprise considers relevant to know the actual status of information integration among its partners. 2) In the automotive Brazilian sector exists cooperation mainly related to the first level supplier.

3) The information exchange with car makers is mainly demand, followed storage and production capacity. 4) The respondent perception about information exchange importance is not confirmed when compared to the indexes that qualify the extent of information exchange between partners enterprises. 5) Analyzing the part 1questionnaire results with customer information exchange dendogram, Figure 2, the enterprise size has no significant influence on the SCCI pattern (see E4 and E8).

The present work is focused on customer and supplier integration. Future work would include the internal dimension of integration. It would be interesting to analyze the cooperation by information exchange considering all the elements of a supply chain from the final customer to the raw material suppliers. This study could identify local actions to be implemented to reach better performance for the entire supply chain. Also, would be interesting to calculate the information exchange assuming value between 0 to 1 to obtain to IE(s) and IE(c) in a continuous space between 0 and 1, to consider different ways of information exchange on production, demand, capacity and storage. Finally this tool would be very useful in the establishment of investments in information technology.

Fig. 1 .

 1 Fig. 1. Customer information exchange dendogramTable 2 Information Intensity Enterprise

  Due to lack of space, this work presents part1 and analyze only the results of the part 3 and part 4 of the questionnaire.

	Part 1
	Distribution of enterprises according to number of employees
	Workers	+ 1500	751  1500	251  750	0  250
	Enterprise	E2, E4, E9	E5, E10	E6, E8, E11, E15,	E3,E12, E14
				E16, E17, E18

Table 3

 3 Supply Chain Coupling Index -SCCI

	Enterpris	Index	Index	SCCI
	e	EI	II	0,5*EI+0,5*II
	E2	1	0,625	0,8125
	E3	0,7	0,625	0,6625
	E4	1	0,875	0,9375
	E5	0,35	0,25	0,3
	E6	0,7	0,25	0,475
	E8	1	0,75	0,875
	E9	0,7	0,25	0,475
	E10	0,7	0,375	0,5375
	E11	0,7	0,50	0,6
	E12	0,7	0,25	0,475
	E14	1	0,25	0,625
	E15	0,85	0,25	0,55
	E16	1	1	1
	E17	0,5	0,75	0,625
	E18	0,5	0,625	0,5625
	MEAN	11,4/15=0,8	7,62/15=0,51	0,6342

Acknowledgements.

The authors would like to thank the reviewers for their comments and suggestions for future work.


Alessandro Brusaferri
email: alessandro.brusaferri@itia.cnr.it

Andrea Ballarino
email: andrea.ballarino@itia.cnr.it

Emanuele Carpanzano
email: emanuele.carpanzano@itia.cnr.it

Distributed Intelligent Automation Solutions for Self-Adaptive Manufacturing Plants

Keywords: Distributed Control Systems, Multi-Agent, IEC 61499, Reconfigurable Manufacturing Systems

Nowadays, a new generation of responsive factories is needed to face continuous changes in product demand and variety, and to manage complex and variant production processes. To such an aim, self-adaptive automation solutions are required, capable to adapt their control strategy in real-time to cope with planned as well as unforeseen product and process variations. In such a context, the present paper describes an automation solution based on a modular distributed approach for agile factory integration and reconfiguration, integrating a knowledge based cooperation policy providing self-adaptation to endogenous as well as exogenous events. The proposed approach is discussed through its application to a plant for customized shoe manufacturing.

Introduction

To face new consumer centered manufacturing paradigms, like mass customization and personalization, factories must be capable to adapt themselves in real time to continuously changing market demand. Thus, the whole production cycle for small or even single batches has to be executed in very short times, i.e. a few days or even hours. In order to properly approach such complex and strict requirements adaptive knowledge based production systems have to be developed. In particular, the conception and development of a new generation of automation solutions, that integrate all factory levels from machines controls up to shop-floor supervision and production planning in a unique real time framework, is mandatory.

Future factory automation systems have to be modular, open, agile and knowledge based in order to promptly self-adapt themselves to changing exogenous conditions, like consumers expectations, market dynamics, design innovation, new materials and components integration. For such an aim, a new generation of intelligent, highlyinteroperable and self-reconfigurable control systems is a fundamental enabling technology.

To tackle such a challenge, agile manufacturing paradigms -particularly flexible manufacturing systems (FMS) -have been adopted, often proving to be expensive and difficult to manage due to overall complexity. Furthermore, the integration of flexibility capability is not feasible for any kind of application. Therefore, to overcome such barriers and to provide cost effective flexible solutions, Reconfigurable Manufacturing Systems (RMS) have been introduced, characterized by strongly modular architectures and easy reconfiguration capabilities. In such a direction [START_REF] Koren | Reconfigurable manufacturing systems[END_REF] identify modularity, integrability, diagnosability, customization and convertibility as key features of a RMS. Among these, system modularity can surely be considered the most important, as outlined in [START_REF] Almeida | Event-Condition-Action Systems for Reconfigurable Logic Control[END_REF] where implications and relationships between the architecture of a logic control system, its modularity and overall level of system reconfigurability, are discussed.

The problem of agile system reconfiguration has been faced mainly from the mechanical point of view with the development of easily pluggable mechatronic solutions. Nevertheless, proper solutions addressing a fully modular and reconfigurable control system have still to be identified.

As a matter of fact, present automation approaches and architectures -adopted in industry -are still based on rigid, loosely-coupled solutions, difficult to manage and to adapt, while current methods and tools for control system programming do not effectively support control system reconfigurability [START_REF] Brusaferri | Enabling Agile Manufacturing through Reconfigurable Control Solutions[END_REF].

The integration of a new device within the overall production system or the replacement of a faulty device very often requires a critical stop of the system, to perform physical connections and allocations of the new device, as well as partial/total reprogramming of some parts of the control system, and modifications in production plans, which need time consuming commissioning operations to be executed afterwards [START_REF] Carpanzano | Advanced Automation Solutions for Future Adaptive Factories[END_REF].

The present paper proposes a self-adaptive control solution in order to support the RMS agility. Particularly, section II briefly analyzes the current state of the art related to the development of self-adaptive control solutions for Reconfigurable Manufacturing Systems and summarizes the main features to be guaranteed; section III presents the proposed overall system architecture; section IV reports conclusions and next developments are acceptable.

Requirements and available technologies 2.1 RMS Architecture

Typically, Reconfigurable Manufacturing Systems architectures may be structured into three major hierarchical layers as shown in Figure 1: unit level, cell level and system level. In particular, the overall system is composed by the aggregation of different cell modules, according to the system layout, while, in its turn, a cell module is constituted by the aggregation of more units. Specifically, units can be either operating machines or modules dedicated to parts handling and transportation, e.g. conveyors, rotating tables and manipulators.

Starting from last sampled status of underlying controlled objects, each module of the RMS control system -being unit control module, cell control module or system control module -decides and performs its control actions according to the fixed decision policy defined and hard-coded during the control system development phase. The interactions between modules are established ex ante and implemented according to fixed bindings between different modules interfaces.

Machine Transport system

Manufacturing Cell

Manufacturing Cell

Manufacturing Cell Such a strictly coupled architecture is very difficult to modify during RMS reconfiguration phases, as time and costs required for such operations grow rapidly with the increase in system complexity. To such an aim, a new generation of looselycoupled control architectures, based on a distributed easy-reconfigurable architecture, integrating a flexible knowledge based decision policy, has to be introduced.

Reconfigurable Manufacturing System

Currently available enabling technologies

Today, the required levels of modularity and distribution of control solutions are not properly adopted in industrial practice due to the lack of well defined and accepted reference models. Major consequences of this lack are twofold. First of all, implemented control and supervision strategies are today typically based on rigid centralized approaches organized into strictly coupled sequences of operations. Difficulties in reconfiguration and in real-time adaptation to production needs are most relevant resulting problems. As a second major consequence, suitable readability, portability and integrability of overall control and automation solutions are not supported. Therefore, the capitalization and reuse of company specific knowhow on process and control is very difficult. Flexibility, optimization and failure management features are not properly tackled as well, thus critically impacting the overall production process efficiency and fault tolerance.

Great research efforts have been spent in recent years to conceive a common and well accepted reference model. In such a direction, the multi-agent system (MAS) paradigm shall be mentioned as one the major efforts for development of robust distributed control systems. Such a paradigm is based on autonomous modules, which integrate knowledge-base for decision making inference, high-level communication protocols and languages to support loosely coupled architectural organizations [START_REF] Pechoucek | Industrial deployment of multi-agent technologies: review and selected case studies[END_REF]. Despite its potential capabilities, major limits of such an approach for complex industrial test-cases reside in difficulties of guaranteeing strict execution time requirements.

Recently different research projects as SIRENA 1 , RIMACS2 , SOCRADES 3 , have considered an alternative architectural solution for developing systems composed of autonomous and interoperable units: the Service Oriented Architecture -SOA. Such paradigm is characterized by coarse-grained service interfaces, loose coupling between service providers and service consumers, and message-based, asynchronous communication [START_REF] Lastra | Web Services in Factory Automation: Fundamental Insights and Research Roadmap[END_REF]. Leveraging the SOA paradigm allows for services to be re-used across processes and systems, and systems to be "built for change". Reliability is improved as applications and systems can be made up of tested and proven components. SOA offers the potential to provide the necessary system-wide visibility and interoperability in complex systems subject to frequent changes and operating in a multi-vendor environment. Nonetheless, Service Oriented solutions are still unable to reach the hard-real time constraints in particular for controlling complex manufacturing processes with huge amounts of data and high numbers of units. Furthermore, the decisional logic is not supported by SOA, thus, intelligence has to be integrated onto the SOA level.

In particular, self-adaptivity needs self-interoperability of information: the knowledge has to be structured in order to be understood by autonomous intelligent agents able to interpret the domain conditions and taking the proper decisions. For such reason, a major research effort is ongoing widespread to exploit the adoption of Semantic Web approaches into the factory automation domain. Such paradigm is oriented to the implementation of machine interpretable information supporting the implementation of intelligent control solutions based on formal knowledge models. The formal definition of classes properties and instances allows inferring new knowledge from knowledge already structured into a model.

To cope with real time distributed control, a formal model has been proposed within the IEC 61499 standard of the International Electrotechnical Commission, promoted by the international O3NEIDA network 4 . The normative states the common interfaces and structure of the embedded solutions from simple basic function blocks, to composite functional integrations, up to overall control systems applications. It also provides guidelines for the application distribution within multi-vendor control execution devices. Nonetheless, it does not provide structured indications related to self-adaptive control systems design.

Several research actions have been also oriented to the integration of the low level, hard real-time, control layer and the high level, low real-time, control/supervision layer. In particular, [START_REF] Lepuschitz | Integration of a Heterogeneous Low Level Control in a Multi-Agent System for the Manufacturing Domain[END_REF] propose an interface for the integration of an heterogeneous low level control based on IEC 61499 standard and a Multi-Agent System for the manufacturing domain. [START_REF] Herrera | Integration of Multi-Agent Systems and Service-Oriented Architecture for Industrial Automation[END_REF] propose the integration of Service Oriented Architecture and a Multi-Agent System (MAS) in order to build a control architecture suitable for automated reconfigurability. [START_REF] Leitao | Implementation of a Holonic Control System in a Flexible Manufacturing System[END_REF] introduce a holonic manufacturing control architecture integrated with the logic control layer, designed to improve the agility and reconfigurability of production systems.

Despite the performed research effort and the emerged benefits, such paradigms are currently not implemented within industrial solutions. In fact, the real world applicability needs to be demonstrated through complex industrial test cases highlighting the concrete advantages and providing guidelines for industrial applications.

Deployed Control Architecture

Present section describes main architectural and functional aspects regarding the proposed self-adaptive control solution. In particular, a real industrial plant is considered as a test-case in order to properly support the description and provide application details. Nonetheless, proposed solutions can be integrated within any manufacturing automation system. Obviously, a proper configuration of specific control rules and knowledge base classes is required.

The focused industrial plant

Before starting the description of the deployed control architecture, the considered real industrial application, an innovative shoe manufacturing plant managed by ITIA-CNR, is presented, see Figure 2. For the sake of brevity, a simplified version of a part of the manufacturing system is here considered. The considered manufacturing system integrates an innovative transport line for moving the semi-finished shoes from a machining station to another one according to operations requests. The innovative molecular structure enhances the modularity, scalability, integrability and reconfigurability properties of the production system, increasing the overall flexibility of the plant.

The basic element of the molecular structure is the "Tern", which is constituted by two rotating tables, called "Table " and "Island", and by a rotating three arms manipulator. The Table moves the semi-finished shoes either to the next Tern or to the Island of the same Tern. Moreover, it moves backward the lasts flowing back towards the warehouse (the last is the object around which the semi-finished shoe is built upon). The Island directs the semi-finished shoes towards the different machining stations, laid around the Island itself. The manipulator carries out the transport of the semi-finished shoes and lasts between Tables and Islands. The arrows in Figure 2 depict the possible movements that involve a generic semi-finished shoe or last in a generic single Tern.

The deployed control solution

Starting from the process specification, a modular and distributed control architecture has been defined, integrating a real-time IEC 61499 distributed control layer and a multi-agent semantic enriched control and supervision layer. First of all, to achieve the desired agility objectives, object-oriented concepts have been exploited within control system development. For such an aim, the IEC 61499 standard has been adopted as design paradigm due to its orientation to the deployment of modular and distributed control solutions [START_REF]International Standard IEC61499, Function Blocks[END_REF]. In particular, the molecular line has been considered as a set of interacting Terns, each one with its own independent control system. Each Tern control module communicates with the related Table, Island and Manipulator control modules, as shown in Figure 3. Moreover, each Tern control module is connected to the adjacent Terns control system modules, to coordinate the exchanges of semi-finished shoes and lasts.

Furthermore, each basic function block encapsulates the control logic by means of a state machine responsible for the activation of dedicated IEC 61131 5 based control algorithms depending on run-time events and conditions. For more details regarding function blocks internal structure see [START_REF] Brusaferri | Enabling Agile Manufacturing through Reconfigurable Control Solutions[END_REF]. Tern Control modules represent the low level control layer, responsible for real time control tasks. In particular, tasks dedicated to manage nominal and failure operating condition have been integrated.

Such control modules have been implemented within the ISaGRAF 5 Workbench 6 . By supporting IEC 61499, such environment acts as backbone for the overall application development, from design to implementation and validation. Furthermore, the distributed hardware architecture can be defined by properly assigning the Resources (Virtual PLCs) executed within each device. Moreover, each device integrates I/O interfaces connected to the factory field.

The application can then be designed as a unique control program. Furthermore, the developed control application can be generated into target-independent C code, executable by a firmware, which emulates a virtual machine on hardware, being it an Industrial PC, an embedded board or a tiny controller. Therefore, portability and scalability of the developed application is guaranteed.

In order to provide self-adaptive capabilities to the deployed automation solution while reconfiguring manufacturing resources (i.e. adding, removing operational units or integrating manufacturing functions) a multi-agent control and supervision layer has been integrated onto the object-oriented real-time control layer. In particular, each Tern control module has been connected to a Tern agent, responsible for the interaction within the high level control layer. The interface between the IEC 61499 modules and the multi-agent layer, deployed in Java language, has been developed by means of the Java Native Interface provided by Sun Microsystems Inc 7 .

Besides, the higher level control layer is responsible for the coordination of the low level real-time control layer in response of predicted as well as unforeseen events. In fact, the decisional logic has to be dynamically adapted to follow changing products features/requirements contextually to machine operational capabilities reconfiguration, tools integrations, and new machines implementation into production cells. The higher level control layer is also aimed at interacting within MES and ERP systems so to receive incoming production orders as well as provide a run-time updated factory image to the management layers. To such an aim, dedicated interaction mechanisms have been implemented.

Furthermore, the self-adaptation mechanism has also to react when operational capabilities become unavailable due for example to failures or maintenance operations. To such an aim, a dedicated management agent has been integrated, implementing a knowledge based reasoner connected to complementary knowledge model based on a common formal domain description:

 Product knowledge base model: aimed at the structuring of information related to products to be processed by the manufacturing system, as required operations and priorities with reference to the overall production plan.  Resource knowledge base model: aimed at the formal description of the intelligent units run-time integrated within the production facility, i.e. the operations provided and execution state. Such models are dynamically updated by means of a dedicated Interface agent, in order to be aligned to the process evolution, supporting the optimal real-time decision

Conclusions

The present paper describes a self-adaptive control architecture deployed for a real industrial plant. To such an aim, a modular and distributed approach has been adopted, integrating an IEC 61499 based control solution for real-time control purposes and a semantically enriched multi-agent control layer for dynamic supervision strategy. Main focus of the paper is kept on the description of the overall solution structure, highlighting the capabilities of run-time updating of the knowledge model used for control decisions, while factory products and resources changes occur.

Next efforts will mainly regard the integration of dedicated supervision and on-line dispatching/scheduling facilities onto the deployed control architecture.

Fig. 1 .

 1 Fig. 1. Reconfigurable Manufacturing System Overall Architecture.

Fig. 2 .

 2 Fig. 2. Shoe manufacturing plant and work pieces flows.

Fig. 3 .

 3 Fig. 3. Control architecture of the Molecular transport line.

SIRENA Project www.sirena-itea.org.

RIMACS Project www.rimacs.org.

SOCRADES Project www.socrades.eu.

O3NEIDA Network www.oooneida.org.

International Standard IEC

-www.iec.ch.

Isagraf Workbench -www.isagraf.com.

Java Native Interface -http://java.sun.com/j2se/1.4.2/docs/guide/jni/.

OWL Web Ontology Language -http://www.w3.org/TR/owl-guide/.

strategy. Two dedicated model update mechanisms have been implemented: the first has in charge the management of the products entering/leaving the system and their operational state change due to processed manufacturing tasks performed within the RMS; the second supervises the resources integrated within the system, updating their available operations depending on their evolving execution state and/or reconfigurations.

Thanks to the adoption of such an asynchronous policy, the model adaptation task is called only when required, reducing the overall execution time. Furthermore, semantically-rich based descriptions have been adopted to implement the knowledge based solution. In particular RDF and OWL-DL W3C 8 standards coming from the Semantic Web area have been considered. Therefore, machine reasoning has been used to perform automatic matchmaking of required and offered services using logical inference, rather than performing hard-coded one-to-one mappings.

Such type of matchmaking enables the use of services that did not exist or were not known when the requestor side was programmed, enabling automation system reconfiguration without control logic reprogramming. The overall control architecture is outlined in Figure 4. Once a new operational unit is plugged into the production system its agent asks for the registration service to the manager passing is description as argument, formally reporting the operations to be provided and the required resources (i.e. tools) to be used during operation execution. The operations to be provided and the resources to be used are described with reference to a common ontology.

The manager interprets the ontological description of the intelligent unit and integrates it into a dedicated knowledge base within the manager architecture. A searching algorithm is then executed in order to find the run-time available manufacturing resources capable of providing the requested operations.


Rosanna Fornasiero
email: rosanna.fornasiero@itia.cnr.it

Andrea Chiodi
email: andrea.chiodi@synesis-consortium.eu

Emanuele Carpanzano
email: emanuele.carpanzano@itia.cnr.it

Luis Carneiro
email: luis.carneiro@inescporto.pt

Guidelines for camera ready

Keywords: supply chain, consumer goods, sustainability

Needs and expectations of specific target groups -such as elderly, obese, disabled, or diabetic persons-are arising as challenging opportunities for European companies which are asked to supply small series of functional and fashionable goods of high quality, affordable price and eco-compatible. In order to design, develop, produce and distribute such products, a new framework and related components of collaborative networking need to be developed, enabling the product to stay as long as digital to produce on-demand. Research is necessary in many topics like: a) consumer integrated collaborative eco-oriented design, b) radical renewal by the adoption of Rapid Manufacturing technologies; and c) the overall integration and co-ordination of business processes and information exchange by a set of new (web)services for network design and ad-hoc (re-)configuration, for real-time planning, forecasting and replenishment, d) tracking and tracing of ecology and quality.

Introduction

In recent years, it is emerging at industrial level that full adoption of methodologies and technologies for collaborative production of small series are of decisive importance for European Manufacturing Industry, SMEs in particular, to proactively respond to the high variability of consumers demand and expectations. This will help reducing the risks of following fast changing trends without appropriate tools, causing serious limits in terms of both customer satisfaction and enterprise competitiveness and sustainability. This is especially true in consumer goods sectors, where customer's tastes change very quickly, especially in the current economic situation of downturn, where the purchase capability of customers has sharply decreased and companies need to strongly focus on high value products.

In this work, consumer goods and in particular shoes are considered. In the last years, in footwear industry, on one hand, the number of seasonal collections has been increasing, enlarging the offer in terms of models along the year, and on the other hand the number of products per model has been decreasing in major markets, leaving best opportunities only for companies producing value added and wide range of products.

Moreover, social phenomena like ageing, increase of obese and disabled people [1] and major sensitivity versus eco-friendly products are also key challenges to be faced by the considered consumer sectors, with reference to healthcare and sustainability [START_REF]EU Commission White Paper on Health "Together for Health:A Strategic Approach for the EU 2008-2013[END_REF]. As a matter of fact, today consumers demand for personalization and value adding of harmonized footwear products, as well as in the textile and clothing industry, is not only in terms of aesthetics, but also in terms of health, innovative functionalities and environmental sustainability. Consumers want to know where the product comes from, how it has been created and how it will satisfy his needs and provide health and well being.

There is a clear need for health fashionable consumer goods, since customers today want to be fully satisfied both in their look and their health, but also demand for personalized solutions for their individual needs. The compromise that fashion products may not be healthy and that healthy products may not be fashionable is not going to be accepted anymore by a changing society with increasing needs and expectations and there is a niche market especially for categories like the one mentioned before (seniors, disables, obese people) where European companies can find their way to better satisfy the customer.

This implies small series production with fast delivery which cannot face long waiting time for materials, components and manufacturing services, and a new way to structure the supply network is needed [START_REF] Fornasiero | Leveraging Knowledge for Innovation in Collaborative Networks[END_REF]. Production lines and equipments need to be changed to meet such challenging requirements [START_REF] Carpanzano | Collaborative networked enterprises: a pilot case in the footwear value chain[END_REF].

Open research issues need to address the design, production as well as supply and distribution of small series of health fashionable goods for specific target groups of wide impact in terms of market for the European industry as elderly, disables, diabetics and obese people through personalized and comfortable shoes (e.g. anallergic and bio materials, reduced stitching, flexible and light components) with dedicated medial insoles for foot measurement. Solutions should be based on cost, social compliance and eco-efficient design and production of customised products that fully satisfy the customers considering their health as well as their desire for fashionable products.

State of the art

There are different categories of research topics to be investigated to offer a complete solution to support companies in answering and/or anticipating customer needs. Dimensions to be considered cover many different aspects of production management from organizational changes, to ICT for design and production collaboration, to new production systems and to Supply Chain management.

Frameworks for sustainable networks

From the organizational point of view, companies are facing a new level of complexity, given by the fact that competition as well as collaboration schemes are transitioning from among companies to among supply networks.

In literature, different forms and specifications of business networks are discussed. They are distinguished for example by value chain orientation (horizontal, vertical, lateral), life span duration (long-term vs. short-term), degree of virtualization or hierarchical structure (hierarchical vs. non-hierarchical networks) [START_REF] Camarinha-Matos | Pervasive Collaborative Networks[END_REF]. While most real-life business networks are formed along the value chain and for long-time purpose, the current market asks for flexible organizational structures which can quickly adapt to new prerequisites and challenges.

The new paradigm of Demand-driven supply networks is emerging in literature as a collaborative scheme in response to consumers direct signals and needs [START_REF] Childerhouse | Analysis and design of focused demand chains[END_REF] and [START_REF] De Treville | From supply chain to demand chain: the role of lead time reduction in improving demand chain performance[END_REF]. This implies different approaches to the market based not only on traditional sales channels (shops, retailers) but more and more on an Internet mediated direct contact with consumers both for product conception and for product sales.

For production aspects, as partners are locally dispersed, and processes are knowledge-intensive, the paradigm of Smart Organizations [START_REF] Filos | Smart Organizations in the Digital Age, Integration of Information and Communication Technologies in Smart Organizations[END_REF], which is based on concepts like the Extended Enterprise, (Dynamic) Virtual Organization and Virtual Breeding Environment, need to be transferred to hybrid and disomogeneuos networks where footwear companies integrate their production with other companies to offer to the customer solutions embedded with high tech devices [START_REF] Camarinha-Matos | Pervasive Collaborative Networks[END_REF]. Collaboration will not only be regarded in the perspective of organizational networking, but also in terms of networking ICT support to achieve strategic goals like resource optimization, synergy creation, the achievement of a critical mass and increased benefit for all partners [START_REF]Virtual Enterprises and Collaborative Networks[END_REF], [START_REF] Camarinha-Matos | Pervasive Collaborative Networks[END_REF].

Knowledge management in networks

Recent literature on knowledge sharing in networks is based on:

• hybrid centralized-decentralized models for data and services to allow private confidential data (like Design data) to be kept by the owner and less private, commercial and collaboration data, to be stored in third party data-service centers, thanks to the new IoS technologies of ICT resources virtualization (i.e. Cloud Computing);

• value added services provided by reliable service centers set up and maintained by IT professionals, while Utility Services (like interoperability and collaboration services) offered by distributed service centers based on the existing infrastructure (like COIN1 proposes);

• real time data capture from the field provided by Open Source platforms (like ASPIRE) also to allow the acquisition of eco-compatible data series.

Co-design and sustainability

Today product co-design tools commercially available do not either encapsulate customer orientation as a common feature or foresee real interoperability for an effective distribution of the design phase along the chain. Considering solutions developed within past and ongoing projects, only some steps within customization domain are covered (see for example EUROShoE project2 and CEC-made-shoe project3 results for CAD).

Another aspect to be considered during design phase is the evaluation of environmental impact of products and processes for each shoe model to be developed and for each collection. Shoes are complex products in terms of their environmental impacts: combination of constituting materials and short use time lifecycle result as critical factors able to increase dramatically the environmental burden. Every year nearly 12 million of shoes are sent in landfill with minimal possibilities of recovery contributing to increase the whole amount of not recyclable waste.

At present, a number of environmental standards provide partial information on process related to product (ISO labels, Ecolabel and Environmental Product Declaration) with a common weak point, such as lack of adequate quantitative information in order to compare different products identified as environmental friendly, or possible hidden steps in product conditions.

Designers suffer from a scarcity in tools and methodologies in order to evaluate easily the impact related to design choices in advance. Current tools are frequently too expensive and not suitable for the use within firms especially within SMEs. The main barrier is the high level of customization and changeability of such products. For each firm, the whole portfolio may include several hundred of models each requiring specific materials and modifications. The introduction of new advanced materials in place of traditional materials introduces a further complexity in impact assessment.

Methods and tools for co-planning production and distribution

Small series and personalized products require totally different supply network structures, having to be configured for each customer order and including small number of companies chosen in a large number of accredited potential partners. In practice scenarios will be characterized by a very large number of small orders, each of them having different partner companies, based on their availability and capabilities. In this context, new co-planning systems will be required to optimize the production plans that result, on a first iteration, from the configuration (or set up) of the supply network for each order. Distribution emerges to be different from the one for traditional products and has to be faster and more flexible, assuring that each product is mainly directed to the sales point where best fits the local customer preferences.

The complex planning problems arising in the context of collaborative networks is based on the broad class of "Combinatorial Optimization" and for tackling hard problems, it is possible to use state-of-the art metaheuristics. These are reasonably simple and flexible optimization algorithms based on local search procedures, and in general quite easily adaptable to cope with new problem configurations.

The "classical metaheuristics'' (Simulated Annealing, Taboo Search and Genetic Algorithms) have evolved to more refined methods, and also have given rise to new methodologies like Variable Neighbourhood Search (VNS), Greedy Randomized Adaptive Search Procedure (GRASP), Ant Colonies Optimization, etc. [START_REF]Metaheuristics: Computer Decision-Making[END_REF], [START_REF] Glover | Tabu search[END_REF].

A recent, extension of these approaches is on the design of multi-objective metaheuristics, thus incorporating some critical requirements of practical problems. These approaches are presenting very promising results in several areas and expected to be key in the successful resolution of optimization [START_REF] Azevedo | An Advanced Agent-Based Order Planning System for Dynamic Networked Enterprises[END_REF], [START_REF] Blum | Hybrid Metaheuristics: An Introduction[END_REF], [START_REF]Advances in Metaheuristics for Hard Optimization[END_REF].

The proposed approach

Future research for healthy fashionable products need to be based on the following pillars:

P1. Reference Framework for Collaborative Supply Networks

The reference framework model for collaborative supply networks shall address, orientate and integrate all aspects both at organizational and technological level concerning interaction of organizations, business processes, considering co-ordination and synchronisation of contents, as well as information exchange and software application modularity for improvements in data management, in order to create a seamless flow of information from market to design and development, to production and distribution.

From the organizational point of view the following topics will be considered to implement an innovative model for footwear collaborative supply networks:

• Hierarchical vs. not-hierarchical supply chains • Business ecosystems vs. smart organizations • Agile and proactive Virtual Organisations creation, management and governance • Social networking, Consumer Communities and Living Labs as vehicles for customer/consumer integration in the context of OpenInnovation. From the technological point of view, the reference data model shall be based on service interoperability defined as a backbone for the development of the related applications in the following pillars. Particular attention will be given to the integration of the new services in already existing solutions in order to avoid replication and overlapping with existing systems.

P2. Innovative consumer-driven environments for product design

This pillar will address the implementation of innovative environments for consumers and suppliers collaboration and knowledge management. The goal is to create a novel concept that enables the vision of an "empowered-to-design" consumer from one side, and the creation of market and design knowledge within a social network environment [START_REF] Hendrickson | TechCrunch. Nine Ways to Build Your Own Social Network[END_REF]. This pillar aims thus to achieve cutting edge innovation along the following lines: • Collaborative design tools, empowering the consumers to design their own products by providing them the ability to collaborate in an informed design process not only regarding aesthetics, prices and delivery times, but also regarding resources consumption and social responsibility, implementing sustainability parameters in the design phase and relying on the synchronization of the design along the supply chain; • A new model of market information sourced from the unstructured information from consumers, designers and suppliers interaction, within a social network/virtual community environment and relying upon the use of semantic technologies for knowledge extraction and pattern matching [START_REF] Lea | Enhancing business networks using social network based virtual communities[END_REF], [START_REF] Boulton | Consolidation Time for White-label Social Networks[END_REF].

Multifunctional design need to be supported by an event driven tool for the coordination of design and industrialization phases with production process. Intelligent tools for product and components design is necessary to plan the ecological, economical and social sustainability of each model based on innovative approach to LCA-Life Cycle Analysis. All of these should be developed as plug-ins and additional services for existing enterprise applications (CAD-PDM solutions).

This pillar need to study how to manage market and product data to define not only "customer-" but also "market virtual profile" and how to use this data during design process. Information on consumers to capture requirements on style preferences, physical measure, health needs and feedback on product previous versions, through implementation of consumer communities, web spaces for customers feedback, "point of opinion" at retailers stores, configurators capable of managing personalized data.

P3. Methods and tools for supply network configuration and distributed production planning.

In this pillar, innovative and adaptive services for production process modeling and supply networks formation and management shall be based on a distributed interaction system to integrate different actors (components suppliers, outsourcers, service providers, retailers, customers) of different sectors collaborating in dynamic networks. Moreover product and process quality control based on environmental impact parameters shall be developed through a shared platform for eco-monitoring. Main contribution in this pillar shall be based on developing innovative services for supply network management based on existing technologies like SOA, EDA, Product Tracking & Tracing, web2.0, semantic web 4 and existing commercial applications.

In particular it will be important to develop the following three services: • Easy-to-use Supply & Distribution Network Design (SDND) Service for configuring supply networks, based on full sustainability parameters. Life Cycle Costing tool for supply networks can be used to evaluate the sustainability impact of each of the possible network configurations according to a peer-to-peer distributed data set published autonomously by each potential supplier. Particular attention need to be paid to cross-domain collaborative processes support and fast changing networks. Companies need to share a reference and extensible competences model, which captures comprehensive relevant information and knowledge to maximize endto-end visibility related to suppliers, distributors, third party logistics providers, based on Availability-to-promise and Capacity-to-promise data.

•

User-friendly Collaborative Planning Forecasting and Replenishment (CPFR) Service, based on ad-hoc combinations of optimization algorithms shall be studied and implemented to guarantee on-time delivery based on optimization of the trade-off between minimization of cost and lead time, quality and customer service. The systems shall be based on real-time product tracking and tracing data, captured from distribution centers, from third party logistics providers and data from producers. Supply and Distribution processes will be managed in a decentralized way allowing the partners of the value network to choose the best option for on-time delivery. New models shall be studied to merge delivery from different producers.

•

A web-and wireless-enabled Eco-and Quality-Monitoring service on product/process quality and eco-sustainability along the value chain, to collect information for producers and customers on who, how, where, when, the product was produced and delivered indicating a level of sustainability and product quality. Such services will be made available for integration into state-of-the-art existing SCM systems, either as plug-ins or as external services to be called on-demand.

P4. Rapid manufacturing technologies for small series industrial production

Rapid manufacturing technologies shall enable the flexible, energy and eco-efficient production of specific added value components/parts of consumer personalized goods [START_REF] Carpanzano | Towards the New Mass Customisation and Personalisation Paradigm: Needed Next Generation Manufacturing Technologies[END_REF]. In particular reduction of set-up time is crucial in the production of small series in order to avoid loss of time when changing models. Cutting-edge technologies for developing a multi-process machine based on laser decoration and engraving for production of small series specifically developed as a unique integrated unit coping with high speed laser cutting, laser engraving, laser marking for personalized shoes.

These four pillars should be integrated in a unique solution and demonstrators need to be implemented to test and validate pilot collaborative supply network offering integrated small series of personalized shoes to target groups. Pilot demonstrators shall be composed of manufacturing companies collaborating with technologies providers along product lifecycle where coordination has to be managed at supply chain level.

Conclusions

The proposed approach to support footwear companies in the implementation of new models for small series production for health and fashionable goods follows the Competitive Sustainable Manufacturing (CSM) paradigm [START_REF]FoF-PPP: Factories of the Future: Public, Private Partnership, Strategic Multi-annual Roadmap[END_REF] and current initiatives of European Technological Platforms like Manufuture [START_REF] Manufuture | Strategic Research Agenda[END_REF] and Footwear [START_REF]ETP-Footwear: Vision and Strategic Research Agenda of the European Footwear Products and Processes Technology Platform[END_REF] asking to join forces for strengthening the European manufacturing sectors for the benefit of the European industry and of the final customer. This means that sustainability is interpreted in the European STEEP (Social Technological Economical Environmental Political) sense to include in strategy definition: globalisation of the economy, climate change, ageing population, public health for all, poverty and social exclusion, loss of biodiversity, increasing waste volumes, soil lost and transport congestion (FoF-PPP). In this context, the specific objective of new research shall be to increase significantly the sustainability of value creation of small series health fashionable consumer goods and in particular of footwear products, for emerging social by systemic/coordinated intra-and inter-sector networking of producers/service providers using cutting-edge (digital and) production technologies and as well as innovative organizational models based on cross-supply network integration through major complementary breakthrough innovations.

P1. Reference Framework for Collaborative Supply Networks

	P2. Innovative consumer-		P3. Sustainable Methods		P4. Rapid manufacturing
	cooperative environments		and tools for production		technologies and
	for product design Market interaction tools Co-design (CAD/PDM) and LCA	Interoperable product data	distributed planning Supply network configuration Capacity Planning Forecasting and Replenishment	Interoperable product data	processes for small series industrial production Advanced laser engraving and
			Eco Track and trace		marking
	Consumer KB interaction tools		Tools for co-planning and distribution		Rapid manufacturing machines
		Pilot demonstration for health fashionale shoes

Collaboration and interoperability for networked enterprises, FP7-ICT-2007.1.3-216256, http://www.coinip.eu

EUROSHOE project, EU VFP

CEC-made-shoe project, EU VIFP mass-customization.blogs.com/.../the-cec-co-design-contest-openinnovation-in-the-footwear-industry.html

under development in ICT projects like COIN (IP www.coin-ip.eu) and iSURF (STREP http://www.srdc.com.tr/isurf/)


Fatah Almabouada
email: falmabouada@yahoo.fr

Djelloul Louhibi

Abderrahmane Haddouche

Abdelkader Noukaz

Ramdan Beggar

A New Automated Trigger Circuit for a Pulsed Nd: YAG Laser

Keywords: Flash lamp, solid-state laser, simmer circuit, trigger circuit

The power supply of flash lamp-pumped a Nd: YAG solid-state laser basically consists of a trigger circuit which initiate the ionization of the gas into the lamp, a simmer circuit that keeps the ionized gas with a low-level dc current and a main discharge circuit where a storage capacitor is discharged into a flash lamp to pump the Nd:YAG laser. The impedance of the flash lamp presents a nonlinear variation and the gas deionization which can occur between two pulses laser, leading to another manual triggering operation. To overcome this operation, we give in this paper a new automated trigger circuit activated by a delivered signal from the simmer circuit. This circuit is simple for implementation and need just few components. It has been simulated by PSpice software and validated by experimental results.

Introduction

Pulsed Xenon flash lamps are gas-discharge devices designed to produce a pulsed radiation. They convert the electrical energy to the optical radiation. This intense pulse of radiant energy is used in many applications. In our case these devices are used for pumping solid-state lasers.

One of the principle diagrams of the power supply circuit of a pulsed flash lamp is the simmer mode operation as shown in Fig. 1. This mode has a several advantages and one of them is the increasing of the flash lamp lifetime.

The power supply performs a number of functions:

-The external trigger circuit provides a high voltage pulse around 20 kV to initiate the ionization of the gas. The secondary of the trigger transformer is connected to a wire which is wrapped around the lamp [1]- [START_REF] Koechener | Solid-state Laser Engineering[END_REF].

-The simmer circuit maintains a partial steady-state ionization by establishing and maintaining a low-current dc arc between the lamp electrodes.

-The charging unit is used to charge the storage capacitor C. The charging must be completed within the inter-pulse time of the laser. The principal capacitor discharge through the flash is ensured by an electronic switch. The capacitor C, the inductor L and the impedance R of the flash lamp constitute the circuit that provides the desired shape pulse during the discharge. The operation of the laser and the flash lamp characteristic, allow to fix the values of C and L [START_REF] Koechener | Solid-state Laser Engineering[END_REF]. During the operation of the laser, the lamp gas can be deionized between two laser pulses obliging to trigger again which is a drawback because in our previous work the triggering operation was activated by a manual command.

Contribution to Technological Innovation

This work is an innovation in the electronic command of a trigger circuit used to energize the flash lamp. In our contribution the command trigger is automated by a circuit which isn't complex and uses little components. Several works were done in this field [START_REF] Changaris | New Albany, IN (US): Method and circuit for repetitively firing a flash lamp or the like[END_REF] and where the trigger is activated at each laser pulse which is a disadvantage because that decreases the flash lamp lifetime [START_REF] Koechener | Solid-state Laser Engineering[END_REF].

Simmer and Trigger Circuit

Simmer Circuit

After the triggering, the flash lamp impedance R varies in a nonlinear way where its measured value is given within 1 kΩ and 17 kΩ [START_REF] Beggar | Caractérisation expérimentale d'une lampe flash utilisée pour le pompage d'un laser à solide[END_REF]. This variation is represented by the electrical characteristic of specified flash lamp as illustrated in Fig. 2. The simmer circuit will be able to follow this variation. The proposed simmer uses a voltage multiplier which is supplied by 200 V as an alternative voltage given by a switch mode power supply. This voltage multiplier delivers 1.2 kV and 100 mA when a flash lamp is non-ignited. At the ionized state, these values vary in accordance with the flash lamp resistor load [START_REF] Noukaz | Modelling And Development Of The Command And Simmer Circuits For The Power Supply Of Flash Lamp Pumped Solid-State Lasers[END_REF].

Before the experimental step, all the simulated results of designed circuits have simulated using the Pspice simulator.

The simulated simmer circuit is represented in Fig. 3, V1 is equal to 200 V and the resistor R10 represents the flash lamp resistor taking several values. The simulated results of the simmer voltage are given for several values of R in Fig. 4.

Trigger Circuit

In our previous work we developed a trigger circuit activated by a manual command [START_REF] Almabouada | The Main Discharge Transformer And The Trigger Circuit For The Power Supply Of A Flash Lamp-Pumped Solid State Laser[END_REF]. This trigger (Fig. 5) is a flyback converter [START_REF] Brown | Practical Switching Power Supply Design[END_REF] using a commercial high voltage transformer (THT model: HR6060). The user has just to push the manual button (S) to supply pulse duration T 1 to the switching transistor (T), adjusted by R1 and C1 of the monostable MC4538, which will be sufficient to produce the high output voltage (V HT ). In general, the THT is supplied by 120 V (Ve) as a voltage at 15.625 kHz (64 µs) allowing pulse duration T 1 equal to 32 µs for a duty cycle of 50%. In our case, a low voltage of 12 V to 24 V is applied for a safety use; therefore the pulse duration T 1 should be adjusted in order to have the same high voltage in the output. For this purpose, the relation between the parameters is expressed by [START_REF] Brown | Practical Switching Power Supply Design[END_REF]:

T 1 = (L p /V e )I pmax .
(

) 1
where L P is the primary inductance and I Pmax is the maximum primary current. For Ve=12 V we must increase T 1 at 320 µs for obtaining the same I pmax .

The circuit was simulated and tested experimentally. The experimental result is given by Fig. 6. To avoid the manual triggering after the deionization of the gas, the useful idea is to automate the command of this trigger circuit.

Simmer Command for Triggering

For the automated command, the command signal is generated by the simmer circuit depending of the ionized state. When the simmer output is around 1.2 kV corresponding to the flash lamp non-ignited state, a pulse voltage is required for the monostable in order to generate the trigger pulse. For the ignited state, the simmer circuit has a small voltage value which is not sufficient to command the monostable. The complete simmer-trigger schematic enclosing the command signal is illustrated in Fig. 7.

Conclusion

In this article, an automated trigger circuit has been developed in order to overcome the manual triggering when the deionized flash lamp gas can occur. The command circuit is simply implemented using available components allowing a quick maintenance. The experimental results are in good agreement as obtained in simulation.

Fig. 1 .

 1 Fig. 1. Principle diagram of the flash tube excitation circuit.

Fig. 2 .

 2 Fig. 2. Electrical characteristic of the flash lamp (Flash-Heraeus Noblelight Ltd. Model: P537).

Fig. 3 .

 3 Fig. 3. Simmer circuit.

Fig. 4 .

 4 Fig. 4. Variations of the Simmer voltage versus the flash resistor.

Fig. 5 .

 5 Fig. 5. Trigger circuit.

Fig. 6 .

 6 Fig. 6. The triggering pulse (trace vertical: 2kV/div)

Fig. 7 .

 7 Fig. 7. Simmer-trigger schematic enclosing the command signal.

Fig. 9 .

 9 Fig. 9. Simulated results of the simmer voltage and the monostable voltage (pin4).

Fig. 10 .

 10 Fig. 10. The simmer voltage (lower trace vertical: 500V/div) and the voltage pin 4 (upper trace vertical: 1V/div).

Fig. 11 .

 11 Fig. 11. The trigger pulse (upper trace vertical: 2kV/div) and the simmer voltage (lower trace vertical: 500V/div).

Experimental Circuit

The Fig. 8 shows the experimental circuit. Fig. 8 describes the all components to achieve the last reported command function. Furthermore, the Pin 4 of the monostable receives a command signal from the additional circuit used to automate our trigger. This circuit employs a resistor divider and an IGBT (or a MOSFET transistor) as common drain with a simple resistor at its source. For the deionized gas state, the resistor divider (R2, R3) gives a sufficient voltage to the gate of the IGBT which works in the switch-on mode. In this case, the IGBT switches to the minimum required voltage (3 V) used by the Pin 4 in order to offer the desired T 1 from the monostable. In the ionized gas state, the resistor divider can not fulfill the voltage condition keeping the IGBT in the switch-off mode.

The simulated results of the monostable input voltage (Pin4) and the simmer voltage verify the behavior of the additional circuit for the automated case as shown in Fig. 9. These results are in good accordance with the experimental results given in the Fig. 10. Fig. 11 represents the experimental behavior of the simmer voltage and the high voltage triggering pulse. It is observed that when the simmer voltage reaches its high value, the trigger circuit delivers the triggering pulse for gas ionization into the flash lamp. At this moment, the simmer voltage drops down to its small value. The circuit was tested with a Xenon flash lamp: Flash-Heraeus Noblelight Ltd. Model: P537 which is used to pump the Nd: YAG laser.