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Protecting Intellectual Property When Outsourcing - By : Xiaoguang Deng, Greg Huet, Suo Tan, Clément Fortin,

Protecting Intellectual Property When Outsourcing


Xiaoguang Deng
Xiaoguang Deng Author profile
Xiaoguang Deng is postdoctoral fellow in the Institute for Information Systems Engineering at Concordia University. He received his Ph.D degree in Industrial Information Systems from Université des Sciences et Technologies de Lille, France.

Greg Huet
Greg Huet was an Assistant Professor in the Operations and logistics engineering Department at ÉTS. He was involved in a Lean transformation initiative at Bombardier Aerospace.

Suo Tan
Suo Tan received his B.Sc. from Huazhong University of Science and Technology, China, his M.A.Sc. in Systems and Computing Engineering from the University of Guelph. He is doing a Ph.D. in Mechanical Engineering at Concordia University.

Clément Fortin
Clément Fortin Author profile
Clément Fortin was Department Chair of Mechanical Engineering at École Polytechnique de Montréal, Canada from 2005 to 2010. He was President and CEO of CRIAQ from 2010 to 2014. Since 2014, he is the principal consultant for Skoltech.

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Header picture is from Timothy B. MCormack, CC licence, source.

Editor’s note

Outsourcing, while sometimes necessary, increase the risk of intellectual property leakage. The authors have developed a method to decompose a product into sub-components and thus decrease the risk of confidential information leakage by inference.

The risks and Benefits of Outsourcing

In global recession, outsourcing becomes a question of survival for most executives who need to restore profitability and growth in many manufacturing industries, such as aircraft, automobile, telecommunication, or information technologies. One of the critical challenges faced by such decisions is the potential risk of leaking confidential information through shared suppliers and partners. In this research, a new approach is proposed to decompose a product into several sub-components for mitigating the risk of Intellectual Property (IP) leakage caused by inferences in supply chains.

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Source [Img1].

Explicit and Implicit Leakages

The nature of information leakage can be categorized as explicit or implicit leakage [1]. Explicit leakage means that confidential information has been mistakenly shared through the supply chain’s information channels. Implicit leakage refers to information that has been leaked by inferences, conclusions or deductions from reasoning over evidence rather than explicit information. This inference is mainly due to the different inherent engineering relationships and interactions (e.g. physical, mechanical, electrical, etc.) between product components.

To the best knowledge of authors, most of the existing literature focuses on explicit leakage, which aims to propose legal, organizational, social, technical methods to prevent direct information leakage. Recently, Zeng and Wang’s Labs have reported on how implicit information leakage happens and how to mitigate the risk of leakage [1–5]. Based on these findings, this article focuses more specifically on the methodological steps and tools to mitigate confidential information leakage by inference.

Design Structure Matrix (DSM)

An original approach is developed to decompose product structures (bill of materials) using DSM. A DSM is a square matrix with identical row and column (figure 1). Using this square matrix, the relationships of parameters between elements can be represented.  The decomposition approach has hence been found to be more suitable to protect product design information. Such approach takes into account the various interactions between the components based on a conceptual supply chain model.

Matrix-based design structuring is referred to the context, where a matrix is used to capture dependency relationships of any two entities related to engineering design applications [6].

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Fig. 1 A Simple Example of DSM Representation Source [Img2].

In this paper, we focus on design decomposition ‘‘two-mode’’ problem, which aims to form the design subcomponents by properly grouping subsets of design functions and parameters. Generally speaking, a design decomposition problem involves three following stages [7]:

1.    Decompose the product structure into elements;

2.    Understand and document the different interactions between the elements;

3.    Integration analysis of the decomposed elements.

The Aircraft Pylon Design Case Study

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Fig. 2 Bombardier Canadair Regional Jet (CRJ) Aircraft with Aft Fuselage Mounted Engines Used in the Design Case Study Source [Img3].

In order to illustrate the practical implications of the methodology, an aircraft pylon design case study was chosen (figure 2). In civil aviation, a pylon is a key structural system which connects the engine to the rest of the aircraft.

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Fig. 3 Detailed Pylon Structure of the Aft Fuselage Mounted Engines Source [Img4].

They exist when the configuration places the engines below the wing, above the wing, or on the fuselage. The data for this case study was provided by a student design project that retrofits an engine in an aft fuselage mount configuration as illustrated in Figure 3.

Figure 4 shows the detail of the forward engine mount and the rear engine mount which are the main connecting structures between pylon and engine.

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Fig. 4 Forward Engine Mount (left) and Rear Engine Mount (right) Source [Img5].

Product Structure Tree

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Fig. 5 Front Engine Mount View Source [Img6].

For the pylon, the main structural systems are the front engine mount and the rear engine mount, illustrated in figures 5 and 6 respectively. Figure 5 shows the front engine mount, which includes four components: an extended yoke, a link and two mount pads.

The rear engine mount purpose is to constrain the engine relative to the aircraft fuselage, it contains three components: a yoke, a link and a mount pad (figure 6).

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Fig. 6 Rear Engine Mount View Source [Img6].

Figure 7 presents an extended product structure tree, which describes the relations between major components and assemblies of the pylon structure. According to the definition, a product structure tree T has only one essential component set (ECS). The ECS of our case is {FY, FL, FP, MPB, PEB, RY, RL, RP, PB, MEB}.

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Fig. 7 Product Structure Tree of the Aircraft Pylon Structure. Source [Img2].

In this case, ‘‘withstanding tensile load’’, ‘‘withstanding shear load’’ and ‘‘withstanding temperature’’ are private parameters to be protected for each component. They are respectively key parameters to represent the interactions of ‘‘spatial’’ (physical effect), ‘‘energy’’ (aerodynamic effect) and ‘‘field’’ (heat effect) between components. Both the front and the rear space have neither interface with fluid line systems (material interaction) nor electronic systems (information interaction). If the three private parameters are inferred, potential competitors may know the material and the method of heat treatment. Thus, the pylon mount has a high risk to be copied by reversed engineering. Moreover, if one component is allocated to a supplier, this supplier is assumed to know all the related manufacturing parameters. The ECS in this case, such as {FY, FL, FP, MPB, PEB, RY, RL, RP, PB, MEB}, is taken as the component of product structure tree.

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Table 1 Component Category Function of Pylon Case Study. Source [Img2].

In this case, the component is roughly divided into two categories (part and connector). The component category function Fcc is shown in Table 1.

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Table 2 Degree of Clustering in Case (Level 1). Source [Img2].

The level 1’s coupling value Degree of clustering is presented in Table 2. In this case, set at α = 0.20, the level 2’s DSM with regrouping component is shown in Table 3.

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Table 3 DSM of Level 2 in Case (α = 0.20). Source [Img2].

The previous approach can be summarized in a hierarchical tree (shown in Figure 8). Based on our proposed method, this figure illustrates the clustering procedure. In this case, according to the experiences of product developer, the tolerance of IP leakage threshold is set as 0.20. Thus, the suitable decomposition of product structure is {FY, RY}, {FL, RL}, {FP}, {RP}, {MPB, PEB, PB, MEB}. Each of these decomposed components is allocated to one specific supplier.

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Fig. 8 Tree Structure in Hierarchical Clustering. Source [Img2].

Additional Information

For a more comprehensive discussion about the Product decomposition using design structure matrix for intellectual property protection in supply chain outsourcing, we invite you to read the Research Paper in the journal Computers in industry:

Deng X., G. Huetb , S. Tana and C. Fortin (2012). Product decomposition using design structure matrix for intellectual property protection in supply chain outsourcing. Computers in Industry, 63, pp.: 632–641. (PDF).

 

 

Xiaoguang Deng

Author's profile

Xiaoguang Deng is postdoctoral fellow in the Institute for Information Systems Engineering at Concordia University. He received his Ph.D degree in Industrial Information Systems from Université des Sciences et Technologies de Lille, France.

Program : Operations and Logistics Engineering 

Author profile

Greg Huet

Author's profile

Greg Huet was an Assistant Professor in the Operations and logistics engineering Department at ÉTS. He was involved in a Lean transformation initiative at Bombardier Aerospace.

Program : Automated Manufacturing Engineering 

Author profile

Suo Tan

Author's profile

Suo Tan received his B.Sc. from Huazhong University of Science and Technology, China, his M.A.Sc. in Systems and Computing Engineering from the University of Guelph. He is doing a Ph.D. in Mechanical Engineering at Concordia University.

Author profile

Clément Fortin

Author's profile

Clément Fortin was Department Chair of Mechanical Engineering at École Polytechnique de Montréal, Canada from 2005 to 2010. He was President and CEO of CRIAQ from 2010 to 2014. Since 2014, he is the principal consultant for Skoltech.

Author profile


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