Shuto Technology’s IBM Maximo-based solution helps reduce costs, streamline maintenance and scale operations worldwide.
As the global footprint of a leading automotive battery manufacturer expanded, so did the complexity of its operations. The company needed a future-ready way to optimize its asset utilization while adhering to rigorous quality standards across regions. Three pressing challenges emerged: increasing asset operational costs, surging production complexity, and fragmented data and processes across facilities.
To remain competitive, the company sought a solution that could unify disparate systems, eliminate data silos, streamline maintenance operations and improve cost control. Existing practices relied heavily on manual processes, resulting in inefficiencies, limited visibility and inconsistent standards across geographies. The goal was clear: leverage digital transformation to build an integrated, intelligent asset management platform that could scale globally while improving responsiveness, productivity and talent development.
To address the battery manufacturer’s global challenges, Shuto Technology—an IBM® Gold Partner—deployed IBM Maximo® Application Suite, an AI-driven asset lifecycle management platform. After a rigorous global evaluation, Shuto chose IBM Maximo Application Suite for its adaptability to complex industrial environments and its robust ecosystem.
Shuto formed a global team to co-design and implement an intelligent asset platform spanning all operational layers—from capital turnover and predictive maintenance to talent upskilling. The result was a seamless integration of equipment management, Internet of Things (IoT) monitoring and AI-powered insights, aligned with the client’s strategic priorities.
Shuto’s collaborative approach addressed fragmented operations by building a system that could support multilanguage, multicurrency and multilocation deployments. The partner leveraged IBM Assist and remote expert systems to accelerate diagnostics, while building a digital talent training infrastructure to ensure sustainable growth. This foundational transformation set a new benchmark for intelligent operations and enabled a shift from reactive maintenance to predictive planning.
The launch of the new platform marks a pivotal step in the client’s comprehensive transformation from traditional to digital asset management. This initiative is projected to deliver a return on investment (ROI) exceeding 450% within five years, underscoring its substantial value and long-term impact.
At the same time, the project is expected to bring multidimensional benefits, reflected in the following key performance indicators (KPIs):
Beyond these quantifiable gains, the client is poised for a significant cultural shift. Data and insights will drive decision-making at all levels, fostering collaboration across global teams and strengthening in-house capabilities through targeted training programs.
From headquarters to the shop floor, digital intelligence and operational resilience will form the foundation for sustainable growth. This initiative not only modernizes the client’s asset management strategy but also sets a new industry standard—demonstrating how Chinese enterprises can scale global operations with AI and hybrid cloud solutions at the core.
Beijing Shuto Technology Co., Ltd. (link resides outside of ibm.com) is a leading provider of enterprise asset management (EAM) solutions, based in Beijing, China. The company specializes in delivering advanced technological solutions to industries requiring efficient and intelligent maintenance systems, including automotive, manufacturing and industrial sectors.
Founded in 2006, Shuto Technology has become a prominent player in the field, with a strong focus on integrating AI, IoT and augmented reality (AR) technologies into maintenance workflows. The company serves a diverse range of clients, enhancing operational efficiency and helping organizations optimize asset management. With a team of over 100 employees, Shuto Technology continues to drive innovation and transform traditional maintenance practices for enterprises globally.
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Examples presented as illustrative only. Actual results will vary based on client configurations and conditions and, therefore, generally expected results cannot be provided.