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Industrial Data Transmission
Published in Sandeep Misra, Chandana Roy, Anandarup Mukherjee, Introduction to Industrial Internet of Things and Industry 4.0, 2021
Sandeep Misra, Chandana Roy, Anandarup Mukherjee
The following features characterize the DeviceNet protocol: The DeviceNet physical layer uses a trunkline-dropline topology for communicating with devices. CAN enables the DeviceNet data link layer, whereas the DeviceNet network layer relies on device MAC ID, and the transport layer relies on message IDs for networking.DeviceNet supports 64 nodes simultaneously. The connected systems are addressed using one of the numbers lying between 0-63.It uses five cable types, all of the twisted pair type, which is used interchangeably depending on the distances and requirements of the application – thick round, thin round, class-1 round, KwikLink flat, KwikLink lite flat.It uses 24 V for powering the network components through one of the cables, and the other part of the pair is used for signaling.DeviceNet is characterized by the data rates of 125 kbps, 250 kbps, and 500 kbps. These data rates decrease depending on the increase in cable length.The devices are connected to the DeviceNet trunkline through droplines.
Distributed Control System (DCS)
Published in Chanchal Dey, Sunit Kumar Sen, Industrial Automation Technologies, 2020
DeviceNet is a network protocol employed in the automation industry and it was originally developed by Allen-Bradley (presently Rockwell Automation). It is an application layer protocol on top of the CAN technology. DeviceNet is a low-cost communication link to connect industrial devices such as limit switches, photoelectric sensors, valve manifolds, motor starters, process sensors, bar code readers, variable frequency drives, panel displays, and operator interfaces. DeviceNet is an open network standard maintained by Open DeviceNet Vendor Association (ODVA). It can connect up to 64 nodes and can communicate over a maximum distance of 500 m with thick trunk with a transmission rate of 125 kbps. Maximum drop length should be within 6 m. DeviceNet uses a differential serial bus and hence has strong noise immunity. Communications data is carried over two wires with a second pair of wires carrying power. DeviceNet provides faster installation and is less expensive compared to traditional point-to-point wiring. It can provide useful diagnostic information which can make systems easier to troubleshoot and minimize downtime. It supports master/slave and peer-to-peer communication; in addition, network-based communication is also supported by DeviceNet. It can also support multiple masters on a single network.
Networked Control Systems for Manufacturing: Parameterization, Differentiation, Evaluation, and Application
Published in Richard Zurawski, Networked Embedded Systems, 2017
James R. Moyne, Dawn M. Tilbury
The major disadvantage of CAN compared with the other networks is the slow data rate, limited by the network length. Because of the bit-synchronization, the same data must appear at both ends of the network simultaneously. DeviceNet has a maximum data rate of 500 kb/s for a network of 100 m. Thus, the throughput is limited compared with other control networks. CAN is also not suitable for transmission of messages of large data sizes, although it does support fragmentation of data that is more than 8 bytes into multiple messages.
Design of smart connected manufacturing resources to enable changeability, reconfigurability and total-cost-of-ownership models in the factory-of-the-future
Published in International Journal of Production Research, 2018
Stelian Brad, Mircea Murar, Emilia Brad
The generic architecture from Figure 3 was implemented into effective CPS solutions, illustrated in Figure 9, according to design requirements, performance requirements and C–R capability index required by the second scenario. This considers the CPS for the dual arm industrial robot in order to reach seven communication interfaces as required by the second scenario, and an FRDM-KL46Z development board featuring three communication protocols (I2C, UART, SPI), while the robot controller has four fieldbuses (Ethernet, Ethernet/IP, Interbus-S, DeviceNet). Considering the design requirements, the development board runs a real-time operating system, and uses a built-in debug interface via USB and a number of 84 GPIO to interface with external devices. When all I/O pins are used, it requires 400 mA, therefore for simple to medium applications current consumption shall be under 250 mA. The dual arm industrial robot and the three-finger adaptive gripper are interfaced to the CPS using the robot I/O board (Figure 9). These two manufacturing resources are designed to handle parts in the manufacturing system. For the complete integration of the robot and the three-finger adaptive gripper, specific robot tasks are also added by means of a dedicated robot application programme. By enabling/disabling I/O signals, the CPS associated to the robot calls specific routines on the robot controller’s side. The second gripper in the case study is a two-finger electric gripper. It is used to assist gripping tasks and it is mounted on the second arm of the industrial robot. This gripper is controlled by a proprietary control unit. It is interfaced to a CPS using a parallel I/O port control unit (Figure 9).
An industry 4.0 approach to electric vehicles
Published in International Journal of Computer Integrated Manufacturing, 2023
Lydia Athanasopoulou, Harry Bikas, Alexios Papacharalampopoulos, Panos Stavropoulos, George Chryssolouris
I4.0 KETs could deliver promising solutions on the generated challenges and issues, related to the vehicle design and the modularity of batteries (Figure 5). This involves the use of I4.0 concepts in various tasks during the development and efficient integration of the modular battery pack, as well as during the accurate monitoring of the battery condition and state of charge. Cloud-based BMS and the use of Digital Twins could deliver real-time and accurate processing of data obtained from the modular battery pack in order for the vehicle designer’s specifications (Weihan et al. 2020) to be metContext aware design of modular configurations, through the Genetic Algorithms for the modular design and connectivity (in series or in parallel) of the battery cells and modules (Breban 2016)Process Planning with main criteria cost, time, safety (i.e. heat during welding) and circularity (Gallagher and Nelson 2014)Product-Service System, as a hybrid technical-business model, to solve intellectual property rights (IPR) data (Meier, Roy, and Seliger 2010)Blockchain towards certification and IPRSafety Network protocols (CIP Safety, PROFIsafe, openSAFETY, FSoE etc.) and communication protocols used for the automation of processes (AS-I, BSAP, ControlNet, DeviceNet, CC-Link Industrial Networks, DNP3, UAVCAN etc.) to ensure safe operation of machinery in the replacing battery stations