A Cloud-Based Collaboration Platform for Model-Based Design of Cyber-Physical Systems

Businesses, particularly small and medium-sized enterprises, aiming to start up in Model-Based Design (MBD) face difficult choices from a wide range of methods, notations and tools before making the significant investments in planning, procurement and training necessary to deploy new approaches successfully. In the development of Cyber-Physical Systems (CPSs) this is exacerbated by the diversity of formalisms covering computation, physical and human processes. In this paper, we propose the use of a cloud-enabled and open collaboration platform that allows businesses to offer models, tools and other assets, and permits others to access these on a pay-per-use basis as a means of lowering barriers to the adoption of MBD technology, and to promote experimentation in a sandbox environment

A PVS-Simulink Integrated Environment for Model-Based Analysis of Cyber-Physical Systems

This paper presents a methodology, with supporting tool, for formal modeling and analysis of software components in cyber-physical systems. Using our approach, developers can integrate a simulation of logic-based specifications of software components and Simulink models of continuous processes. The integrated simulation is useful to validate the characteristics of discrete system components early in the development process. The same logic-based specifications can also be formally verified using the Prototype Verification System (PVS), to gain additional confidence that the software design complies with specific safety requirements. Modeling patterns are defined for generating the logic-based specifications from the more familiar automata-based formalism. The ultimate aim of this work is to facilitate the introduction of formal verification technologies in the software development process of cyber-physical systems, which typically requires the integrated use of different formalisms and tools. A case study from the medical domain is used to illustrate the approach. A PVS model of a pacemaker is interfaced with a Simulink model of the human heart. The overall cyber-physical system is co-simulated to validate design requirements through exploration of relevant test scenarios. Formal verification with the PVS theorem prover is demonstrated for the pacemaker model for specific safety aspects of the pacemaker design

Digitalization of Battery Manufacturing: Current Status, Challenges, and Opportunities

As the world races to respond to the diverse and expanding demands for electrochemical energy storage solutions, lithium-ion batteries (LIBs) remain the most advanced technology in the battery ecosystem. Even as unprecedented demand for state-of-the-art batteries drives gigascale production around the world, there are increasing calls for next-generation batteries that are safer, more affordable, and energy-dense. These trends motivate the intense pursuit of battery manufacturing processes that are cost effective, scalable, and sustainable. The digital transformation of battery manufacturing plants can help meet these needs. This review provides a detailed discussion of the current and near-term developments for the digitalization of the battery cell manufacturing chain and presents future perspectives in this field. Current modelling approaches are reviewed, and a discussion is presented on how these elements can be combined with data acquisition instruments and communication protocols in a framework for building a digital twin of the battery manufacturing chain. The challenges and emerging techniques provided here is expected to give scientists and engineers from both industry and academia a guide toward more intelligent and interconnected battery manufacturing processes in the future

Digitalization of Battery Manufacturing: Current Status, Challenges, and Opportunities

As the world races to respond to the diverse and expanding demands for electrochemical energy storage solutions, lithium-ion batteries (LIBs) remain the most advanced technology in the battery ecosystem. Even as unprecedented demand for state-of-the-art batteries drives gigascale production around the world, there are increasing calls for next-generation batteries that are safer, more affordable, and energy-dense. These trends motivate the intense pursuit of battery manufacturing processes that are cost effective, scalable, and sustainable. The digital transformation of battery manufacturing plants can help meet these needs. This review provides a detailed discussion of the current and near-term developments for the digitalization of the battery cell manufacturing chain and presents future perspectives in this field. Current modelling approaches are reviewed, and a discussion is presented on how these elements can be combined with data acquisition instruments and communication protocols in a framework for building a digital twin of the battery manufacturing chain. The challenges and emerging techniques provided here is expected to give scientists and engineers from both industry and academia a guide toward more intelligent and interconnected battery manufacturing processes in the future.publishedVersio

A Sequential Control Language for Industrial Automation

Current market trends for industrial automation are the need for customizable production, shorter time to market, and powerful global competitive pressure. Based on these trends two challenges have been identified: 1) flexible production systems and 2) integration and utilization of devices and software. Applications from both process automation, manufacturing, and robotics have been considered. More flexible languages and tools are needed to get a flexible production system. The graphical programming language Grafchart, based on the IEC 61131-3 standard language Sequential Function Charts (SFC), is considered with the aim to make both the language and its implementation more flexible. In particular, new constructs have been added to the Grafchart language and modern compiler techniques are evaluated for JGrafchart, a Grafchart implementation, with focus on an extensible language implementation. A first step toward real-time execution of Grafchart applications is also taken to make it possible to use Grafchart for hard real-time control. High execution rates often reveal concurrency issues and thus execution concurrency has also been investigated. Access to more data from industrial devices and software can be used to optimize production. Architectures for factory integration have been considered as this is the foundation to connect all devices and thus address the challenge of integrating and utilizing devices and software. Service Oriented Architecture (SOA) is a flexible software design methodology widely used in IT systems and for business processes. SOA service orchestration is brought to industrial automation by integrating support for both Devices Profile for Web Services (DPWS) and OPC Unified Architecture (OPC UA) in JGrafchart. Looking further, SOA 2.0 is event driven and features extremely loose coupling between components. An architecture based on SOA 2.0 where it is easy to integrate any device or software, in particular legacy devices with limited knowledge and capabilities, has been developed with focus on service choreography in industrial manufacturing. Another step toward real-time execution of Grafchart applications is integrated support for the high performance communication protocol LabComm. Additionally, it is investigated how Grafchart can be connected to Functional Mock-up Interface (FMI) for co-simulation to further address the shorter time to market trend by introducing simulation support. The PID controller is the most common controller for industrial automation. A PID implementation has been added to a Grafchart library and a flaw with the PID algorithm has been discovered. The problem occurs for PID controllers with a derivative part when the process value saturates. The derivative part then backs off which leads to undesired changes in the control signal. This issue has been analyzed and a solution to the problem is proposed