Hussein Khlifi
email: hussein.khlifi@ensam.eu

Abhro Choudhury

Siddharth Sharma

Frédéric Segonds

Nicolas Maranzana

Damien Chasset

Vincent Frerebeau

Towards cloud in a PLM context: A proposal of Cloud Based Design and Manufacturing methodology

Keywords: Cloud, Collaborative Design, PLM, Additive Manufacturing, Manufacturing

Product Lifecycle Management (PLM) integrates all the phases a product goes through from inception to its disposal but generally, the entire process of the product development and manufacturing is time-consuming even with the advent of Cloud-Based Design and Manufacturing (CBDM). With enormous growth in Information Technology (IT) and extensive growth in cloud infrastructure the option of design and manufacturing within a cloud service is a viable option for future. This paper proposes a cloud based collaborative atmosphere with real-time interaction between the product development and the realization phases making the experience of design and manufacturing more efficient. A much-optimized data flow among various stages of a Product Lifecycle has also been proposed reducing the complexity of the overall cycle. A case study using Additive Manufacturing (AM) has also been demonstrated which proves the feasibility of the proposed methodology. The findings of this paper will aid the adoption of CBDM in PLM industrial activities with reduced overall cost. It also aims at providing a paradigm shift to the present design and manufacturing methodology through a real-time collaborative space

Introduction

With the emergence of new advanced technologies and rapidly increasing competition for efficient product development, researchers and industry professionals are constantly looking for new innovations in the field of design and manufacturing. It has become a challenge to meet the dynamics of today's Marketplace in the manufacturing field as the product development processes are geographically spread out. In the research community of Cloud Based Design and Manufacturing ongoing debate constantly takes place on the key characteristics like cloud based design, communication among users, safety of data, data storage, and data management among others. Such discussions have now been answered with the developments of cloud based design and manufacturing. Efforts are now directed towards making advancements in the field of design and manufacturing by using IT tools & PLM concepts. Few researchers are advancing in the field of developing a PLM paradigm in linking modular products between supplier and product developers [START_REF] Belkadi | Linking modular product structure to suppliers' selection through PLM approach: A Frugal innovation perspective[END_REF], few others have extended their PLM research in the domains of Building information modeling by taking motivation and best practices from PLM by emphasizing more on information centric management approach in construction projects [START_REF] Boton | Comparing PLM and BIM from the Product Structure Standpoint[END_REF]. A revolutionary advancement of cloud services which now offers distributed network access, flexibility, availability on demand and pay per use services has certainly given push for applying cloud computing technology in the field of manufacturing. The intended idea of performing manufacturing on cloud has reached to such an extent that industries are forced to carry out operations in cloud rather than using the traditional methods. Today's world is moving faster and is more connected than ever before due to globalization which has created new opportunities & risks. Traditional methods lack the ability to allow users, who are geographically spread out to work in a collaborative environment to perform design & manufacturing operations. Traditional Design processes have a one-way process that consists of four main phases: customer, market analysis, designer and manufacturing engineers followed in the same order where each phase was a standalone centralized system with minimum cross functional interaction. With the time technologies like CAD, internet services and client server model evolved drastically but overall the advantages provided by these systems were limited in nature as it was still following the same one-way methodology [START_REF] Abadi | Data Management in the Cloud: Limitations and Opportunities[END_REF]. Moreover, there exists a rigid and costly system of supply chain till now whereas in Cloud-based Supply Chain, the supply chain is customer centric and the users with specific needs are linked with the service providers while meeting the cost, time and quality requirements of the user. This is where adoption of Cloud Based Design and Manufacturing (CBDM) becomes essential as it is based on a cloud platform that allows users to collaborate and use the resources on demand and on a self-service basis. This provides flexibility and agility, which is required to reconfigure the resources to minimize the down-time, also called Rapid scalability. CBDM is designed to allow collaboration and communication between various actors involved from design to delivery phase in the crossdisciplinary teams to work in a collaborative way in real time from anywhere in the world with access to internet. Cloud manufacturing allows to produce variety of products of varying complexity and helps in mass customization. Using the CBDM system, the prototypes of the part can be manufactured without buying costly manufacturing equipment. Users can pay a subscription fee to acquire software licenses and use manufacturing equipment instead of purchasing them. Finally, usage of cloudbased environment leads to saving of opportunities as the tasks that were not economically viable earlier can be done using the cloud services.

2

State of The Art

Cloud Based Collaborative Atmosphere

With the coming & advancement of Web 2.0, social collaborative platforms provided a wonderful way to exchange information and data [START_REF] Wu | Cloud-based design and manufacturing systems: A social network analysis[END_REF]. The internet based information and communication technologies are now allowing to exchange information in real time and are providing means to put into practice the concepts of mass collaboration, distributed design & manufacturing processes [START_REF] Schaefer | Distributed Collaborative Design and Manufacture in the Cloud-Motivation, Infrastructure, and Education[END_REF]. Collaboration-based Design & Manufacturing comprises all the activities that revolve around the manufacture of a product and leads to significant economies of scale, reduced time to market, improvement in quality, reduced costs etc. In a cloud manufacturing system, manufacturing resources & capabilities, software etc. are interconnected to provide a pool of shared resources and services like Design as a Service, Simulation as a Service, and Fabrication as a Service to the consumers [START_REF] Ren | Cloud manufacturing: From concept to practice[END_REF]. Current researches have emphasized a lot on the connectivity of products or in other words smart connected products via cloud environment for better collaboration of various operations of manufacturing being carried out on a product [START_REF] Goto | Multi-party Interactive Visioneering Workshop for Smart Connected Products in Global Manufacturing Industry Considering PLM[END_REF] and hence this acted as a first motivation of going into cloud domain for design and manufacturing. Also many larger scale enterprises have formed decentralized and complex network of their operations in the field of design and manufacturing where constant interaction with small scale enterprise is becoming a challenge. However, with the emergence of cloud computing there is an observation that more and more enterprises have shifted their work into cloud domain and have saved millions of dollars [START_REF] Wu | Cloud-based design and manufacturing: Status and promise," a service-oriented product development paradigm for the 21st century[END_REF][START_REF] Wu | Cloud-based manufacturing: old wine in new bottles?[END_REF] and hence this forms our second motivation behind implementing manufacturing which in our case is AM on "Cloud" which is backed by the fact that the currently automobile and aeronautics giants have been shifting wide portion of their work into cloud platform by implementing cloud computing technology into many business lines pertaining to engineering domain. This also reaffirms our belief that cloud computing is envisaged to transform enterprise both small and big to profit from moving their design and manufacturing task into the cloud. Hence this forms the first pillar of the proposed CBDM.

Rapid manufacturing scalability

The idea of providing manufacturing services on the internet was in fact developed a long time ago when researchers envisaged the propagation of IOT (Internet of Things) in the production. Recent research has showcased the importance to have continuous process flow in lean product development which gave rise to an idea of having scalability in manufacturing process to have more liquidity in the manufacturing process.

In a world of rapid competition, scalability of rapid manufacturing is more important than ever. In the alignment to the statement made by Koren et al [START_REF] Yoram | Design of Reconfigurable Manufacturing Systems[END_REF] regarding importance of reconfigurable manufacturing systems (RMSs) for quick adjustment in production capacity and functionality, CBDM allows users to purchase services like manufacturing equipment, software licences with reconfiguration module which in turns allow scalability of the manufacturing process and prevents over purchasing of computing and manufacturing capacities. This digital manufacturing productivity greatly enhances the scalability of the manufacturing capacity in comparison to the traditional manufacturing paradigm and this has been evident from the recent research work carried out by Lechevalier et al. [START_REF] Lechevalier | Model-based Engineering for the Integration of Manufacturing Systems with Advanced Analytics[END_REF] and Moones et al. [START_REF] Moones | Interoperability improvement in a collaborative Dynamic Manufacturing Network[END_REF] who have showcased efficient interoperability in a collaborative and dynamic manufacturing framework. As stated by Wua et al [START_REF] Wua | Cloud-based design and manufacturing: A new paradigm in digital manufacturing and design innovation[END_REF], from the perspective of manufacturing scalability, CBDM allows the product development team to leverage more cost-effective manufacturing services from global suppliers to rapidly scale up and down the manufacturing capacity during production. Hence, Rapid manufacturing scalability forms our second pillar of the proposed methodology.

Design and additive manufacturing methodology model

In this section, the flow of information in the digital chain has been studied to optimize the quality of AM which remains our focus in the experiment to test proposed methodology. This information management system interacts with the support infrastructure [START_REF] Kim | Streamlining the additive manufacturing digital spectrum: A systems approach[END_REF] (The standards, methods, techniques and software). The table whose phase 3 to 6 are represented in Fig. 1, provides an overview of the eight distinct stages and transitions. With a clear understanding of the various phases of additive manufacturing and transitions of information between each phase, we were able to identify optimization opportunities of additive manufacturing and establish mechanisms and tools to achieve them. In the current research phase 3 and 4 have been considered as represented by dotted line region in Fig. 1. This transition is an important preparedness activity to AM that is essential to the achievement of the final product [START_REF] Fenves | A core product model for representing design information[END_REF]. It includes activities like journal of 3D model, generation of the carrier around the 3D model, decomposition in successive layers of a 3D model and generating a code which contains the manufacturing instructions for the machine. It is this transition stage "Activities for AM process" which is dealt later in this research project where AM process is optimized in the proposed methodology making this model a fourth pillar to the methodology.

Real-Time Business Model

One of the major advantages of using CBDM is that we are always linked to the outer world and this lets us know the real-time scenario. So as one of the pillars of our methodology we propose Real-time Business model to execute the entire process in the most efficient way in terms of quality and cost. The Real-Time Request for Quotation (RT-RFQ) is an interesting feature which increases the utility of the system. This basically utilizes the Knowledge Management System (KMS) which are an integral part of Cloud based design and manufacturing systems [START_REF] Li | Cost, sustainability and surface roughness quality-A comprehensive analysis of products made with personal 3D printers[END_REF]. The selection of candidate KSPs is done based on the abilities and the capacities of the KSP to produce the product within stipulated time, cost and quality. The entire process of generating a request for quotation, finalising the service provider and delivery of the final product is in real-time thus creating collaboration between the sellers and the buyers, which we name it as "Market Place". The entire Material Management and the Supply Chain of the product in a collaborative platform is an integral part of our proposed methodology thus forming one of the pillars.

Proposal of a methodology

Synthesis

Synthesis of the proposed methodology is supported by four foundation pillars: Cloud environment, Rapid manufacturing scalability, Design and additive manufacturing methodology model and real-time business model. As discussed in the section 2.3, optimization process involved in AM workflow is rich in research opportunities and thus important to reduce the number phases involved in the manufacturing process. In the construction of methodology, a centralized system has been considered which controls all the process i.e. cloud domain and forms a platform where all actions will take place. Thus "Cloud" atmosphere forms heart of the methodology which starts with inputs that are decided during the RFQ and award acknowledgement process of a project. 3D design (phase-1) followed by two new functionalities such as Preparation for manufacturing (phase-2) and the Marketplace (phase-4). Then comes generic processes manufacturing (phase 4) which in combination with phase-1, phase-2 and phase-3 gives the power of rapid manufacturing scalability as discussed in the section 2.2. Last two phases represent packaging (phase-5) and delivery (phase-6) that constitutes the supply chain network of the process and are interconnected to phase-3 "Mar-ketplace" in cloud by the means of interactions. Phase-3, phase-5 and phase-6 along with inputs given to the process is inspired form the real-time business model as discussed in the section 2.4. This way four pillars forms the backbone of the methodology. Collaboration at each phase in form of propagation of design, consultation, evaluation and notification happens in parallel or simultaneously during the process which forms a distributed and connected network in the methodology.

In addition to defining pillars, the existing methodologies workflow was simplified. The methodology process has been scaled down to six phases, instead of eight as mentioned by Kim D [START_REF] Kim | Streamlining the additive manufacturing digital spectrum: A systems approach[END_REF]. For that, some sub-stages were regrouped into phases to optimize the process and simplify the methodology Indeed, it was noticed that by reducing phases and regrouping linked sub-stages to a single phase, we can minimize the interactions that could happen during transitions between the different phases that aided us in achieving 6 phase methodology process with multiple parallel interactions. By grouping sub steps to main steps, we proposed a 6-phase methodology. This approach of grouping sub steps represents our idea of moving for a "task to do" vision to a "defined role" vision. Instead of thinking as a task of 3D scanning, 3D modelling or a triangulation together, it would be a better to think as a task of a function such as 3D designer or a mechanical engineer. Following this approach, we group several tasks to a specific role. That's how we simplified our methodology, which is checked and validated in the case study applied to AM.

Methodology

From the 3D design to the product delivery, this methodology describes six phases including five transitions with tractability on the cloud as outlined in the Fig. 2.

As shown on Fig. 2, the methodology process starts with a 3D design phase (1) which involves designing the product in a 3D environment, produce 3D CAD File and save it on the Cloud by allowing collaborative work with someone who has the access. This file is then sent to be prepared for manufacturing [START_REF] Boton | Comparing PLM and BIM from the Product Structure Standpoint[END_REF]. A preparation of the 3D model before manufacturing is basically deciding the manufacturing process that will be used to produce the designed part. Sub steps such as repair geometry, meshing, weight optimization and finite elements simulations are grouped in a single manufacturing preparation phase [START_REF] Boton | Comparing PLM and BIM from the Product Structure Standpoint[END_REF]. Once the file prepared for manufacturing, it's uploaded to a Marketplace (3) platform where the product will be evaluated and reviewed by service providers. It an online collaborative platform which brings together buyers (designers, engineers and product developers) and sellers the key service providers (KSPs) who manufacture and bring the design and the concept to realization. Here phase 2 and 3 works in parallel to double check whether the 3D file is ready for manufacturing or requires a further preparation or optimization for manufacturing process to be used. At this stage, the product design has been optimized, prepared for manufacturing and the most efficient service provider has been awarded the order by the designer. Those service providers will lead the customer to the appropriate manufacturing process and will start the manufacturing phase (4). A validation and evaluation product loop occurs after manufacturing to make sure the product matches the requirement specifications. Once the product is manufactured and validates the re-quirements, the service provider proceeds to the packaging (5) then the delivery (6). The service provider selected in the Market place also has the responsibility of providing packaging and delivery service. The methodology proposed here, is the result of a conceptual and theoretical work. However, it must be applied at a practical level to evaluate its efficiency. We have implemented the proposed thermotical model on a case study to enlighten the benefits of this model in a real-world scenario. The following section describes a case study of the proposed methodology, applied to Additive Manufacturing.

Additive manufacturing (AM) has become a new way to realize objects from a 3D model [START_REF] Thompson | Design for Additive Manufacturing: Trends, opportunities, considerations, and constraints[END_REF] as it provides a cost-effective and time-efficient way to produce lowvolume, customized products with complex geometries and advanced material properties and functionalities.

From 3D design to product delivery, step by step the proposed methodology discussed in the section 3 has been applied in AM context and thus changing the step (2) from "Preparation for manufacturing" to "Preparation to Additive Manufacturing" and the rest remains the same. As the project was conducted in a partnership with Dassault Systèmes, and the fact that we want to use a unique platform for the whole CBDM process, the "3DEXPERIENCE" solution by enterprise was used to test the proposed methodology. The focus was on optimizing the methodology dataflow, which impacts directly the product quality.

Step 1: 3D design In the first phase, the user will use a 3D design app on the cloud and work collaboratively. Once the product is designed and converted into an appropriate format, we proceed to the preparation process for manufacturing.

Step 2: Preparation for manufacturing

We have a 3D model file at this stage which requires preparation for the 3D printing. The Fig. 3 describes the fundamental AM processes and operations followed during preparation for manufacturing the CAD model in an AM environment. During the process Pre-context setting, Meshing were also carried out. Step 3: The 3DMarketplace The 3DMarketplace is a platform for additive manufacturing. It addresses the end-toend process of upstream material design, downstream manufacturing processes and testing to provide a single flow of data for engineering parameters. The objective here as a buyer is to select the most efficient key service provider possessing the required capabilities and skill sets on the Marketplace to proceed to the manufacturing phase (Fig. 4). The Marketplace shows up a list of service providers that can process the product manufacturing. A printing request was sent to the laboratory where a back and forth transition between the buyer and the service provider is necessary to make assure the printability of the 3D model and the use of the right manufacturing technology. This phase is done by confirmation of the order and starting of the AM process.

Step 4-5-6: Manufacturing, Packaging and delivery As defined in the proposed methodology section, the service provider from the Marketplace takes care of the manufacturing, packaging and delivery service. For the delivery, we chose to pick up the part. The customer can rate their experience and raise complaints on the 3DMarketPlace if required, and thus allowing improvement in the services provided.

Conclusion and Future work

The successful implementation of Cloud based additive manufacturing demonstrated that Collaborative and distributed design and manufacturing task as complex as AM can be performed with ease by using cloud based service. This research points towards a centralized user interface i.e. cloud platform which forms the heart of the proposed methodology thus allowing its users to aggregate data and facilitate coordination, communication and collaboration among its various players of design, development, delivery and business segments. We optimized the digital workflow while applying the proposed methodology, which helped in obtaining better quality products, shorter machining time, less material use and reduced AM costs. One of the main gains from study was the use of 3D mar-ket place in the methodology which offers a collaborative atmosphere for discussing subjects such 3D model design, geometry preparation and the appropriate manufacturing and also aides in the evaluation and validation of the two previous phases of the proposed methodology which is great from the outlook of the optimization and accuracy point of view in product development and delivery. The prototype of the CBDM system presented in this work will help to develop confidence in the functioning of a CBDM system especially in the domain of AM and will serve an ideal framework for developing it better for the near future.

Future work can consist of an adapted version of the proposed methodology CBAM (Cloud Based Additive Manufacturing) with more optimized process for AM. Overall the proposed methodology based on the work performed in the case study offers: a simplified, optimized, collaborative and AM applied solution that could be used in industrial and academic contexts and further strengthens the idea of adoption of cloud based services in the manufacturing sector soon.

Fig. 1 .

 1 Fig. 1. Extract of digital channel Information flow for AM as proposed by Kim D [17]

Fig. 2 .

 2 Fig. 2. Proposal of a CBDM methodology

Fig. 3 .

 3 Fig. 3. Preparation for manufacturing steps

Fig. 4 .

 4 Fig. 4. The 3D Marketplace procees with used service providers during experiment

Case study: Additive ManufacturingThis research is conducted in a partnership between the LCPI, a research lab in the Engineering School Arts et Métiers ParisTech, and Dassault Systèmes company. Collaborate to unify an academic research entity and an industrial Leader is one of our main purposes to point out merits of CBDM such as distributive & collaborative network as a solution to today's design & manufacturing activities. The proposed model in this paper, is tested by carrying out designing, manufacturing, trading on Marketplace and finally packaging for a very common industrial product called "joiner" in a collaborative & distributed environment on a cloud platform to demonstrate the feasibility of the proposed solutions by experimental tests.


Farouk Belkadi

Ravi Kumar Gupta

Stéphane Natalizio
email: snatalizio@audros.fr

Alain Bernard

Modular architectures management with PLM for the adaptation of frugal products to regional markets

Keywords: PLM, Modular Architecture, Product Features, Co-evolution 1

Nowadays companies are challenged with high competitiveness and saturation of markets leading to a permanent need of innovative products that ensure the leadership of these companies in existing markets and help them to reach new potential markets (i.e. emerging and mature market). Requirements of emerging markets are different in terms of geographic, economic, cultural, governance policies and standards. Thus, adopting existing European product to develop new products tailored to emerging markets is one possible strategy that can help companies to cope with such challenge. To do so, a large variety of products and options have to be created, managed and classified according to the requirements and constraints from a target regional market. This paper discusses the potential of PLM approach to implement the proposed modular product design approach for the adaptation of European product and production facilities to emerging markets. Using modular approach, the product design evolves iteratively coupling the configuration of various alternatives of product architectures and the connection of functional structures to their contexts of use. This enables the customization of adapted product to specific customer's needs.

Introduction

Customer's requirements fluctuate across geographical regions, standards, and context of use of the product of interest, whereas global production facilities to address such requirements are constrained by local governing policies, standards, and local resources availability. In order to address emerging market's needs and adapt existing product development facilities, it is important to analyze and evaluate different possibilities of product solutions against specific requirements of one regional market.

An emerging market is generally characterized as a market under development with less presence of standards and policies comparing to mature markets in the developed countries [START_REF]MSCI Market Classification Framework[END_REF]. To respond to the competition from these emerging countries, frugal innovation is considered as a solution to produce customized products in a shorter time for improving the attractiveness of western companies [START_REF] Khanna | Emerging Giants: Building World-Class Companies in Developing Countries[END_REF]. Frugal innovation or frugal engineering is the process of reducing the complexity and cost of goods, and their production. A frugal product is defined in most industries in terms of the following attributes: Functional, Robust, User-friendly, Growing, Affordable and Local. The details of these attributes are given in [START_REF] Bhatti | Frugal Innovation: Globalization, Change and Learning in South Asia[END_REF][START_REF] Berger | Frugal products, Study results[END_REF].

As per the study [START_REF] Gupta | Adaptation of european product to emerging markets: modular product development[END_REF], these frugal attributes are not always sufficient for adapting existing product development facilities in European countries to emerging markets. Several additional factors can influence consumer behavior as well such as cultural, social, personal, psychological and so on. To answer this demand, companies have to provide tangible goods and intangible services that result from several processes involving human and material resources to provide an added value to the customer.

However, looking to the large variety of markets, customer categories, needs and characteristics, companies have to create and manage a huge variety of products and services, under more complex constraints of delivery time reduction and cost saving. To do so, optimization strategy should concern all steps of the development process, including design, production, packaging and transportation [START_REF] Ferrell | Marketing: Concepts and Strategies[END_REF].

Generally, three categories of product are distinguished depending on the level of customization and the consideration of customer preferences, namely: (i) standard products that don't propose any customization facility; (ii) mass customized product offering customization on some parts of the product, and (iii) unique product developed to answer specific customer demand. Despite this variety, every product is defined through a bundle of elements and attributes capable of exchange and use. It is often proven that modular architectures offer high advantages to support creation and management of various product architectures from the same family. Taking advantage from this concept, this paper proposes the use of a modular approach to address the emerging market requirements through the adaptation of original products. The key issue is the use of PLM (Product Lifecycle Management) framework as a kernel tool to support both the management of product architectures and the connection of these architectures with production strategies. The specific use case of product configuration of mass customized product is considered as application context.

The next section discusses the main foundation of modular approach and its use for the configuration of product architectures. Section 3 discusses the implementation of the proposed approach in Audros software. Audros is a French PLM providing a set of flexible tools adaptable to a lot of functional domains through an intelligent merge of the business process model, the data model generator and the user interface design. Finally, section 4 gives the conclusion and future works.

2

Product configuration strategies within modular approach

Product modular architectures

Product architecture is the way by which the functional elements (or functions) of a product are arranged into physical units (components) and the way in which these units interact [START_REF] Eppinger | Product Design and Development[END_REF]. The choice of product architecture has broad implications for product performance, product change, product variety, and manufacturability [START_REF] Ulrich | The role of product architecture in the manufacturing firm[END_REF]. Product architecture is thought of in terms of its modules. It is also strongly coupled to the firm's development capability, manufacturing specialties, and production strategy [START_REF] Pimmler | Integration analysis of product decompositions[END_REF].

A product module is a physical or conceptual grouping of product components to form a consistent unit that can be easily identified and replaced in the product architecture. Alternative modules are a group of modules of the same type and satisfy several reasoning criteria/features for a product function. Modularity is the concept of decomposing a system into independent parts or modules that can be treated as logical units [START_REF] Pimmler | Integration analysis of product decompositions[END_REF][START_REF] Jiao | Fundamentals of product family architecture[END_REF]. Modular product architecture, sets of modules that are shared among a product family, can bring cost savings and enable the introduction of multiple product variants quicker than without architecture. Several companies have adopted modular thinking or modularity in various industries such as Boeing, Chrysler, Ford, Motorola, Swatch, Microsoft, Conti Tires, etc. [START_REF] O'grady | The age of modularity: Using the new world of modular products to revolutionize your corporation[END_REF]. Hubka and Eder [START_REF] Hubka | Theory of technical systems[END_REF] define a modular design as "connecting the constructional elements into suitable groups from which many variants of technical systems can be assembled". Salhieh and Kamrani [START_REF] Salhieh | Macro level product development using design for modularity[END_REF] define a module as "building block that can be grouped with other building blocks to form a variety of products". They also add that modules perform discrete functions, and modular design emphasizes minimization of interactions between components.

Generic Product Architecture (GPA) is a graph where nodes represent product modules and links represent connections among product modules according to specific interfaces (functional, physical, information and material flow) to represent a product or a set of similar products forming a product family. A GPA represents the structure of the functional elements and their mapping into different modules and specifies their interfaces. It embodies the configuration mechanism to define the rules of product variant derivation [START_REF] Elmaraghy | Product Variety Management[END_REF]. A clear definition of the potential offers of the company and the feasibility of product characteristics could be established for a set of requirements [START_REF] Forza | Application Support to Product Variety Management[END_REF]. Figure 1 shows an example of modular product architecture for the case of bobcat machine, including the internal composition of modules and the interaction between them [START_REF] Bruun | Interface diagram: Design tool for supporting the development of modularity in complex product systems[END_REF]. The similar concepts mentioned in the literature are 'building product architecture', 'design dependencies and interfaces' and 'architecture of product families', which can be used for the development of GPA. The GPA can be constructed by using different methods presented in the literature [START_REF] Jiao | Product family design and platform-based product development: a state-of-the-art review[END_REF][START_REF] Bruun | PLM support to architecture based development contribution to computer-supported architecture modelling[END_REF].

Construction of modular architectures

The use of the modular approach should propose the facility to work in different configurations. The concept of GPA can give interesting advantages for these issues. Indeed, by using existing GPA to extract reusable modules, a first assessment of interfaces compatibilities and performance of the selected modules can be performed regarding various product structures. Thus, module features are defined to support these assessments and used to link process specifications, production capabilities, and all other important criteria involved in the product development process. As the developed GPA is a materialization of the existing products, the adaptation of these products to the new market requirements will be obtained through some swapping, replacing, combining and/or modification actions on the original product architectures.

In fact, the application of customer-driven product-service design can follow one of two ways processes; either collectively through generic product architecture by mapping all the requested functions, or by mapping functions individually through features and then configuring product modules (cf. Figure 2). In this last case, more flexibility is allowed for the selection of products modules and consequently more innovative possibilities for the final product alternatives. However, more attention is required for the global consistency of the whole structure. The concept of "feature" is considered as a generic term that includes technical characteristics used for engineering perspective as well as inputs for decision-making criteria, useful for the deployment of customer-driven design process in the context of adaptation of existing European product and development facilities to an emerging market.

Fig. 2. Two ways product configuration strategies for identification of modules for a product

In the first case, starting from existing solutions implies a high level of knowledge about the whole development process and will reduce considerably the cost of adaptation to a new market. Using individual mapping of modules, the second way will give more possibilities to imagine new solutions (even the design process doesn't start from scratch) by reusing modules that are not originally created for the identic function. The implementation scenarios detailing these two ways are the following:

 Configuration 1: Mapping of Requested Functions to GPA. The starting point in this configuration is the existing product families, really produced to meet certain functions and sold to customers in other markets. The goal is then to adapt the definition of modules regarding the new requirements according to their level of correspondence with existing functions, the importance of each customer option, and possible compatibilities between local production capabilities and those used for the realization of the original product. The modular approach is used to satisfy set of functions collectively through GPA by mapping all the functions required.

 Configuration 2: Mapping set of functions to modules through features. In the second configuration, the modular approach is used to satisfy functions individually through features. More attention is given to product modules separately regardless of the final products structures involving these modules. This is also the case when the previous product structures contain partial correspondence with new requirements. This configuration offers more innovation freedom for the design of new product but include a strong analysis of interface compatibilities across modules. In this configuration, we go from the interpretation of the functions to identify all modules' features and then, search if there are some adequate modules and then configure these modules to possible products architectures.

Implementing modular approach in PLM for the configuration of customized product

By using modular architectures, different product configurations can be built as an adaptation of existing products or the creation of new ones through the combination and connection of existing modules developed separately in previous projects. Product Configuration is already used for mass customization perspective [START_REF] Daaboul | Design for mass customization: Product variety VS process variety[END_REF]. This can be also used to increase product variety for regional adaptation and improve the possibility to the customer to choose between different options for an easily customized product with low production cost. This is possible through the matching among product modules, process modules and production capabilities. The development of a product for a new market can then be obtained through a concurrent adjustment of the designed architecture and the production strategy, considered as a global solution. Following this approach, the involving of the customer into the product development process is made through an easier clarification of his needs as a combination of functions and options. These functions/options have to be connected in the design stage to pre-defined modules. Customers are then engaging only in the modules which they are interested in and presenting a high potential of adaptation. In the production side, alternatives of process are defined for each alternative of product configuration so that all the proposed options presented in the product configurator are already validated in terms of compatibility with the whole product architecture and production feasibility. This ensures more flexibility in the production planning.

Figure 3 shows a global scenario connecting a product configurator with the PLM. Following this scenario, the customer can visualize different options for one product type and submit his preferences. These options are already connected to a list of pre-defined models which are designed previously and stored in the PLM. The selection of a set of options will activate various product architectures in the PLM. Based on the selected set of options, the designer extracts the related product architectures. For every option as displayed to the customer in the configurator, a set of modules alternatives are available in the PLM and can be managed by the Designer to create the final product architecture as a combination of existing architectures.

In addition, when selecting the product family and the target market, the PLM interfaces provide a first filtering of modules respecting the target market requirements.

Fig. 3. Scenario of product configuration with PLM

The creation of the predefined models in the PLM is part of a design process which is fulfilled in the design department based on the configuration strategies presented in section 2.2. For each target market or potential category of customers, every type of product is presented with its main architecture connected to a set of alternative architectures. Each alternative implements one or more product options that are tailored to specific regional markets by means of related alternatives of production process.

The main question to be resolved in this design stage concerns the characteristics which the concept of modules should adopt in order to cope with the co-evolution strategy of product architecture and production process, respecting customization constraints. In this case, specific features are defined with the module concept as decision-making criteria to support the product configuration process within a coevolution perspective as given below:

 Criticality: The importance of a module in the final product architecture regarding the importance of the related option/function to the customer. This will help the designer to choose between solutions in presence of some parameters conflicts.  Interfacing: The flexibility of one module to be connected with other modules in the same architecture. This increases its utilization in various configurations.  Interchangeability: The capacity of one module to be replaced by one or more other modules from the same category to provide the same function. Based on this feature and the previous one, the customer can select only compatible options.

 Process Connection: It gives information about the first time the related module is used in the production process and the dependency with other assembly operations. This is particularly important if the company aims to propose more flexibility to the customer for selecting some options although the production process is started.

To support the implementation of such process, a data model is implemented in the Audros PLM to manage a large variety of product alternatives connected to several alternatives of production (cf. Figure 4). In this model, every function is implemented through one or several technical alternatives. The concept of "module" is used to integrate one (and only one) technical solution in one product structure. Every product is composed of several structures representing product alternatives. Each structure is composed of a set of modules and connectors that present one or more interfaces. The concept of product master represents the models of mature products that will be available for customization within the product configurator and able.

Fig. 4. PLM Data model implementing modular approach

Based on this data model, several scenarios are defined as an implementation of the construction and use processes of modular architectures (see Figure 2). These scenarios concern, for instance, the creation of original products from scratch or from the adaptation of existing ones, the connection between PLM and product configurator for the ordering of new customized product and the connection PLM-MPM (manufacturing process management) for the realization of the selected alternatives, etc. A recognition scenario of the ordering and customization of a frugal product based on the adaptation of an existing one, using PLM is described as follow. The customer or the marketing department choose an existing product as a base and define customization to be applied to adapt the product by the design office.

 Actors: Customer/Marketing department of the company + Design department  Goal: select the product to be customized and ordered  Pre-condition:

─ If request comes from the Marketing department, a new product family will be developed with options. ─ If the request comes from the customer, a new customer order with customization will be considered.  Post condition: Instance of the product master is created, request is sent to design  Events and interactions flow:

─ The user chooses product type and target market ─ The system returns the list of suitable options ─ The user creates an order for the desired products ─ The system creates a new product, instance of chosen product master ─ The user selects the options ─ The system analyzes the order and identifies suitable modules for each option ─ The system filters the alternatives of modules for each function regarding the interfacing and compatibility criteria. ─ The system generates potential alternatives of product architecture ─ The system sends a notification of design request to design office.

The Graphical User Interface (GUI) of the PLM tool has been designed to provide flexible and user-friendly manipulation of any type of product structure as well as its different modules and features. The global template of the GUI is the same for all screens, but the content adapts itself depending on the data to be managed and the context of use (Scenario and Use). With this GUI, the user will have a unified interface that will help the designer for the design of a frugal product and its co-evolution with the production process as follow:

 Create and analyze various product architectures at any level, from different point of view (functional, technical solutions, compatibility, manufacturing, etc.)  Promote re-use and adaptations of existing solutions in the design of product architectures. This is based on the searching facilities for object (function, modules, alternatives …) in a very simple and quick way.  Manipulate product and production data (create/modify/adapt solutions)  Access easily to all related documents like market survey, customer feedback, etc.

The following figure (cf. Fig 5) presents the main GUIs of the proposed PLM platform as used in the proposed frugal design process. The flexibility of this platform takes advantage from the use of the "effectivity parameter" describing the link between two PLM objects. The effectivity parameters, displayed in the GUI, are used for data filtering as well as representation and manipulation of objects during the configuration process. There is no limit for the definition of effectivity parameters. Examples of effectivity parameters used in the case of frugal product configuration are: Criticality; Customization; Manufacturing plant; Sales country; Product option/variation; and Begin/end date of validity.

Conclusion

PLM tool configuration for the representation and the management of Product modular architectures has been introduced so as to respond to the requirements of adapting product-service design and production in a customer-driven context. The focus is the tailoring of mature product solutions to customer's needs in emerging market. Module features have been defined to help translate the regional customer requirements into product functions and product structure design. It is also used to connect the product design to production planning as well as other downstream activities.

The modular design approach for the adaptation of European product to emerging markets has been proposed for this objective. The proposed modular product design approach is actually under implementation for supporting the configuration and customization of aircrafts in aeronautic domain and the co-design of production systems tailored to regional markets. Another application, in domestic appliance industry concerns the integration of the customer in the definition of product variety through a smart organization of feedback survey following modular structures, highlighting the preferences of potential customers in a target regional market. Software interoperability and information exchanges between involved tools in these industrial scenarios is ensured using PLM framework, considered as a hub.

Fig. 1 .

 1 Fig. 1. Example of generic product architecture of Bobcat machine (adapted from [16]).

Fig. 5 .

 5 Fig. 5. Several PLM GUIs as a whole process

Acknowledgement

The presented results were conducted within the project "ProRegio" entitled "customer-driven design of product-services and production networks to adapt to regional market requirements", funding by the European Union's Horizon 2020 research and innovation program, grant agreement n° 636966.


D Morales-Palma

I Eguía

M Oliva

F Mas

C Vallellano

Managing maturity states in a collaborative platform for the iDMU of aeronautical assembly lines

Keywords: Product and process maturity, Industrial Digital Mock-Up (iDMU), Digital manufacturing, Digital factory, PLM

Collaborative Engineering aims to integrate both functional and industrial design. This goal requires integrating the design processes, the design teams and using a single common software platform to hold all the stakeholders contributions. Airbus company coined the concept of the industrial Digital Mock Up (iDMU) as the necessary unique deliverable to perform the design process with a unique team. Previous virtual manufacturing projects confirmed the potential of the iDMU to improve the industrial design process in a collaborative engineering environment. This paper presents the methodology and preliminary results for the management of the maturity states of the iDMU with all product, process and resource information associated with the assembly of an aeronautical component. The methodology aims to evaluate the suitability of a PLM platform to implement the iDMU in the creation of a control mechanism that allows a collaborative work.

Introduction

Reducing product development time, costs and quality problems can be achieve through effective collaboration across distributed and multidisciplinary design teams. This collaboration requires a computational framework which effectively enables capture, representation, retrieval and reuse of product knowledge. Product Lifecycle Management (PLM) refers to this enabling framework to help connect, organize, control, manage, track, consolidate and centralize all the mission-critical information that affects a product and the associate processes and resources. PLM offers a process to streamline collaboration and communication between product stakeholders, engineering, design, manufacturing, quality and other key disciplines.

Collaboration between product and process design teams has the following advantages for the company: reduction of time required to perform tasks; improvement of the ability to solve complex problems; increase of the ability to generate creative alternatives; discussion of each alternative to select as viable and to make decisions; communication improvement; learning; personal satisfaction; and encouraging innovation [START_REF] Alonso | Enterprise Collaboration Maturity Model (ECMM): Preliminary Definition and Future Challenges[END_REF]. However, collaboration processes need to be explicitly designed and managed to maximize the positive results of such an effort.

Group interaction and cooperation requires four aspects to be considered: people have to exchange information (communication), organize the work (coordination), operate together in a collective workspace (group memory) and be informed about what is happening and get the necessary information (awareness).

Maturity models have been designed to assess the maturity of a selected domain based on a comprehensive set of criteria [START_REF] Bruin | Understanding the main phases of developing a maturity assessment model[END_REF]. These models have progressive maturity levels, allowing the organization to plan how to reach higher maturity levels and to evaluate their outcomes on achieving that.

A maturity model is a framework that describes, for a specific area of interest, a set of levels of sophistication at which activities in this area can be carried out [START_REF] Alonso | Enterprise Collaboration Maturity Model (ECMM): Preliminary Definition and Future Challenges[END_REF]. Essentially, maturity models can be used: to evaluate and compare organizations' current situation, identifying opportunities for optimization; to establish goals and recommend actions for increasing the capability of a specific area within an organization; and as an instrument for controlling and measuring the success of an action [START_REF] Hain | Developing a Situational Maturity Model for Collaboration (SiMMCo) -Measuring Organizational Readiness[END_REF].

Product lifecycle mainly comprises several phases, e.g. research, development, production and operation/product support [START_REF] Wellsandt | A survey of product lifecycle models: Towards complex products and service offers[END_REF]. The development phase comprises the sub phases shown in Fig. 1: feasibility, concept, definition, development and series, which involve improvement and modifications. Product collaborative design encompasses all the processes before the production phase, and the information management strategy of products achieve internal information sharing and collaborative design by integrating data and knowledge throughout the whole product lifecycle and managing the completeness of the information in each stage of product design. Researches on the product maturity are mainly about project management maturity which are used to evaluate and improve the project management capabilities of enterprises. A smaller part of the researches have discussed the concept of product maturity, and the number of works devoted to studying maturity of related processes and resources is insignificant. Wang et al. [START_REF] Wang | Research on Space Product Maturity and Application[END_REF] proposed the concept of space product maturity and established a management model of product maturity, but it lacks the research about product maturity promoting the product development process. Tao and Fan [START_REF] Tao | Application of Maturity in Development of Aircraft Integrated Process[END_REF] discussed the concept of maturity and management control method in the process of integration, but the division of the maturity level is not intuitive, and discussed little about application of product maturity in collaborative R&D platform. Chen and Liu [START_REF] Chen | Maturity Management Strategy for Product Collaborative Design[END_REF] provided the application of a strategy of product maturity for collaborative design on the collaborative development platform Teamcenter to verify the effectiveness and the controllability of the strategy. Wuest et al. [START_REF] Wuest | Application of the stage gate model in production supporting quality management[END_REF] adapted the state gate model, a well-established methodology for product and software development, to production domain and indicated that it may provide valuable support for product and process quality improvement although the success is strongly dependent of the right adaptation.

The main objective of this paper is the design of a maturity management model for controlling the functional and industrial design phase of an aeronautical assembly line in the Airbus company (Fig. 1), and explores the development of this model in 3DExperience, a collaborative software platform by Dassault Systémes [9].

Antecedents and iDMU concept

The industrial Digital Mock-Up (iDMU) is the Airbus proposal to perform the design process with a unique team with a unique deliverable. The iDMU is defined by Airbus to facilitate the integration of the processes of the aircraft development on a common platform throughout all their service life. It is a way to help in making the functional and the industrial designs evolving jointly and collaboratively. An iDMU gathers all the product, processes and resources information to model and validate a virtual assembly line, and finally to generate the shopfloor documentation needed to execute the manufacturing processes [START_REF] Menéndez | Virtual verification of the AIRBUS A400M final assembly line industrialization[END_REF][START_REF] Mas | Collaborative Engineering: An Airbus Case Study[END_REF].

Airbus promoted the Collaborative Engineering in the research project "Advanced Aeronautical Solutions Using PLM Processes and Tools" (CALIPSOneo) by implementing the iDMU concept [START_REF] Mas | Collaborative Engineering Paradigm Applied to the Aerospace Industry[END_REF][START_REF] Mas | iDMU as the Collaborative Engineering engine: Research experiences in Airbus[END_REF][START_REF] Mas | PLM Based Approach to the Industrialization of Aeronautical Assemblies[END_REF]. The iDMU implementation was made for the industrialization of the A320neo Fan Cowl, a mid-size aerostructure. It was built by customizing CATIA/DELMIA V5 [9] by means of the PPR model concept. The PPR model of this commercial software provided a generic data structure that had to be adapted for the products, processes and resources of each particular implementation. In this case, a specific data structure was defined to support the Airbus products, the industrial design process, the process structure nodes, the resources structure nodes and their associated technological information, 3D geometry and metadata.

The process followed by Airbus to execute a pilot implementation of the iDMU is briefly described as follows. The previously existing Product structure was used and an ad-hoc application was developed that periodically updated all the modifications released by functional design. The Process and Resources structures were populated directly in the PPR context. The Process structure comprised four levels represented by four concepts: assembly line, station, assembly operation and task. Each concept has its corresponding constraints (precedence, hierarchy), its attributes and its allocation of products to be assembled and resources to be used. Once the PPR structures were defined, the system calculated the product digital mock-up and the resources digital mock-up that relate to each process node. As a result, the designer created simulations in the 3D graphical environment to analyse and validate the defined manufacturing solution. This validation of the process, product and resource design, by means of Virtual Manufacturing utilities in a common context, is a key feature in the Collaborative Engineering deployment.

The iDMU supports the collaborative approach through 3 main elements. First, it allows sharing different design perspectives, to reveal solutions that while valid for a perspective (e.g. resources design) cause problems in other perspectives (e.g. industrialization design), and to solve such issues. Second, it enables checking and validation of a high number of alternatives, allowing improving the harmonization and optimization of the design as a whole. And third, it is possible to reuse information contained in the iDMU by other software systems used in later stages of the lifecycle, facilitating the integration and avoiding problems with translation of models into intermediate formats, and making easier the use of new technologies such as augmented reality.

The CALIPSOneo project [START_REF] Mas | Collaborative Engineering Paradigm Applied to the Aerospace Industry[END_REF][START_REF] Mas | iDMU as the Collaborative Engineering engine: Research experiences in Airbus[END_REF][START_REF] Mas | PLM Based Approach to the Industrialization of Aeronautical Assemblies[END_REF], with a scope limited to the A320neo fan cowl, allowed confirming that the iDMU provides a suitable platform to develop the sociotechnical process needed by the collaborative engineering. However, the project also revealed that the general functionalities provided by the adopted PLM commercial solution required an important research and development work to implement the data structures and functions needed to support the iDMU.

An important factor in the implementation of an iDMU is the need for a PLM tool capable of coordinating the workflow of all participants by means the definition and control of the lifecycle of allocated elements of the PPR structure, i.e. to manage its maturity states. At present, this issue is being addressed in the research project "Value Chain: from iDMU to Lean documentation for assembly" (ARIADNE).

Methodology

As said before, one of the studies carried out within the scope of the ARIADNE project was the analysis of capabilities that a PLM tool requires to manage the maturity states of the iDMU. Such a PLM tool aims the following objectives:  To define independent and different maturity states sets for Product, Process and Resource revisions.  To define precedence constraints between the maturity states of a Process revision, and the maturity states of its related Products and Resources.  To define, for each Process revision maturity state, other conditions (e.g. attribute values) that are to be met prior to evolving a Process revision to the maturity state.  To define, for each Process revision maturity state, that some process data or relations are not modifiable from this maturity state onwards.  To display online, in the process revision iDMU, the Products and Resources evolved through maturities from the last time it was vaulted.

 To display online, in the process revision iDMU, the impact of the evolved Products and Resources and how easy these issues can be fixed.

In order to prove the capabilities of a new PLM tool to meet these objectives, a simple lifecycle model is proposed. The model has only three possible maturity states for every element of the PPR structure: In Work, Frozen and Released. However, the importance of the proposed model lies in a set of constraints that prevent the promotion between maturity states, as described below. This simple model aims to be a preliminary test to evaluate a new PLM tool, so that it can be improved and extended with new states, relationships, constraints, rules, etc.

The In Work state is used for a new version of a product, process or resource element in the PPR structure. In Work data are fully modifiable and can be switched to Frozen by the owner, or to Released by the project leader. Frozen is an intermediate state between In Work and Released. It can be used, for example, for data waiting for approval. Frozen data are partially modifiable (for minor version changes) and can be switched back and forth between In Work and Frozen by the owner, or to Released by the project leader. Released is the final state of a PPR element, e.g. when a product is ready for production, a process is accepted for industrialization, or a resource is fully configured for its use. Released data cannot be deleted and cannot switched back to previous states. In this situation, all product, process and resource elements in the PPR structure are In Work. The collaborative environment must allow the visualization and query of information under development to the different actors of the system, based on roles and permissions, so that it helps to detect design errors and make right decisions.

The new PLM tool must provide a set of rules or constraints that allow to control and alert the designer about non-coherent situations. Fig. 2 schematically presents some constraints to promote a PPR element. For instance, it is not possible to assign to a process node a maturity state of Frozen until the related product node has a maturity state of Released and the allocated resource has a maturity state of Frozen. In a similar way, to promote a process to Released, the allocated resource must be in Re-leased. On the other hand, the resource element can only reach the maturity state of Released when the process element has been Frozen previously.

In addition to define constraints between elements of different types (product, process and resource), it is necessary to establish rules between elements of the same type to control the change of maturity states of their interconnected elements. For instance, the following constraint inside the Product structure could be established: the designer of a product consisting of several parts can change the state of the product element to Frozen/Released when all its parts already have that same state, so that a part still unfinished (In Work) alerts him that the product cannot be promoted yet.

Practical application

The proposed model for managing the maturity states of an iDMU was implemented and tested in a PLM commercial software, within the frame of the ARIADNE project.

The implementation was carried out with the 3DExperience software solution by Dassault Systémes. The PPR structure in 3DExperience differs slightly from CATIA/DELMIA V5 so that the process of building the iDMU is different from those developed in previous projects. A significant difference is that the previous 3-elements PPR structure is replaced by a 4-elements structure, as represented schematically in Fig. 3:  Product: it presents the functional zone breakdown in an engineering oriented organization. It is modelled by Design Engineering to define the functional view for structure and system installation.  Process: it is focused to model the process plan from a functional point of view. It is indeed a product structure composed of a cascade of components identified by part numbers that presents how the product is built and assembled. Thus, both product and process elements of the PPR structure are directly correlated.

 System: it defines the work flow operation. It contains a set of system/operations that corresponds to the steps necessary to correlate with the Process structure. It contains the information necessary to perform operations such as balancing the assembly lines.  Resource: it represents the layout design for a manufacturing plant. Resources can be classified as working (e.g. robot, worker, conveyor), non-working (e.g. tool device) or organizational (e.g. station, line). The required resources are attached to operations in the System structure, as shown in Fig. 3.

The adopted PLM software integrates a default lifecycle model to any created object that controls the various transitions in the life of the object. This model includes elements such as user roles, permissions, states and available state changes. To facilitate the collaborative work, 3DExperience also provides a lifecycle model to manage Engineering Changes, which has links to PPR objects, and a transfer ownership functionality that can be used to pass an object along to another authorized user to promote it. Both PPR and Engineering Changes lifecycle models can be customized. These characteristics made 3DExperience an adequate collaborative platform for the purpose of this work. The objectives that a PLM tool must satisfy for managing the maturity states, described in the previous section, were analysed to fit the 4-element PPR structure of the 3DExperience software. Accordingly, the proposed model was redefined as shown in Fig. 4(a). As can be seen, the set of constraints for the System lifecycle is equivalent to the previous set of constraints for the Process lifecycle, whereas that Process elements are the bridge between Products and Systems.

A series of roles has been defined (see Fig. 4(a)) to implement the proposed model of maturity states in 3DExperience, such as the Project Leader (PL) and a different type of user to design each of the PPR structures: a Designer Engineer (DE), a Process Planner (PP), a Manufacturing Engineer (ME) and a Resources Designer (RD). Each system user is responsible for designing and promoting/demoting each node of its structure to the three possible states, as shown in Fig. 4(a). The PL coordinates all maturity state changes: he checks that there are no inconsistencies and gives the other users permission to make the changes.

Designers have several possibilities for building the iDMU using the 3DExperience graphical interface. Briefly, the maturity state is stored as an attribute of each PPR element, so it can be accessible from the query tool "Properties". The software also provides the "Team Maturity" utility to display information in the graphical environment about the maturity states. This utility displays a coloured flag in each element of the model tree that indicates its maturity state; however, it applies just for Product and Resource elements, i.e. elements that have associated geometry. Another utility allows displaying graphical information about the related elements of an allocated iD-MU element. Both graphical utilities, for maturity states and related elements, were used to search and filter information before changing an object state. To promote or demote the maturity state of an iDMU element, the "Change Maturity" utility presents different fields with the available changing states and related information according to the lifecycle model, roles and permissions.

The Airbus A400M empennage (about 34000 parts, see Fig. 4(b)) and its assembly processes were selected to develop the iDMU in 3DExperience. The empennage model developed in CATIA V5 was used as the Product structure. Process, System and Resource structures were modelled from scratch. Different use cases were evaluated by choosing small and more manageable parts of the iDMU to change their maturity states in the collaborative platform. The following is a summary of the implementation process carried out. An example is shown in Fig. 5. At the beginning of the lifecycle, the PL authorized all other system actors to work together in the iDMU at the same time in the collaborative platform (label a in Fig. 5). The main PPR structures were created and scope links were established between them. In this situation, all PPR nodes were In Work while the iDMU was designed in a collaborative and coordinated way.

One of the first state changes in the iDMU is made by the DE when it promotes a component or subproduct to Frozen (b). In this situation, only minor design changes could be made to the frozen component, which will have no impact on the rest of the iDMU (including other components of the product). Demoting the component to an In Work state (c) would indicate that major changes are required as a result of the current design state in other areas of the iDMU. In general, the promotion to Released of every PPR structure will be carried out in an advanced state of the whole iDMU. This means that their design has been considered as stable and that no significant changes will occur that affect other parts of the iDMU.

Maturity state changes in the Process structure are conditioned by the state of related components in the Product structure. Thus, before promoting a Process element (d), the PP must check the status related components with the aforementioned 3DExperience utilities to search and analyse the related elements and their states of maturity. If the related product is Frozen/Released, the PP can request authorization to the PL to promote the Process element.

Another of the first state changes of maturity that occurs in the iDMU is that of resources. Thus, the RD promotes a resource to Frozen (e) or demotes it to In Work (f) following the same guidelines as the DE with the products. Instead, the promotion of a resource to Released (g) can only be authorized by the PL when the related assembly system is Frozen, indicating that the assembly line has been designed except for possible minor changes that would not affect the definition of the resources.

The ME is the last actor to promote the state of his work in the iDMU: the design of the assembly system/line. In order to freeze his work (h), the ME needs to know in advance the final design of the product assembly process and also the definition of the necessary resources. Any changes in product or process structures, even if they are minor, could have a relevant impact on the definition of the assembly line. Therefore, the ME must previously verify that related assembly processes are Released and required resources are Frozen. Since resource nodes are linked to the System structure through operation nodes, the ME extensively uses the 3DExperience utilities to trace all affected nodes and check their maturity states. As discussed above, the promotion to Released of all PPR structures occurs in an advanced development of the iDMU, being the last two steps those relating to Resource and System structures.

Conclusions

This paper presents the methodology and preliminary results for the management in a collaborative environment of the maturity states of PPR elements with all product, process and resource information associated with the assembly of an aeronautical component. The methodology aims to evaluate the suitability of PLM tools to implement the Airbus methodology in the creation of a control mechanism that allows a collaborative work. The proposed model shows in a simple way the importance of the flow of information among the different participants of a unique team to build an iDMU as the unique deliverable in a collaborative platform. An outstanding feature of the lifecycle model is its ability to authorize or restrict the promotion of a product, process or resource element depending on the states of the related elements. Different use cases with coherent and non-coherent situations have been successfully analysed using 3DExperience to implement an iDMU for the Airbus A400M empennage.

In this work, the change management of maturity states has been coordinated by a Project Leader. The next step will be to customize 3DExperience to automate the maturity state changes, so that the system is responsible for evaluating the information of related elements, allowing or preventing the designer from promoting an iDMU element.

Fig. 1 .

 1 Fig. 1. Airbus product lifecycle and milestones development.

Fig. 2 .

 2 Fig. 2. Proposed simple model for the lifecycle of the PPR structure.

Fig. 2

 2 Fig.2shows a schema of the proposed model. At the beginning of the lifecycle, since Design Engineering starts the product design, usually Manufacturing Engineering can begin to plan the process, set up the layout and define the necessary resources. In this situation, all product, process and resource elements in the PPR structure are In Work. The collaborative environment must allow the visualization and query of information under development to the different actors of the system, based on roles and permissions, so that it helps to detect design errors and make right decisions.The new PLM tool must provide a set of rules or constraints that allow to control and alert the designer about non-coherent situations. Fig.2schematically presents some constraints to promote a PPR element. For instance, it is not possible to assign to a process node a maturity state of Frozen until the related product node has a maturity state of Released and the allocated resource has a maturity state of Frozen. In a similar way, to promote a process to Released, the allocated resource must be in Re-

Fig. 3 .

 3 Fig. 3. Schema of implementation of Airbus iDMU concept in 3DExperience.

Fig. 4 .

 4 Fig. 4. (a) Extension of proposed model and (b) Airbus A400M empennage.

Fig. 5 .

 5 Fig. 5. An example of implementation of the proposed simple model.

Acknowledgements

The authors wish to thank the Andalusian Regional Government and the Spanish Government for its financial support through the research project "Value Chain: from iDMU to Lean documentation for assembly" (ARIADNE). The work of master thesis students, Gonzalo Monguió and Andrés Soto, is also greatly acknowledged.


Manuel Oliva
email: manuel.oliva@airbus.com

Jesús Racero

Domingo Morales-Palma

Carmelo Del Valle
email: carmelo@us.es

Fernando Mas
email: fernando.mas@airbus.com

Jesus Racero

Carmelo Del Valle

Value Chain: From iDMU to Shopfloor Documentation of Aeronautical Assemblies

Keywords: PLM, iDMU, interoperability, Collaborative Engineering, assembly 2 ARIADNE project

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

Introduction

PLM systems integrate all phases in the product development. The full product lifecycle, from the initial idea to the end-of-life, generates a lot of valuable information related to the product [START_REF] Ameri | Product lifecycle management: closing the knowledge loops[END_REF].

In aerospace industry, the long lifecycle (about 50 years), the number of parts (over 700.000 as average in a short range aircraft) and the modifications, make the aircraft a high complex product. Such complexity is drawn both from the complexity of the product and from the amount of resources and multidisciplinary work teams involved.

A complexity of multidisciplinary is found during the interaction between functional and industrial designers which brings inefficiencies in developing time, errors, etc. Research studies propose the necessity to evolve from the concurrent way of working to a more efficient one with the objective to deliver faster, better and cheaper products [START_REF] Pardessus | Concurrent Engineering Development and Practices for aircraft design at Airbus[END_REF], [START_REF] Haas | Concurrent engineering at Airbus -a case study[END_REF], [START_REF] Mas | Concurrent conceptual design of aero-structure assembly lines[END_REF]. One proposal to comply with such challenge is the Collaborative Engineering concept [START_REF] Lu | A scientific foundation of Collaborative Engineering[END_REF], [START_REF] Morate | Collaborative Engineering Paradigm Applied to the Aerospace Industry[END_REF].

Collaborative Engineering involves a lot of changes in terms of organization, teams, relationships, skills, methods, procedures, standards, processes, tools, and interfaces: it is a business transformation process. The main deliverable of a collaborative team is the iDMU [START_REF] Mas | iDMU as the Collaborative Engineering engine: Research experiences in Airbus[END_REF]. The iDMU concept is the approach defined by Airbus to facilitate the integration of the aircraft development on a common platform throughout all their service life. An iDMU gathers all the product, processes and resources data, both geometrical and technological to model a virtual assembly line. An iDMU provides a single environment, in which the assembly line industrial design is defined and validated.

To cover the bridge between the complexity of product information and the different PLM software tools to manage it, interoperability has raised as a must nowadays to improve the use of existing data stored in different formats and systems [START_REF] Penciuc | Towards a PLM interoperability for a collaborative design support system[END_REF]. Interoperability foundation is the Model Base Engineering (MBE), as a starting point for organizing a formal way of communicating and building knowledge [START_REF] Liao | Semantic annotations for semantic interoperability in a product lifecycle management context[END_REF] from data and information.

The development of solutions, to facilitate the implementation of both the concurrent engineering and the Collaborative Engineering in the aerospace industry, was the objective of some projects since the end of the 1990's decade. Two of the most relevant ones are the European projects ENHANCE [START_REF] Braudel | Overall Presentation of the ENHANCE Project[END_REF], [START_REF]VIVACE Project[END_REF] and VIVACE [START_REF] Van | Engineering Data Management for extended enterprise[END_REF].

In the last decade, different research projects have been conducted for a complete integration of the iDMU and all the elements in the different stages of the life cycle (from design to manufacturing). The CALIPSOneo project [START_REF] Mas | PLM based approach to the industrialization of aeronautical assemblies[END_REF] was launched by Airbus to promote the Collaborative Engineering. It implements the iDMU as a way to help in making the functional and the industrial designs evolving jointly and collaboratively. The project synchronizes, integrates and configures different software applications that promote the harmonization of common set of PLM and CAD tools.

EOLO (Factories of the future. Industrial development) project was developed as an initiative to achieve a better integration between information created in the industrialization phases and the information created in the operation and maintenance phases.

The ARIADNE project emerges as an evolution of both, CALIPSOneo and EOLO projects, which incorporates the integrated management of the iDMU life cycle (product, processes and resources), the Collaborative Engineering and interoperability between software systems (independent vendor). These characteristics will provide an improvement of data integration, knowledge base and quality of the final product. , the PLM platform currently running in most of the aerospace companies, and 3DExperience. An analysis of the 3DExperience platform is been performed in ARIADNE with the objective of checking the main functionalities needed for the industrial design, that represents an improvement over CATIA v5. It is not an exhaustive analysis of all functionalities of 3DExperience, but it is a study of the characteristics provided by 3DExperience that covers the main requirements of manufacturing engineering activities for the industrialization of an aerospace assembly product.  HELIOS (New shopfloor assembly documentation models). HELIOS proposes research on a solution to extract information from an iDMU independently of the software provider. The conceptual solution is based on developing the models and transformations needed to explode the iDMU for any other external system. Currently, any system that needs to exploit the iDMU would have to develop its own interfaces. In case the iDMU is migrated to a different PLM, those interfaces must be changed also. To help with those inefficiencies and to be independent from any existing PLM, HELIOS will generate a standardized software code (EXPRESS-i) that any external system can use to communicate and obtain the required information from the iDMU.  ORION (Laser authoring shop floor documentation). ORION aims to develop a system to exploit assembly process information contained in the iDMU with Augmented Reality (AR) technics using laser projection technology. This system will get any data from the iDMU needed for the assembly, verification or maintenance process. ORION is based on the SAMBAlaser project [START_REF] Serván | Augmented Reality Using Laser Projection for the Airbus A400M Wing Assembly[END_REF], an 'AR by laser' technology developed by Airbus. ORION will analyze new ways for laser programming besides numerical control and will provide a 3D simulation tool. Also it will propose a data model to integrate the iDMU with the AR laser system and to facilitate the laser programming and execution.

ARIADNE project functional architecture

ARIADNE architecture is a consequence of the conclusions and the proposed future work in CALIPSOneo project in 2013. CALIPSOneo architecture for a collaborative environment was CATIA v5 in conjunction with DPE (DELMIA Process Engineering) to hold the process definition in a database (also called Manufacturing Hub by Dassault Systèmes). The architecture in CALIPSOneo, although still in production in Airbus and available in the market, is not and architecture ready to support the requirements from Industry 4.0 and is quite out of phase in technology to connect or communicate with today's technology.

To develop MINOS, the decision on the tool to support it was 3DExperience a natural evolution of CATIA v5. Data used in MINOS, the Airbus military transport aircraft A400M Empennage shown in Figure 3a, are in CATIA v5 format. To keep the 3DExperience infrastructure simple, and thanks to the relative low volume of data of the A400M empennage, a single virtual machine with all the required servers were deployed for the project.

For the interoperability between CATIA v5 and 3DExperience, CATIA v5 the input data are stored in file based folders containing the geometry in CATPart and the product structure in CATProduct as Figure 5. FBDI (File Based Data Import) is the process provided by Dassault Systémes that reads and or imports information (geometry and product structure) into 3DExperience. The option 'Import as Native', selected in FBDI will read the CATIA v5 as a reference, meaning, creating a 3D representation in 3DExperience as in CATIA v5, but will not allow it to be modified. Resources and assembly processes will be designed in 3DExperience based on the product (in CATIA v5) previously imported. For the interoperability analysis, the wing tip of the Airbus C295 (a medium range military transport aircraft) was chosen.

Developments in HELIOS and ORION will be based also on CATIA v5 data availability.

ARIADNE pretends to use only off-the-shelf functionalities offered natively by 3DExperience with no additional development.

Implementation and results

Collaborative Engineering, interoperability and iDMU exploitation are the targets in the different work packages of ARIADNE. The implementation and results are described in this section.

Collaborative Engineering

Collaborative Engineering requires an integrated 3D environment where functional and industrial engineers can work together influencing each other. The main driver for the Collaborative Engineering method is the construction of the iDMU. ARIADNE is focused in the collaboration between the functional design and industrial design teams. ARIADNE will check if 3DExperience provides such environment to build the iDMU where Collaborative Engineering can be accomplish.

To analyze 3DExperience collaborative environment a few use cases were defined and tested with the Airbus A400M empennage product represented in Figure 2a.

One of the bases to integrate the information in a PLM is to be able to hold the different ways or views (As-Design, As-Planned, As-Prepared) [START_REF] Mas | Proposal for the conceptual design of aeronautical final assembly lines based on the Industrial Digital Mock-Up concept[END_REF], shown in Figure 2b, for defining the product in Airbus. Keeping these views connected is basic to the Collaborative Engineering [START_REF] Mas | iDMU as the Collaborative Engineering engine: Research experiences in Airbus[END_REF]. In the work performed it was possible to build the As-Design view. Following, the As-Planned view was built from the As-Designed view while sharing the same 3D geometry for each of the structures. This is represented in Figure 3b. The third structure created in ARIADNE, which is the main one used for the industrialization of a product, is the As-Prepared. This structure is also a product structure rearranged as a result of the different assembly processes needed to build the product. The As-Prepared tree organization shown in Figure 4a is a consequence of the network of assembly processes. To build such network, precedence between assembly processes and operations must be assigned as in Figure 4b. Also tools like Gantt representation in Figure 4c helps deciding the precedence based on constrains (resources and times). Additional functionality for balancing constrains is too basic in 3DExperience for Airbus product complexity. Optimization tool is not offered by 3DExperience. Additional development would be needed to cover these last two functionalities [START_REF] Rios | A review of the A400m final assembly line balancing methodology[END_REF].

c) Operations Gantt chart

The iDMU was built by assigning product and resources to each operation together with the precedence. With such information in the iDMU, the use case design in context was performed. The design of an assembly process or a resource requires the representation of the product and the industrial environment based on the operations previously performed. This context was possible to be calculated and represented in 3DExperience.

The reconciliation between As-Planned and As-Prepared was tested to make sure that every product was assigned to a process. This functionality is also shown in the tree process structure with color code nodes. ARIADNE analyzed the capabilities to check how functional designers and industrial designers could carry out their activities influencing each other. For this, a mechanism to follow the evolution of the maturity states of the product, process and resources was proposed [START_REF] Morales-Palma | Managing maturity states in a collaborative platform for the iDMU of aeronautical assembly lines[END_REF]. This mechanism is intended to foster an interaction between both design areas.

3.3

Interoperability CATIA v5 and 3DExperience.

Recent developed aircrafts (A380, A350 and A400M) in Airbus have been designed in CATIA v5. Migration of a complete product design of an aircraft requires a high effort in resources and cost. Finding a solution where the product design can be kept in CATIA v5 while downstream product lifecycle uses a more adequate environment to cover their activities becomes a target for MINOS work package.

MINOS analyzed the degree of interoperability between 3DExperience and CATIA v5. Interoperability in this use case is understood as the set of required characteristics to develop the industrialization activities performed by manufacturing engineering in 3DExperience without affecting the product design activities (functional design) of the design office performed in CATIA v5. Initially a reading of product design (product structure and product design) in CATIA v5 was carried out in 3DExperience, step 1 in Figure 5. Checking the result of such work in 3DExperience demonstrated a successful import of the information for the product structure and for the 3D geometry. Following, a modification was intro-duced in the CATIA v5 product, step 2 in Figure 5. FBDI process did detect such change of the product and propagated it in 3DExperience, step 3 in Figure 5. Also 3DExperience sent a warning to update the product structure with the modified product. An impact on the process and resources related to the modified product was performed based on functionalities provided by 3DExperience.

3.4

Interoperability and iDMU exploitation.

Due to the increasing added value that the iDMU provides, it becomes an important asset to a company. Once assembly processes are designed and stored in the iDMU, information to production lines to perform the tasks can be extracted with an automatic application system.

As the current production environment in Airbus is CATIA v5, extracting information from the iDMU is constrained to such environment. HELIOS has developed an interoperable framework based in a set of transformations to exploit the iDMU independently from the PLM vendor and STEP is the tool selected. The use case HELIOS is based on is the ORION UML (Universal Model Language) model. The ORION UML model is transformed (UML2EXPRESS) into a schema defined in a standard language such as EXPRESS [START_REF]Industrial automation systems and integration -Product data representation and exchange[END_REF]. The schema is the input to any PLM (CATIA v5 or 3DExperience) to extract the information from the iDMU with a second set of transformations (PLM2EXPRESS). This last transformation will generate the instantiated code (EXPRESS-i) with the required information. This standardized code will be the same input to the different laser vendors.

Currently, in Airbus, the SAMBAlaser [START_REF] Serván | Augmented Reality Using Laser Projection for the Airbus A400M Wing Assembly[END_REF] is in production for projection of work instructions. To enhance the SAMBAlaser functionalities, ORION work package has developed an integrated user interface with the laser system control, optimized the quantity of information to project without flickering and built a simulation tool to check the capabilities of projecting within an industrial environment without occlusion.

Conclusions

Main conclusion is the successful proof of concept of the existing PLM technology in an industrial environment.

As mentioned, first test of interoperability CATIA v5 and 3DExperience was successfully. As preliminary conclusions it would be possible for industrialization engineers to work in a more advanced environment, 3dExperience, while functional designers can keep working in CATIA v5. Additional in-depth use cases (annotations, kinematics, and tolerances) need to be performed to check the degree of interoperability.

The introduction of HELIOS as the framework that 'separates' or make any iDMU exploitation system independent of the PLM that support it, is an important step for interoperability between different PLM systems and vendor independency and also enhances the necessity to have a model based definition for the iDMU. Thus, once 3DExperience becomes the production environment in Airbus, ORION will not need to be modified. HELIOS will be able to support any other iDMU exploitation system just by expanding the UML model.

The three views interconnected (As-Design, As-Planned, As-Prepared) together with the capability of creating a network of processes and operations have proven to build an iDMU to support the collaboration engineering and the facilitation of the interaction between functional an industrial engineers. 3DExperience has demonstrated to provide an interoperable collaborative 3D PLM environment to the industrialization of aeronautical assemblies. However an enterprise organizational model must be put in place to bring together functional and industrial engineering as one team with the iDMU as the unique deliverable.

Since ARIADNE is a proof of concept, no direct estimates on cost, time or other benefits are measured. However, based on previous experiences, significant benefits (time, costs, and reduction of errors) are expected after the deployment phase.

5

Future work

The current status of ARIADNE project suggests some improvements and future work after the proof of concept of the technology. ARIADNE project has tested some basic 3DExperience capabilities. The need to explore the 3DExperience capabilities to support the industrialization of an aircraft requires launching additional industrial use cases to cover industrialization activities. ARIADNE project avoids developing IT interfaces. Connection and interfaces from other tools that provide solutions not fully covered by 3DExperience such as line or station balancing and optimization might need to be analyzed. ARIADNE objective was not to test computing performances. Performing stress test with high volume of data (metadata, 3D geometry) is another important point to study, mainly for the aerospace industry.

Figure 1 .

 1 Figure 1. ARIADNE project organization

Figure 2 .

 2 Figure 2. a) Empennage A400M. b) Airbus product viewsA set of additional functionalities were performed in the As-Planned view such as the possibility of navigating through the structure as well as in the As-Design or filtering of product nodes in the product tree. Reconciliation in 3DExperience has proven to be an important functionality to assure a fully connection As-Design and As-

Figure 3 .

 3 Figure 3. a) As-Design view. b) As-Planned view

Figure 4 .

 4 Figure 4. a) As-Prepared. b) Precedence between operations. c) Operations Gantt chart

Figure 5 .

 5 Figure 5. Interoperability CATIA v5 (functional design) and 3DExperience (industrial design)

Acknowledgments

Authors wish to thanks to Andres Soto, Gonzalo Monguió and Andres Padillo for their contributions. ARIADNE is partially funded by CTA (Corporación Tecnológica Andaluza) with support from the Regional and National Government.