This project aims to improve cyber-physical systems dependability through the introduction of Digital Dependability Identities. The DEIS project will develop an open model for DDIs, a framework for generating and evaluating DDIs, and apply the approach to four industrial use cases. The project involves 10 partners, is funded by the European Union Horizon 2020 program, and runs from 2017 to 2020 with a total budget of €4,889,290.

1. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 732242”.
DEIS - DEPENDABILITY ENGINEERING
INNOVATION FOR CPS
Ran Wei1, Tim Kelly1, Richard Hawkins1, Eric Armenguad2
1University of York
2AVL List GmbH

2.  DEIS : Dependability Engineering Innovation for CPS
 Funding scheme: H2020 ICT-01-2016
 Total Budge: €4,889,290
 Start Date: January 1st, 2017
 Duration: 3 years
 Consortium: 10 partners
 Coordinator: AVL List
H2020 ICT-01-2016 DEIS
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3.  Involves both computer and physical systems and are connected to Internet/local networks
 A mechanism controlled/monitored by computer-based algorithms, tightly integrated with the
internet and its users.
 Tendency: Open and adaptive
 Loosely connected (openness)
 Systems come together to form new system with temporary configuration, and provide service as a whole
(adaptivity)
 Number of configurations: unknown
 Challenge: assuring dependability of CPS
 How well they can function with one another
 How safe they are as a whole
CYBER-PHYSICAL SYSTEMS
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4. Addresses assurance of dependability for CPS
 Important and unsolved challenge
Forming a “science of dependable system integration” for CPS
Core concept: Digital Dependability Identity (DDI)
 Composable and executable
 Contains attributes that describe the systems or components dependability
behavior: faults propagation, described using concepts from the theory of safety
contracts
 Contains requirements on how the component interacts with other entities in a
dependable way, described in terms of the level of trust and assurance.
 Produced during design, issued when the component is released, and
continuously maintained over the complete lifetime of a component or system.
DEIS
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5.  Automotive: development of a stand-alone system for intelligent physiological
parameter monitoring
 Automotive: Evaluation of automated driving functions and the dependability
impact of connected powertrain on advanced driver simulator
 Railway: Plug-and-play environment for heterogeneous railway systems
enabling dependable exchange of information between components and
subsystems
 Healthcare enhancement of clinical decision app for oncology professional
targeting higher degree of dependability for ad-hoc systems
DEIS: DEPLOYMENT TARGETS
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6. Improve Cyber-Physical Systems (CPS) by the
introduction of Digital Dependability Identity (DDI)
a. Efficient synthesis over the supply chain
b. Safe and secure composition of highly distributed
and autonomous CPS
Apply to four use industrial use cases from 3 different
domains
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DEIS – THE USE CASES

7. Target: intelligent physiological parameter monitoring for automotive applications to monitor driver comfort
and capability to safely control the vehicle for transition scenarios
Challenge: secure transmission of driver health information
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USE CASE 1: AUTOMOTIVE DOMAIN

8. Target: Evaluation of automated driving functions and the dependability impact of connected powertrain on
advanced driver simulator
Challenge: evaluation and integration of cyber-physical systems and systems of systems with a high degree of
autonomy
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USE CASE 2: AUTOMOTIVE DOMAIN

9. Target: Dependability framework with heterogeneous (cross-industry) participants
Challenge: interoperability in the area of safety engineering across companies, railway operators as well as
safety authorities
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USE CASE 3: RAILWAY DOMAIN

10. Target: Clinical decision support app for oncology professionals
Challenge: higher capability for ad-hoc integration in Electronic Health Records, taking into consideration
security issues
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USE CASE 4: HEALTHCARE DOMAIN

11.  Universal exchange of dependability information
 Lack of common model for representing DDIs
 Expressive and machine executable
 Shield sensitive information to protect IP
 Efficient dependability assurance across industries and value chains
 Component providers should be able to generate DDIs based on the dependability
information of the components
 Include information for dependability assurance
 Dependability considered from the early stage: MDE is applicable for its advantages in
automation
 Dependable integration of systems in the field
 Dependability of CPS cannot be fully assured prior to deployment, thus need automated
evaluation of DDIs
DEIS: CHALLENGES FOR DDI
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12.  Objective 1: An open model for specifying Digital Dependability
Identities enabling the efficient integration of modular
dependability assurance cases
 Objective 2: Semi-automated framework for the generation and
evaluation of DDIs
 Objective 3: A framework for the in-the-field dependability
assurance in CPS
 Objective 4: autonomous and connected CPS use cases
DEIS TECHNICAL APPROACH – THE DDI
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13. 13
PROJECT STRUCTURE
WP1 project
management
WP2 project requirements
WP3 model concept
WP4 dependability
collaboration workspace
WP6 Case studies and evaluations
WP7 impact
management –
clustering,
dissemination
and
exploitation
WP5
autonomous
and
connected
CPS

14.  Definition of a metamodel for DDI: Open Dependability Exchange (ODE)
metamodel
 A semi-automated framework for the generation and evaluation of DDIs
 A framework for the in-the-field dependability assurance in CPS
 Autonomous and connected CPS use cases and evaluations
DEIS: EXPECTED OUTCOMES
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15.  Requirement elicitation
 Requirements for the exchange of dependability-related information and the specification of modular
DDIs
 Requirements for the tooling support needed to check the validity of the available dependability
information and to model DDIs
 Requirements for applying the DEIS approach within the automotive, healthcare and the railway domain
and evaluating the project results compared to the state-of-the-art and the state-of-practice
 DDI concept
 Engineering stories
 Progress from University of York
 Implementation of Structured Assurance Case Metamode (SACM) in EMF
 Implementation of Goal Structuring Notation (GSN) in EMF: metamodel, editor, framework
 Model to model transformation from GSN to SACM
 Tool support for SACM and GSN creations
DEIS: CURRENT STATUS
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16.  Questions
THANK YOU
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