Quant streamlines preventive maintenance with IBM watsonx.ai
With over three decades of experience in professional industrial maintenance services, Quant offers asset-class outsourcing and maintenance management across multiple sectors while prioritizing safety, efficiency and reliability. They faced a challenge, however, when one of Quant’s customer sites encountered an operational challenge stemming from legacy processes.
Preventive maintenance (PM) instructions—critical for uptime and productivity—were buried in over 1,500 Microsoft Excel files on SharePoint, accessible only as attachments in IBM® Maximo® Manage work orders. Technicians had to manually reference these files, limiting use of advanced Maximo features. This fragmented process decreased efficiency, risked data accuracy across more than 17 sites and resulted in a slow process that took over an hour per file to manually carry over content from Excel to Maximo. It prompted Quant to pursue automation and integration to unlock the full potential of Maximo.
To address the challenges of legacy preventive maintenance workflows, Quant collaborated with IBM® Client Engineering to build a cloud-native solution leveraging IBM technology. The solution focused on automating extraction, validation and transformation of PM data from Excel into formats compatible with IBM Maximo Manage.
Excel files were stored in a secured environment using IBM Cloud® Object Storage, with JSON outputs for integration and IBM Cloud Code Engine was used to create a scalable, serverless architecture for APIs and UIs.
At the core of the solution, the IBM watsonx.ai® AI studio assisted with intelligent data extraction using large language models (LLMs). AI services were executed within the IBM watsonx® machine learning runtime to help ensure secured, high-performance deployment. This modular design enabled scalable automation and seamless integration with IBM Maximo Manage.
Ultimately, Quant and IBM successfully developed a minimum viable product (MVP) that automates the conversion of Excel-based preventive maintenance instructions into structured job plans within IBM Maximo Manage. Leveraging intelligent automation, the solution streamlines maintenance workflows and reduces operational inefficiencies.
The MVP introduced a clear process supported by a user interface for validating and correcting extracted data. It separated tasks by asset, frequency and responsibility, producing JSON outputs compatible with Maximo. This method eliminated manual referencing of Excel attachments and enabled full use of the advanced features of Maximo.
As a result, Quant reduced manual labor for data extraction and job plan creation by 65% and shortened computerized maintenance management system (CMMS) implementation timelines by 30% for new sites and greenfield projects. These improvements marked a major step in the company’s modernization journey while reinforcing their commitment to scalable, data-driven maintenance operations.
Quant Service, founded over 35 years ago and headquartered in Stockholm, Sweden, provides professional industrial maintenance services. With a global presence, Quant’s references include over 400 facilities across sectors, supporting improvements in safety, equipment performance and operational reliability.
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