IBM and business partner bring intelligent equipment maintenance to automotive company with IBM Maximo

IBM® recently announced that it has worked with its business partner, Beijing Shuto Technology Co., Ltd. (hereafter as Shuto Technology) to help a joint venture Original Equipment Manufacturer (OEM) in China to obtain information in an accurate and cost-effective way for on-site technicians. This makes the client’s equipment repair work more efficient and improves the reliability of its equipment.

Founded in 2006, Shuto Technology is a leading asset management solution provider in China that focuses on helping industry-leading enterprises build asset operation and management platforms, and empower their core competitiveness through digitalization. With the professional ability and rich accumulation in the field of asset management, Shuto provides full-stack services of asset management (EAM) for hundreds of industry leading enterprises. Shuto also combines IBM Maximo® best practices and international standards (e.g. ISO55000), various business, process and data standards, management strategies and KPI systems that cover the asset lifecycle to form the best practices of asset management (EAM) in various industries.

In today’s automotive industry—with its rapid growth and increased market competition—improving equipment stability, reducing maintenance costs and improving production quality have become top priorities. However, for large automotive enterprises, the traditional equipment management and maintenance methods are faced with many challenges:

• Technical difficulties in maintenance: With the continuous transformation of automotive technology and process, maintenance technology is also constantly upgrading. Maintenance workers need to consume a lot of energy to check up the equipment data to understand and learn new skills, resulting in not only low maintenance efficiency, but also leading to a decline in employee satisfaction and loyalty.

• High cost of equipment maintenance: Due to the many auto parts, maintenance personnel need to master a more comprehensive failure analysis and diagnosis capabilities, resulting in a lot of investment in manpower, material and financial resources. This will make it harder to transfer existing skillsets in talents enablement.

• Unstable maintenance quality: The traditional maintenance approach relies on personal experience and the capabilities of maintenance workers. It is difficult to investigate the root cause due to the lack of professional technical guidance and unstable quality of maintenance that leads to frequent failures. The stability and lifecycle of the equipment is also decreasing, which is prone to production quality problems such as low yield rate.

To cope with these challenges, a major joint-venture automotive enterprise in China needs a holistic approach to achieve rapid access to equipment knowledge, intelligent diagnosis of faults, and expert online guidance, to make the maintenance process standardized, intelligent and transparent. Likewise, the venture looks to reduce costs and increase efficiency while enhancing user satisfaction and improving the comprehensive benefits of enterprise asset management.

Based on the AI-powered capabilities of IBM Maximo Application Suite (MAS), Shuto Technology joins hands with IBM Client Success Team and IBM China Development Lab to provide intelligent knowledge mapping, AI intelligent maintenance diagnosis, and AR remote maintenance assistance for the maintenance work of this automobile enterprise, making it an AI-powered EAM assistant.

The introduction of these features empowers maintenance personnel with all-around support and guidance, enabling them to quickly and accurately locate problems and provide solutions, as well as realize instant assistance from remote experts through AR-augmented reality technology, which improves maintenance personnel’s digital one-man capabilities, shortens mean time to repair (MTTR) by an average of 25% and improves maintenance efficiency while dramatically reducing the cost of enterprise equipment operation and maintenance.

Specifically, IBM Maximo Application Suite’s Intelligent Maintenance Assistant (Maximo Assist) can provide enterprises with the following capabilities:

• Intelligent Maintenance Knowledge Graphs: Intelligent Maintenance Knowledge Graph function utilizes AI technology through the import of equipment documentation, and uses knowledge extraction capabilities to establish a full-text search knowledge graph, provide a fast and accurate knowledge base, help on-site personnel give independent solution to technical problems, and provide rapid access to equipment and maintenance information.

• AI intelligent maintenance diagnosis: AI intelligent maintenance and diagnosis uses AI technology and intelligent diagnostic models to guide technicians in diagnosing faults in the form of questions and answers. Likewise, it provides the percentage of fault possibility through AI diagnostic model analysis and formulates a fast and accurate maintenance plan. At the same time, the diagnostic process bolsters the accuracy of model analysis with the help of the powerful self-learning ability of AI, to continually improve through the use and feedback.

• AR remote maintenance assistance: AR remote maintenance assistance uses AR augmented reality technology to realize real-time visual sharing and interaction between remote equipment experts and field personnel, providing visual maintenance guidance and technical support, and at the same time builds a platform for enterprise knowledge inheritance through the expert database and passes through the “last mile” of experts to the production site.

Through the deployment of IBM Maximo Application Suite Intelligent Maintenance Assistant (Maximo Assist), the automobile enterprise has gained the following benefits:

• Improve the efficiency of information acquisition: Through the implementation of the IBM Maximo Application Suite, the maintenance management level of this large automobile enterprise has been successfully optimized. This has changed the traditional on-site maintenance approach where personnel used to run to the data room to flip through the information; adopting the intelligent positioning of maintenance data through on-site scope helps promote transparency, standardize the maintenance management, and automate the maintenance method. Thistop-down approach to maintenance data and document standardization provides valuable intangible assets that lay solid foundation to corporate knowledge and learning and development (L&D)
• Shorten repair time: Through the construction of fault diagnosis model, IBM Maximo Application Suite platform can accurately track down the problems, find out the root cause and provide solutions in a problem response mode called PDCA. In addition, Maximo Assist can accurately jump to the function of the document corresponding to the fault and the repair solution, and allows users to provide feedback and ratings on the repair solution. Likewise, it can provide best practice repair methods based on historical data and sort the matching degree. In addition to improving maintenance efficiency and reducing the mean time to repair (MTTR), it also provides maintenance personnel with more convenient and accurate solutions for difficult troubleshooting.
• Enhance and empower existing IT systems: IBM Maximo Application Suite can be seamlessly integrated with the client’s existing work order system, asset management system and human resource management (expert database) and other systems to automatically generate maintenance knowledge graphs. At the same time, through instant training of AI models, maintenance knowledge is combined with work order and asset business to ensure that equipment maintenance information can be accurately, timely and completely reflected in the standard work of the enterprise’s own asset management platform, thus building a comprehensive maintenance knowledge base. This integrated solution ensures the data integration and information sharing within the company, enhancing inter-system data connectivity to improve the efficiency and quality of maintenance work.
• Establish a “Four-Pool” knowledge system: Given the inefficient retention of skills and experience, the client and Shuto Technology created an enablement system to support maintenance skills enhancement and personnel training, also known as the “4 knowledge pools:” 
  • An equipment knowledge pool for knowledge accumulation and query;
  • An equipment course pool of learning resources for eliminating weak points in skills;
  • A talent pool able to quantitatively evaluate the knowledge and skill mastery of personnel with gamification features;
  • An expert pool incorporating experts in all relevant areas to support the maintenance guidance of field operators.

Through the creation of the “four pools,” around the “knowledge accumulation–knowledge sharing–skills evaluation–skills inheritance” training model, the client manages to improve equipment management and employee competence, providing a merit-based motivation mechanism of performance bonuses, promotion and recognition, with the “four pools” at the core.

After adopting IBM Maximo Assist, the client’s equipment maintenance efficiency improvement has begun to bear fruit, shortening average repair time from 13 minutes to 9 minutes. For next steps, Shuto Technology and IBM will continuously deepen and expand the application of the intelligent maintenance assistant, integrate with more information systems (e.g. production systems, IoT platforms etc.) of the client to optimize data sharing and business synergy.

At the same time, the two companies will help the client expand its use of Maximo Assist, build a unified equipment knowledge sharing and management platform, create an expert pool at the group level, and build a cross-region and cross-factory remote maintenance guidance and service center.

As Zhu Shufeng, General Manager of Shuto Technology said, “Intelligent digital transformation is the future of enterprises, and IBM Maximo is an ideal solution for achieving that goal. The successful implementation of this project not only reflects the leading position of Shuto Technology in the field of enterprise asset management, but also highlights our deep understanding and practice of combining innovation with equipment maintenance. Shuto Technology will maintain a close partnership with IBM, accelerate our R&D efforts and deployment, and continuously innovate to build a more intelligent and efficient equipment management ecosystem that provides our clients with sustainable growth and value add.”