Wi-Fi QoS improvements for industrial automation

Digitalization caused a considerable increase in the use of industrial automation applications. Industrial automation applications use real-time traffic with strict requirements of connection of tens of devices, high-reliability, determinism, low-latency, and synchronization. The current solutions meeting these requirements are wired technologies. However, there is a need for wireless technologies for mobility,less complexity, and quick deployment. There are many studies on cellular technologies for industrial automation scenarios with strict reliability and latency requirements, but not many developments for wireless communications over unlicensed bands. Wireless Fidelity (Wi-Fi) is a commonly used and preferred technology in factory automation since it is supported by many applications and operates on a license free-band. However, there is still room for improving Wi-Fi systems performance for low-latency and high-reliable communication requirements in industrial automation use cases. There are various limitations in the current Wi-Fi system restraining the deployment for time-critical operations. For meeting the strict timing requirements of low delay and jitter in industrial automation applications, Quality of Service (QoS)in Wi-Fi needs to be improved. In this thesis, a new access category in Medium Access Control (MAC) layer for industrial automation applications is proposed.The performance improvement is analyzed with simulations, and a jitter definition for a Wi-Fi system is studied. Then, a fixed Modulation and Coding (MCS) link adaptation method and bounded delay is implemented for time-critical traffic in the simulation cases to observe performance changes. Finally, it is shown that the new access category with no backoff time can decrease the delay and jitter of time-critical applications. The improvements in Wi-Fi QoS are shown in comparison with the current standard, and additional enhancements about using a fixed modulation and coding scheme and implementation of a bounded delay are also analyzed in this thesi

Level-Headedness in Wireless Sensor Networks

Well-groomed surroundings be a sign of the next evolutionary step in construction, utilities, industrial, residence, shipboard, and haulage system automation. The well-groomed atmosphere needs information about its environment as well as about its internal workings. Sensor networks are the input to assembly the information needed by well-groomed surroundings, whether in buildings, utilities, industrial, home, shipboard, transportation systems, automation, or elsewhere. Localization is one of the basic challenges and it plays vital role. In this paper we are discussing various Application Requirements, probable Approaches, Position unearthing Approaches, Localization Techniques and QOS

On a Uniform Causality Model for Industrial Automation

The increasing complexity of Cyber-Physical Systems (CPS) makes industrial automation challenging. Large amounts of data recorded by sensors need to be processed to adequately perform tasks such as diagnosis in case of fault. A promising approach to deal with this complexity is the concept of causality. However, most research on causality has focused on inferring causal relations between parts of an unknown system. Engineering uses causality in a fundamentally different way: complex systems are constructed by combining components with known, controllable behavior. As CPS are constructed by the second approach, most data-based causality models are not suited for industrial automation. To bridge this gap, a Uniform Causality Model for various application areas of industrial automation is proposed, which will allow better communication and better data usage across disciplines. The resulting model describes the behavior of CPS mathematically and, as the model is evaluated on the unique requirements of the application areas, it is shown that the Uniform Causality Model can work as a basis for the application of new approaches in industrial automation that focus on machine learning

Technical Management for Buildings

This paper is a presentation of an 'instrument' for the optimization of the functionality and conservation of tertiary buildings. This technique has several different names: Building Automation Systems (BAS), Central Control and Monitoring System (CCMS) in English, and Gestion Technique du Bâtiment' (GTB) or Gestion Technique Centralisée (GTC) in French. With this technique it is possible to manage all the functions of a building, it is a modern instrument that introduces the concept of 'automation' in the operation of buildings using computerized procedures, earlier reserved for industrial processes. The system is structured with different automation levels with a distributed intelligence, each level characterized by a communication system (Fieldbus for the lowest and Ethernet for the highest level). In order to apply the BAS to CERN buildings it is necessary to evaluate the advantages, the CERN requirements and the integration with the several existing control and automation systems

Modified Beacon-Enabled IEEE 802.15.4 MAC for Lower Latency

Industrial sensing, monitoring and automation offer a lucrative application domain for networking and communications. Wired sensor networks have traditionally been used for these applications because such networks adequately meet two vital requirements, i.e., low latency and high reliability, needed for an industrial deployment. Wired sensor networks, however, are not very cost effective due to higher components’ cost. These networks also lack the flexibility needed for subsequent topological changes. Wireless sensor networks (WSN), on the other hand, are less expensive and offer high degree of flexibility. Wireless networks, therefore, can offer an attractive and viable solution for industrial sensing and automation. IEEE 802.15.4 standard defines a specification for MAC and PHY layers for shortrange, low bit-rate, and low-cost wireless networks. However, the specified system is inefficient in terms of latency and reliability and fails to meet the stringent operational requirements for industrial applications. In this paper, we propose a set of new MAC superframes with an aim to enhance both performance metrics. We then use simulation to compare the performance of our proposed systems with that of the one specified in IEEE 802.15.4 standard

Modelling of a Flexible Manoeuvring System Using ANFIS Techniques

The increased utilization of flexible structure systems, such as flexible manipulators and flexible aircraft in various applications, has been motivated by the requirements of industrial automation in recent years. Robust optimal control of flexible structures with active feedback techniques requires accurate models of the base structure, and knowledge of uncertainties of these models. Such information may not be easy to acquire for certain systems. An adaptive Neuro-Fuzzy inference Systems (ANFIS) use the learning ability of neural networks to adjust the membership function parameters in a fuzzy inference system. Hence, modelling using ANFIS is preferred in such applications. This paper discusses modelling of a nonlinear flexible system namely a twin rotor multi-input multi-output system using ANFIS techniques. Pitch and yaw motions are modelled and tested by model validation techniques. The obtained results indicate that ANFIS modelling is powerful to facilitate modelling of complex systems associated with nonlinearity and uncertainty

Interoperable Architecture For Logical Reconfigurations Of Modular Production Systems

Individualisation of products and ever-shorter product lifecycles require manufacturing companies to quickly reconfigure their production and adapt to changing requirements. While most of the existing literature focuses on organisational structures or hardware requirements for reconfigurability, requirements and best practices for logical reconfigurations of automated production systems are only sparsely covered. In practice, logical system reconfigurations require adjustments to the software, which is often done manually by experts. With the ongoing automation and digitisation of manufacturing systems in the context of Industry4.0, the need for automated software reconfigurations is increasing. However, heterogeneous and proprietary technologies in the field of industrial automation pose a hurdle to overcome for generally applicable approaches for logical reconfigurations in the industrial domain. Therefore, this paper reviews available technologies that can be used to solve the problem of automated software reconfigurations. For this purpose, an architecture and a procedure are proposed on how to use these technologies for automatic adaptation and virtual commissioning of control software in industrial automation. To demonstrate the interoperability of the approach, collective cloud manufacturing is used as a composing platform. The presented approach further includes a domain-specific capability model for the specification of software artefacts to be generated, allowing jobs to be described and matched on the platform. The core element is a code generator for generating and orchestrating the control code for process execution using the reconfigurable digital twin as a validator on the platform. The approach is evaluated and demonstrated in a real-world use case of a modular disassembly station