Genyuan Fei

James Xiaoyu Gao
email: j.gao@gre.ac.uk

Dele Owodunni

Xiaoqing Tang

Oladele Owodunni

A Method for Engineering Design Change Analysis Using System Modelling and Knowledge Management Techniques

Keywords: Change management, Knowledge management engineering design, change management, system modelling, design conflict solving, knowledge management system

published or not. The documents may come

Engineering changes have been recognised as inevitable in complex engineering product development [START_REF] Huang | Current practice of engineering change management in Hong Kong manufacturing industries[END_REF][START_REF] Palani Rajan | An empirical foundation for product flexibility[END_REF][START_REF] Keller | Using an engineering change methodology to support conceptual design[END_REF]. They have great influences on downstream developing and production activities, thus making product development very costly and time consuming [START_REF] Huang | Current practice of engineering change management in Hong Kong manufacturing industries[END_REF]. Therefore, it is critical to keep them under control.

Engineering changes have also been recognised as a source of innovation and creativity which can facilitate evolutions of products and technologies [START_REF] Balogun | Re-conceiving Change Management:: A Knowledge-based Perspective[END_REF][START_REF] Jarratt | Environmental legislation as a driver of design[END_REF][START_REF] Eckert | Change and customisation in complex engineering domains[END_REF]. From this perspective, knowledge acquired from engineering changes is also very useful to product development in In the past, a lot of research has been done in engineering change management (ECM) regarding computerising traditional paper-based engineering change processes [START_REF] Huang | Development of a web-based system for engineering change management[END_REF], improving communicating methods between engineers [START_REF] Shiau | A distributed change control workflow for collaborative design network[END_REF], clarifying knock-on change effects between components [START_REF] Eckert | Supporting change processes in design: Complexity, prediction and reliability[END_REF]Clarkson 2006, Clarkson, Simons andEckert 2004). Most early research shows the efforts made in dealing with engineering changes in the manufacturing process. Recently, changes happening in the critical stage of product development, the product design stage, have been emphasised [START_REF] Mckay | Design change impact analysis during early design specification[END_REF]. It is recognised that the design stage of product development could determine the largest cost savings during the product life cycle. This means changes happening at the design stage would have a greater impact than those happening in the manufacturing phase.

This project focuses on analysis of changes and their propagations in the product design phase and solving design conflicts arising from them by using knowledge management technologies.

As an important part of product development, engineering change management (ECM) has been studied by many academia and industrial practitioners in the past decade. They have identified issues within engineering change management and tackled them with proposed solutions from different perspectives. An introduction of the concept of ECM and an overview of previous research is given below.

The Concept of Engineering Change Management

Although engineering change has been studied for many years, its definition varies according to statements of different researchers. [START_REF] Wright | A review of research into engineering change management: implications for product design[END_REF] defined engineering change as modification to a component of a product before it goes into production. Some researchers agree that engineering change is modification to dimensions, fits, forms, functions and materials to product or components after the product design is released (Huang, Yee andMak 2003, Kocar and[START_REF] Kocar | ADVICE: A virtual environment for Engineering Change Management[END_REF]. Whilst some other researchers view engineering changes as changes occur in a wider range from customer requirements to product in use [START_REF] Pikosz | A comparative study of engineering change management in three Swedish enginnering companies[END_REF]Malmqvist 1998, Eckert, Clarkson and[START_REF] Eckert | Change and customisation in complex engineering domains[END_REF].

While research focuses have been shifting over time, the scope of research on engineering change has been widened. The initial motive of studying ECM was to avoid engineering changes during the manufacturing process due to the adverse effects they cause.

The adverse effects caused in terms of delivery time, developing cost and product quality are noticeable but very difficult to estimate [START_REF] Huang | Current practice of engineering change management in Hong Kong manufacturing industries[END_REF]. Later on, people realised that engineering changes are actually inevitable. Therefore, researchers have turned to finding out how engineering changes go on and what kind of impacts they may cause [START_REF] Clarkson | Predicting Change Propagation in Complex Design[END_REF][START_REF] Kocar | ADVICE: A virtual environment for Engineering Change Management[END_REF][START_REF] Ouertani | Supporting conflict management in collaborative design: An approach to assess engineering change impacts[END_REF]. Recently, some researchers argue the benefit of engineering changes to innovation and creativity, which can enhance the competitiveness of companies. Thus some researchers have started to study engineering changes from perspectives of knowledge management and knowledge reuse [START_REF] Balogun | Re-conceiving Change Management:: A Knowledge-based Perspective[END_REF][START_REF] Palani Rajan | An empirical foundation for product flexibility[END_REF][START_REF] Lee | Capturing and reusing knowledge in engineering change management: A case of automobile development[END_REF][START_REF] Keese | Product flexibility measurement with enhanced Change Modes and Effects Analysis CMEA[END_REF].

The process of organising engineering change activities have also been explored in the past decade, in order to find most efficient and effective approach of engineering change management. A general process of engineering change has been proposed by [START_REF] Clarkson | Design process improvement: a review of current practice[END_REF]. This process includes six steps, namely engineering change request, possible solution identification, risk/impact assessment, solution selection and approval, solution implementation, and change process review. Although the general process of engineering describes a reasonable approach to addressing change issues in product development, in reality, different companies have quite different processes to deal with engineering changes in order to fit their specific organisational and production requirements [START_REF] Pikosz | A comparative study of engineering change management in three Swedish enginnering companies[END_REF][START_REF] Eckert | Change and customisation in complex engineering domains[END_REF][START_REF] Huang | Current practice of engineering change management in Hong Kong manufacturing industries[END_REF].

Change Propagation Analysis

One of the most difficult issues in analysing engineering change is that when a component is changed it may also change its related components [START_REF] Ariyo | Challenges in identifying the knock-on effects of engineering change[END_REF].

Therefore, an initial change may cause changes spreading at several structural levels.

Essentially, the reason why changes propagate is because of the dependency between components. This situation is so-called change propagation or the knock-on effects of changes, which makes change analysis very tricky. Some researchers have made some efforts in dealing with this issue.

Clarkson and his colleagues have proposed a method called change prediction matrix (CMP) to trace change propagations and analyse the impacts they may cause [START_REF] Clarkson | Predicting Change Propagation in Complex Design[END_REF]. The method transforms the dependency relationship between components in a product model to a design matrix. Based on this matrix, the likelihoods that potential change propagations may happen between components are estimated. Also in the same way, the impacts of these potential change propagations may cause have also been estimated. By combining the change likelihood matrix and the change impact matrix, a change risk matrix has been generated. With help of visualising method, change propagation paths and their relative risks have been clarified. In another study, Eckert and his colleagues (2004) have proposed a method to analyse change propagation at a parametric level and identify four types of change propagation behaviours, namely constants, absorbers, carriers, and multipliers. These four types of change propagation behaviours help to analyse change propagations that cross multi-levels. Four type of change propagation behaviours represent four situations when a change of a component propagating to another component via some other components, which includes changes being passed without effect, being reduced or eliminated, being replaced with new changes from the intermediate component, and being enhanced. This method has also been integrated with the CMP method to enhance the performance of change propagation analysis in product conceptual design [START_REF] Keller | Using an engineering change methodology to support conceptual design[END_REF]. [START_REF] Kocar | ADVICE: A virtual environment for Engineering Change Management[END_REF] have proposed a different method to analyse change propagations. They use visualisation technique and data mining technique to represent product models and find out dependencies between components. Users would be warned visually if potential change propagation is predicted to happen. [START_REF] Ouertani | Supporting conflict management in collaborative design: An approach to assess engineering change impacts[END_REF] has also proposed a visualisation tool called DEPNET to model product data and their dependencies within them. By using the product data dependent relationships, changes emerging during collaborative design process would be tracked down.

Information Systems for ECM

Although methods for engineering change management (ECM) have been proposed with rigorously analytical or reasoning approaches, designers will be easily exhausted before having investigated the entire search space [START_REF] Ariyo | Challenges in identifying the knock-on effects of engineering change[END_REF]. Therefore, it is important that computer aided tools have been developed and used in engineering change management. Previous investigations have shown that computer-aided ECM systems have been rarely utilised in companies [START_REF] Pikosz | A comparative study of engineering change management in three Swedish enginnering companies[END_REF]Malmqvist 1998, Huang, Yee and[START_REF] Huang | Current practice of engineering change management in Hong Kong manufacturing industries[END_REF].

Although some companies have used electronic documents management systems to replace paper-based ECM documents, the data are non-structural and it's difficult to semantically trace similar engineering change cases.

Although there are currently not many companies are using computer-aided systems to facilitate their engineering change management, there are some systems that have been developed by academia trying to enhance communication and information sharing in change management process. [START_REF] Huang | Development of a web-based system for engineering change management[END_REF]

Aim and Objectives of the Project

Based on previous research reviewed by the authors, some gaps in engineering change management have been identified. First, changes of functional requirements should be considered together with changes in the physical domain in the design phase. For example, in the domain definitions of the product design stage in the theory of Axiomatic Design [START_REF] Suh | Axiomatic design: advances and applications[END_REF], when the changes in physical components are considered, the changes in the functional domain and their effects on the physical domain have not been considered. Second, there is a lack of consideration of the impact of change solutions on the change propagation analysis. A lot of efforts have been made to predicting change propagations with predefined component interactions. However, specific solutions for change requests may dramatically change predefined interacting relationships between components, which may make predictions of later changes fail. Third, there is a lack of tools to help engineering designers reuse knowledge from previous cases regarding design change management in industry. In many design change cases, technical solutions for a design change request, or say for some similar design change requests, may have been re-developed on many other occasions. That may be because experience or This project therefore aims at dealing with changes in the functional domain and the physical structure domain of complex product design. It would help designers analyse design change propagations within these two domains. It would also help to solve design conflicts arising from design changes by reusing knowledge from previous design change cases. There are mainly three objectives, i.e., (1) dynamically capture changes and their propagations between functional requirements and physical structures; (2) identify and formalise design conflicts arising from design changes; and (3) use knowledge based engineering (KBE) technology to facilitate finding solutions for design conflicts from previous design cases. A method for design change management is proposed by putting the emphasis on analysis of changes in the functional requirement domain and the physical structure domain. A modelling method is employed to enhance the traceability of changes occurring between functional model and structural model. A matrix based method is constructed to capture dynamic change propagations between the two domains. In the end, a knowledge based method is developed to help to solve conflicts arising during design change analysis. An industrial example has been used to show how the method works.

Analysis of Design Change Management (DCM) Practices

Referring to literature reviewed above, most researchers focus on the engineering change analyses among physical components. Although some of them mentioned functional requirements would be influenced by changes of physical components, detailed discussion has not been made regarding how these influences happen and how to deal with them. In this section, changes taking place between the functional domain and the physical structure domain

Change of Functional Requirements

Change of functional requirements may have many reasons, for example, changes of customer demands, changes of government policies, or changes of project aims for better competing with rivals [START_REF] Rouibah | Change management in concurrent engineering from a parameter perspective[END_REF]Caskey 2003, Clarkson, Simons andEckert 2004). Changes occurring in functional requirements may affect three aspects of product design. (1) Functional requirement change needs to be verified according to customer requirements to make sure all the changes meet the original customer demands. As one of the most important inputs of a product design project, customer requirements should be monitored all the time during changes of functional requirements to make sure all the changes meet the original customer demands. (2) Any change of a functional requirement may result in potential changes of other functional requirements depending on the interrelationships among them. These changes will be captured in the functional requirement model so that causal impacts can be analysed and controlled. (3) Obviously, any changes in the functional requirement domain will affect physical structures which are correspondingly constructed according to functional requirements.

Change of Physical Structures

Change of physical structures is another important part of design change management. A lot of situations may give rise to changes in the physical structure design, for example, changes of functional requirement (discussed above), physical conflicts within solutions, solution changes on the supplier's side, technical innovation, manufacturing restrictions. Changes of physical structure may also directly affect three domains, namely the functional requirement domain, the physical structure domain itself and the manufacturing domain. In the functional the relationships between components and related functions need to be clarified. Therefore, any change in the physical domain needs be verified to make sure that target functional requirements have been met. In the physical structure domain itself, components are linked together by physical connections, which make it possible to realise demanded functions.

Change of a component may potentially change operations of other components, which in turn may change the realisation of related functions.

Figure 1 shows the change propagation routes within the functional domain and the physical structure domain, and the routes between them. For example, change of the functional requirement F n may require changes on components involved in the realisation of it, in this example let's say C 2 . The change of C 2 could have influence on C i via some behavioural or spatial relationships between them. C i is one of the components involved in the realisation of F i . Then C i needs to be checked against functional requirement F i to see if F i can be satisfied. If not, then C i or other components involved the realisation of F i may need to be changed to accommodate the influence of the previous change. These components may be also involved in realisations of other functional requirements (for example F 1 , F 2 in the diagram) so further changes may be needed. In this diagram, change of F n directly cause changes of its components and also indirectly cause changes of other components and functional requirements. In the manufacturing domain, change of physical structure may change downstream activities, such as manufacturing process planning, supply chain management, risk and cost evaluation. discussions in the last two sections, there is a lack of method for supporting tackling the change propagation process between the two domains, solving problems arising from the process and analysing change impacts. An important part of this paper is focused on developing such a method to bridge the gap. The matrix-based method for analysing change propagations has been described in section 3.

(Figure 1)

Conflict Solving in Design Change Management

Conflict solving is one of the most concerned issues in design change management. In many cases, changes of a component or a function may require other parts of the design to change correspondingly. Furthermore, changes of these parts would cause changes of more parts of the design. This effect is the so called change propagation or knock-on effect. Actually, the reason why a change of a part of the design causes changes of other parts is because the initial change of the design may harm or obstruct operations of other components or satisfactions of other functional targets, which can be seen as functional or structural conflicts. In other words, change propagations are caused by design conflicts. Once there is no design conflict arising from any design changes, the change propagation stops. Although many design conflicts may have been solved during the change implementation by experienced engineers, many others may not be recognised in the design phase due to the lack of systematic methods and they would have been carried over to the manufacturing phase which may cause a huge amount of cost in later phases. Therefore, an effectively analytical method is needed to identify conflicts in design change management and solve them as early as possible. The second aspect is regarding design conflict solving. During a company's daily operations, there are a lot of solutions that have been proposed by engineers in attempt to tackle design conflicts arising from product development. These solutions whether successfully implemented or just on sketches are important assets of the company which should be properly generalised and deposited in the knowledge repository of the company. Once new design conflicts emerge and there is no similar design change mode that can be referred to, engineers can follow a formalised route to try to find proper solutions for them.

The third aspect is to use design knowledge to facilitate change impact analysis. Some knowledge of physical structure development has always been studied by companies, for example knowledge regarding developing time, developing cost and developing risks of solutions, components and parts. When a design change is initiated, engineers not only need to find its solutions and solutions for propagating changes, but also have to estimate the overall impact caused by the initial design change by taking consideration of time, costs and risks for development of new solutions. Therefore, decisions can be made for whether it is worth proceeding or not, or which parts of these solutions need to be modified, in order to make sure the change impact will not be too heavy to afford.

The Proposed Methodology

Analysis of the DCM Process

There are three types of relationships existing in a product design, i.e., mapping relationship between functional requirements and physical structures, physical interaction relationship between structures, and spatial connection relationship between structures [START_REF] Christophe | RFBS: A model for knowledge representation of conceptual design[END_REF]. These relationships within product design largely cause change propagations. The method of design change management proposed in this paper is based on analyses of these three types of relationships.

The process of design change management has been depicted in Figure 2. The whole process can be divided into three main steps: (i) system modelling of the product design; (ii) change propagation analysis based on the composite matrix; and (iii) knowledge-based design conflict solving.

In the system modelling step, the product design with change (initial or propagated)

The Industrial Example Used

The industrial example used in this project to evaluate the proposed methodology is a cooling system which is a critical part of a wind turbine (Figure 3). This new model of wind turbine is under development in our collaborative company which is a pioneer in gearless wind turbine development. Nearly 2000 wind turbines (by May 2010) based on their solutions have been deployed in Europe, Asia and America. There is a real design change scenario that the wind turbine needs to be deployed in a very sandy environment so that air filtering measure of the cooling system needs to be suppressed to prevent more sands than normal from coming to the cooling system and damaging it. This change causes some knock-on effects that give rise to changes on other parts of the system. The methodology proposed in this paper is going to be used to solve this problem by modelling the cooling system, identifying design changes and related design conflicts, and solving design conflicts by using a knowledge-based system.

(Figure 3)

Modelling Methods Used in this Project

Modelling of engineering design includes three parts, namely functional structure model, physical interaction model and physical structure model. In this paper, modelling methods for functional structure and physical interaction are adopted from SysML™ which is a comprehensive system engineering modelling language (Object Management Group 2008). The reason of using SysML™ is because it is a standard modelling method having intuitively visual presentations, standard descriptive language and well software tool support. It can be Deleted: In this model, the initial design change may arise in the functional requirement domain or in the physical structure domain. When a change arises in the functional requirement domain, specifications of the changed functional requirements have been updated. By following the mapping relationship between functional requirements and physical structures, corresponding changes in the physical structure have been determined. Then connected physical components of the changed component have been identified and changes of interactions between them are clarified. After that, the functional domain has been checked to see whether these changed interactions between physical structures will influence the realisations of related functional specifications. If the functional specifications cannot be met, then these connected structures needs to be changed further in order to meet these functional specifications. Furthermore, more spatially connected physical structures and their related functional specifications need to be inspected until changes of structures do not influence functional specifications or the influence is tolerable. ¶ During proposed process of change management, knowledge of design changes has been used in order to solve design conflicts arising during change analysis. Also general knowledge regarding product development has been retrieved to evaluate the impact that each change may cause. ¶ Deleted: be Deleted: improved The next section presents further explanation of how potential propagating changes are identified.

(Figure 6)

Identifying Change Propagation and Design Conflicts

Change analysis is intended to uncover changes and their propagations by following connections within functional requirements and physical components and relationships between them. This section shows the idea of identifying change propagations and their impacts arising from a change of a component. The description of the method is associated with a scenario of improving air filtering as mentioned above and based on the composite matrix of change analysis (Figure 6). The process of identifying change propagation is described in the following steps. In this scenario, the change is triggered by a functional requirement called 'F2: Filter hot air'. Therefore, the analytical process starts from the function-component part of the matrix (the green part).

Step 1: Identify component changes caused by functional change. As mentioned above, because of the sandy environment where the wind turbine will be deployed, the current air filtering measure cannot meet the new functional requirement. In Figure 6, it shows components involved in the realisation of function, filter hot air (F2). In this case, there is just one component (C2, air filter mat) identified. To meet the sandy environment, the current air filter mat with a dust holding capacity 650g/m 2 needs to be changed to a more effective one with dust holding capacity 750g/m 2 . Step 2: Identify potential affected components. The component changed in the above step may change the physical statuses of flows going through it and also it may change its neighbouring components due to changes of its spatial characteristics. Led by component C2, the row shows flows and neighbouring components that are potentially affected by the change of C2. In this case, flow FL1 (air from the generator) and neighbouring component C1 (inner air incoming pipe) are related to C1. The flow FL1 also goes through C1, C3, C4, C5, so these 4 components may also be potentially affected by the change of C1. The side effects of changing the air filter mat is that the mat with higher dust holding capacity is thicker and it causes larger air pressure drop, which can significantly reduce the efficiency of heat exchanging.

F

Step 3: Check change effects with related functions. Components that are affected by the flows and the spatial connections need to be checked whether the changed flows or the changed spatial connections would affect the realisations of their related functions. In this case, the air flow after the filter mat has a lower pressure which means components C3, C4 and C5 would be potentially affected since the status of air through them is changed (see the column led by FL1). According to the analysis by engineers, the lower air pressure through C3 (inner fan) will weaken its performance. Also the lower air pressure through C4 (air heat exchanger) will reduce the efficiency of heat exchange. But it has almost no effect on C5 (the inner air outgoing pipe). The spatial change (thicker filter mat) has been considered as not noticeable change on C1 (inner air incoming pipe) since the change can be easily accommodated by the current design. Although in this case change caused by spatial connection is negligible, in many other cases it may be significant and corresponding changes need to be made. For example, in this case, change the component C1 or add some other structures to accommodate the changes caused by spatial connections. Therefore, in this case, C3 and C4 have been identified as affected components which need to be changed to accommodate the previous change on C2.

Step 4: Identify and solve design conflicts. By analysing affected components, design conflicts can be identified. Taking C4 as an example, the changed input flow is the incoming air pressure which is lowered and the affected parameter is the heat exchange efficiency which is also lowered. The effect means the heat exchange cannot meet the functional requirement F4. Therefore this design conflict needs to be solved. In this paper, we develop a knowledge based method to help designers find reference solutions from previous design cases. Detailed discussion of how to solve design conflicts using a knowledge based method is presented in section 3.3.

Step 5: Analyse change propagations caused by component changes in step 4. When a proper solution has been found in step 4, changes on affected components have been determined. These changes would potentially affect other components as well. In the above case, if component C4 has been changed flows FL1, FL2 and connected components C2, C6 may also be potentially affected. Thus, a next round of change analysis also needs to be carried out until there is no further change effect being identified, which means change propagation stops and change analysis initiated by the first change is finished.

Knowledge System Support for Design Conflict Solving

As the authors argued above, the reason why design changes propagate is that there are design conflicts between components when one or some of them changed. TRIZ, which is originated from Russia, is a set effective problem solving methods [START_REF] Altshuller | And suddenly the inventor appeared : TRIZ, the theory of inventive problem solving[END_REF]. The contradiction matrix and invention principles are useful tools of TRIZ for solving technical conflicts. The (2) generalise technical conflicts by using 39 engineering parameters; (3) find invention principles via a standard contradiction matrix; (4) explore specific solutions by following the indications of invention principles (Altshuller 1996, Fey and[START_REF] Rivin | Innovation on demand: new product development using TRIZ[END_REF]. Although techniques of problem solving of TRIZ are innovative and inspirational to engineers, the method is difficult to master without a lot of trainings and long-time experience.

In this paper, the authors proposed a knowledge-based method working in a similar way but more intuitive and easier to use. When a specific design conflict is identified during the change analysis, it will be formalised by referring to a set of predefined ontology. Then the formalised design conflict will be reasoned in the knowledge repository to find semantically similar generalised design cases. Therefore specific design cases which are associated with generalised design cases can be retrieved. These selected design cases will be used as reference solutions for the current design conflict. Figure 7 depicts the process of how design conflicts have been solved. (Figure 7)

Formalisation of Design Conflicts

Design conflict

Design conflicts are identified in the change propagation analysis based on the composite matrix. Occurrence of design conflict has been simply depicted in Figure 8 in order to help understand the idea. Given that component2 is one of the components serving a function, when there is a change request applied to a component (conponnet1) which has interactional connection with componnet2, it may change the input flow of component2, which may further affect its output flow. If the affected output flow cannot satisfy the requirement of the, then it's For example, in the cooling system, there are two characteristics of the heat exchanger are important to its functionality. One is the area of the heat exchanger surface. Wider surface can have a higher heat exchanging efficiency. The other one is the material that the heat exchanger is made of. Some material, for example bronze, has a better heat conduction performance than some others, for example steel.

The flow ontology and the behaviour ontology used in this paper are adopted from the work of Hirtz and his colleagues [START_REF] Hirtz | A Functional Basis for Engineering Design: Reconciling and Evolving Previous Efforts[END_REF]. They proposed a functional ontology, so called functional basis, contains generalised functions (called as behaviour in this paper to differ from the term function of design) and flows which are seen as a useful and comprehensive engineering functional ontology by the authors. Also the authors developed domain-based component ontology and its characteristics by synthesising terms used in the investigated company. The characteristics ontology associated with flow ontology is also developed by synthesising related work by other researchers. We adopt Protégé as an ontology editor to formalise predefined ontologies in computer language.

The tool which is developed by Stanford University is de facto in the academic area for ontology development.

Figure 10 shows some parts of the ontology, including definitions of flows, definitions of behaviours, and definitions of components.

(Figure 10)

The Knowledge System for Design Conflict Solving

Figure 11 shows the framework of the knowledge base for design conflict solving. When a design conflict arises from design change analysis, it is formalised in the way as discussed in section 4.1. The formalised model of the design conflict will then be thrown into the International Journal of Computer Integrated Manufacturing knowledge system. The system will reason in the knowledge repository by analysing the semantic similarities between different concepts to find most similar generalised design cases.

After that, design cases associated to these generalised design cases will be retrieved as reference solutions for the current design conflicts. Designers can adjust or adopt retrieved reference solutions to solve current problems. The method of generalising design cases is as the same as the way formalising meta-interactional-model. It collects design cases and formalises their target problems or functions. The generalised design cases work as indices of those associated physical design cases.

In this system, design cases are collected from many sources including different functional departments and IT systems. The design cases are formalised in a hierarchical way, which clarifies functions or problems a design case is to address, the solutions used in this design case, the components involved in this solution and characteristics that contribute to the realisation of the function or the problem solving. The formalised structure is also been generalised by the predefined ontology.

(Figure 11)

Reasoning method for design conflict resolving

The reasoning method is critical to finding reference solutions for design conflicts arising from design change propagation analysis. The general approach to solving design conflicts is depicted in Figure 12.

(Figure 12)

In the reasoning method, one of the most important steps is to analyse semantic similarities between formalised design conflicts and generalised design cases stored in the knowledge repository. Given that a design conflict is defined as a definition (D) and all of the Deleted: Therefore, the analysis of design conflict can be generalised by the same domain ontology and then find general solutions for that. The general solution can also be specified by following the relationship between the domain ontology and design cases. stored general design cases are defined as a set of definitions {D 1 ... D n }, the first step is to find the most similar solutions from the set of general design cases. The algorithm of calculating the semantic similarities between a formalised design conflict and a generalised design case is comparing the semantic similarity of each corresponding element and then adding them up to get an overall semantic similarity.

(Figure 13) Figure 13(a) represents hierarchically ontological definition of a group of concepts.

The higher of levels a concept stays in, the more general semantic meaning it represents. While in lower levels, the semantic meaning of a concept is more specific. In Figure 13(b), IC(S1) represents the semantic meaning of the concept S1. Since S1 is the parent of S11 and S12, S1 has a wider semantic meaning than S11 and S12, which means:

(1)

Theoretically, the following equation can represent how S11 (a child) is semantically similar to S1 (a parent) by comparing scales of semantic meaning of each concept:

(2) While the similarity of S11 (a brother) to S12 (a brother) can be expressed as:

(3) While in reality, it is well-known that exact semantic meaning of a concept is very difficult to measure. More often than not, people can tell the qualitative similarity between two concepts by their experience and common sense. Particularly, people in the professional area are better to tell similarities between concepts of professional terms some of which are not normally used by people out of the area. So in this research, a survey is developed and experienced engineers are interviewed to rate semantic similarities between child-concepts and their direct parent-concepts (e.g., Sim(S11, S1)), and also between their brother-concepts (e.g., Sim(S11, S12)). The survey and the rating process is a multi-criteria decision making process which is not discussed in details in this paper.

With rated similarities between parent-child concepts and brother concepts, the similarity of any two concepts (e.g., S111 and S22) can be expressed as:

(4)

Based on the ideas of rating and calculating similarities between concepts, the similarity between a formalised design conflict and a generalised design case can be described as:

Where DC represents design conflict, GD represents generalised design case, CF represents changed flow, and AF represents affected flow. Similarity between changed flows can be represented as:

(6) Similarity between affected flows can be represented as:

(7) By comparing the overall similarities between the formalised deign conflict and the generalised design case, a set of prioritised similarity values are generated: By exploring and reviewing design cases associated with retrieved generalised design cases from higher priority to lower priority, the suitable design cases are chosen as reference solutions for the target design conflict.

Results of the industrial example and system implementation

The example used in previous sections has been processed in this system. Application of the methodology has been partially displayed during the discussion of the methodology. In order to have an overview of the results and the general process in an intuitive way, a tabular form has been used to organise the results (shown in Figure 14).

(Figure 14)

A three-tier web-based pilot system has also been developed to implement the proposed methodology for engineering design change management. The pilot system is partly developed.

Integrations with other business systems like PDM, ERP and SCM are going to be done at the next stage of this research. Software systems involved in this prototype include MySQL as an infrastructure of data storage, Tomcat 6.0 as a web server and servlet container, Java enterprise edition (Java EE) as the business implementation architecture, and also Java Server Page (JSP) as a presentation technology. Figure 15 shows an overview interface of design conflict solving of design change analysis. The page shows the final stage of the design conflict solving analysis process, which is trying to get reference solutions from the knowledge repository to help designers work out a viable solution for the current design conflicts.

(Figure 15)

Conclusions and Further Work

Any design changes either in functional requirement domain or in the physical structure domain will potentially affect operations of other parts. Change propagations and their impacts are difficult to be captured, which makes product design in uncertainty. The authors argue that design change propagation is caused by design conflicts arising from the initial change and Many design conflicts arising from change analysis can be tackled by reusing well-formalised and managed knowledge abstracted from previous design cases. In this paper, a methodology for design change management has been proposed to implement these ideas by using modelling method, matrix analytical method and knowledge support. First, the system engineering modelling method captures critical interactions between functions and components. The matrix-based analytical method helps to trace change propagations and identify design conflicts by following mapping relationship between functions and components, and behavioural and spatial connections between components. By using the design conflicts formalisation approach, design conflicts can be formalised based on predefined ontology, which makes knowledge reasoning in the knowledge base possible. The framework of the knowledge base is proposed to collect knowledge of design change from previous design cases.

With help of the knowledge base and the reasoning method, designers are able to find proper solutions and evaluate their potential impacts. A prototype system has been developed to show that the idea of this paper is technically feasible and can benefit companies with IT approach to integrating with other enterprise systems will be developed. This approach is to acquire knowledge regarding contributions that previous products make to related projects in terms of factors of project success. With help of knowledge acquired, an algorithm will be developed to calculate change impact more accurately. Comments to the Author This manuscript presents a novel methodology that has been developed to help designers trace, analyse and evaluate engineering changes occurring in the product design phase. However, the major problems about this manuscript are as follows:

1. Both "modelling method" and "matrix based method" have been well developed; it is hard to find innovative points in the proposed methodology.

Response: We do not claim that SysML modelling method is an innovative point in this paper, but it is a necessary tool for clarifying functional requirements and interactional relationship between components.

The composite matrix-based method is new and different from the ways that other researchers proposed, which contains three types of the relationships in one model, which enables to track change propagations dynamically with consideration of three types of relationships together. Therefore it can help identify design conflicts. The composite matrix can repeat as many times as needed to continuously refine the design.

2. The proposed process of design change management (Figure 2) is one of the most important results of this study. It should be better to explain specifically that how to come out the results.

Response: The diagram of design change management has been redrawn and the description of the process has been rewritten in order to be more specific.

3. Why use ontology to proceed the design conflict solving in section 4?

Response: Ontology is defined and used to formalise design conflict and problems/functions that previous design cases have resolved/realised. Therefore, a generalised design conflict can be semantically compared with generalised previous solved problems/functions so that reference solution can be found. Development and use of ontology have been presented in section 4. 4. In the manuscript, some paragraphs are too long and should be shortened.

Response: Some parts of the paper have been rewritten or improved to make it more concise. Response: Some figures have been improved to make them more legible.

Figures should be simplified

Response to the first referee's comments:

Comments to the Author Page 5 and page 7: Pikosz 1998 has to be changed to Pikosz and Malquist 1998 Response: Corrected Page 12: last paragraph before Figure 1 : How to be sure that finally the solution will be found ? Is there a unique solution to this change propagation process? Please justify and clarify this issue.

Response: This part of the paper is supposed to explain how changes propagate between the functional domain and the physical domain of design, which is one of the findings from analysis of design change management practices. Sorry that the problem was not explicitly given. It has been revised by adding the declaration of the problem from this part of the findings and what this paper is to offer.

The change propagation analytical process is described in section3. A knowledgebased method for solution finding is presented in section 4 with some improvements. In the same section: "By following the mapping… have been determined". This supposes that there is always a solution. Who is going to choose/ to decide/ to validate the changes? A KBE system or a designer? Please comment and justify.

Response: Yes, as an important part of the research, there is a method for finding proper solutions for design conflicts, which is described in section 4 regarding using a knowledge-based system to solve design conflicts. The description of section 4 has been enhanced. The expression of this sentence may not be proper. Description of the process has been rewritten and better explained in section 3.1 Page 15 same section: "Futhermore, more spatially… is tolerable." Does this mean that each function corresponds to different performance indicators, with respect to given ranges of possible values (for example, does it has to be between amin and amax)?

Response: At the end of the early product design (conceptual design), functional requirements of the design and their specifications should be clarified. Yes, as you mentioned, the specifications are usually given as ranges of values that the outcomes of the functions will drop in. Any outcomes dropping out of the range means their corresponding functional requirements having not been satisfied and which also means 'intolerable'.

Page 15, same section: "During proposed process…that each change may cause." This is the theory. But how is this done in practice?

Response: This part has been rewritten and better explained how design knowledge is used in design conflict solving. The solution for using knowledge of previous design cases are better explained in section 4 by adding the method of semantic similarity comparison.

Impact evaluation using general knowledge is a part of the further work and will not be discussed in detail in this paper Page 15: "cooling system needs (be to be suppressed) to be improved" Response: Corrected Page 16: Figure 4: what does "specifications" attribute of "cool down the generator" function represent? Specifications should concern each function. Are all functions independent? Please justify and proof.

Response: The functional specification has been better explained in section 3.3.

Functions are not required to be independent in this proposed methodology. Functional dependency is not concerned in this paper. The change propagation analysis just concerns three types of relationships: mapping relationship between functional requirements and physical components, interactional relationships between components and spatial relationships between components.

Response:

The proposed composite matrix is used to help solve this problem. Please refer to section 3.4 Page 18: "A marked cell… in the row." This means that there is a kinematic assembly liaison between these two components? Please clarify.

Response: Yes, the spatial relationships represented by marked cells include static and kinematic physical connections based on assembly relationships but excludes any flow-based interaction. A bit more explanation has been added in Section 3.3 paragraph 3.

Page 18: "In this case, ……..holding capacity 750 g/m2." In this case, the change of the characteristics of the component is enough (a filter with different characteristics is adopted) but sometimes, for example, because of improvements of resistance and mechanical characteristics, one component has to be transformed in several ones. How this aspect is managed? Please clarify and justify.

Response: Method of change propagation analysis can accommodate multiple component changes. When change decision has been made, designers need to restructure those three models and the composite model as well. If the change decision involves changes to multiple components, those components will be modelled in those re-structured models. Any propagated changed caused by them will be further analysed. The process is described in section 3.1, where the diagram has been redrawn and the description of the process has been rewritten. propagation of this choice and the obtention of the new "coherent" system with the new characteristics? Please clarify and justify.

Response: When reference solutions have been retrieved and selected, designers need to work out a proper solution based on the reference solutions. Then the designers need to go back with the improved design and re-structure the models. They will do the change propagation analysis again and make sure there is no significant impact on other functions. The process of design change analysis has been improved in Figure 2, which better explains the approach.

"is caused by design (instead of deing)"

Response: Corrected

Concerning the reference list: please decide either this is necessary to develop all the "et al." list of authors or not. But please, put it coherent in the list and in the text.

Response: Improved

Page 40, Figure 11: please change "volecity" to "velocity" in the second column from the right.

Response: Corrected

Editor Comments 1. Please revise your paper and respond to the referees comments in a separate .doc file and submit this with the revised manuscript.

2. Please have your paper proof read by a native English Speaker or a person more familiar with the English language.

  . Despite of the different perspectives, both of the two arguments reflect the importance of engineering change management in product development.

  Do and his colleagues (2008) have also proposed a method for tracking engineering change propagation between different product data views based on a shared base product model. The method reduces data redundancy in engineering change management and maintains consistency between different product data views.

  developed a web-based system to implement the whole process of engineering change management, including engineering change log, engineering change request, engineering change evaluation and engineering change notice. The distributed system has improved the efficiency of ECM and enhanced the collaborations between engineers. Also structural ECM data make it possible to integrate with other computer-aided systems such as Product Data Management (PDM), Enterprise Resource Planning (ERP), Computer Aided Design (CAD) and Supply Chain Management (SCM). Ouertani and Gzara (2008) have developed a system called DEPNET to visually track dependencies within product specifications so that change propagations can be captured if any design changes of a product specification happen. As mentioned above, Kocar and Akgunduz (2010) developed a track change propagation which is well integrated with 3D modelling system. Lee and his colleagues (Lee, Ahn, Kim and Park 2006) developed a knowledge based system to facilitate engineering change management in a collaborative environment. The authors have used ontology technology and case based reasoning method to construct a knowledge base of previous development experience. It also implements the knowledge base with a web-based system which enables users go through the whole engineering change management process from change request initiated to change approved.

  previous design change cases have not been formalised and shared effectively.

  design stage have been discussed. Additionally, knowledge use during design change management at this stage has also been covered.

  International Journal of Computer Integrated Manufacturing requirement domain, any changes in the physical structure may change target outputs of related functions. Since one component is possibly involved in realisations of more than one function,

  Impacts on these product development activities need to be analysed or re-evaluated. Although change propagation between the functional domain and physical domain looks obvious from

  Use in Design Change ManagementKnowledge use is critical for design change management to ensure results from change analysis are fact-based and consistent. There are mainly three aspects where design knowledge can be used to help solve change problems.The first aspect is to identify design change modes. The design change mode is structured records of design changes implemented in previous applications. The point of having design change modes formalised in a knowledge repository is for frontline design engineers to find out whether similar design changes have happened. They can use these similar design change cases (if there is any) as references to help to find proper solutions and estimate potential change propagations and their impacts.

  applied has been modelled by three types of models, i.e., the functional structure model (in the form of SysML block definition diagram), the physical interaction model (in the form of SysML activity diagram) and the spatial connection model (in the form of CAD model). Each model clarifies one aspect of the product design correspondingly. By synthesising the relationships obtained from these three models, a composite matrix has been generated which is critical to change propagation analysis. Differing from other matrix-based methods in some research in change propagation analysis, the composite matrix combines three types of design together and provides an intuitive and dynamic way to capture change impacts across components and their functions. Explanation of each step is given in section 3.3.In the change propagation analysis step, the design change has been examined by checking changes to related flows (representing interactions between components) and spatial connections. Any components connected with these flows and spatial connections are then examined with functions that they serve for. If the effects on the components, which are caused by changes of those flows and spatial connections, make realisations of corresponding functions fail, it means there are design conflicts existing which are caused by the design change. Design conflicts are then identified during the analysis with the composite matrix. The process of change propagation analysis using the composite matrix is described in detail in section 3.4.In the knowledge-based design conflict solving step, design knowledge which is acquired from previous design cases is used to help solve design conflicts identified in the last step. Firstly, design conflicts are formalised by using pre-defined engineering ontology. Secondly, the formalised design conflicts are reasoned in the knowledge repository by semantically comparing with formalised general design cases stored in the knowledge repository. General solutions in the knowledge repository are formalised by the same set of the pre-defined engineering ontology. Thirdly, a prioritised list is generated with the most semantically similar general solutions at the top and the designers check those general solutions starting from the top of the list and their related design cases to find reference solutions for the design conflicts. At last, based on the reference solutions, proper solutions are worked out by designers and change decisions are made. The design with changes generated in International Journal of Computer Integrated Manufacturing this step will be re-modelled and further possible change propagation are analysed again as what is done in the last two steps. (Figure 2)

  Figure 5. When there are changes happening on a component (an element in the first column), related flows going through it will be identified in the matrix. Components that these flows go through are also identified. The third part (the grey part) represents the physically spatial

  International Journal of Computer Integrated Manufacturing idea of TRIZ to solve conflicts includes generally four steps: (1) identify technical conflicts;

Formatted

  Figure 10). The component is also formalised by the behaviour ontology and the component ontology. The behaviour ontology defines what the component does with the input flows and generates the output flows. The component ontology defines which type of components it is. The component ontology contains related component characteristics as its properties. These component characteristics are critical for the performance of the operation of the component.

Formatted

  Design conflicts, identified through the matrix-based analysis in the above section, need to be formalised with defined ontology which is the basis of the knowledge system. Deleted: the Deleted: design conflict Deleted: design conflict Deleted: s Deleted: that cause the conflict Deleted: that are affected by the changed input flows Deleted: , the behaviour ontology Deleted: the Deleted: ontology Deleted: the Deleted: possesses Deleted: The behaviour ontology defines the how the flow is changed, which is used with the characteristics and/or other flows or objects. Deleted: functional Deleted: functional Deleted: and what object the component uses while it operates Deleted: is also Deleted: defined by the component ontology which is also associated with the characteristics ontology

  The functional ontology includes three types of ontology, namely the behaviour ontology and the flow ontology.Deleted: ontology to classify products, subsystems and Deleted: s Deleted: wind turbine Deleted: Examples for these ontologies can be found in system implementation section.

Formatted

Formatted

Formatted

  Change propagations are difficult to predict without knowing their preceding change solutions since all following changes are based on the solutions of preceding changes. Knowledge from previous design change cases is an important asset for companies.

  technologies. The emphasis of further work will be put on development of methods for evaluating design change impact in terms of factors of project success. Any changes made in product development need to be evaluated in terms of development time, development risk and development cost. However, in practice, impacts of design changes are normally estimated by experienced engineers or other staff in the company. The results of change impact evaluations Deleted: functional ontology and systemInternational Journal of Computer Integrated Manufacturing could be very inconsistent with estimations from different people who have different experience and different knowledge backgrounds. In the next stage of this research, an

Figure 1 .Figure 8

 18 Figure list:

Figure 3 .Figure 10 .

 310 Figure 1. Design changes between functional and physical domains

  to illustrate and support the text.Response: Some figures have been redrawn and improved texts in some figures are too small and not clear.

Page 14 :

 14 Paragraph 3 -section 3.1 When you write "There are three types… and physical structures", Please refer to paper: F. Christophe, A. Bernard, E. Coatanéa (2010), RFBS: A model for knowledge representation of Conceptual Design, CIRP Annals -Manufacturing Technology, Vol 59/1/2010, pp.155-158 ( doi:10.1016/j.cirp.2010.03.105) Response: Reference added. Thanks a lot.

  Page 17: Figure5shows the interaction… functional requirements." This is true but what is proposed in your method to face and solve/ help solving this problem? Please justify and clarify this point.

  based (instead of base)"Response: Corrected "then, the generalized the (to be deleted) problem" Response: Corrected "similar cases": what does it mean? How the similarity analysis is proceeded?Response: The idea of similarity analysis has been added in section 4.3 "Figure8shows… a design conflict." It seems that there is no "conflict" within Figure8. Please clarify.

  Figure 8 has been improved. It's not accurate to name the model as a design conflict. It's actually a meta -model of interactional behaviour which would potentially cause design conflict if the affected output flow causes related functions cannot be realised correctly. The description has been improved. Page 22: "The flow ontology… The Characterics ontology…" In Figure 9, there is no flow ontology, no characteristics ontology. Please clarify and put it coherent. Response: The flow ontology and behaviour ontology have been added. They were previously combined together in the first part of the diagram. The characteristics ontology and its relation to the flow ontology has been displayed in the same figure.

"

  Figure12shows… design conflicts." This means that the system proposes some alternative solutions, then the designer chooses one of them. But what about the

Acknowledgements

This project has been supported by the wind turbine design company Vensys Energy AG in Germany and the leading wind turbine manufacturer Goldwind Ltd in China. Some of their engineering designers provided advice in developing the methodology and the illustrative example.


Sandy Faye

Jean-Louis Moyen

Hélène Gares

Jean-Jacques Benet

Bruno Garin-Bastuji

María-Laura Boschiroli
email: ml.boschiroli@afssa.fr

Determination of decisional cut-off values for the optimal diagnosis of bovine tuberculosis with a modified IFNγ assay (Bovigam ® ) in a low prevalence area in France

The Bovigam ® gamma interferon (IFNγ) assay was used to complement official skin-test screening in a low bovine tuberculosis (bTB) prevalence region in France.

The aim of our work was to determine decisional cut-off values for protein purified derivatives (PPD) and ESAT6-CFP10 antigens (R) in order to optimize the efficacy of the

The sensitivity of the IFNγ assay relative to post-mortem bTB-positive animals (Se r ) was studied in 60 cattle from 20 bTB-infected herds. Its absolute specificity (Sp) was studied in 492 cattle from 25 bTB-free herds from a bTB-free zone. Its operational specificity (relative to the positive skin test) (Sp r ) was also studied in 547 skin-test positive cattle from 172 bTBfree herds from an infected zone.

Using normalized interpretations for individual (PPD or R) results, the cut-off values at 0.02 for PPD and 0.01 for R were obtained with a view to employing them in low prevalence areas with no previously observed non-specific reactions to SITT.

Concerning its use after positive skin tests, cut-off values were set at 0.05 for PPD and at 0.03 for R. The choice of an interpretation method considering positive results with PPD and/or R (PPDUR), justified in a high risk context, provided a test Se r of 93% [84][85][86][87][88][89][90][91][92][93][94][95][96][97][98] and Sp r of 71.8% [67.9-75.6]. Analysis of positive results with PPD and R (PPD∩R), ideal for low-risk contexts, provided a test Sp r of 94.3% [92.0-96.1] and Se r of 77% .

Thus, adapting the criteria to the region's infection status and to the conditions for its application is essential for the appropriate use of the IFNγ assay.

Keywords: Bovigam ® IFNγ assay, ESAT6-CFP10, Diagnosis, Cut-off, Sensitivity, Specificity.

Introduction

Bovine tuberculosis (bTB) is an important zoonosis found throughout the world which is particularly difficult to control and eradicate. France has been officially bTB-free since 2001, however, the number of infected herds in the south-west rose to 10-20 per year between 2003 and 2006 [START_REF] Anonymous | Bilan du rapport annuel ruminants[END_REF], despite strict bTB regulations.

BTB-infection status in a herd is officially established if Mycobacterium bovis is confirmed by bacteriology from at least one animal, or if bTB-like lesions are detected by histology from a positive single intradermal comparative cervical tuberculin test (SICTT) from the animal. In

France, official screening of bTB is based on the skin test. The frequency of skin test controls depends on the area's bTB prevalence. Pre-movement controls have not been mandatory since

2005.

A single intradermal cervical tuberculin test (SITT) [START_REF] Benet | Tuberculose Bovine[END_REF]) is carried out first, which, if positive (i.e. detecting an increase in skin thickness at the bovine tuberculin injection site of more than 2 mm), leads to the herd being disqualified and activity being suspended until a SICTT is carried out six weeks later. In the event of a negative SICTT result (i.e. if the bovine reaction is less than or equal to 2 mm or if the bovine reaction is greater than 2 mm but the difference between bovine and avian reactions is less than 1 mm), the herd is considered as bTB-free; on the contrary, if the SICTT result is positive (i.e. if the bovine reaction is greater than 2 mm and the difference between bovine and avian reaction is greater or equal to 1 mm), diagnostic culling of the affected animal is carried out. However, there are certain disadvantages to the skin test such as subjectivity in result interpretation, lack of specificity for the SITT and lack of sensitivity for the SICTT. An alternative diagnostic test, the gamma interferon (IFNγ) assay, allows early detection of bTB [START_REF] Buddle | Immunological responses and protection against Mycobacterium bovis in calves vaccinated with a low dose of BCG[END_REF][START_REF] Buddle | Advances in ante-mortem diagnosis of tuberculosis in cattle[END_REF]Wood et al., 2001;[START_REF] Gormley | Diagnosis of Mycobacterium bovis infection in cattle by use of the gamma-interferon (Bovigam ® ) assay[END_REF]De la Rua-Domenech et al., 2006a, 2006b;Vordermeier et al., 2006). In contrast to the skin test, the IFNγ assay is a laboratory test that can be standardized, whose results can be interpreted objectively, independent of veterinary practitioners. Moreover, it can be carried out without any delay between the two analyses.

Due to the rise in the incidence of bTB in the region, preventive measures have been strengthened and the Bovigam ® IFNγ assay (Prionics), has been included as an additional diagnostic tool to reinforce the skin test findings.

Since 2006, the Bovigam ® assay has been included in surveillance programs to allow the rapid confirmation of positive SITTs (serial use) and also for simultaneous use with SITTs for epidemiological studies (parallel use) in this French region. ESAT6 and CFP10, M. tuberculosis complex specific antigens (from the Statens Serum Institut, SSI), have also been used to improve IFNγ assay specificity [START_REF] Aagaard | Optimizing antigen cocktails for Mycobacterium bovis diagnosis in herds with different disease prevalence: ESAT6/CFP10 mixture shows optimal sensitivity and specificity[END_REF], especially in population groups testing positive to the SITT. In addition, several modifications to the original protocol [START_REF] Faye | Study of the specificity and the sensitivity of the dosage of the interferon gamma technique to the cattle for the diagnosis of bovine tuberculosis[END_REF][START_REF] Schiller | Optimization of a whole-blood gamma interferon assay for detection of Mycobacterium bovis-infected cattle[END_REF] have been introduced to optimize the test in a context of low bTB prevalence.

The aim of our work was to determine decisional cut-off values for the protein purified derivatives (PPDs) and specific antigens (ESAT6 and CFP10) in order to obtain optimal results in terms of sensitivity and specificity from this modified use of the Bovigam ® assay in a low-prevalence area, in the region's infected or non-infected cattle population or after positive SITT responses.

Materials and methods

The IFNγ assay sensitivity study, relative to post-mortem bTB positive confirmation (Se r ), was conducted retrospectively using the results obtained during the 2006-2007, 2007-2008 and 2008-2009 bTB control programs in the affected French south-west region.

The IFNγ assay absolute specificity (Sp) study was performed in early 2008 in the same region [START_REF] Faye | Study of the specificity and the sensitivity of the dosage of the interferon gamma technique to the cattle for the diagnosis of bovine tuberculosis[END_REF].

Cut-off values to determine optimal Se r and Sp values were obtained by combining the results of the two studies (Se r & Sp).

However, since the IFNγ assay was widely used as a routine SITT confirmatory tool, the operational specificity of the IFNγ assay, i.e. its relative specificity to positive SITTs (Sp r ), was also studied. This was carried out using the results of the 2007-2008 bTB control program.

I. Description of the IFNγ method employed

I.1. Cellular stimulation and IFNγ dosage: Micro-method

The guidelines for the use of the Bovigam ® kit were those provided by the manufacturer, although the initial volumes for cellular stimulation were reduced (micro-method) as similar results are obtained with either of these methods [START_REF] Schiller | Optimization of a whole-blood gamma interferon assay for detection of Mycobacterium bovis-infected cattle[END_REF].

Cellular stimulation was performed in duplicate in a 96-well plate. The bloods were processed on the day of collection (6-8 hours max delay). Each aliquot of blood ( 250 After 16-24 h incubation at 37°C in a humidified atmosphere, the plate was centrifuged for 10 minutes at 500 g to facilitate plasma collection.

IFNγ concentrations were determined for each supernatant plasma (tested in duplicate), using the sandwich enzyme immunoassay (EIA) method (see Bovigam ® documentation). Bovigam ® negative (NC) and positive (PC) controls were used. An additional external positive control, a homemade tracer consisting of a pool of positive IFNγ cattle plasma with a constant and well known optical density (OD) value, was also used in order to evaluate the test's reproducibility.

I.2. Method of interpreting results

The different control values (NC and PC) used for validating EIA were those of the manufacturer. The control values (PWM and PBS) used for validating the samples' quality were the following: OD PWM -OD N >0.40 for PWM [START_REF] Faye | Study of the specificity and the sensitivity of the dosage of the interferon gamma technique to the cattle for the diagnosis of bovine tuberculosis[END_REF] and OD N <0.30 for PBS (as previously described by [START_REF] Coad | Blood-based assays to detect Mycobacterium bovis-infected cattle missed by tuberculin skin testing[END_REF]. The level of variation between duplicate samples was below 10 %.

A new result interpretation calculation formula was used. It takes into account the NC and PC results per analysis plate, and thus absorbance variations due to analytical conditions (recommended by the French standard for EIA (NF U47-019)) and used by [START_REF] Olsen | Bovine NK cells can produce gamma interferon in response to the secreted mycobacterial proteins ESAT-6 and MMP14 but not in response to MPB70[END_REF]: (OD B -OD A )/( OD PC -OD NC ) for PPD and (OD R -OD N )/( OD PC -OD NC ) for R. [START_REF] Faye | Study of the specificity and the sensitivity of the dosage of the interferon gamma technique to the cattle for the diagnosis of bovine tuberculosis[END_REF].

Consequently, the 0.1 cut-off recommended for the Bovigam ® kit has been adapted with a formula including median OD PC -OD NC at 2.40: (OD B -OD A )/(OD PC -OD NC )= 0.10/2.40= 0.04

A c c e p t e d M a n u s c r i p t FAYE S 7/7 19/02/2011 [START_REF] Faye | Study of the specificity and the sensitivity of the dosage of the interferon gamma technique to the cattle for the diagnosis of bovine tuberculosis[END_REF]. The PC and NC OD values (for each analysis plate) are those obtained from our sensitivity and specificity studies.

Thus, the individual positive results of the IFNγ assay were as follows:

Positive result in PPD if (OD B -OD A )/( OD PC -OD NC ) ≥ selected cut-off Positive result in R if (OD R -OD N )/( OD PC -OD NC ) ≥ selected cut-off
The final result of the IFNγ assay is determined according to the combined individual results

of PPD and R. It is divided into 3 categories: positive (POS, positive individual results), negative (NEG, negative individual results) and divergent (DIV, different individual results), [START_REF] Faye | Study of the specificity and the sensitivity of the dosage of the interferon gamma technique to the cattle for the diagnosis of bovine tuberculosis[END_REF].

II. Specimen description and processing

II.1. IFNγ assay sensitivity study in relation to post-mortem bTB positive confirmation (Se r )

The IFNγ assay sensitivity study in relation to post-mortem bTB confirmation (Se r ) was carried out retrospectively in 73 cattle from 28 recognized bTB-infected herds (i.e. where at least one animal has been found to be culture-positive for M. bovis) from a high-prevalence zone in the studied region. All these cattle presented bTB-like lesions at the slaughterhouse and were thus considered bTB-positive (as described by [START_REF] Gormley | Diagnosis of Mycobacterium bovis infection in cattle by use of the gamma-interferon (Bovigam ® ) assay[END_REF]. In addition, 40 of these 73 animals were further analyzed and confirmed as bTB-infected by different direct diagnostic methods: 26 at least by culture and 14 at least by Mycobacterium tuberculosis complex PCR and/or histology [START_REF] Faye | Study of the specificity and the sensitivity of the dosage of the interferon gamma technique to the cattle for the diagnosis of bovine tuberculosis[END_REF].

Collection of these blood samples was carried out between 3 and 10 days after the SITT.

II.2. IFNγ assay absolute specificity study (Sp)

A c c e p t e d M a n u s c r i p t

FAYE S 8/8 19/02/2011
IFNγ assay absolute specificity (Sp) was studied in 492 cattle from 25 bTB-free herds (i.e.

where no cattle have been found to be culture-positive since 2001) from a bTB-free zone (no positive animal in any of the screening tests (SITT and SICTT) and no recognized outbreak for at least 10 years), [START_REF] Faye | Study of the specificity and the sensitivity of the dosage of the interferon gamma technique to the cattle for the diagnosis of bovine tuberculosis[END_REF]. These herds are still considered as bTBfree to date.

Collection of these blood samples was carried out on the same day as the SITT.

II.3. IFNγ assay specificity study in relation to positive SITT (Sp r )

IFNγ assay specificity relative to positive SITT (Sp r ) was studied in 578 cattle testing positive to SITT from 176 bTB-free herds (i.e. where no cattle have been found to be culture-positive since 2001). Unlike the above-mentioned absolute specificity study, these herds were located in a bTB-infected zone (i.e. a zone where several bTB outbreaks had taken place in recent years). These herds were subsequently monitored annually and to date they are still considered bTB-free.

Collection of these blood samples was carried out 3 days after the SITT.

III. Statistical methods

Different cut-off values were evaluated in a simulation to determine their effects on the sensitivity (Se r ) and specificities (Sp r & Sp) of the test [START_REF] Lauzi | Evaluation of the specificity of the γ-interferon test in Italian bovine tuberculosis-free herds[END_REF]. The R statistical software (R version 2.9.2 (August 2009), R Foundation for Statistical Computing, Vienna, Austria, http://www.R-project.org) was used to estimate sensitivity and specificity values (with a 95% confidence interval, 95% CI).

To establish a set of conditions (a cut-point) to provide both the optimal test's sensitivity and specificity, receiver-operator characteristic (ROC) analyses of single variables were used [START_REF] Ryan | An evaluation of gamma interferon test for detecting bovine tuberculosis in cattle 8 to 28 days after tuberculin ski testing[END_REF]. [START_REF] Faye | Study of the specificity and the sensitivity of the dosage of the interferon gamma technique to the cattle for the diagnosis of bovine tuberculosis[END_REF].

The results presented in Table 1a show that PPD is more specific than sensitive (cut-off at 0.04, 83% [95% CI, 72-92%] for PPD Se r and 99.4% [95% CI, 98.2-99.9%] for PPD Sp).

A ROC curve of PPD [(OD B -OD A )/(OD PC -OD NC )] was plotted from these PPD Se r and Sp values (Figure 1a). The optimal PPD Se r (93% [84-98]) and PPD Sp (98.0% [96.3-99.0]) were obtained when the cut-off is about 0.02 (Figure 1a and Table 1a). 1b.

The results presented in Table 1b show that R is more specific than sensitive (cut-off at 0.04, 80% [68-89] for R Se r and 99.4% [98.2-99.9] for R Sp) as described in the literature.

A ROC curve of R [(OD R -OD N )/(OD PC -OD NC )] was plotted from these R Se r and Sp values (Figure 1b). The optimal R Se r (97% [89-100]) and R Sp (95.9% [93.8-97.5]) were obtained when the cut-off is about 0.01 (Figure 1b and Table 1b). In the Sp r study of the IFNγ test, 31/578 animals yielded invalid results in PPD. Therefore, only the remaining 547 cattle (172 herds) were subsequently kept for our study.

I.2. Final Se

Plasma from these invalid-result animals was diluted tenfold in PBS which allowed us to overcome the OD saturation problem and assign them as real negative infected animals (data not shown).

II.1. Combined results of individual Se r & Sp r studies of the IFNγ assay

II.1.1. PPD Se r & PPD Sp r at different cut-off values

For the different cut-off values obtained from the Se r study, the PPD Se r figures are given in Table 1a. For the different cut-off values obtained from the Sp r study, the PPD Sp r figures are also given in Table 1a.

The results, presented in Table 1a, show that PPD is more sensitive than specific (cut-off at 0.04, 83% for PPD Se r and 73.3% [69.4-77.0] for PPD Sp r ) in contrast to the results obtained in the absolute specificity (Sp) study.

A second ROC curve of PPD [(OD B -OD A )/(OD PC -OD NC )] was plotted from these PPD Se r and Sp r values (Figure 1c). The optimal PPD Se r (83% ) and PPD Sp r (75.5% [71.7-79.0]) were obtained when the cut-off is about 0.05 (Figure 1c and Table 1a). given in Table 1b.

The results, presented in Table 1b, show that R is more specific than sensitive (cut-off at 0.04, 80% for R Se r and 93. 1% [90.6-95.0] for R Sp r ) as described in the literature.

A second ROC curve of R [(OD R -OD N )/(OD PC -OD NC )] was plotted from these R Se r and Sp r values (Figure 1d). The optimal R Se r (87% [75][76][77][78][79][80][81][82][83][84][85][86][87][88][89][90][91][92][93][94]) and R Sp r (90.7% [87.9-93.0]) were obtained when the cut-off is about 0.03 (Figure 1d and Table 1b).

This cut-off corresponds to 0.07 (0.03 x 2.4) with the following calculation method: OD R -OD N. 3.

II.2. Final Se

The Se r PPD∩R and Se r PPDUR obtained were estimated at 77% [64-87] and 93% [84][85][86][87][88][89][90][91][92][93][94][95][96][97][98] respectively (Table 3). The Sp r PPD∩R and Sp r PPDUR obtained were estimated at 94.3% [92.0-96.1] and 71.8%

II.2.2. Final Sp

[67.9-75.6] respectively (Table 3).

Discussion and Conclusion

In our study, a normalized interpretation formula was used to improve the test's The cut-off value of our PPD calculation method is estimated at 0.02 for optimal PPD Se r of 93% [84-98] and Sp of 98.0% [96.3-99.0] (Table 1a), while the cut-off value of our R calculation method is estimated at 0.01 for optimal R Se r of 97% [89-100] and Sp of 95.9%

[93.8-97.5] (Table 1b).

However, Bovigam ® 's OD PC values are generally too high (average value about 2.5) and thus no longer corresponding to the dose-response zone. It is thus recommended for subsequent studies to dilute the kit's positive control so as to obtain OD PC values in the linear zone which are constant for each batch.

The test's specificity and sensitivity were assessed considering positive and divergent results

(PPDUR) or just positive results for each method (PPD∩R).

If we consider PPD∩R, the values of the relative sensitivity and absolute specificity of the IFNγ assay were finally estimated respectively at 90% [82-98] and 100% [99.2-100] ( We can then propose to interpret the test results according to different epidemiological contexts. Indeed, in the case of animals from an unfavorable context, i.e. belonging to a previously bTB-infected herd (risk of bTB resurgence) and/or a presently bTB-infected herd and/or a herd epidemiologically linked to another recognized bTB-infected herd, sensitivity should be favored rather than specificity. The PPDUR interpretation should then be chosen.

For this type of interpretation, we obtained excellent test sensitivity (Se r of 100%) with good specificity values (Sp of 93.9%).

Conversely, in a favorable context, i.e. a herd considered free of bTB for several years and presenting no other epidemiological link with other infected herds, or a herd from a bTB-free zone, specificity should be favored rather than sensitivity. The PPD∩R interpretation would thus be more suitable. Here, we obtain excellent test specificity (Sp of 100%) with acceptable test sensitivity (Se r of 90%).

However, since the IFNγ assay was mostly used after a positive SITT, we also studied the operational specificity of the test (Sp r ). The results obtained show that R is more specific than PPD at a selected cut-off value of 0.04 (93.1% [90.6-95.0] for R Sp r (Table 1b) & 73.3%

[69.4-77.0] for PPD Sp r (Table 1a)). The use of R clearly allows the specificity of the IFNγ assay to be improved (Van Pinxteren et al., 2000;[START_REF] Buddle | Use of ESAT-6 in the interferon-γ test diagnosis of bovine tuberculosis following skin testing[END_REF][START_REF] Buddle | Use of mycobacterial peptides and recombinant proteins for the diagnosis of bovine tuberculosis in skin test-positive cattle[END_REF][START_REF] Buddle | Advances in ante-mortem diagnosis of tuberculosis in cattle[END_REF]Vordermeier et al., 2001Vordermeier et al., , 2006;;Wood et al., 2001 and[START_REF] Aagaard | Optimizing antigen cocktails for Mycobacterium bovis diagnosis in herds with different disease prevalence: ESAT6/CFP10 mixture shows optimal sensitivity and specificity[END_REF]De la Rua-Domenech et al., 2006a;[START_REF] Coad | Blood-based assays to detect Mycobacterium bovis-infected cattle missed by tuberculin skin testing[END_REF].

Thus, as has already been described by others [START_REF] Rothel | A sandwich enzyme immunoassay for bovine interferon-γ and its use for the detection of tuberculosis in cattle[END_REF]Wood et al., 1991Wood et al., , 2001;;[START_REF] Ryan | An evaluation of gamma interferon test for detecting bovine tuberculosis in cattle 8 to 28 days after tuberculin ski testing[END_REF][START_REF] Gormley | Diagnosis of Mycobacterium bovis infection in cattle by use of the gamma-interferon (Bovigam ® ) assay[END_REF], the Bovigam ® assay appears to be a useful additional diagnostic tool for the detection of bTB in low-prevalence areas when used with specific peptides and an adapted protocol. The cut-off value of our PPD calculation method was estimated at 0.05 for optimal PPD Se r of 83% and Sp r of 75.5% [71.7-79.0] (Table 1a); the cut-off value of our R calculation method was estimated at 0.03 for optimal R Se r of 87% [75][76][77][78][79][80][81][82][83][84][85][86][87][88][89][90][91][92][93][94] and Sp r of 90.7% [87.9-93.0] (Table 1b).

If we consider PPD∩R, the values of the relative sensitivity and specificity of the IFNγ assay were finally estimated respectively at 77% [64-87] and 94.3% [92.0-96.1] ( ). In these population groups, the loss in specificity led to a modification of the employed cut-off values and thus, a decrease in the sensitivity. This effect is more noticeable for PPD than for R.

In retrospective studies, i.e. Ser and Spr studies, the totality of the assays could not be carried out with same delay after SITT. We did not take into account this variability in performing the test (3-10 days after SITT), even though the literature shows it may sometimes affect the results [START_REF] Schiller | Bovine tuberculosis: Effect of tuberculin skin test on in vitro interferon gamma responses[END_REF].

On the whole, the values for individual sensitivity and specificity depend on the specific field conditions when applying the test (the total population or just the positive SITT population).

As a result, their corresponding decisional cut-offs also vary. Subsequent to the choice of The different data obtained show that, according to the region's infection status and the conditions of the test's application, it is necessary to study individual (PPD and R)

sensitivities and specificities so as to define optimal decisional cut-off values for PPD and R.

Moreover, the PPDUR interpretation method should be used when a bTB high-risk estimate is established (based on an unfavorable epidemiological context) whereas a PPD∩R interpretation method should be used for a low-risk assessment (favorable epidemiological context).

Finally, adapting the analysis criteria (cut-offs & interpretation method) to the region's infection status (for example low or high bTB prevalence, frequency of non-specific reaction, etc.) and to the test application conditions (for example confirmation of previous SITT results, total or partial depopulation, etc.), is essential for the appropriate use of our modified IFNγ

  test, in this low-prevalence area, for optimal classification of infected or non-infected herds following positive skin tests.

  Because until 2005 animals testing positive to the SITT were under-declared, bTB surveillance in this region was almost entirely based on post-mortem examination at the slaughterhouse. Indeed, notification of a positive SITT reaction leads to a long suspension of s status at least until a further SICTT is carried out. Besides, due to the very low bTB prevalence in France, the positive predictive value (PPV) of the SITT is consequently too low and thus the test is considered unreliable by veterinary practitioners.

  µl) was stimulated with either (i) 25 µl of avian tuberculin (PPD A = A) or bovine tuberculin (PPD B = B) at 20 µg/ml (Prionics PPDs), (ii) 25 µl of the recombinant peptides ESAT6 and CFP10 (R, from SSI) at 5 µg/ml of final blood concentration for each, (iii) 25 µl of the Pokeweed Mitogen (PWM, from Sigma), an immunocompetence control at 5 µg/ml of final blood concentration, 25 µl of the Phosphate Buffer Saline (PBS = N) as a negative control for cellular stimulation.

  Sensitivity relative to post-mortem bTB positive confirmation (Se r ) & Absolute Specificity (Sp) and final Se r & Sp at selected cut-off values for optimal individual Se r & SpIn the Se r study, 13/73 animals yielded invalid results with PPD stimulation. The OD value for A (OD A ) was high, as was that of B (OD B ) (each >2.5 OD units), with an OD B /OD A ratio ranging from 0.850 to 1.150. Indeed, beyond 2.5 OD units, the graph representing OD as a function of the IFNγ concentration was not linear (absorbance saturation). Therefore, only the remaining 60 cattle (from 20 herds) were used in our analysis.Plasma from these invalid-result animals was diluted tenfold in PBS which allowed us to overcome the OD saturation problem and assign them as real positive infected animals (data not shown). The limited number of samples made it impossible to draw valid statistical conclusion.I.1. Combined results of individualSe r & Sp studies of the IFNγ assay I.1.1. PPD Se r & PPD Sp at different cut-off values

  r & R Sp at different cut-off values ESAT6-CFP10 (R) Se r values are shown in Table 1b using different cut-off values obtained from the Se r study. The R Sp figures, using different cut-off values obtained from the Sp study, are shown in Table

  r of the IFNγ assay, at cut-off values 0.02 and 0.01 for PPD and R calculation methods respectively, are shown in

  [1 -% (POS) = % (NEG + DIV)] and Sp PPDUR [1 -% (POS + DIV) = % (NEG)] obtained were estimated at 100% [99.2-100] and 93.9% [91.4-95.8] respectively (Table 2). II. Individual Sensitivity relative to post-mortem bTB positive confirmation (Se r ) & Specificity relative to positive SITT (Sp r ) and final Se r & Sp r at selected cut-off values for optimal individual Se r & Sp r

  r & R Sp r at different cut-off valuesThe R Se r figures, for different cut-off values obtained from the Se r study, are given inTable 1b. The R Sp r figures, for different cut-off values obtained from the Sp r study, are also

  r & Sp r of the IFNγ assay at selected cut-off values for optimal individual Se r & Sp r II.2.1. Final Se r at cut-off values 0.05 and 0.03 for PPD and R calculation methods respectively The final Se r of the IFNγ assay, at cut-off values 0.05 and 0.03 for PPD and R calculation methods respectively, are shown in Table

  r at cut-off values 0.05 and 0.03 for PPD and R calculation methods respectively The final Sp r of the IFNγ assay, at cut-off values 0.05 and 0.03 for PPD and R calculation methods respectively, are shown in Table3.

  reproducibility. Combining the individual results of the Se r (sensitivities relative to postmortem bTB positive confirmation) of PPD and ESAT6-CFP10 (R) stimulation and the Sp (absolute specificities) of PPD and R made it possible to determine the cut-off values for obtaining optimal values of individual Se r and Sp.

  results from the individual Se r and the individual Sp r studies (specificities, relative to positive SITTs, of PPD and R) made it possible to determine cut-off values for obtaining optimal individual values.

  off values, the result interpretation method (PPD∩R or PPDUR method) is selected according to a favorable or unfavorable epidemiological context.To conclude, the present work made it possible to determine cut-off values of 0.02 and 0.01 for PPD and R respectively for the use of the modified IFNγ assay in parallel to SITT, in a particular region in Dordogne, i.e. in a population without previous SITT's non-specific reactions and with a low bTB prevalence context. Concerning the use of this IFNγ assay after positive SITTs and in a low prevalence area, we obtained cut-off values of 0.05 and 0.03 for PPD and R respectively. These cut-off values could also be suitable for other areas where cross reactions with environmental mycobacteria might occur.

  to thank the Dordogne Regional Veterinary Services for their collaboration and the Immunoserology team at the LDAR24 for their technical contribution to this work. L.A.H., Ravn, P., Agger, E.M., Pollock, J., Andersen, P., 2000. Diagnosis of tuberculosis based on the two specific antigens ESAT-6 and CFP-10. Clin. Diagn. Lab. Immun. 7, 155-160. Vordermeier, H.M., Whelan, A., Cockle, P.J., Farrant, L., Palmier, N., Hewinson, R.G., 2001. Use of synthetic peptides derived from the antigens ESAT-6 and CFP-10 for differential diagnosis of bovine tuberculosis in cattle. Clin. Diagn. Lab. Immun.

  Table 1a shows the PPD Se r figures for different cut-off values obtained from the Se r study. PPD Sp values are shown in Table 1a using different cut-off values obtained from the Sp study

Table 2 .

 2 PPD∩R results correspond to positive results while PPDUR results correspond to positive and divergent results.

	The Se r PPD∩R [% (POS)] and the Se r PPDUR [% (POS + DIV)] obtained were estimated at
	90% [82-98] and 100% [95-100] respectively (Table 2).
	I.2.2.

Final Sp at cut-off values 0.02 and 0.01 for PPD and R calculation methods respectively

The final Sp of the IFNγ assay, at cut-off values 0.02 and 0.01 for PPD and R calculation methods respectively, are shown in Table

2

.

Table 2

 2

	)

and absolute specificity were estimated at 100% [95-100] for Se r and 93.

9% [91.4-95.8]

for Sp (Table

2

).

Table 3

 3

	) at

r (Table

3

), with regard to the PPDUR method. Then, in an unfavorable context, the PPDUR interpretation would provide good test sensitivity (Se r about 93%) with suitable test specificity (Sp r about 71.8%). Conversely, in a favorable context, the PPD∩R interpretation would provide good test specificity (Sp r about 94.3%) with suitable test sensitivity (Se r about 77%

  8, 571-578. Vordermeier, H.M., Ewer, K., 2006. Specificity trial of the Bovigam ® IFN-gamma test in GB cattle. G.V.J. 16, 72-80. http://www.defra.gov.uk/foodfarm/farmanimal/diseases/atoz/tb/docu ments/gifn_specificityreport.pdf, Accessed August 08, 2006; last accessed March 15, 2010. Wood, P.R., Corner, L.A., Rothel, J.S., Baldock, C., Jones, S.L., Cousins, D.B., McCormick, B.S., Francis B.R., Creeper, J. Tweddle, N.E., 1991. Field comparison of the interferongamma assay and the intradermal tuberculin test for the diagnosis of bovine tuberculosis. Aust. Vet. J. 68, 286-290. Wood, P.R., Jones, S.L., 2001. Bovigam ® : an vitro cellular diagnostic test for bovine tuberculosis. Tuberculosis 81, 144-155.

Acknowledgments

We would also like to thank Prionics and the Statens Serum Institut for their collaboration.

We are grateful to the Dordogne Federation of Sanitary Defense Groups Health (GDS24). We are also grateful to the National Association for Research and Technology (ANRT) and the European Regional Development Funds (ERDF) for their financial contribution. Finally, we would like to express our gratitude to Dr. Keck, from the Hérault Regional Veterinary Laboratory (France).

Conflict of Interest Statement

The authors have not declared any conflict of interest.