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Industry 4.0: Key Concepts Contributing To Energy Management

Industry 4.0: Key Concepts Contributing To Energy Management

Coined by the German government in their strategic initiative to be more competitive, Industrie 4.0, or Industry 4.0 to the rest of the world, is a term that continues to gain strength. Its principal objective is to drive digital manufacturing and promote interconnectivity between products, value chains, and business models.

Today, many recognise Industry 4.0 as the digital transformation of the industrial market with smart manufacturing on the front lines. Moreover, it represents and is interchangeably referred to as the Fourth Industrial Revolution, which has been looked at from the perspective of many other sectors leading to the conception of more ‘4.0’ terms, such as Logistics 4.0 and Construction 4.0. Going beyond all these jargons, let us now explore the important concepts and technologies behind Industry 4.0 in energy and utility management.


1. Industrial Internet of Things 

The Internet of Things (IoT) is a widely discussed concept defined as a network of physical devices, including electronics, actuators, sensors, and connectivity, that enable the integration of computer systems and the physical world. In the context of Industry 4.0, this becomes Industrial IoT, which refers to the application of key technologies like Big Data and machine learning to take advantage of sensor data, automation systems, and communication between machine to machine (M2M) to enhance industrial and manufacturing processes.

Regarding energy and utility management, Industry 4.0 realises the connectivity between measuring devices and the whole IT and automation architecture of organisations. As a result, extending the capacities for communication, collection, and storage of immense volumes of data related to the generation, consumption, and transformation of energy inputs becomes possible.


2. Analysis of large volumes of data

Virtually all industrial applications now involve high data collection frequencies and enormous amounts of data per day. For instance, in energy quality applications, current specialised meters help visualise the network every millisecond. The increasing availability of computational power and abundance of data prompts the use of artificial intelligence and its techniques to predict variables and identify patterns of interest in many industrial processes.

Due to these high volumes of data and the limitations of the devices used to capture them, developing prediction models based on this collected data involves significant levels of noise that impose more pressure on the variety, volume, veracity, and speed requirements of the data, which is rather common to Big Data applications. As such, algorithms that can efficiently process data quality are becoming essential components in developing prediction models.


In energy and utility management, this available data can lead to:

Prediction models for energy generation or consumption of operations, beginning from planned production levels to other contextual variables

Models for analysing a given process’s energy efficiency

Models for learning and establishing which modes of operation permit the most effective and ideal levels of energy consumption


3. Extensive monitoring

With today’s advanced monitoring instruments for industrial processes, it is now possible to capture data in higher resolutions, which leads to even more powerful analyses. When it comes to energy and utility management, modern physical instruments and meters allow it to interpret physical quantities that help understand processes of interest and monitor variables from harmonics to applied power to describe the quality of electricity consumed.

Besides technological advances, the costs of acquiring and installing sophisticated sensors and instruments have also become highly accessible, resulting in a deeper understanding of the characteristics of said processes. This allows for redundancy of measurements and access to high-quality data, both essential components to planning, controlling, and improving energy and operational efficiency.


4. Efficiency and sustainability

Improving the competitiveness and efficiency of an operation is the ultimate objective behind all the investments toward Industry 4.0. The benefits it offers are direct and can potentially lead to establishing an advantageous cycle of investment, results, and reinvestment. Greater competitiveness leads to improved financial results. And with more cash in hand, additional investments can be spent on productivity technologies, capacity expansion, and energy and operational efficiency. Optimised efficiency promotes lower greenhouse gas emissions, reducing an organisation’s environmental impact and improving the quality of work.


Conclusion

Energy and utility management is one of the main pillars behind Industry 4.0, and it is motivated by several factors such as cost pressure and regulation, along with the proactiveness of many organisations towards achieving greater efficiency in their energy and utility consumption. 

Working with a reputable energy management company in Singapore is the best option if your organisation wants to achieve similar efficiency levels in your energy consumption and save on energy costs. At KJFEM, we provide energy management solutions that incorporate a consistent performance-based Operation and Maintenance (O&M) methodology that delivers the best possible results cost-effectively. To learn more about our energy management services in Singapore and the benefits it brings to your organisation, don’t hesitate to contact us today!

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