Evaluation of Energy Consumption in Industry 4.0

Wireless sensor networks (WSN) are significantly important in the advanced monitoring of applications for the Internet of Things, particularly in difficult-to-access locations where wired solutions are impractical or expensive. Critical elements and characteristics of WSNs in terms of power consumption are being characterized and evaluated. However, there is a gap in research in terms of selecting and structuring the most efficient (WSN) in consideration of energy sustainability and the amount of required energy by the WSN that can be supplied wirelessly. In this thesis, a systems-level approach was taken to evaluate the energy required for sensing, processing, and communication over a WSN for an industrial application. A literature review was also conducted to identify the power consumption of some transducers typically used in manufacturing, such as temperature, acceleration, and displacement transducers. Additionally, the power consumption of the commonly available local processing units used to produce “smart” sensors was compared in this work. Different data transmission protocols were also evaluated for power consumption in different operation modes for different microcontrollers. These requirements and results taken from the literature were used to identify the power consumption at each location in WSN. This was then used to create a framework for surveying the theoretical requirement (limits) to power each of these locations. Various power sources were considered as possible solutions, including energy storage (wired and wireless charging), power distribution, and power harvesting techniques. The framework can be used in one of two ways; the WSN can either be modified to reduce power consumption to meet supply (for example, changing the operational mode to a more energy-efficient one), or a different power supply can be proposed to meet demand. In this way, the framework provides a tool for the design of any industry-based WSN. Finally, a machine tool was used as a case study to show how the framework can be used, in consideration of the available energy harvesting techniques that can be used to power specific elements of the WSN. Further work should focus on investigating the possibility of using other techniques to optimize the power consumption of WSNs considering the available wireless energy sources, as well as suggest other efficient techniques.