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!  Five Component Subsystem of Magellan GPS 315

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Why do we care? !  In complex multi-component systems, the components are either Original Equipment Manufacturer (OEM), purchased from a trusted supplier or purchased from an unverified source.

!  The unverified source could potentially introduce counterfeit components with the purpose of 1) malicious intent 2) espionage or 3) economic advantage.

!  Counterfeit components lead to lack of assurance of reliability of complex systems, and it may endanger operational performance and safety.

What do we propose? We propose the construction of a stochastic computational model: !  for identifying counterfeiting and studying its effects in the military supply chain, and

!  for the simulation to compare expected failures of a system as a whole versus failures due to the counterfeit components of lesser quality.

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!  The output of the computational model contains two parts: a)  Plots of Failure Counts for both Verified and Counterfeit Components

b)  Visualization of the System

CONCLUSIONS !  We build a stochastic agent-based computational model using the Stochastic Pi Machine (SPiM).

!  We discuss the combinatorial complexity of the agent-based model.

!  We implement a visualization of the system.

!  We perform statistical tests to analyze the difference in multi-component system’s performance relative to the proportions of verified and counterfeit components.

ONGOING AND FUTURE WORK !  Compare field data.

!  Handle counterfeits with non-failure properties. For example, performance of counterfeit components can be affected by exposure to heat.

!  Apply our stochastic computational modeling approach to other complex interdisciplinary domains.

Figure 1: Computational Modeling Approach

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Figure 2: A handheld and waterproof GPS used for hiking

X.01=4GE>@>?=A@L04=I:L?AK0@GGF=@1N0①  Identify and index all components in the system and populate sets P and CP, where Pi

P, if P is a component from a verified source (OEM or trusted supplier) and CPi CP, if CP is a component from an unverified source.

② Baseline the system performance as per contractual component performance requirements.

③ Understand Counterfeiting Effects:

④ Use a proportions test to statistically identify changes in performance based on the failure counts.

Figure 3: Agent-Based Model of Magellan GPS 315

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Stochastic Pi-Calculus !  Allows modular description of concurrent and non-deterministic systems. !  It contains:

•  Processes – Agents •  Channels – Inter-agent communication (!/? Handshake) •  Stochastic rates associated with channels. •  Both channels and processes can be dynamically created.

Figure 4: Process Model of Effects of Verified and Counterfeit Components

!  Assembled Systems – 4 Types

!  Failed Assembled Systems – Non-Counterfeit Case •  Failure due to 1 Verified Component

•  Failure due to 2 Verified Components

•  Failure due to 3 Verified Components

•  Failure due to 4 Verified Components

•  Failure due to 5 Verified Components

!  Failed Assembled Systems – Counterfeit Case •  Failure due to Single Counterfeit Component

•  Failure due to One or More Counterfeit Components

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let Unit() = do ?a1(); ?a2(); AUnit(0.0); !c0() or ?ca1(); ?a2(); AUnit(1.0); !c1() or ?a1(); ?ca2(); AUnit(2.0); !c2() or ?ca1(); ?ca2(); AUnit(12.0); !c12()

and AUnit(n:float) = do ?cf1(); if n = 1.0 then !fc1() !fc1(Send) and ?cf1(Receive) else if n = 12.0 then !fc121() else () or ?cf2(); if n = 2.0 then !fc2() else if n = 12.0 then !fc122() else () or ?cf1(); ?cf2(); if n = 12.0 then !fc1212 else ()

Let P1() = !a1(); AP1() and AP1() = delay@0.0001; !f1()

Let CP1() = !ca1(); ACP1() and ACP1() = delay@1.0; !cf1()

Let P2() = !a2(); AP2() and AP2() = delay@0.0002; !f2()

Let CP2() = !ca2(); ACP2() and ACP2() = delay@2.0; !cf2() Figure 5: 3 Runs; Run 1 (Black), Run 2 (Blue), Run 3 (Red)

Table 1: Input data for the Computational Model

Figure 6: 1st time stamp – Configuration of assembled systems (ASystem)

Figure 7: Last time stamp – Failed assembled systems (FSystem)

Table 2: Statistical Hypothesis Testing for Simulation Results in Figure 5

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1.  Vishakha Sharma, Adriana Compagnoni and Jose Emmanuel Ramirez-Marquez. Computational Modeling of the Effects of Counterfeit Components. To appear in Proceedings of the Summer Computer Simulation Conference (SCSC), Monterey, CA, July 6 - 10, 2014.

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