June 25, 2024 By Kendra DeKeyrel 6 min read

It can be a daunting task to manage and maintain a complex system of assets for daily operational success. Organizations must constantly consolidate information from various sources and address issues in real time while also focusing on how to best innovate. The cost of unplanned downtime is increasing, skills shortages are hurting productivity, and sustainability initiatives increasingly pose a challenge to traditional maintenance practices. 

To address these challenges, companies must use technology that can provide intelligent and comprehensive asset management while also embedding sustainable practices. The positive results of this combination are tangible—an IBM Institute for Business Value study found that organizations that embed sustainability are 52% more likely to outperform their peers on profitability. 

IBM® is already helping its clients find the right solutions for their asset management needs while simultaneously exploring the future of asset lifecycle management (ALM). With the help of innovative AI-infused technology, enterprises can extend the lifespan of their assets and improve productivity and reliability, while reducing costs and advancing decarbonization. By bringing together generative AI, Internet of Things, environmental insights and our existing platforms, we are helping co-create a more automated and sustainable future for business. 

Moving toward ALM with AI-infused technology 

Asset lifecycle management combines a range of strategies designed to extend the lifespan of assets and increase their efficiency for a more comprehensive approach to strategic asset management. IBM is a leader in the ALM market, as IDC recognized in their latest Worldwide Semiannual Software Tracker®. Adopting ALM practices includes evolving maintenance efforts from reactive to predictive, which requires technology to proactively monitor an asset’s condition and performance rather than waiting for it to fail.  

A good demonstration of ALM capabilities is the effort that Transport for London (TfL) is putting into optimizing the city’s public transportation vehicles, including buses, boats, bikes and the tube. Our technology helps them proactively mitigate issues and extend the lifecycle of existing assets, reducing the need for replacement parts and limiting the risk of catastrophic failures. TfL estimates net savings of GBP 21 million over the next decade solely for its London Underground responsibilities.

This is just one example of ALM’s expected results, but there are even more opportunities to save time and money and to reduce emissions.  

The latest release of IBM® Maximo® Application Suite (MAS) version 9.0 introduces innovations that help to optimize asset lifecycles and meet evolving business needs by incorporating new data and AI features: 

Work order intelligence 

Generative AI can advance asset lifecycle management and provide organizations with further operational efficiency, asset reliability and success. Maximo Work Order Intelligence, now available in MAS version 9.0, uses IBM watsonx™ generative AI capabilities to speed up work order approval, improve data quality and provide highly reliable failure code recommendations. We continue to work together with IBM Research® to unlock further value from gen AI and our asset management solutions. 

To identify the right problem, we need sufficient and accurate data. Maintenance managers often spend significant time assigning the right problem code without enough information to identify the root cause of the issue, which leads to delays, errors and unnecessary resource expenditure. Maximo Work Order Intelligence uses generative AI to enhance insufficient data, and an AI model trained on work order descriptions provides recommendations for the most likely problem code. Maintenance managers can now quickly identify the issue, assign the right problem code, allocate the technicians accordingly and reduce troubleshooting time.  

This feature helps to speed up work order approval, prioritize maintenance resources and reduce errors. If more details are added to the work order, the AI recommendation is regenerated with the latest information to further increase the reliability score. As a result, organizations can reduce maintenance errors, avoid unnecessary operations, lower material costs and save maintenance personnel time to better prioritize their resources.  

Field service management 

To maintain assets, teams need visibility into their current state, which can be challenging when managing a wide variety of equipment and facilities, sometimes spanning different locations.

Maximo Field Service Management is a new solution in this 9.0 release that helps our clients provide exceptional field service experiences. This technology allows maintenance and dispatching teams to access advanced scheduling and intelligent dispatching. IBM Research provided advanced algorithms for Maximo Field Service Management that enable the system to handle 10 times more work orders and improve the number of jobs completed, total resources used, and job completion time by over 10%.

Thanks to this collaboration, the solution considers technicians’ location, availability, skills and craft to schedule and dispatch the right personnel at the right time. They can now also access critical asset information on the go, which helps resolve issues even faster. 

Reliability strategies 

Another challenge companies face is determining when maintenance of a particular asset is needed. Traditional preventive maintenance practices often rely on reactive or scheduled maintenance, which can lead to unnecessary downtime and costs. Optimizing preventive maintenance offers significant cost savings but can be time-consuming and resource-intensive, and might not show accelerated ROI.

Maximo Reliability Strategies now provides organizations with the ability to analyze failure modes and access a comprehensive library of asset-specific failure details and mitigation activities. This new solution makes it easier to create and optimize highly customized maintenance reliability strategies. We are further addressing this need by providing clients with the ability to access, create, import and modify failure mode and effects analysis (FMEAs) in this Maximo release. 

This technology can help companies develop more reliable assets that are less likely to unexpectedly fail. For the new MAS version 9.0, we collaborated with IBM Research and employed watsonx generative AI to develop more FMEAs and expand the library. It is now available for technical preview and will be fully released in the next MAS update for clients to build FMEAs faster and more effectively for any asset that is specific to their industry. By combining innovations from across the business, we provide more comprehensive solutions that drive greater value for our customers, moving us forward toward AI-powered ALM.   

Advancing decarbonization strategies with ALM  

Organizations in asset-intensive industries can play a significant role in driving sustainability. Research shows that 79% of greenhouse gas (GHG) emissions are sourced from the energy, industry, transportation and buildings sectors. This data highlights the need for enterprises, especially in these industries, to reduce their GHG emissions. Managing their assets with ALM systems can help reduce emissions by facilitating less costly and resource-intensive daily operations. 

Emissions management 

As industries strive for growth and profitability, they also face a critical challenge: managing operational emissions. Tools such as Maximo Emissions Management, now available in the Maximo Application Suite, can help balance operational efficiency with environmental responsibility. This integrated solution allows enterprises to monitor continuous and fugitive emissions in near real time and manage compliance programs. It also supports operational emissions reporting and strengthens corporate sustainability tracking through an integration with IBM® Envizi™ ESG Suite.  

We are also further empowering organizations with our new cloud-based data platform, Environmental Intelligence. The platform provides them with environmental data and insights that can help them mitigate the environmental impact on their assets and build more climate-resilient operations. This powerful combination of technology can unlock a more efficient, responsible and sustainable approach to business operations. 

Driving innovation in ALM 

In working with companies around the world, we continuously identify the new challenges surrounding asset management and develop new technology to keep up with this changing landscape. Maximo Application Suite version 9.0 includes new capabilities that can propel organizations toward higher levels of efficiency, reliability and success.

We are looking forward to further collaboration with IBM Research, IBM Consulting® and our clients to identify more ways to integrate AI capabilities in our software to achieve greater outcomes. In doing so, we continue to build comprehensive, integrated and automated solutions that can facilitate more efficient and effective operations. Ultimately, we aspire to continue innovating and building upon the future of asset lifecycle management. 

IBM Maximo Application Suite

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