Tongtai CPS Agent: AI-Powered Production Planning
Source: Business Next, October 19, 2026
Topics: Smart Manufacturing, AI Agents, Cyber-Physical Systems (CPS)
What Is a CPS Agent?
The CPS Agent is an in-house AI agent developed by Tongtai Machine & Tool Co., Ltd. to support production line planning proposals.
CPS stands for Cyber-Physical System, which integrates physical manufacturing systems with their digital counterparts. By using this approach, Tongtai can simulate and validate production line configurations in a virtual environment before actual implementation, helping reduce the cost and effort associated with repeated trial and error in customized production line projects.
The CPS Agent takes on many of the engineering tasks traditionally performed manually, including writing programs, operating simulation tools, and analyzing production line configurations. Engineers remain responsible for reviewing the results and making final decisions.
The Engineering Challenges of Customized Production Lines
Since its establishment, Tongtai has focused on developing special-purpose machines tailored to customer requirements. The company later expanded its portfolio to include general-purpose machine tools, while maintaining its commitment to solving customers’ manufacturing challenges.
Unlike standardized production solutions with established configurations, customized production lines require engineering teams to design and evaluate each project according to specific manufacturing requirements.
Tongtai has adopted digital twin technology to simulate production line operations in a virtual environment before actual installation. However, as customization requirements become increasingly diverse, engineers must evaluate more production line configurations, costs, and feasibility scenarios.
A considerable amount of engineering time can be spent on preliminary data preparation, such as gathering files and generating datasets, rather than on engineering analysis itself.
Another challenge is that critical expertise is often distributed across different specialists. Professionals with programming and AI expertise may not have in-depth machine tool industry knowledge, while experienced engineers with extensive manufacturing know-how may be less familiar with newer programming tools.
Tongtai’s approach is to bring these complementary capabilities together through the CPS Agent workflow.
Structuring Engineering Expertise into Knowledge, Skills, and Tools
Tongtai breaks down engineering work into three fundamental elements, gradually transforming them into capabilities that AI can understand and invoke:
- Knowledge: What to know.
- Skills: How to perform a task.
- Tools: Which tools to use to complete the task.
Rather than simply storing static information, the CPS Agent is designed to understand how a specific requirement can be translated into engineering data, processes, and solutions for evaluation.
By structuring engineering expertise in this way, Tongtai aims to make accumulated knowledge and practical experience more accessible and reusable within AI-assisted engineering workflows.
How the CPS Agent Supports Production Line Planning
Previously, engineers were responsible for interpreting production line layouts and processes, writing simulation programs, operating digital twin tools, and analyzing the results.
With the CPS Agent, engineers first define the problem and prepare the necessary data. The agent then takes over many of the intermediate engineering tasks, while engineers review the results and make the final decisions.
Depending on project complexity, the time required to complete a production line planning proposal has been reduced from approximately three days to 180 minutes, with some cases completed in as little as six minutes.
This approach allows AI to assist with time-consuming engineering tasks while keeping technical judgment and decision-making in the hands of experienced professionals.
Why Tongtai Keeps Software and AI Capabilities In-House
Since the Industry 4.0 era, Tongtai has maintained a strategy of developing and retaining its software capabilities internally.
Machine tools typically have long service lives, often exceeding 10 to 20 years. Throughout this period, manufacturers must continue providing technical support, software maintenance, and after-sales services. Relying heavily on external partners can create long-term challenges if their departments, priorities, or development programs change.
The same consideration applies to AI transformation. Excessive dependence on external consultants may make it difficult to establish sustainable AI applications within an organization, particularly if the expertise and capabilities are not retained after external teams leave.
Tongtai’s Smart Manufacturing Division currently has approximately 90 employees, including around 30 software engineers. When introducing AI into engineering workflows, Tongtai also encourages employees closest to the actual work to explore suitable applications, rather than relying solely on top-down KPI requirements.
This approach helps build practical AI capabilities based on real engineering needs and internal expertise.
TLM: Extending AI Agent Capabilities to Connected Manufacturing Systems
Tongtai’s TLM (Tongtai Line Management) is an internally developed production line connectivity system that connects manufacturing equipment and collects shop-floor data. It can also integrate machines from other manufacturers and currently connects approximately 2,000 machines.
With the addition of AI agent capabilities, customers can use natural language to access equipment status and operational performance information more efficiently.
Previously, customers might have needed to request customized data reports from Tongtai. With AI assistance, these reports can now be generated and modified more quickly.
Tongtai anticipates that industrial software users will increasingly include not only people, but also AI agents and human-AI collaborative systems.
As Tongtai develops AI agents for its own products, it is also preparing communication interfaces that allow customer-side AI agents to interact with and invoke machines and software as tools.
This provides a foundation for broader intelligent integration across entire production lines and manufacturing facilities.
Conclusion: Turning Engineering Expertise into AI-Accessible Capabilities
Tongtai’s approach to AI integration focuses on three key areas: structuring engineering work into knowledge, skills, and tools; developing and maintaining software and AI capabilities in-house; and extending AI agent applications to customer-facing manufacturing systems through TLM.
By making engineering expertise more accessible to AI, Tongtai aims to support engineers in handling complex tasks more efficiently while retaining human judgment in critical engineering decisions.
As smart manufacturing continues to evolve, the integration of engineering knowledge, digital tools, and AI capabilities will play an increasingly important role in addressing diverse manufacturing requirements.
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