Abstract
The Industrial Internet of Things and Industry 4.0 paradigms are steering the industrial landscape towards better connected entities, superior interoperability and information exchange, which lays the basis for developing more intelligent solutions that are already starting to bring numerous benefits. The current research aligns to this course, in an attempt to build an automated and autonomous software tool, capable of reducing the energy consumption of a water treatment and distribution facility, by optimizing the water sources usage. Based on several previous researches, the present paper details both the complete automation of the optimizing strategy inside a proactive historian application and the tests executed with the finished solution. Possessing the abilities to directly influence the monitored system in a non-invasive manner, and to link all the sequences of the algorithm automatically, the solution is now ready for long-term functioning without any external interference.
Highlights
As a first remark, the primary point of interest regarding future research and development in the contemporary industrial environment gravitates around improvements in availability, safety, productivity and cost reduction, all of them obtainable through better interoperability, connectivity and information exchange between different industrial entities
The primary point of interest regarding future research and development in the contemporary industrial environment gravitates around improvements in availability, safety, productivity and cost reduction, all of them obtainable through better interoperability, connectivity and information exchange between different industrial entities. Those new links between previously isolated mechanical systems would set the required conditions for the emergence of intelligent software solutions that, eventually, will be capable of optimizing technical systems and maximizing their performances, with directly measurable benefits for all parties involved. This relatively recent, wide spectrum, fast advancing, high potential, huge interest drawing research direction from the industrial branch is guided at the conceptual level by the Industrial Internet of Things (IIoT) [1,2,3,4,5] and Industry 4.0 [6,7,8,9,10] paradigms, both very similar approaches which are pleading towards the introduction of digitalization into industry and connecting the physical world to the Internet [11]
It must be highlighted that the objective of the current paper was not to prove the efficiency of the energy consumption reduction strategy, because the results had been proven in [40], where it was shown that the strategy reduced the energy consumption of a drinking water treatment plant (DWTP), by 9% in a model with real input data, and by 30% in a test conducted on a real process that used only a part of the algorithm
Summary
The primary point of interest regarding future research and development in the contemporary industrial environment gravitates around improvements in availability, safety, productivity and cost reduction, all of them obtainable through better interoperability, connectivity and information exchange between different industrial entities Those new links between previously isolated mechanical systems would set the required conditions for the emergence of intelligent software solutions that, eventually, will be capable of optimizing technical systems and maximizing their performances, with directly measurable benefits for all parties involved. Narrowing the focus on the water industry, which represents the deployment target of the current research, the specific landscape of this domain is still predominated by legacy systems, consisting of a large variety of technical solutions and processes, contributing to a heterogeneous, chronologically dispersed perspective and even inefficiency, if modern standards are considered. The general perspective in the manufacturing industry is more or less the same
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