Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring

Abstract

Industrial environments are heterogeneous systems that create challenges of interoperability limiting the development of systems capable of working collaboratively from the point of view of machines and software. Additionally, environmental issues related to manufacturing systems have emerged during the last decades, related to sustainability problems faced in the world. Thus, the proposed work aims to present an interoperable solution based on events to reduce the complexity of integration, while creating energetic profiles for the machines to allow the optimization of their energy consumption. A publish/subscribe-based architecture is proposed, where the instantiation is based on Apache Kafka. The proposed solution was implemented in two robotic cells in the automotive industry, constituted by different hardware, which allowed testing the integration of different components. The energy consumption data was then sent to a Postgres database where a graphical interface allowed the operator to monitor the performance of each cell regarding energy consumption. The results are promising due to the system’s ability to integrate tools from different vendors and different technologies. Furthermore, it allows the possibility to use these developments to deliver more sustainable systems using more advanced solutions, such as production scheduling, to reduce energy consumption.

From Industry 4.0 towards Industry 5.0: A Review and Analysis of Paradigm Shift for the People, Organization and Technology

“…The adoption of new technologies has negative impacts on the environment, such as air pollution and intensive use of raw materials and energy [95]. However, by adoption of new technologies, the energy can be reduced by analyzing data during the production process and across the supply chain [96]. Furthermore, the process of the technology selection should include environmental and social criteria in order to select technology that is greener and more sustainable, although it can be less productive, at the same time [97].…”

Real-Time Streaming and Event-driven Control of Scientific Experiments

“…There is an abundance of work surrounding event-driven data management in the context of manufacturing processes [31]. One such example uses Kafka, Grafana, and SQL databases to collect, monitor, and act on manufacturing data [4]. The main difference with their approach is using the ksqlDB database to perform operations on data.…”

“…The adoption of Internet of Things (IoT) devices, sensor networks, industrial IoT tools, and event-driven data management has been particularly widespread in advanced manufacturing [3], [4] and is instrumental to Industry 4.0 [5]. Examples of industrial IoT include devices to monitor instruments and shop floors [6], predict necessary maintenance [7], and optimize processes [6].…”

Influence of working height on the energy consumption of an industrial robot

“…The amount of used energy depends on robot size and type, type of performing task, efficiency of components or operating conditions [4]. Reducing energy consumption plays an important role not only in reducing the cost of the production process, but also in reducing the impact on the environment due to the reduction of the carbon footprint [5]. In addition, research of industrial robot energy consumption can help manufacturers to improve their strategy for energy flexibility in energy supply [6].…”