With the emergence of “Industry 4.0”, the integration of cloud technologies and industrial cyber-physical systems (ICPS) becomes increasingly important to boost productivity by simplifying business operations and enhancing collaboration. By associating cloud, infrastructure platform and service applications, ICPS will promote the next generation of intelligent and autonomous systems, as well as increased quality, efficient production and sustainable industrial systems.
Along with the significant benefits, this trend comes with many associated challenges. The ICPS infrastructures and their fusion with the cloud lead to massive amounts of real-time and non-real-time data acquired for controlling particular processes, but also for supporting decision-making at system level. By means of virtualization techniques, IT services are accessed over the Internet, with data being computed in the network but not in a-priori known places. In such context, ensuring timely interaction from data collection to analysis and decision is non-trivial. Moreover, the co-existence of private industry-specific cloud services with public cross-industry cloud services within the same ecosystem entails that some cloud-based data might need to be undisclosed to users outside a particular company or domain. At the same time, private cloud data needs to be combined with data from public clouds, therefore both data security and interoperability need to be ensured. ICPS failures may result in havoc with escalated effects that may cause serious harm to people and property, therefore tackling the safety of cloud-based ICPS ecosystems is a key factor for their application in critical systems. Although cloud- assisted ICPS are increasingly important in many industrial domains, and ensuring their dependability is crucial, existing platforms do not provide satisfactory support to meet the dependability demands of industrial applications.
The overall goal of ACICS is to provide models, methods and tools that facilitate a substantial increase of dependability of cloud-based platforms for ICPS applications, with respect to consistency, security and interoperability of data, timing predictability of using shared virtual resources, together with a framework of guaranteeing QoS enforcement by formal analysis and verification.
Through ACICS, Mälardalen University and three companies, ABB, Volvo GTO, and Ericsson, will develop deep competence to boost the dependability of cloud-based platforms with respect to timing, safety, and data security of ICPS applications. We will be able to drastically enhance the current practices for the design, analysis, and virtual allocation of applications for cloud-based ICPS.
The ACICS team is composed of a strong group of researchers covering all aspects of the synergy, with proven research records, and a group of companies strategically important for Swedish industry.
|First Name||Last Name||Title|
|Eduard Paul||Enoiu||Associate Professor|
|Séverine||Sentilles||Senior Lecturer,Thesis Coordinator|
|Peter||Backeman||Associated Senior Lecturer|
Analysing Interoperability in Digital Twin Software Architectures for Manufacturing (Sep 2023) Enxhi Ferko, Alessio Bucaioni, Moris Behnam, Patrizio Pelliccione 17th European Conference on Software Architecture (ECSA 2023)
Automatic Clustering of Performance Events (Sep 2023) Shamoona Imtiaz, Gabriele Capannini, Jan Carlson, Moris Behnam, Marcus Jägemar 28th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA2023) (ETFA2023)
Test Generation and Mutation Analysis of Energy Consumption using UPPAAL SMC and MATS (Aug 2023) Jonatan Larsson , Eduard Paul Enoiu The 7th International Workshop on Testing Extra-Functional Properties and Quality Characteristics of Software Systems (ITEQS 2023)
Model-Based Policy Synthesis and Test-Case Generation for Autonomous Systems (Apr 2023) Rong Gu, Eduard Paul Enoiu 19th Workshop on Advances in Model Based Testing (A-MOST 2023)
Supporting 5G Service Orchestration with Formal Verification (Mar 2023) Peter Backeman, Ashalatha Kunnappilly, Cristina Seceleanu Computer Science and Information Systems (ComSIS,10(1))
Automatic Segmentation of Resource Utilization Data (Dec 2022) Shamoona Imtiaz, Moris Behnam, Gabriele Capannini, Jan Carlson, Marcus Jägemar 1st IEEE Industrial Electronics Society Annual On-Line Conference (ONCON2022)