Operation and Maintenance (O&M) has always been the focus of Industrial Robots (IRs) research. Currently, Complex, large-scale, and multi-party industrial robot O&M pose the following challenges. On the one hand, traditional O&M methods have to be broken through to reduce downtime, improve process quality, and lower labor costs. For example, preventive maintenance may be unnecessary and costly, process optimization based on the Six Sigma strategy may be inaccurate, and knowledge sharing through documentation and expert experience is inefficient. On the other hand, parties related to IRs including manufacturers, users, and research institutions all hope to establish a multiple-tenant mechanism to strengthen collaboration while ensuring data isolation, thus achieving economies of scale.

To solve the problems, a research team led by Xudong LIU published their new research on 15 Apr 2025 in Frontiers of Computer Science co-published by Higher Education Press and Springer Nature.

The team proposed ACbot, the first IIoT platform for IR with a multitenancy-oriented information model and a three-tier cloud-edge-device architecture. Then, they realized a cloud-edge collaboration mechanism implemented by a containerized solution, microservices service, and orchestration engine. Above the architecture, they developed real-time monitoring, health management, production process optimization, and a knowledge graph as four intelligent applications for IR. Finally, the ACbot platform was applied in real-world scenarios for validation. It accessed 10 companies and academic institutions, managed 60 IRs, collected about 100 billion time series points from devices, and provided the abovementioned services for them.

Currently, the largest IR customers are automotive manufacturers with more than 1,000 IRs in a single plant, but they have doubts about accessing the ACbot platform because of issues such as vendor lock-in and data security concerns. In the future, new cooperation mechanisms and standardized architectures need to be explored with manufacturing companies and vendors to facilitate IIoT platforms to access a large number of industrial devices and deploy more intelligent applications.

DOI: 10.1007/s11704-024-3449-x