Better decision making

Better decision making

Digitalization gives all industrial companies the means for better operational decision making and cost management. Basing decisions on accurate data and its expert analysis leads to improved health, performance and energy efficiency, and reduced CO₂ emissions from electrical motion equipment.

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Mari E. Haapala ABB Motion Baden, Switzerland mari.e.haapala@ch.abb.com

Globally, there are about 300 million systems that are driven by electric motors and this number is likely to increase. Improving motor system efficiency is of growing importance. Indeed, it is estimated that if all the motor systems currently in use were replaced with higher-­efficiency equipment, global energy consumption could be reduced by up to 10 percent [1].

One way to improve efficiency is to modernize older and less energy-efficient equipment. However, one-off modernization is only one possible step in the improvement process: Digital solutions now enable energy efficiency to be assessed and optimized on an ongoing basis →01. To enable these digital solutions, the equipment and processes concerned must be connected. Connection enables actual energy use data to be gathered, monitored and analyzed. Using the insights gained, service experts – either from the customer or their service partner – can then identify inefficiencies and opportunities and make recommendations for continuous improvement in energy use. One significant contribution to energy efficiency comes from keeping equipment in good working order. Here, data from digital solutions helps the operator choose the best maintenance strategy.

01 Digital solutions now enable continuous optimization of energy efficiency.
01 Digital solutions now enable continuous optimization of energy efficiency.

Better decision making with connected assets
To decide how to optimize energy efficiency on an ongoing basis, data about actual energy use and equipment performance must be collected. However, merely accumulating raw data is not enough: Relevant data needs to be identified and this is where a trusted service partner can be very valuable. There must also be access to the internal or external experts who can analyze and interpret results to identify effective ways to improve energy efficiency →02. The type of expertise required includes an understanding of the technology involved – for example, brand-­agnostic motors, or ABB drives.

02 Expert analysis of data is critical to performance optimization.
02 Expert analysis of data is critical to performance optimization.

Data gathering in practice
Connecting to devices to collect data and provide remote services has become much more straightforward since the advent of secure cloud platforms. Here, specially developed solutions – such as ABB Ability™ Condition Monitoring – can gather data from connected devices for use, even in remotely based facilities. Customers can then benefit from cloud-based analytics and insights without building or supporting data storage or computing facilities on their site. ABB Ability Condition Monitoring for powertrains, for example, is enabled through sensors that can be added to motors, generators, bearings and pumps or via sensing functions that are an integral part of the equipment, as with ABB drives. Parameters such as usage patterns, cooling, stress levels and power consumption can then be measured and tracked.

Data gathering is increasingly being applied to individual pieces of equipment as well as to whole processes and process areas. For example, it is possible to assess an entire powertrain’s condition and maintenance needs, rather than just those of the individual motors →03.

03 ABB Ability Condition Monitoring for powertrains is a solution that gathers data from drives, motors, pumps and can also be applied to applications such as compressors, conveyors, mixers and extruder main shafts.
03 ABB Ability Condition Monitoring for powertrains is a solution that gathers data from drives, motors, pumps and can also be applied to applications such as compressors, conveyors, mixers and extruder main shafts.

Continuous monitoring and condition-based maintenance
In condition-based maintenance, data is continuously gathered from equipment to monitor its status. The data is transmitted securely to the cloud, where the customer or authorized partners access, process and analyze it. An engineer will then interpret the data to assess the condition of the equipment, identify maintenance needs and recommend maintenance actions to their customer. This approach improves equipment reliability and performance and enables better maintenance scheduling while avoiding unnecessary maintenance work and reducing the need for manual inspections. Because the system monitors the equipment continuously, it can also provide alerts and alarms automatically if an unexpected deviation occurs.

In services that focus on energy efficiency, data about energy use is continuously gathered from connected motors and drives. Service experts can examine the data to gain insights into where energy could be saved, where the greatest inefficiencies are and where the most significant opportunities for savings can be found. Using this information, they can then advise on the options available and recommend the most effective course of action to improve energy efficiency. Once any changes are made, continuous monitoring enables the experts to follow up and verify the efficiency gains and to ensure that all motor systems continue to run as efficiently as possible in the long term.

Digital solutions in operation
At SCA’s kraftliner mill in Munksund, Sweden, the move to a fossil-free future is facilitated with the help of ABB digital solutions. Sustainability is at the core of the Swedish SCA Group’s operations, with a long-term goal of establishing a fossil-free value chain. SCA’s industrial processes are already 95 percent fossil-free thanks to bioenergy production. ABB Ability Condition Monitoring allows SCA to conduct secure collection of data, tailored to a specific operation, including indicators such as temperature or operational patterns.

The deeper insights into production processes that are realized through analysis of the collected data helps identify long-term trends in performance, thus improving equipment energy efficiency, reliability and uptime, and facilitating predictive maintenance.

Predictive maintenance
Predictive maintenance uses data to identify potential issues before they become a problem, which helps ensure process stability and maximum uptime. With predictive maintenance, service experts analyze current and historical data from motors and drives. With this longer-term overview, optimal maintenance intervals can be established, deviations in performance can be pinpointed and problems can be prevented →04. In addition, bottlenecks and opportunities for improvement can be identified.

04 Predictive maintenance on electrical rotating machines prevents small issues becoming big ones. Photo fig.: ©Banana Republic/stock.adobe.com
04 Predictive maintenance on electrical rotating machines prevents small issues becoming big ones. Photo fig.: ©Banana Republic/stock.adobe.com

ABB’s predictive maintenance approach was used in a cement factory operated by Mokrá in the Czech Republic, where there were difficulties tracking down the source of repeated, unplanned outages [2]. Using ABB Ability Condition Monitoring for drives, ABB personnel monitored the condition of Mokrá’s variable-speed drives continuously. The knowledge gathered from this data allowed ABB to identify the cause of the failures and recommend areas to investigate. This information enabled Mokrá to change from schedule-based maintenance to an approach in which they concentrated maintenance actions on the right equipment at the right time. By using ABB’s preventive maintenance solution, Mokrá can now also identify potential failures in advance, thus preventing unplanned shutdowns →05. In just three months, Mokrá saved over $210,000 and improved the performance and efficiency of their smoke fans without needing to make unplanned investments.

05 ABB Ability Condition Monitoring for drives solved an issue Mokrá had in a cement factory.
05 ABB Ability Condition Monitoring for drives solved an issue Mokrá had in a cement factory.

Outcome-based business models
Digitally enabled solutions can also be exploited to approach customer relationships in entirely new ways. For example, with traditional services, equipment manufacturers and service partners focus on responding to needs and finding solutions to any problems that arise. In contrast, with outcome-based business models, the idea is to shift risk from the customer to the service partner. The customer and their service partner work together to define critical outcomes and how these can best be achieved. The service partner then commits to the agreed objectives. For example, a customer might pay their service provider to ensure a guaranteed production availability or continuous energy efficiency. The service provider will then monitor the customer’s equipment remotely and take proactive maintenance actions to ensure the agreed outcome. Similarly, in the future, a customer might pay their service provider to improve their energy efficiency and optimize their energy use.

ABB already has such outcome-based business models in place. For instance, ABB has signed a 10-year service contract with Statkraft, Europe’s largest generator of renewable energy. This turnkey contract includes the design, manufacture and installation of two high-inertia synchronous condenser systems for the Lister Drive Greener Grid project in the UK [3]. As part of their service, ABB will ensure round-the-clock availability for the condenser system. With this outcome-based service, Statkraft will get a guaranteed level of uptime, together with maintenance from ABB. ABB will continuously monitor the equipment and take proactive maintenance actions to ensure that breakdowns never occur.

A digital and energy-efficient future
As industrial electrical motion equipment becomes increasingly connected, ABB is partnering with customers to deliver new digital solutions and service models that help them exploit digital data to enable better decision making. ABB’s digital services – such as condition monitoring and condition-based maintenance – use data to improve process reliability, maintenance optimization and energy utilization. Planned services, like predictive maintenance, look deeper into the data to reveal trends, enabling upcoming maintenance needs to be predicted well in advance. Both types of service help equipment run more efficiently and save energy and costs.

ABB is leading the way in digital solutions for energy efficiency for motors, generators and drives and offers digitally enabled services accessible to almost any business. These powerful new technologies can be adopted in small steps as customers digitalize their business. In the future, digital, outcome-based business models are expected to be a regular part of business life. ABB has the expertise and the technology to make the transformation to a digital and energy-­efficient future easier than ever before. 

References
[1] P. Waide et al., “Energy-efficiency policy opportunities for electric motor-driven systems,” International Energy Agency working paper, Paris, 2011, pp. 13, 17 and 118.
[2] “ABB’s condition monitoring services help Mokrá cement plant save $210K, while increasing operational efficiency.” Available: https://new.abb.com/news/detail/80450/abbs-condition-monitoring-services-help-mokra-­cement-plant-save-210k-while-increasing-operational-efficiency. [Accessed December 8, 2021.]
[3] “Statkraft chooses ABB synchronous condensers to help the UK National Grid meet its zero-carbon targets,” ABB press release, February, 2021. Available: https://new.abb.com/news/detail/74025/statkraft-chooses-abb-synchronous-condensers-to-help-the-uk-national-grid-meet-its-zero-carbon-targets. [Accessed December 12, 2021.]

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