IIoT-based energy management for flexible production

Energy flexibility is gaining momentum since renewable energy increases volatility in the energy market. By increasing renewable energy sources like wind energy, PV power harvesting etc., more green energy is pushed into the market and prices decrease in the spot market [1,2]. Actually, a win-win situation in terms of cost and emission reduction. In the manufacturing sector energy flexibility often means optimising production plans according to the cost-efficient available energy in the market. By connecting manufacturers and consumers, the Internet of Energy — or IoE for short — give you opportunities for demand-side energy management by responding to current and forecasted energy costs.

But how high are your savings relating to energy efficiency potentials?

It isn’t easy to give generalised estimates of cost savings. It depends very much on your specific use case, the depth of analysis and the actions of improvements that have been done. Was only one target value changed in a production program or was a complete process changed? This blog highlights the challenges and suggests solutions to make your production more energy-flexible.

Status quo

What are the current challenges of manufacturing companies when using energy management?

Although awareness of the importance of energy management has arrived in the manufacturing sector, a successful implementation proves challenging in practice. The hurdles arise at the beginning: Infrastructure development is costly, detailed knowledge about energy consumption is rare, and energy data is often collected separately with energy meters and stored in isolated energy management solutions. These solutions are often pure time series tools with simple visualisations without consideration of production context information or further business logic. Production plans and order information are stored mostly in ERP systems, machine and product information are stored in PDM/PLM (short for Product Data/Lifecycle Management) systems and are not linked directly to energy data. These data silos do not yet enable an automatic analysis of energy data using key performance indicators.
PDCA (Plan-Do-Check-Act) cycles are required by ISO 50001 [3] to continuously loop actions for planning, doing, checking and acting in order to improve energy savings. In practice, it can be difficult to implement. In a consulting project, a machine manufacturer wanted to increase energy efficiency. Energy monitoring was implemented at the factory level. For this purpose, the air conditioning of the factory, the electricity consumption and the cooling of machine tools were recorded. Nevertheless, the company was unable to assess its energy efficiency. The company uses simple energy monitoring tools that only store energy data. Because changes to production processes were not documented with links to corresponding energy data, improvements could not be traced back to resulting consumption.

Integrate the shop floor

This results in the central challenge for energy management: Automated, context-based and standardised shop floor data evaluations are the basis for energy management.

But how can IIoT Systems support this challenging requirement? The industrial Internet of Things or IIoT for short can be understood as the manufacturing operation backbone of a company. IIoT systems allow you to manage the company’s assets from your shop floor like products, plants, systems and machines — and to monitor current operations in production. As a central location, IIoT Systems lets you collect, aggregate, store, visualise and analyze data. Energy KPIs can be configured on every level in your factory hierarchy and thus give you the context for evaluations. In addition openness and connectivity are characteristics of IIoT systems which helps to connect energy meters and link information from other company-wide systems. Bringing IIoT and IoE together means the possibility to monitor production, enrich energy data with current electricity prices and use forecasting techniques to optimise and estimate production plans accordingly.

We have used CONTACT Elements for IoT [4] to show what an energy management dashboard can look like. Here we see on the dashboard how order data is linked to energy data. As an example, we can see the energy assessment of a production order for the manufacturing of a motor shaft. The production order is linked to a production plant whose utilisation can be evaluated through operating states and energy indicators. In addition, the energy consumption can be used to apply to the manufactured products. Due to the standardisation of energy data and production information, predefined energy KPIs can be applied automatically for reporting and continuous improvement in PDCA cycles. Improvement actions can be documented in the context of an asset and management at the factory level.

Conclusion

How high are the savings potentials using energy flexibility under real conditions?

To optimise energy consumption, a valid data basis must be created. Procuring and integrating data sources represents a major organisational and technical challenge. IIoT systems can provide technical support as they are already networked on the shopfloor. Production orders, product information and energy consumption can be consolidated in an IIoT system to record production load profiles systematically and continuously. This provides the basis for implementing PDCA cycles for continuous improvement and optimisation.

How can organisational integration into everyday planning succeed?

This question must be evaluated individually and represents a challenge that each organisation must address in an adapted manner. Production planners work differently and are subject to different constraints. Series manufacturers certainly have less potential for flexibilisation than contract manufacturers. The identification of energy assessments can be a first step in promoting energy optimisation within the company. A simple classification using a traffic light system that evaluates the energy consumption of a production order can be a first step towards the automatic optimisation of production plans in a flexible sense.

References

[1] https://www.irena.org/news/pressreleases/2022/Jul/Renewable-Power-Remains-Cost-Competitive-amid-Fossil-Fuel-Crisis
[2] https://www.smard.de/page/home/topic-article/209944/211148
[3] https://www.umweltbundesamt.de/publikationen/energiemanagementsysteme-in-praxis
[4] https://www.contact-software.com/en/products/iot-platform-for-digital-business-models

About CONTACT Research. CONTACT Research is a dynamic research group dedicated to collaborating with innovative minds from the fields of science and industry. Our primary mission is to develop cutting-edge solutions for the engineering and manufacturing challenges of the future. We undertake projects that encompass applied research, as well as technology and method innovation. An independent corporate unit within the CONTACT Software Group, we foster an environment where innovation thrives.