A cyber-physical machine tools platform using OPC UA and MTConnect

Cyber-Physical Machine Tools (CPMT) represent a new generation of machine tools that are smarter, well connected, widely accessible, more adaptive and more autonomous. Development of CPMT requires standardized information modelling method and communication protocols for machine tools. This paper proposes a CPMT Platform based on OPC UA and MTConnect that enables standardized, interoperable and efficient data communication among machine tools and various types of software applications. First, a development method for OPC UA-based CPMT is proposed based on a generic OPC UA information model for CNC machine tools. Second, to address the issue of interoperability between OPC UA and MTConnect, an MTConnect to OPC UA interface is developed to transform MTConnect information model and its data to their OPC UA counterparts. An OPC UA-based CPMT prototype is developed and further integrated with a previously developed MTConnect-based CPMT to establish a common CPMT Platform. Third, different applications are developed to demonstrate the advantages of the proposed CPMT Platform, including an OPC UA Client, an advanced AR-assisted wearable Human-Machine Interface and a conceptual framework for CPMT powered cloud manufacturing environment. Experimental results have proven that the proposed CPMT Platform can significantly improve the overall production efficiency and effectiveness in the shop floor

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

A modern teaching environment for process automation

Emergence of the new technological trends such as Open Platform Communications Unified Architecture (OPC UA), Industrial Ethernet, cloud computing and the 5th wireless network (5G) enabled the implementation of Cyber-physical System (CPS) with flexible, configurable, scalable and interoperable business models. This provides new opportunities for the process automation systems. On the other hand, the constant urge of industries for cost and material efficient processes demands a new automation paradigm with the latest tools and technologies which should be taken into account while teaching future automation engineers. In this thesis, the modern teaching environment for process automation is designed, implemented and described. This work explains the connections, configurations and the test of three mini plants including the Multiple Heat Exchanger, the Three-tank system and the Mixing Tank. In addition, OPC UA communication between the server and its clients has been tested. The plants are a part of the state of the art of the architecture that provides the access of ABB 800xA to the cloud services via OPC UA over the 5G test wireless network. This new paradigm changes the old automation hierarchy and enables the cross layered communication in the old architecture. This modern teaching environment prepares the students for the future automation challenges with the latest tools and merges data analytics, cloud computing and wireless network studies with process automation. It also provides the unique chance of testing the future trends together in this unique process automation setup

Data Analysis in Automotive Industrial Cells

The manufacturing industry always has been one of the leading energy consumers, so companies in this area are always trying to use the best tools provided by the evolution of the technology, to analyse and lower the production costs. Many known studies don’t mind inconveniences such as stopping the production of the factory to perform studies or deep architecture improvements in the transport system. The proposed solution offers two different sets of tools. A device adapter, that targets the gather and storage of data, from industrial robotic cells devices, being the main requirement for a data analysis application, and a data analysis system, that analyses the stored data, without changing the existing production model. The analysis procedure aims the energy usage of a cell and its robot, and the duration of the executed processes. This solution was tested in two different robotic cells, that execute the same process. Multiple executions with different robot velocities were performed in order to gather the required data to provide an analysis and the conclusion was that, for both cells, the energy usage for each executed product was lower when the robot speed was higher, and that one of the cells is more efficient that other cell when executing at high speed but less efficient on lower velocities

Engineering methods and tools for cyber–physical automation systems

Much has been published about potential benefits of the adoption of cyber–physical systems (CPSs) in manufacturing industry. However, less has been said about how such automation systems might be effectively configured and supported through their lifecycles and how application modeling, visualization, and reuse of such systems might be best achieved. It is vitally important to be able to incorporate support for engineering best practice while at the same time exploiting the potential that CPS has to offer in an automation systems setting. This paper considers the industrial context for the engineering of CPS. It reviews engineering approaches that have been proposed or adopted to date including Industry 4.0 and provides examples of engineering methods and tools that are currently available. The paper then focuses on the CPS engineering toolset being developed by the Automation Systems Group (ASG) in the Warwick Manufacturing Group (WMG), University of Warwick, Coventry, U.K. and explains via an industrial case study how such a component-based engineering toolset can support an integrated approach to the virtual and physical engineering of automation systems through their lifecycle via a method that enables multiple vendors' equipment to be effectively integrated and provides support for the specification, validation, and use of such systems across the supply chain, e.g., between end users and system integrators

A Complex Event Processing System for Monitoring of Manufacturing Systems

Future manufacturing systems will require to process large amounts of complex data due to a rising demand on visibility and vertical integration of factory floor devices with higher level systems. Systems contained in higher layers of the business model are rapidly moving towards a Service Oriented Architecture, inducing a tendency to push Web Technologies down to the factory floor level. Evidence of this trend is the addition of Web Services at the device level with Device Profile for Web Services and the transition of OPC based on COM/DCOM communication to OPC-UA based on Web Services. DPWS and OPC-UA are becoming nowadays the preferred options to provide on a device level, service-oriented solutions capable to extend with an Event Driven Architecture into manufacturing systems. This thesis provides an implementation of a factory shop floor monitor based on Complex Event Processing for event-driven manufacturing processes. Factory shop monitors are particularly used to inform the workshop personnel via alarms, notifications and, visual aids about the performance and status of a manufacturing process. This work abstracts the informative value of the event-cloud surrounding the factory shop floor by processing its content against rules and formulas to convert it to valuable pieces of information that can be exposed to business monitors and dashboards. As a result, a system with a generic framework for integrating heterogeneous sources was reached, transforming simple data into alarms and complex events containing a specific context within the manufacturing process

A Mini Review on the utilization of Reinforcement Learning with OPC UA

Reinforcement Learning (RL) is a powerful machine learning paradigm that has been applied in various fields such as robotics, natural language processing and game playing achieving state-of-the-art results. Targeted to solve sequential decision making problems, it is by design able to learn from experience and therefore adapt to changing dynamic environments. These capabilities make it a prime candidate for controlling and optimizing complex processes in industry. The key to fully exploiting this potential is the seamless integration of RL into existing industrial systems. The industrial communication standard Open Platform Communications UnifiedArchitecture (OPC UA) could bridge this gap. However, since RL and OPC UA are from different fields,there is a need for researchers to bridge the gap between the two technologies. This work serves to bridge this gap by providing a brief technical overview of both technologies and carrying out a semi-exhaustive literature review to gain insights on how RL and OPC UA are applied in combination. With this survey, three main research topics have been identified, following the intersection of RL with OPC UA. The results of the literature review show that RL is a promising technology for the control and optimization of industrial processes, but does not yet have the necessary standardized interfaces to be deployed in real-world scenarios with reasonably low effort.Comment: submitted to INDIN'2