Kostas Kalaboukas
email: kkalaboukas@singularlogic.eu

Borislav Jerabek
email: boro.jerabek@gorenje.si

Rok Lah
email: rok.lah@gorenje.si

Freek Van Polen

Seamless access to sensor networks for enhanced manufacturing processes

Keywords: integrated manufacturing processes, network design, sensor networks, smart factories

WSNs are largely deployed nowadays in "smart factories". However, their smooth operation is hindered by device heterogeneity and lack of integration with the current IT systems. The SIMPLE project aims at seamless inter-working of sensors, actuators, tags and devices with business IT systems and distributed control systems towards simpler integrated manufacturing processes. SIMPLE delivers a novel hierarchical network architecture, based on the envisioned manufacturing processes and reflecting the functional hierarchy of aggregations of goods or production processes found in the manufacturing use case.

Introduction

Wireless Sensor Networks (WSNs) have been identified as one of the most important technologies for the 21 st century. The deployment of WSN in "smart factories" applications is already a fact and has attracted the interest of the research community and the electronics development giants worldwide. In a medium sized manufacturing plant over an area of 10000m 2 , 5000 pressure sensors, 1000 temperature sensors and 500 sensors of other types exist on average [START_REF] Mols | Making Measurement Count[END_REF]. However, significant problems hinder their wide exploitation: this great number of sensors includes sensors of different type (e.g. temperature, pressure, RFID reader), operating on different device platforms with different capabilities and communication characteristics. This heterogeneity prevents the simple, uniform access of information throughout the sensor cloud and its seamless integration with the business IT systems, which will be more and more needed, as the number of cheap multi-purpose sensors proliferates and even more reconfigurable sensor nodes are under development [2]. The seamless inter-working of sensors, actuators, tags and devices with business IT systems (e.g., ERP, WMS, MES) and distributed control systems towards "simpler" integrated manufacturing processes is at the core of the SIMPLE1 project [3]. SIMPLE aims at designing and developing a flexible sensor network architecture and a middleware solution in order to compensate for the current lack of open-source and commercial solutions capable of monitoring the state of shipments at different grouping levels (e.g. at the crate and case levels) and, more generally, of tracing goods along the whole supply chain. The vision is to enable information collection from all over the manufacturing plant in a uniform way without having to consider the heterogeneity of the underlying infrastructure. The present paper starts from the analysis of the current manufacturing processes (in section 2), which was carried out to create a concrete list of requirements, and reports the improvements, that an integrated solution can bring in section 3.To achieve these objectives and meet the identified requirements, a hierarchical network architecture has been designed and is presented in section 4. It reflects the functional hierarchy of aggregations of goods or production processes found in the manufacturing use case. Conclusions are drawn in section 5.

Manufacturing "As-is" Situation

To capture the functionality that can significantly simplify the manufacturing process, first the currently adopted white goods manufacturing process was analysed, based on input provided by Gorenje2 . Currently, white goods manufacturing consists of 4 main phases:

Phase A: Framework Construction. All mechanic parts of the product are being assembled. The parts are picked from the warehouse and transferred to the production centre. There, a fully automated assembly line is responsible for putting together all parts to create the framework of the product. Phase B: Electronic parts assembly. The framework goes to the second phase, where all electronic parts, circuits, accessories, control mechanisms, etc. are manually inserted. Similar to the mechanic parts, the electronics, are picked by the warehouse, exit it and transferred to the production center. Once assembled, the final product enters the testing phase. Phase C: Testing. According to the results and the severity of the failures (if found), the product may have one of the following paths: 

The product has no failures and ready to be released. The product goes to the warehouse of final products for further delivery.



The product has minor failures. In this case, the technical team disassemblies the product. All parts then are returned to the materials warehouse.



The product has severe failures. The product is being disassembled and the technical team checks all parts separately. Those that are reusable go to the materials warehouse and the damaged ones are destroyed. Phase D: After Sales Support. When the product has been sold, automated management support can still be provided. Within regular intervals, the appliances perform self-testing and upon detecting a malfunction, an alert message is sent or an error code appears on the built-in led display. The after-sales support office is informed either by the client or automatically, so that the problem gets fixed.

Manufacturing "To-be" Situation

Through SIMPLE the manufacturing process is being automated in various phases allowing for easy monitoring of incoming/outgoing goods in the warehouse, as well as better tracking of the production and product-in-use phases. The modifications that were considered necessary for each manufacturing phase are described next:

Phase A: Framework Construction. A visual camera could test the position of the part to be assembled, the part type, as well as any possible anomalies. Phase B: Electronic Parts assembly. Parts will be RFID-tagged in the warehouse and RFIDs will be registered in the SIMPLE server. A motion sensor will register parts transportation to the production center. After assembly, the final product is being tagged and the aggregated RFID is registered in the SIMPLE server. Phase C: Testing. Depending on the testing result, the following SIMPLE intersection points can be triggered: 

The product has no failures. The product will be released, while a motion sensor will register the event of the product being ready for delivery.



The product has minor failures. All parts will contain this information and enter the warehouse. A motion sensor will also register this event.



The product has severe failures. The product is disassembled and the aggregated tag is being destroyed. The reusable parts are led to the warehouse and this event is recorded through a motion sensor. Each (tagged) part also contains the severe failures history and "reusable" status. The tags of the non-reusable parts are also deleted from SIMPLE. Additionally, integration with the ERP system can lead to automatic creation of material consumption reports and warehouse documents (when a part enters or leaves it, as well as automatically tracking the production process). Phase D: After Sales Support. The product has an embedded Automated Testing Tool (ATE), which is beyond the scope of SIMPLE. According to the envisioned manufacturing scenario, a number of system requirements have been derived. The requirements, related to the network architectural design, which is at the focus of this paper, are the following:  Collection, filtering and processing of the readings from a variety of sensors, tags and sensor networks (e.g., RFID, temperature, pressure, humidity), and accordingly delivering them as reports.



Mapping and correlation of the above reports to business events associated with user-defined business contexts and processes for integrated manufacturing. RFID tags will allow for accurate and automated association of manufacturing processes and items with wider business processes.



Enabling configuration and invocation of actuating services in machines, devices and actuators.  Provision of techniques and graphical tools for managing sensors, devices, as well as business contexts and processes.

The SIMPLE Solution

SIMPLE is understood as a middleware platform and as such, it shall be a software layer operating on every device that is part of a SIMPLE application, and form the bridge among these devices capitalizing on emerging works on programming sensor nodes [START_REF] Mottola | Programming Wireless Sensor Networks: Fundamental Concepts and State of the Art[END_REF]. To efficiently face the diversity of devices mainly with respect to their hardware (processing and storage) capabilities, we have reviewed the devices usually involved in a manufacturing plant and we have organized them in classes, prior to designing the overall SIMPLE network and node architecture. Then, to address the scalability issues arising in such systems, we have designed a hierarchical network architecture that discriminates different hierarchy layers and specifies the functionality (including the middleware, networking and application functionality) that the device belonging to each layer should execute. It is worth stressing that there is no one-to-one relation between device class and layers, since a device belong to a specific class depending on its hardware capabilities while it plays the role of a layer -x device depending on the functionality it supports. Finally, to guide the development of the SIMPLE system, based on the network architecture and the specified functionality per layer, the SIMPLE node architecture is drawn.

SIMPLE Nodes classification

The SIMPLE devices are classified according to hardware limitations as follows: Class 0 Devices: RFID Tags. Radio-frequency identification (RFID) makes use of radio signals to exchange data between a reader and an electronic tag attached to an object, for the purpose of identification and tracking. RFID tags can be read by the RFID reader, in case of short distance, antenna matching and possible signal propagation. The RFID tags contain an integrated circuit for storing and processing information, modulating and demodulating a radio signal and an antenna for receiving and transmitting the signal. RFID tags can either just have a fixed ID or they could in addition also have a read-write memory from and to which the reader is able to read and write information. In case of RFID tags the RFID readers that communicate to the individual tags are the interfaces to the rest of the SIMPLE system. The RFID readers collect the information from the tags, store it locally and, if required, communicate the information to the rest of the SIMPLE system and write new information to the RFID tags via the middleware interface. The main functions that these tags types support are tag inventorying and optimizing, reading/writing, locking and killing. Class 1 Devices: WSN Nodes. WSNs are distributed networked systems composed of embedded computing nodes, each one being equipped with a processing unit (typically a microcontroller), a wireless communication interface, sensor(s) board and a battery. The wireless sensor networks typically make use of ad-hoc multi-hop networking schemes, which means that all nodes operate as routers, as well as they should be able to join and leave the network without any disruptions to the network operation. Class 2 Devices: Hand-held RFID Readers. While RFID readers by themselves may be very small and attached to WSN nodes, hand-held RFID readers are included in a separate class, mainly due to their specific role in the SIMPLE systems. This class will typically be able to engage in user interaction, while also being able to read RFID devices, and thus be a powerful tool in a SIMPLE system for configuring installations. This type of device shall typically be used to add RFID tags to the system, to aggregate groups of devices, and to attach RFID tags to objects that need to be represented in the system. Class 3 Devices: Hand-held and Embedded Devices. Hand-held and embedded devices, even personal and general-purpose devices, such as smartphones, are expected to be present in manufacturing environments. Devices of this type are marked by a high degree of connectivity. In SIMPLE, this class of devices could fulfill several different functions. First, their ubiquitous presence and high connectivity gives them the potential to be powerful ad-hoc routing hops. Second, they could operate as mobile sinks for any WSNs in the vicinity, as well as gather their own sensor data, with any sensors they might have equipped themselves. Third, these devices typically are designed for user interaction, and so could be used by any SIMPLE application. Class 4 Devices: Desktops and Laptops. Desktops and laptops feature great processing power and memory, which allow them to sit in the background behind a sink node and operate on data that have been collected by a WSN. Within SIMPLE, desktops and laptops will be a readily available source of computing power and user interaction. Therefore, they could store and process large amounts of data in a local fashion. Additionally, they will be the most obvious choice for SIMPLE applications to interface with users, allowing them to monitor processes and configure a SIMPLE installation. Class 5 Devices: Servers and "The Cloud". With recent developments in cloud computing and the increase in cloud computing services being offered, a virtually unlimited amount of computing power and storage room becomes available. Recently, however, services have become available that focus specifically on the storage and processing of sensor data. Within SIMPLE, this class of devices will be able to store and backup all data gathered in an installation. While the capabilities of this class of devices are virtually unlimited, they do have their limitations in that the amount of communication required may introduce lag in the system. Therefore, a the kind of data being stored and processed locally (typically recent data that may become relevant very quickly), as well as the kind of data being transported to the cloud for storage and processing should be carefully chosen.

4.2

The SIMPLE network architecture for the manufacturing use case The SIMPLE hierarchical network architecture can be applied to a variety of cases and is specifically useful for large and heterogeneous WSN systems. However, as the focus of this paper is on the enhancement of the manufacturing process, we concentrate on its operation for the manufacturing ("to-be") use case. The SIMPLE layered network architecture is presented in Fig. 1.

Fig. 1. The SIMPLE high level network architecture for the manufacturing case

In Phase A, the RFID reader and the camera or other visual inspection devices are considered as layer-1 devices. A layer-2 node (acting as information aggregator) receives the sensed data and can create a list of the mechanical parts that will be used for a specific good and their condition. This list is created either periodically or upon user request. In Phase B, the RFID reader and the camera are regarded as layer-1 nodes. In Phase C, testing, once a new device has been produced, a layer-2 node or another layer -1 node inspects the product. The result is announced to the layer-2 node, which has also collected information about the parts that the product consists of. This node now creates a product ID, associates it with the RFIDs of the parts it consists of and creates a message towards the server to inform that a new product is ready providing the details of its sub-parts. In the case of failure, the product is disassembled and the layer-2 node generates a different message providing the list of RFIDs of the parts. If any of them is no longer reusable, its RFID is sent to the server marked as "to be destroyed". In Phase D, after sales support, it is the embedded Automated Testing Tool (ATE) that assists in problem fixing and SIMPLE is not involved. From a communication perspective, layer-3 nodes are assumed to be installed in large manufacturing areas and are responsible for collecting information from sensor nodes regarding one or multiple production lines, as well as area-related information (e.g. temperature, humidity, light). Layer-3 nodes are also acting as gateways to the enterprise server. Layer 1, 2 and 3 nodes are either in one or multi-hop distance between them, thus the need for realizing a WSN routing protocol arises. As regards the location, all nodes will most probably be placed in fixed locations, thus the exact coordinates can be statically configured. As regards functionality, 1. layer-1 nodes sense data (RFID reader, anomaly detection, visual inspection), 2. layer-2 nodes generate product IDs and associate them with the IDs of the parts that form the product, 3. layer-3 nodes aggregate information regarding one or more production lines and areas and connects the layer 2 nodes to the server.

4.3

The SIMPLE-node architecture The high level architecture of the SIMPLE node following an OSI approach is shown in Fig. 2. The SIMPLE research efforts are focused on the layers above the MAC layer. At the network layer, a location manager module will exist which will either become aware of the nodes location through GPS or will execute a localization technique.

Fig. 2. The SIMPLE OSI-aligned node architecture

At the same OSI layer, the trust-aware routing block will undertake the responsibility to define the path of any message from any SIMPLE node towards the SIMPLE sink node. In addition, a trust management system will guarantee the detection and avoidance of malicious nodes. The trust information will be kept in the Local Storage block per one-hop neighbor and will be combined with the location information to define the next-hop node. The Energy manager monitors the remaining energy of the node for two purposes: first, to inform the upper layers in case the remaining energy is running low and second to inform any layer (e.g. routing) about the current energy level so that it takes this information into account to reduce the overall energy consumption. The middleware layer contains the data model, containing all necessary data for the manufacturing case. The data fields specified in this model are a listing of the data type stored in the middleware layer. Consequently, all functionality offered to the SIMPLE applications shall ultimately operate on these data fields. The data model provides functionality to store sensor data, as well as device IDs and aggregations between devices. Also, the data model is able to represent real world objects, which are not SIMPLE devices, and associations between SIMPLE devices and objects. For the manipulation of these basic data fields, low-level data manipulation functions are defined, which are part of this data model. The SIMPLE Application API forms the bridge between the SIMPLE middleware layer and SIMPLE applications. The API allows applications to pose queries and subscribe to specific events. Moreover, the API allows the application to set certain conditions on the validity of the data that are to be returned. These conditions can be on the value of data itself, but also on the geographic region from which the data originate, the time at which the data were gathered, or the confidence the middleware layer has that indeed it is valid data.

Conclusions

SIMPLE has been presented as an integrated solution to the manufacturing automation. SIMPLE aims at delivering answers to as yet unsolved problems and products long needed for the commercialization of sensor networks in large-scale manufacturing and logistics applications. These objectives are met by progressing the state-of the art in three key research areas, namely in a) energy efficient and secure sensor routing, b) middleware technologies and c) sensor's network architecture design. The present work was focused on the third field, elaborating the manufacturing process, continuing with the heterogeneous hardware classification, the SIMPLE high-level node architecture, supporting the aforementioned situation and ending in the SIMPLE network architecture design presentation. Obviously, the SIMPLE architecture definitely supports fully automated manufacturing operation. The designed architecture, along with the defined functionality, will be mapped to a real-life test-bed, demonstrating the complete functionality of the SIMPLE system. The proposed developments will be able to provide traceability of the components and the products, store the history of each product and provide monitoring and transparent trace data to the manufacture plants, the warehouse, the distribution stores and the final customers. The test-bed will be set up in the Gorenje premises.

Self-organizing Intelligent Middleware Platform for manufacturing and Logistics Enterprises

Gorenje is one of the partners of the SIMPLE project consortium and the largest Slovenian manufacturer of white goods (larger home appliances)

Acknowledgement

The work presented in this paper was partially funded by the ARTEMIS SIMPLE project.


Uwe Dombrowski

Sebastian Weckenborg

Michael Mederer

Demand Control Loops for a Global Spare Parts Management

Keywords: Spare Parts Management, MRO, Maintenance, Repair, Overhaul

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

Introduction

The efficient delivery of spare parts during the entire life cycle of the product is a differentiating quality characteristic in competition that leads to improved customer loyalty and, therefore, strengthens the company in the market. Changing conditions, such as the increasing number of product variants with rapidly shortened innovation cycles and increased competition in many sectors, are new challenges in the spare parts business, which the companies have to meet. In the field of electronics the situation is more complicated. Electronic components are generally built for the entire life cycle of the primary product (e.g. cars or aircrafts). Nevertheless, a failure may occur during the life cycle of the component. This can be the result of internal influences, e.g. production failures, or external influences like an accident. [START_REF] Dombrowski | Klassifizierung kritischer Elektronikbauelemente unter Lebenszyklusaspekten[END_REF] In the field of aviation the competition and cost pressures in the MRO sector (Maintenance, Repair and Overhaul) increased strongly in recent decades. The main goal of a MRO service provider is to ensure on-time supply of spare parts. In addition, the spare parts inventory and thus the capital costs and process costs have to be minimized. Spare parts logistics and inventory planning therefore are a major challenge in globally networked structures.

Four main characteristics of the spare parts supply in the field of aviation are the global need for parts, the demand unpredictability, the traceability of parts for safety reasons and especially the high cost of not having a part. The latter situation is called AOG (Aircraft on Ground). [START_REF] Ghobbar | Sources of intermittent demand for aircraft spare parts within airline operations[END_REF] In order to avoid long-term ground time of an aircraft and an AOG situation, so-called Line Replaceable Units (LRU) are used in aircrafts when possible. A change of these LRUs is carried out quickly and the aircraft is therefore immediately ready for use again. Meanwhile, the exchanged part is repaired or overhauled and preserved for the next installation.

2

Inventory Pooling

Description of the processes of inventory pooling

In addition to the standard maintenance services, large maintenance organizations sometimes offer a component pooling service for aircraft operators. According to the individual user agreements the pool participants get access to the pooled aircraft components. If a defect of a component occurs and a pool contract is closed through the customer and the MRO service provider, a new component is provided by the pool provider. The pool provider can also be the MRO service provider at the same time. In this case the component will be replaced by a new or repaired pool component directly by the MRO service provider. Meanwhile, the removed part will be analyzed in a service center of the pool provider and depending on technical and economic aspects the decision is made whether the component will be repaired or replaced. [START_REF] Schmidt | Mehrwert schaffen durch Fokussierung auf das Servicegeschäft[END_REF], [START_REF] Hinsch | Industrielles Luftfahrtmanagement: Technik und Organisation luftfahrttechnischer Betriebe[END_REF] Fig. 1. Tasks of the MRO service provider [START_REF] Schmidt | Mehrwert schaffen durch Fokussierung auf das Servicegeschäft[END_REF] The task of the MRO service provider is to ensure the availability of the spare parts. The general process of the inventory pooling service is shown in Fig. 1. The process starts with the delivery of the defective part by the customer. The MRO ser- vice provider analyzes the part in the repair shop and decides whether it can be repaired in the own repair shop or it could be done by an external repair shop. The disposal of parts and the purchase of new parts are options as well. In the meantime the customer is supported with another part from the stock of the service provider. General tasks of the service provider are the determination of the repair float quantity of parts and the inventory management, the supply chain management, the management of modernizations and the tracking of structural condition of spare parts. [START_REF] Schmidt | Mehrwert schaffen durch Fokussierung auf das Servicegeschäft[END_REF], [START_REF] Hinsch | Industrielles Luftfahrtmanagement: Technik und Organisation luftfahrttechnischer Betriebe[END_REF] The participation in inventory pooling may lead to the following advantages. The first advantage is the utilization of experiences and synergies as well as economies of scale of large MRO service providers and thus reducing operating costs. In particular this applies to airlines with smaller fleets. Another advantage is an increased availability of components away from the home base and thereby higher aircraft operational capability. Finally inventory pooling may lead to predictable maintenance costs and usage-based pool contributions (e.g. based on flight hours or flight cycles). [START_REF] Hinsch | Industrielles Luftfahrtmanagement: Technik und Organisation luftfahrttechnischer Betriebe[END_REF]

Challenges within the framework of inventory pooling

A main challenge in the processes of MRO service providers is the calculation of the optimal stock level of the pool components. The stock level has an influence on the service level and therefore on the customer satisfaction and on the other hand on the profitability of the processes. The basis of an optimal inventory planning for the supply of spare parts is the quality of the input parameters used for the calculation. The optimal stock level is highly influenced by the demand of the customers. The demand is furthermore influenced by different impact factors, which can be divided in four categories. Impact factors related to the primary product, impact factors related to the spare part, impact factors related to the maintenance and impact factors related to the market situation and other surroundings (Fig. 2) [START_REF] Loukmidis | Lebenszyklusorientierte Planungsstrategien für den Ersatzteilbedarf[END_REF]. primary products, the life cycle of the spare parts is important. An increased life cycle of the spare parts leads to a lower demand. In this case as well, factors such as wear resistance, usage and operating conditions play through its own activities an important role. The MRO service provider has also an impact on the spare parts requirements. The MRO service provider can use different maintenance strategies which also could have an influence on the demand of spare parts: the damage-based, the time-based and the condition-based maintenance strategy. In the first case parts are replaced after a defect. In the second case parts are replaced according to specified time intervals, independently of their condition. In the third case parts are checked as part of inspections and are replaced if necessary. Finally the spare parts demand is also influenced by the market situation, e.g. legal regulations or the introduction of new technologies.

[5]

Demand control loops for a global MRO spare parts management

The main objective of this research project is the development of demand control loops for a global MRO spare parts management. For this purpose different sub objectives have to be achieved. The first sub objective is the calculation of the mean durability of different parts and the second sub objective is the analysis of the requirements for an organizational implementation. In the following part of this paper the sub objectives are described.

Calculation of the Mean Durability of different parts

The failure of LRU parts leading to unscheduled removals can be modeled as stochastic renewal process, where often the demand is rather sparse. Historically the distribution of this demand has been modeled as a Poisson process, where the interarrival times (e.g. flight times) between two removals are exponentially distributed. Additional complexity arises when incorporating removals resulting from hard-time requirements, condition-based maintenance and/or maturity characteristics of the material (non-homogenous stochastic process).

A basic approach described in literature to approximate the demand (D) in the aviation industry is in form of a correlation to the intensity of use. It is assumed that the demand (failure rate) is proportional either to the flight hours (FH), the flight cycles (FC) or the calendar time (CT) per part number depending on the type of material in question. The denominator represents the mean durability in terms of type of usage. The Mean Time Between Removal (MTBR), the Mean Cycles Between Removal (MCBU) and the Mean Duration Between Removal (MDBR) can be differentiated.

Due to the sparsity of the data, there are two major challenges in this approach that will be analyzed in this research work. Firstly, the mean durability is often calculated from historic data. However, the finite observation window cuts off a significant amount of data and therefore interferes with the data. Given this fact Zhao [START_REF] Zhao | Parametric interference from window censored renewal process data[END_REF] has shown, that the stochastic distribution of demand strongly influences the method of calculating the mean in [START_REF] Dombrowski | Klassifizierung kritischer Elektronikbauelemente unter Lebenszyklusaspekten[END_REF]. He shows that the calculations (1) are of good quality only for the Poisson distribution assumption.

Secondly, the influences of additional factors will be examined as part of the research work in this project. A distinction between measurable impact factors and categorical impact factors is useful. Measureable impact factors are e.g. the number of flight hours, the number of flight cycles and the calendar time between the appearances of maintenance events. Categorical impact factors are e.g. the aircraft type, the operator, regional influences of climatic conditions, seasonal influences or the usage profile of the customer (e.g. long-distance or short-distance) [START_REF] Bauer | Lebenszyklusorientierte Optimierung von Instandhaltungssystemen für hochwertige Investitionsgüter[END_REF]. The identified impact factors have to be checked by relevance and suitability. Furthermore the dependencies between the impact factors have to be analyzed.

The influence of the age of the primary product is exemplarily shown in Fig. 3. In an analysis of different ATA chapters (Air Transport Association), a standard numbering system, a dependency of the failure rate and the age in flying hours has been determined. [START_REF] Wagner | Estimation of daily unscheduled line maintenance events in civil aviation[END_REF] An analysis on the basis of the ATA chapter is probably no appropriate reference level as different material numbers are assigned to the ATA chapters. The appropriate reference level has therefore to be analyzed. Fig. 3. Influence of the age of an aircraft on the failure rate of components [START_REF] Wagner | Estimation of daily unscheduled line maintenance events in civil aviation[END_REF] For a forecast of the future demands the historical plan demands have to be constantly matched with the actual demand. By the permanent matching of the plan demand with the actual demand the control loops can be established. In the first step the identified relevant impact factors are set by the initially calculated value and should constantly be optimized. Approaches for forecasting methods in this context can exemplary be found in [START_REF] Luxhøj | Comparison of regression and neural network models for prediction of inspection profiles for aging aircraft[END_REF], [START_REF] Ghobbar | Evaluation of forecasting methods for intermittent parts demand in the field of aviation: a predictive model[END_REF], [START_REF] Regattieri | Managing lumpy demand for aircraft spare parts[END_REF], [START_REF] Bevilacqua | Failure rate prediction with artificial neural networks[END_REF], [START_REF] Louit | A practical procedure for the selection of timeto-failure models based on the assessment of trends in maintenance data[END_REF].

Of special importance is the measurement of the forecast quality. Table 1 shows an excerpt from the existing data base used in this project (data anonymized, values changed). Each line represents a change of a component. The table contains the changes of components and their material properties and their exchange proper- ties.The material properties are the material code, the material group and the material number. The material code describes a technical function in an aircraft. In a material group several material numbers are combined, which are completely interchangeable. The level of detail increases from the material code up to the material number. The previously described ATA chapter is in the detail level several steps above the material code. These three groups are chosen to illustrate the approach. Even more detailed material properties, for example the serial number, are available in practice. In addition to the material properties the exchange properties are shown in table 1. These are on one hand measureable impact factors such as the flight hours, the flight cycles and the calendar time and on the other hand the categorical impact factors such as the operator and aircraft type, which are listed as examples. For each component change this information is recorded.

Table 1. Example of the structure of the data base

Based on the existing component changes reference values are generated for the demand forecast. For this, the complete data set is separated into two random data sets, a training set and a test set. By these separate data sets demand forecasts can be generated by the training set and finally the quality of the forecast can be reviewed on the basis of the test set. In table 2 the division of the data is shown. In this example the material group is chosen as a reference. Based on the material group the MTBR, MCBR and MDBR are calculated in the training set. With the values determined in the training set, the resulting changes in the test set according to formula (1) are calculated. These values are compared to actual changes, which in this specific test set turn out to be 7. In comparison 7.3 changes are determined with the calculated MTBR based on the training set. Furthermore 6.3 changes are determined with the calculated MCBR and 5.2 changes are identified with the calculated MDBR. Thus, the best forecast value is calculated by the use of the MTBR. In other words, the flight hours have the most significant impact on the number of changes. These values have to be validated by repeated random separation of the data into a training and a test set. By combining different material and exchange properties other influencing factors can be analyzed. The combination of (material group x operator), (material group x aircraft type) or (material group x operator x aircraft type) are only a few possible combinations in this example.

Analysis of the requirements for an organizational implementation

The analysis of the requirements for an organizational implementation is another topic in the research project. Different departments of an organization have varying requirements regarding the use of the calculated demands. E.g. a repair shop needs the demand to schedule the work orders or the technology management uses the information in the context of the reliability analysis. To determine the Repair Float Quantity (RFQ) this information is used in the materials planning. It should be examined whether it is possible to develop an universal approach which generates the corresponding varying values for the different departments on the basis of a consistent data selection.

Summary

The efficient delivery of spare parts during the entire life cycle of the product is a differentiating quality characteristic in competition that leads to improved customer loyalty and, therefore, strengthens the company in the market. In the field of aviation the competition and cost pressures in the MRO sector increased strongly in recent decades. The main goal of a MRO service provider is to ensure on-time supply of spare parts and a main challenge in the processes of MRO service providers is the calculation of the optimal stock level of the pool components which is influenced by different impact The main objective of this research project is the development of demand control loops for a global MRO spare parts management. Due to the sparsity of the data, there are two major challenges in this approach that will be analyzed in this research work. Firstly, the calculation of the mean durability of components and the integration of the influences of additional factors like regional influences of climatic conditions. Finally the requirements for an organizational implementation are another topic in this research project.

Fig. 2 .

 2 Fig. 2. Impact factors on spare parts demand [5]Primary product-related factors include the age structure of the primary products, the intensity of use and the operating conditions. In addition to the life cycle of the

ATA 23 ATA 27 ATA 21 ATA 29 ATA 36 ATA 28 ATA 24 ATA 25 ATA 33 ATA 32 ATA 71 ATA 51 ATA 38 ATA 49 10000 15000 20000 25000 30000 35000 Age [Total FH] Failure Rate 10000 15000 20000 25000 30000 35000 Age [Total FH] Failure Rate

	ATA Chapter	System
	21	Air Conditioning
	23	Communications
	24	Electrical Power
	25	Equipment & Furnishing
	27	Flight Controls
	28	Fuel
	29	Hydraulic Power
	32	Landing Gear
	33	Lights
	36	Pneumatic
	38	Water & Waste
	49	Auxilliary Power Unit
	"51" -51,53,54,55,57	"Structures"
	"71" -71 to 80	"Engines"

Table 2 .

 2 Calculation of the mean durability in terms of type of usage as a reference value

number material code material group material number operator aircraft type … flight hours flight cycles calendar time

	1	material code 1 material group 1	material number 1 operator 1	A330	…	13245	2835	39120
	2	material code 1 material group 1	material number 1 operator 2	A330	…	9682	4494	29760
	3	material code 1 material group 1	material number 1 operator 2	A340	…	9007	3452	19608
	4	material code 1 material group 1	material number 2 operator 3	747	…	14864	1183	16533
	5	material code 1 material group 2	material number 3 operator 1	777	…	1617	1306	5808
	6	material code 1 material group 2	material number 3 operator 2	A320	…	7420	6387	26808
	7	material code 1 material group 2	material number 4 operator 1	747	…	8979	7362	32880
	8	material code 1 material group 2	material number 4 operator 3	A320	…	4950	4020	27600
	9	material code 1 material group 2	material number 4 operator 2	A330	…	10870	9000	38400
	10	material code 1 material group 2	material number 4 operator 2	A330	…	9703	6973	29488
	11	material code 1 material group 3	material number 5 operator 1	747	…	8979	7362	32880
	12	material code 1 material group 3	material number 5 operator 3	A320	…	4950	4020	82800
	13	material code 1 material group 3	material number 5 operator 3	747	…	8501	7103	29976
	14	material code 1 material group 3	material number 6 operator 2	747	…	5194	4471	18766
	…	…	…	…	…	…	…	…	…	…

number material code material group flight hours flight cycles calendar time set by chance MTBR MCBR MDBR

							calculated
	1 2	material code 1 material group 1 material code 1 material group 1	13245 9682	2835 4494	39120 29760	training training	11464	3665	34440
	5	material code 1 material group 2	1617	1306	5808	training
	7	material code 1 material group 2	8979	7362	32880	training	7155	5889	25696
	9	material code 1 material group 2	10870	9000	38400	training
	12 13	material code 1 material group 3 material code 1 material group 3	4950 8501	4020 7103	82800 29976	training training	6726	5562	56388
							D MTBR D MCBR D MDBR
	3	material code 1 material group 1	9007	3452	19608	test	0,8	0,9	0,6
	4	material code 1 material group 1	14864	1183	16533	test	1,3	0,3	0,5
	6	material code 1 material group 2	7420	6387	26808	test	1,0	1,1	1,0
	8	material code 1 material group 2	4950	4020	27600	test	0,7	0,7	1,1
	10	material code 1 material group 2	9703	6973	29488	test	1,4	1,2	1,1
	11	material code 1 material group 3	8979	7362	32880	test	1,3	1,3	0,6
	14	material code 1 material group 3	5194	4471	18766	test	0,8	0,8	0,3
							∑ 7,3	6,3	5,2

Acknowledgements

The results presented in this paper were developed in the research project "Demand control loops for a global component spare parts management". This research project is part of the regional aviation research program LUFO II-2 funded by the German Federal State of Hamburg (Behörde für Wirtschaft, Verkehr und Innovation).


Jose Angel Lakunza¹
email: ¹jalakunza@ikerlan.es²jcastiazaran@ikerlan.es³melejoste@ikerlan.es

Juan Carlos Astiazaran²

Maria Elejoste³

Service model for the service configuration

Keywords: Service configuration, Service model, Service personalization

Service is a concept difficult to define. It has been extensively used in different contexts. According with literature a service can be seeing: as an activity or as an output of a process.

By service customization we mean the definition and adaptation of a service according to the customer' requirements, when this customization process is carried out in a systematic way.

A company can respond to user needs diversity offering services than can be customized easily, and/or increasing the service variety offered to the market. The increasing in the service offer variety raises also the variety and complexity in the company transactions that involves cost increments for these transactions. Therefore, the challenge will be to extend the range of services offered to the market maintaining the efficiency , that is similar to the Mass Customization concept

Introduction

The importance of service industry in the economy is growing ( [START_REF] Fitzsimmons | Service Management -Operations, Strategy, and Information Technology, Fourth Edition, International Edition[END_REF]). Customers are demanding services that meet their needs. The differences between goods and services are fuzzy as it has been argued that products always contain a service dimension . Human needs are satisfied not only with physical goods but also services. Different authors argue that research on service customization is sparse and needs to be developed in depth ( [START_REF] Borenstein | Mass Customization: Literature review and research directions[END_REF]). In the other hand, due to the service nature, it should be adapted to the customer needs.

Our research goal has been focused on the service customization. The main research questions we try to answer are:

 What are the different configuration moments in the service life cycle?  How can we define a generic "Service Family" model?

First we made a literature review on the service concept. Next, we developed a service classification. After that, we focused on the definition of a generic model for the services that might be configured taking into account the customer needs. And finally, we analyzed the applicability of configuration along the service life.

Literature background

Service is a difficult term to define, because it is extensively used in different contexts. This difficulty has been widely mentioned in the literature by different authors ( [START_REF] Fitzsimmons | Service Management -Operations, Strategy, and Information Technology, Fourth Edition, International Edition[END_REF], [START_REF] Johns | What is this thing called service[END_REF]), and using different definitions for the service concept ( [START_REF] Kotler | Marketing management: analysis, planning implementation and control[END_REF], [START_REF] Fitzsimmons | Service Management -Operations, Strategy, and Information Technology, Fourth Edition, International Edition[END_REF]).

According to [START_REF] Jiao | Towards high value-added products and services: mass customization and beyond[END_REF] two main streams can be identified in the service definition literature: from the service provider's view as an activity (service) and from the customer view as an output of a system (service result).

Reference [START_REF] Johns | What is this thing called service[END_REF] mentions these different approaches. The provider sees the service offering in terms of process, related to service operation. On the other hand, the customer views it as a service outcomes. As an output a service represents what a customer receives. As an activity it represents how a customer receives the service.

According with [START_REF] Heiskala | Modeling configurable services. Information and Comunication Technology Enabled Commerce (ICTEC)[END_REF], configurable services are services that can be customized to individual specifications by means of a set of options to meet a predetermined range of customers needs. Some examples can be: insurance agreements; machinery maintenance contracts; mobile subscriptions; traveling trips; etc.

Increasing the service offering in order to allow the service customization, increases the complexity of the company's operations. The challenge is to broaden the range of the services offered without risking performance [START_REF] Martines-Tur | Linking service structural complexity to customer satisfaction -The moderating role of type ownership[END_REF] that seems similar to the Mass Customization concept as was established in [START_REF] Pine | Mass Customization: The New Frontier in Business Competition[END_REF].

Taking into account the active role of the customer, a service model has to be customer oriented . It is easily realized that a natural way of customizing a service is along the course of customer service experience.

Modularization as a way to customize services seems not to be a wide research subject. Nevertheless, using and matching modules in response to customer needs has been proposed in [START_REF] Meyer | PERSPECTIVE: Creating a platform-based approach for developing new services[END_REF] and [START_REF] Peters | IT and mass customization of services: the challenge of inplementation[END_REF]. Reference [START_REF] Goldstein | The service concept: the missing link in service design research[END_REF] discusses the pros and cons of breaking down a service into its components. For that the designer should identify the different service elements and check them against the customer' needs. That means that modularity is an area for future research in service development [START_REF] Ma | A generic model and design representation technique of service products[END_REF]. Modularization seems as one way to achieve service customization.

Literature describing the support of existing configurators in the service configurations is very limited. The ILOG JConfigurator [START_REF] Junker | Preference Programming: Advanced Problem Solving for Configuration[END_REF] and the CAWICOMS Workbench [START_REF] Ardissono | A Framework for the Development of Personalized, Distributed Web-Based Configuration Systems[END_REF] are examples of product configurators that support the configuration of both goods and services.

Process Map

The figure 1 represents the process map that can be executed along the service life cycle. As we can see, we have defined three different process levels depending in the time horizon for the process:

 Process level with large time horizon. The input for the process is the market requirements and the output is also the offer to the market. At this level we can distinguish the process for the service strategy definition and the process for the service framework definition for the market (for instance the definition of the city bus lines and timetables).

 Process level with a medium time horizon. In this case the input for the process is the customer needs and output for the process is the service level agreement (SLA) for the customer. At this level we can see the process for the development of the SLA bid and the process for the development of the service platform. Both processes are framed by the framework defined in the previous level (for instance the definition of the car insurance conditions for a customer).

Fig. 1. Process Map

 Process level with a short time horizon. In this case the input is an event for the customer and the output is the executed service for the customer. At this level we can see the following activities in the process for the delivery of the service: definition of the facts for the service and the activities needed to execute the service (WHAT & HOW); definition of the resources to execute the service (WHO); and the execution of the service itself. These activities are framed by the framework (contract) defined in the previous level (for instance the response for a car accident from the insurance company).

Service Configuration

In order to answer the possed question what are the different configuration moments in the service life cycle?, we have identified two different service contexts from the point of view of the service configuration: services without SLA definition and services that need SLA definition.

Configuration of services without SLA definition

When the company doesn't define a service level agreement (SLA) for the customer, the service framework is the same for any customer that wants the service. That means the company has defined a general framework for the service offer. In this case, firstly the company defines a general framework for the service, and after that, the company sells an instance of service to a customer, according with the specifications required for the customer.

The configuration of the service is carried out during the sale and specification definition of the service from the required needs of the customer. This service configura- tion takes into account the service offer defined previously by the company. In fact in this moment the process needed to answer to the customer requirement is configured (HOW) and also the type of resources needed to execute the process.

In this scenario of services, there is only a configuration possibility for the service: at the moment of specification definition and sale of the service. An example of this service could be the mail service. In this case the customer defines the specifications for the mail at the same moment that pays for the service.

Configuration of services with SLA definition

In the field of services, there are a lot of examples in which is necessary to define previously a service level agreement (SLA) for the customer, establishing the characteristics of the service to be provided in the future to the customer. Some examples are insurance services, maintenance services, etc. In these cases of services we can distinguish three different moments along the service life cycle:

1. Service offer definition for the market. 2. SLA definition and sale for the customer 3. Customer event turn up and service execution for the customer How does it works in the case of car insurance?. In a first moment, the company defines the overall service offer for the insurance of a car [START_REF] Ardissono | A Framework for the Development of Personalized, Distributed Web-Based Configuration Systems[END_REF]. Next, the customer in collaboration with the company defines a specific SLA for the insurance of the customer's car, mentioning all the options covered by the company (2). Once the SLA has been established, as response to any kind of event suffered by the customer (an accident, a car breakdown, etc.), the company provides the customer with the adequate service [START_REF] Fitzsimmons | Service Management -Operations, Strategy, and Information Technology, Fourth Edition, International Edition[END_REF]. In this scenario, two different service configuration moments can be identified along the service life cycle:  A first moment is the configuration of the SLA itself, taking into account the customer requirement for the SLA and the overall service offer defined for the company. This kind of configuration is quite similar to the used for the configuration of goods. Defines WHAT is going to be provided by the company. For instance when a customer establish with the insurance company the SLA for the car insurance  In a second moment the company, as a response to a customer event, configures the service process to be execute (HOW), and the kind of resources to be used, taking into account the framework posed by the SLA. For instance when the customer suffers and accident with his car and the insurance company provides the adequate service

Service execution planning

Apart from the configuration of the service contract (WHAT the contract covers) and when an event happens, HOW is going to be delivered the service (the configuration of the process for the service), taking into account the event characteristics and the service contract defined for the customer and the defined type of resources to be used for the execution of the process. Alter this definition and in order to execute the defined service in response to an event, we must to define exactly which are the resources to be used in the service process (WHO) and when this resources are going to be used (the scheduling). That means two different activities:

 To find resources in the supplier's network: from the information generated as result of the service configuration (HOW the service will be executed and the type of resources needed for the execution of the service) and taking into account the resources available in the network of suppliers, its finds the appropriate resources for the service execution.  To allocate resources for the service process: once identified the resources, these will be allocated to the corresponding service process activity and the scheduling will be defined. As result of this we will have the customized service process with the allocated resources plus the execution scheduling for the service.

Service Model

According with [START_REF] Goldstein | The service concept: the missing link in service design research[END_REF], the service should describe what are the customer needs, how this is going to be achieved, and with what kind of resources. The breakdown of a service into its components, allows the designer to check them against the customers' needs. This approach is necessary in order to customize services in a mass customization schema.

Reference [START_REF] Meyer | PERSPECTIVE: Creating a platform-based approach for developing new services[END_REF] is using product platform concepts that have been used for physical products. Applying modularization techniques to the service is seen as one way to achieve service customization. As in the case of goods, modules can be combined in response to specific customer needs. Usually these service modules are seen as work tasks, parts of processes or groups of activities.

Fig. 2. Conceptual model of services

The figure 2 shows a high level conceptualization of service proposed in [START_REF] Heiskala | A conceptual model for modeling configurable services from a customer perspective[END_REF] as the result of the service literature analysis.

The aim of our work has been to apply the ideas of Product Family Architecture (PFA) developed in [START_REF] Jiao | Design for Mass Customization by Developing Product Family Architecture[END_REF] in the field of services, in order to define a service architecture that can be used by a service configurator. Our approach for the definition of this service architecture is based in the analysis of the different moments identified in the service life:  Definition of the service offer to be provided by the company.  Definition of the processes to be carried out inside this service offer  Sale of a service contract  Specification of the service to be provided to the customer as response to an event  Planning and scheduling of the service As the result of our work we propose a service model to answer the question how can we define a generic service model that represents a "Service Family"?.

Our proposal for the conceptual service model derives from that proposed in [START_REF] Heiskala | A conceptual model for modeling configurable services from a customer perspective[END_REF].

Fig. 3. Conceptual model proposed

In this model each one of the elements that appear in the figure 3 is defined as:

 Service Offering: framework offered by the company to the market (service family).  SLA (Service Level Agreement): represents the negotiated agreement between the customer and the service provider.  Service: service element that can be offered by the company to a customer. This service element will be the results of a process.  Service Process: Services are produced by processes. It represents the set of activities to be carried out to give a service to a customer.  Resource: element needed to execute the process associated to a service. Resources can be material or human.

The service offering framework for a company represents the company offer to the market that can be customized to the customer needs. This customization of the service offered to a customer will be embodied in as a Service Level Agreement. It records a common understanding about services, priorities, responsibilities, guarantees, and warranties. This service offering and its instances (SLA) is made up of elementary services. Each elementary service will be characterized by several parameters. Every parameter will be constrained to a domain of values. In some cases and as a decision of the company, a parameter will have a fixed value that cannot be changed for the customer.

Each elementary service belongs or not to the service offering depending on a condition or rule.

Moreover, in the proposed model we can establish dependence relationships of different types between the services that take part of the service offering.

How the service can be seen depends on the point of view of the user. The point of view of the customer and the point of view of the company are not the same. Also from the company point of view there are differences between design and production.

From the customer point of view, the service will be defined by its different functions and options and by the list of parameters and value domain for each one.

On the other hand, form the company point of view the service will be defined by the processes, activities and resources needed to deliver the service.

According to this, each elementary service has been broken down into service modules (problems to be solved) and each one will be solved following different variants (service variant).

Each one of the defined service variants will have a process variant to be executed and also needs a resource to deliver the service variant. The set of process variants makes the whole process for the service.

Furthermore, each process variant will be made up of tasks that are broken down into activities.

Taking into account this model, the customization of a service entails the selection of the different service modules needed for the service and for each one of the modules, the selection of the service variant to be delivered to the customer. The sum of these selected variants will put together the service to be delivered.

Conclusion

As result of our research goal, we have answered the main research questions posed:

 how can we define a generic "Service Family" model?;

 what are the different configuration moments in the service life cycle?.

Answering the first question we have defined a service architecture that allows the model of services that can be customized to the customer needs and that takes into account the two aspects posed by the literature: service as an outcome and service as a process.

To answer the second question we have identified the different moments for the service configuration in the two different scenarios of the service: service without contract and service with contract.

These developments has been tested, during the 2012, in lab cases and later on will be tested in real cases of services.

As future work we are going to go deeply into the following:

 To adapt the configurator tool developed for the configuration of goods (physical products) to the configuration of service contracts.  To develop new configurator tool for the configuration of the service processes to be executed by the service provider company, as answer to the event.

As result of this work, we have been able to apply this approach to a company leader in the Spanish lift sector, that provides maintenance services. In this scenario the maintenance service is a complex task for the company: the process depends on the lift; it changes with the year month and each maintenance worker must to carried out the maintenance of a big amount of lifts.

We have modeled the maintenance service and using a configurator tool, we have provided the maintenance worker with a tool that automatically creates the maintenance process to be carried out for each specific lift. That helps the worker in the execution of the maintenance service.

  service framework (market) Definition of the service contract (customer) event Define the service WHAT HOW Delivery of the Service (customer)


Ourania Markaki
email: omarkaki@epu.ntua.gr

Panagiotis Kokkinakos
email: pkokkinakos@epu.ntua.gr

Dimitrios Panopoulos

Sotirios Koussouris

Dimitrios Askounis
email: askous@epu.ntua.gr

Benefits and Risks in Dynamic Manufacturing Networks

Keywords: Dynamic Manufacturing Network, DMN, Benefits, Risks

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

Introduction

Survival and growth of enterprises in the intense competitive and innovation-driven environment of the 21 st century are beyond any doubt determined by their ability to continuously improve their performance, skills and the complete set of operations, both internally and externally. Today's manufacturing landscape is characterized by dramatic and often unanticipated changes in demand, rapid change and increased use of technology, short product lifecycles, time compression, complexity and fierce global competition [START_REF] Shi | International Manufacturing Networks -to develop global competitive capabilities[END_REF]. In this competitive environment, the manufacturing enterprise must develop and implement new and innovative strategies in order to succeed.

In the light of remaining flexible and competitive, the manufacturing enterprise witnessed during the last decades a progression of initiatives targeting the improvement of its operation. In the 1980s, many companies focused on Total Quality Management (TQM) [START_REF] Powell | Total Quality Management as Competitive Advantage: A Review and Empirical Study[END_REF]. Later, they implemented factory automation in various "islands" on the factory floor and afterwards they focused on how to integrate these "islands of automation" [START_REF] Davenport | Putting the Enterprise into the Enterprise System[END_REF]. Flexibility became a key component, while agility took the former concept one step further by embodying as well the ability to respond to unanticipated change. The next step of improvement was to extend beyond the factory, to suppliers.

Supply chain management has had a similar progression over the years in the interest of reducing costs, improving quality and shortening delivery cycles [START_REF]Evolution of Supply Chain Management: Symbiosis of Adaptive Value Networks and ICT[END_REF]. In the 1980s, improvements were focused on solving specific quality problems, and shifting inventory risk from the large company to the supplier base was the primary strategy applied during this period, while the early 1990s were characterized by crossfunctional teams of primes and suppliers working to improve process capability and implement compatible systems interfaces with a limited contribution of suppliers' engineering knowledge to new product development.

Nowadays, competition and other pressing market situations, such as fluctuating demand or market saturation have greatly intensified to the point where manufacturing enterprises and supply chain initiatives must yield greater improvements than ever before. As indicated by the outcomes of recent business reports [START_REF] Payne | Supply Chain Functional Excellence Key Initiative Overview[END_REF], large enterprises have yet exhausted most of the efficiencies available within their existing supply chain, so that further gains require structural changes that streamline the flow of supply and eliminate product and portfolio complexity that do not provide or protect value. These changes call for a dynamic and holistic approach that takes into consideration all aspects of the entire supply chain from a systems view [START_REF] Shi | A Roadmap of Manufacturing System Evolution-From Product Competitive Advantage towards Collaborative Value Creation[END_REF].

An increasingly popular approach for enterprises striving to cope with the challenges of today's rapid changing and demanding environment has been the concept of "upgrading" their supply chains to Dynamic Manufacturing Networks (DMNs). The DMN concept evolves and particularizes the notion of virtual organizations [START_REF] Katzy | The Virtual Enterprise[END_REF] in the manufacturing sector, as it is a dynamic alliance of manufacturing entities collaborating for gaining mutual benefits [START_REF]IMAGINE Project: Innovative End-to-end Management of Dynamic Manufacturing Networks[END_REF][START_REF] Viswanadham | Partner Selection and Synchronized Planning in Dynamic Manufacturing Networks[END_REF][START_REF] Papakostas | On the Configuration and Planning of Dynamic Manufacturing Networks[END_REF]. Compared to a virtual organization however, a DMN is a real formation, though with loose ends and a quite flexible structure, which includes geographically dispersed OEMs and a pool of potential suppliers of various tiers. For an enterprise, participating in (or forming) a DMN can be considered as a systematic way for cultivating extended co-operation with other members of its supply chain, and calls for modifications in its modus operandi, while it necessitates the network's dynamic management [START_REF]Accenture: Developing Dynamic and Efficient Operations for Profitable Growth -Research Findings from North American Manufacturers[END_REF][START_REF] Williams | Dynamic Order Allocation for Make-to-order Manufacturing Networks: An Industrial Case Study of Optimization under Uncertainty[END_REF][13], so as to enable real-time communication and active collaboration among the different network nodes.

This new modus operandi offers the enterprise a number of important benefits in the directions of enhancing manufacturing capacity and operational procedures, enlarging market share and improving viability and profits, but is also associated with a series of risks -the most important being related with information security and trustwhich have to be identified and mitigated. In this context, this paper aims to present benefits and risks that accrue from the formation of DMNs under the prism of the end-to-end DMN management methodology, developed within the context of the IMAGINE FP7 project. The remaining of this paper is thus structured as follows: Section 2 introduces the concept of DMNs in IMAGINE, along with the key drivers for their establishment and outlines the respective DMN management methodology. Section 3 exposes the anticipated DMN benefits identified, while Section 4 provides insight on the associated risks and the respective mitigation strategies. Finally, Section 5 summarizes the ideas presented and concludes the work.

DMN Concept, Business Incentives and IMAGINE Methodology

The main idea behind DMNs is to achieve market differentiation through focusing on the core competencies and obtaining all other activities from outside, i.e. from other DMN members. The prospects of improving competitiveness, productivity and quality, enhancing efficiency and responsiveness to market demands, and exploring possibilities to lower overheads and costs are considered [START_REF] Cunha | Agile Virtual Enterprises: Implementation and Management Support[END_REF][START_REF] Cueni | Virtual Organizations -the next Economic Revolution? Swiss Federal Institute of Technology[END_REF] as the most important driving forces for an enterprise to overcome its traditional operation and adopt a collaborative way of thinking and dealing with suppliers and partners, and are at the same time the benefits anticipated regardless of the scheme or scope of the DMN.

The term Dynamic Manufacturing Network denotes a permanent or temporal coalition, comprising production systems of geographically dispersed SMEs and/or OEMs that collaborate in a shared value-chain to conduct joint manufacturing [START_REF]IMAGINE Project: Innovative End-to-end Management of Dynamic Manufacturing Networks[END_REF]. Each member of the network produces one or more product components that can be assembled into final service-enhanced products under the control of a joint production schedule. Production schedules are monitored collectively to accomplish a shared manufacturing goal, while products are composed, (re-) configured and transformed on demand through dynamic and usually ad-hoc inter-organisational collaborations that can cope with evolving requirements and emergent behaviour.

From an operational point of view, this complex context of collaborations and interactions among enterprises and their suppliers, partners and customers is coordinated by a sophisticated IT platform and the respective DMN end-to-end management methodology [START_REF]IMAGINE Project: Innovative End-to-end Management of Dynamic Manufacturing Networks[END_REF]. The former revolves around the DMN lifecycle -comprising the DMN configuration, design, and monitoring and management phases -and is based on a Blueprint Model which gathers, consolidates and integrates manufacturing data and processes in order to develop actionable insights that help manage enterprise resources, product life cycles, supply chains, partner relationships, operational planning, manufacturing process execution, compliance regulations and safety issues for the DMN lifecycle, and thereby maximise the performance of participating enterprises. This model is a declarative meta-model that aggregates and modularises production, manufacturing operations and logistics information, distilled from Manufacturing Integration Standards, such as the ISA-88 and ISA-95 and the Open Applications Group Integration Specification (OAGIS), reference models such as the Supply Chain Operations Model (SCOR), and the Business-to-Manufacturing-Markup-Language (B2MML), and consists of four interrelated blueprints supporting information sharing, collaboration, enterprise-wide visibility and interoperability as follows:

• the Partner Blueprint, which provides business and technical information to facilitate partners' selection by a specific contractor, • the Product Blueprint, containing all components necessary, such as machines, tools, personnel skills, materials, other equipment, for producing a product, as well as other entities necessary for the manufacturing work, • the Quality Assurance Blueprint, used to capture metrics for operations analytics and associate these with the end-to-end manufacturing processes, and

• the end-to-end Process Blueprint, which ties together the many discrete processes associated with all aspects of product development while providing the ability to adapt to changing conditions and environments. The idea of the DMN, as defined in the IMAGINE project along with the concept and applicability of the DMN management methodology and Blueprint Model are the keys for materialising a series of anticipated DMN benefits, which are presented in Section 3, and mitigating the associated risks, exposed in Section 4 of this paper.

Expected DMN Benefits

Every DMN, regardless of its size and formation, has the same closely defined mission which is to enhance the entire value creation process of products and services and consequently to create extra profit and other benefits for all DMN members. In the context of the IMAGINE methodology, the expected DMN benefits can be classified in three categories, namely Time savings, Cost reduction and Enhancement of operations: Time savings are mainly associated with the time-to-market reduction, the optimized design of end products and individual components, collaborative product development, the network-optimized production planning and scheduling, the fast selection of suppliers for each project/product and the corresponding rapid network set-up, the instant reconfiguration of the suppliers' network, the automated communication and data exchange with suppliers/clients and partners, as well as the increased visibility and access speed to information and network/manufacturing data. On the other hand, cost savings may include the cost-optimized selection of suppliers, the reduction of inventory costs, the cost-optimized management of resources, as well as the decrease of marketing expenses. The last category of benefits, concerned with operations' enhancement includes these kinds of gains that are associated with improvements in the way that each individual enterprise and consequently the whole network operate, and can be indirectly linked either to time/cost reductions or to profitability rise for the whole network. This type of benefits in fact enumerates: a clear focus on core competences, product/services co-creation, cost/risk sharing with collaborating partners, real-time monitoring of product development and manufacturing operations, reduction of design and production flaws, optimal selection of suppliers and collaborators, improved quality throughout the complete product lifecycle, know-how exchange, access to new customers/markets, and diverse enterprise IT systems' integration for better, holistic and more efficient production. Despite the above-mentioned long list of benefits, the decision of joining a DMN is still an important one for any enterprise, since it is related to many changes not only to the way the enterprise collaborates with the external environment, but also to the way that almost all the internal processes are being performed. This is why such a decision should always be based on real estimations of the expected benefits, taking into consideration good practices and success results achieved in previous collaboration cases, as specified through an extensive literature review:

As far as cost savings are concerned, research [START_REF] Chalmeta | Performance Measurement Systems for Virtual Enterprise Integration[END_REF][START_REF] Thompson | Achieve Supply Chain Agility through Virtual Enterprise Networks[END_REF] shows that in a typical manufacturing sector like automotive, amazingly only 30% of the cost of the final product has to do with "value activities". The other 70% are the costs and overheads of running a major manufacturer in its current form. The scope for cost savings through collaborating in a DMN is therefore huge.

Previous experience on networked manufacturing as presented in several studies proves moreover that if manufacturing networks run properly they can generate up to 30% additional profit per member after the initial settling in period [START_REF] Thompson | Achieve Supply Chain Agility through Virtual Enterprise Networks[END_REF][START_REF] Landeg | Implementation of Airbus Concurrent Engineering[END_REF]. As seen in Table 1, this has to do with an estimated reduction of up to 25% concerning total manufacturing and operational costs, as well as a maximum of 20% reduction concerning costs, incurred due to poor quality issues. Additionally, increased profitability is also linked with the expected rise of productivity in a well-established DMN that can reach up to 30%, according to cases examined in past studies [START_REF] Chalmeta | Performance Measurement Systems for Virtual Enterprise Integration[END_REF]. Another important fact is that not only profits grow higher but also at the same time the financial exposure of partners may be decreased by 25%. In fact, the overall reduction of required investments by the DMN members, whether the former regard IT infrastructure, knowledge or machinery, is estimated at a maximum of 20% [START_REF] Thompson | A kick-start plan for setting up a Virtual Enterprise Network in 6 weeks[END_REF].

Furthermore, very good results are expected, by joining a DMN, on the product development operations. Previous applications of collaborative product development processes like those in DMNs have proved that a reduction of lead-time and cost up to 30% and 50% respectively are realistic goals which can be achieved [START_REF] Karlsson | Information driven Collaborative Engineering: Enabling Functional Product Innovation[END_REF].

Finally, a carefully established and well-managed DMN can lead to a very efficient operation of all of its members. This is proved not only by the financial results, previously presented, but also by the improvement on the values of several metrics related to the operation of each individual enterprise and of the supply chain as a whole. According to the literature on virtual enterprises and manufacturing networks the following achievements can be expected: reduction of time required for co-operation contractual formalization up to 50% [START_REF] Santoro | Evaluation of Benefits and Advantages of the Virtual Enterprise approach adoption for Actual Business Cases[END_REF], reduction of time-to-market up to 25% [START_REF] Santoro | Evaluation of Benefits and Advantages of the Virtual Enterprise approach adoption for Actual Business Cases[END_REF], [START_REF] Renton | Virtual Manufacturing Technology Implementation at Boeing[END_REF], reduction of lead time up to 20% [START_REF] Santoro | Evaluation of Benefits and Advantages of the Virtual Enterprise approach adoption for Actual Business Cases[END_REF], [START_REF] Kingsbury | Use of Virtual Prototyping in Design and Manufacturing[END_REF], improved efficiency of co-operation processes (manufacturing network design, re-configuration and re-engineering) up to 30% [START_REF] Santoro | Evaluation of Benefits and Advantages of the Virtual Enterprise approach adoption for Actual Business Cases[END_REF], decrease of product cycle times up to 50% [START_REF] Landeg | Implementation of Airbus Concurrent Engineering[END_REF], of life cycle costs up to 30% [START_REF] Renton | Virtual Manufacturing Technology Implementation at Boeing[END_REF], and of maintenance costs up to 30% [START_REF] Landeg | Implementation of Airbus Concurrent Engineering[END_REF].

It has to be noted that the figures presented in this paragraph are mostly based on specific examples/cases analyzed in the literature and cannot be considered as reference values for all cases. However, they provide a direction with regard to the objectives that should be set and expected when establishing a Dynamic Manufacturing Network and a good starting point for quantifying the above-mentioned anticipated DMN benefits, which are to be assessed along the course of the IMAGINE project.

Potential DMN Risks

Inarguably, the introduction of any new innovation does not come without any risk for possible adopters. According to Hallikas et al. [START_REF] Hallikas | Risk Management Processes in Supplier Networks[END_REF], functions that generate the possibility of beneficial effects or profit often include risks. The same applies for the idea of walking away from typical, long operating models of traditional supply chains and moving to new models of virtual factories and the DMN concept in particular.

The risks that may be encountered in a DMN are in fact associated with: Information security and trust. Information leaks due to unwanted and malicious attacks, and disclosure of corporate practices and other critical or strategic importance data can prove to be very harmful for an enterprise, and can be mitigated by applying efficient security and efficient mechanisms, that impede unauthorized access and define different access rights for different partners, as well by signing contractual agreements with special clauses on information confidentiality.

Poor configuration, design and management of the network. This makes up a risk which may come up as a result of the provision of non-valid, deficient or even outdated information for carrying out partner searches and negotiations in the first place, as well as for coordinating the complex grid of multiple and diverse actors, functions, processes and flows of information involved thereafter. This risk may prove to be fatal even for the network's survival and can be addressed by granting dynamic, and therefore accurate information on the actual manufacturing and delivery capacity of each DMN member, as well as global visibility across the whole network so as to constantly fine tune its performance.

DMN dissolution when key partner drops out of the network. Withdrawal of a key supplier/manufacturer could jeopardize the success of a project, resulting even in the network's dissolution. Thus, it should be foreseen as a risk in the contracts signed upon the establishment of the DMN, so as to legally bind DMN members not to be able to waive their DMN responsibilities and obligations at will.

Transition issues related to resistance to change, modifications to procedures and IT systems. The transition from an isolated to a collaborative manufacturing model is not easy and may be accompanied by modifications in the procedures followed and the systems used as well as the employees' resistance. This risk is addressed by intro-ducing a set of adapters that interconnect the IT systems of all DMN members to the DMN platform, and facilitating the unhampered exchange of information, enabling thereby smooth transition for both processes and people.

Competitive threats after a partner's withdrawal or the dissolution of the DMN. The risk of important R&D knowledge misuse for gaining competitive advantage over former collaborators, in case a member exits the DMN or the former is dissolved, can be mitigated by signing legal agreements that explicitly define the use and exploitation of intellectual property and knowledge generated during the operation of the DMN.

Loss of DMN/ partners' reputation. A partner's inability to deliver as planned may affect the operation and damage the reputation of the overall DMN structure. Such a risk is to be mitigated pro-actively by allowing selection of the most appropriate partners as well as early detection of any deviation in the production plan, and triggering the network's reconfiguration with zero or minimal damage to the DMN reputation.

Concluding Remarks

The identification and analysis of the associated benefits and risks is the first step for identifying key factors that could be utilized in order to attract organizations and enterprises into embracing the vision of DMNs. In this context, and as a concluding remark, attention should be drawn to the fact that in most cases the drivers for setting up or for participating in a DMN are practically a mixture of several of the benefits identified, as well as to the observation that both the benefits and risks specified may have a different impact on DMN enterprises with different goals and expectations. This is something that should be taken into account when forming the DMN and setting the rules and norms for managing and operating it efficiently.

Table 1 .

 1 Expected Benefits following a DMN formation

	Metric	Improvement up to
	Total Profitability	⇑ 30%
	Total operational & manufacturing cost	⇓ 25%
	Cost due to quality issues	⇓ 20%
	Total productivity	⇑ 30%
	Financial exposure of partners	⇓ 25%

Acknowledgements

The research leading to these results has been supported by the EC 7 th Framework Programme under the project "IMAGINE -Innovative end-to-end management of Dynamic Manufacturing Networks" Grant Agreement Νο. 285132, (http://www.imagine-futurefactory.eu).