Huier: The manufacturing AI super brain created by Fangtian Software, reshaping the new paradigms of
From "experience-driven" to "data intelligence": How does Fangtian "Huier" reconstruct the four core lifelines of the manufacturing industry?
Say Goodbye to Guessing: Fangtian AI Assistant "Hui'er" Ignites a Revolution in Pricing, Processing, and Scheduling Efficiency
A New Engine for Intelligent Manufacturing: Unveiling How Fangtian's "Hui'er" Uses AI to Seamlessly Connect Quotation and Delivery
When a seasoned craftsman meets a large-scale model: Fangtian "Hui'er" defines a new standard for intelligent decision-making in manufacturing.
In the deep waters of digital transformation in manufacturing, enterprises often face the dual dilemmas of "numerous data silos" and "a gap in expert experience." From rapid quotation at the sales end to process planning at the technology end, and then to time assessment and intelligent scheduling at the production end, any lag or deviation in any link will be amplified into delivery delays, cost overruns, and even customer loss.
As a national-level specialized and innovative "little giant" enterprise, Fangtian Software has launched an AI intelligent assistant based on large model technology in its core product, T-ONE system.Hui'erIt's more than just a chatbot; it's a "super brain" for the manufacturing industry, deeply integrating over two decades of Fangtian's industry know-how. Through the combination of generative AI and operations research algorithms, "Hui'er" is completely reshaping...Intelligent quotation, automatic process generation, standard working time calculation, AI intelligent schedulingFour core scenarios help enterprises move from "sweat-driven" to "smart-driven".
Intelligent pricing: Instant response, eliminating waiting time for business opportunities.
In the traditional model, quoting for non-standard customizations (such as molds and parts) is a grueling task that heavily relies on the experience of senior engineers. Faced with complex 3D drawings, engineers need to manually dissect features, estimate materials, predict process routes, and calculate working hours, often taking several days to produce a quotation. This not only results in a slow response time but also makes it difficult to guarantee the accuracy of the quotation due to differences in personnel capabilities, easily leading to the awkward situation of "quoting too high and losing the order, quoting too low and incurring losses."
Hui'er's solution to break the deadlock:
Automatic drawing parsing and feature recognitionCombining computer vision and large language models, "Hui'er" can directly read CAD/3D drawings and automatically identify the geometric features (such as holes, slots, and curved surfaces), material requirements, and precision levels of parts.
Intelligent matching of historical casesBased on the massive historical order database accumulated by Fangtian T-ONE, "Hui'er" can instantly retrieve processing cases of similar parts and refer to the actual materials, labor hours and equipment types consumed.
Dynamic cost modelingThe system has a built-in, real-time updated database of raw material prices, equipment rates, and labor cost models. "Hui'er" can automatically generate detailed quotations including material costs, processing fees, management fees, and profits based on current market fluctuations and corporate strategies.
ResultsThe quotation cycle has been reduced from "days" to "minutes", improving the accuracy of quotations by more than 30%, enabling the sales team to respond to customer inquiries instantly and significantly increasing the success rate of closing deals.
Process flow generation: digitizing and standardizing the experience of master craftsmen.
Standard Operating Procedures (SOPs) are the "legal documents" that guide production. However, traditional process development is not only time-consuming and labor-intensive, but also highly dependent on the personal experience of individual "master craftsmen." Once personnel turnover occurs, valuable process knowledge is lost, new employees are slow to learn, and process consistency is difficult to guarantee.
Hui'er's solution to break the deadlock:
Construction of process knowledge graphFang Tian transforms industry-standard processing rules and implicit experiences within enterprises (such as the heat treatment deformation laws of a certain type of material and the optimal cutting parameters of a specific piece of equipment) into structured knowledge graphs and feeds them to "Hui'er".
One-click generation of process routesInput the part information and technical requirements, and "Hui'er" will automatically generate a complete process route, including the sequence of operations, selected equipment, cutting tools and fixtures, cutting parameters and quality inspection points.
Explainable RecommendationsUnlike black-box algorithms, "Hui'er" can explain "why this process was chosen" and "why this equipment was used," and provide alternative solutions for engineers to review and confirm, achieving the best collaborative model of "AI assistance + human decision-making."
Continuous self-evolutionAs production data is fed back (such as actual processing time and yield feedback), "Hui'er" continuously corrects and optimizes its process recommendation logic, becoming smarter the more it is used.
ResultsImproved process planning efficiency80%This shortened the work that originally took 3 days to be completed in 2 hours, while significantly reducing reliance on specific personnel and realizing the assetization and transfer of process knowledge.
Standard working hours calculation: From "estimation" to "precise forecasting"
Standard working hours (ST) are the cornerstone of production planning, cost accounting, and performance evaluation. Traditional time setting often relies on stopwatch measurement or experience-based estimation, which suffers from strong subjectivity, data lag, and difficulty in covering all product variations, leading to inaccurate planning and distorted costs.
Hui'er's solution to break the deadlock:
Feature-based parametric modeling"Hui'er" no longer relies on a single historical average, but instead conducts in-depth analysis of the processing characteristics of parts (such as processing volume, surface area, number of holes, and precision level), and combines equipment performance parameters to establish a multi-dimensional time prediction model.
Deep learning predictionBy using deep neural networks (DNNs) to learn from massive amounts of historical work reporting data, the system can identify the patterns of work hour fluctuations under different personnel, equipment, and batches, and accurately predict "standard working hours" rather than "ideal working hours".
Dynamic adjustment mechanismWhen new equipment, processes, or materials are introduced, "Hui'er" can quickly learn new data and update the model to ensure the timeliness of work hour standards.
ResultsThe accuracy of time calculation has been improved to over 95%, providing a solid data foundation for APS scheduling and effectively avoiding frequent plan adjustments and wasted capacity due to inaccurate time calculations.
AI-powered intelligent scheduling: From "static calculation" to "dynamic decision-making"
If pricing, processes, and time are the "inputs" of scheduling, then scheduling itself is the "brain" of manufacturing management. While traditional APS can take constraints into account, it often appears rigid and slow to recalculate when faced with disturbances such as sudden order insertions or equipment failures.
Deep integration of "Hui'er" and T-ONE APS:
Real-time sensing and second-level response"Hui'er" connects to MES (Manufacturing Execution System) and MDC (Machine Tool Networking) data in real time. Once an anomaly is detected (such as equipment downtime or material delay), "Hui'er" immediately triggers a reordering and outputs a new optimal solution within seconds, achieving "disturbance-as-it-is" response.
Multi-objective adaptive optimizationFactory goals are often contradictory (delivery time vs. cost vs. inventory). "Hui'er" uses reinforcement learning to understand the company's current operational priorities (such as "delivery this month"), automatically adjust scheduling weights, and find the globally optimal solution.
Linkage between process and schedulingThanks to "Hui'er's" precise capabilities in process and time management, the scheduling engine is no longer based on rough estimates, but on real process paths and accurate time predictions, which greatly improves the feasibility of the plan.
Natural Language InteractionPlanners do not need to learn complex software operations; they can simply ask "Hui'er" questions in natural language (such as "If this urgent order is inserted, what impact will it have on existing deliveries?"), and "Hui'er" can simulate and provide suggestions.
ResultsShorter average lead time20%-30%Emergency order response speed has been improved from "days" to "hours", equipment utilization rate has increased by 10%-20%, and work-in-process inventory has decreased by 20%-40%.
Ushering in a new era of intelligent manufacturing through "human-machine collaboration"
Fangtian Software's "Hui'er" is not intended to replace human experts, but rather to liberate them from tedious, repetitive, low-value labor so that they can engage in more creative and strategic work.
For the boss"Hui'er" is a powerful tool for reducing costs and increasing efficiency, ensuring that every investment yields a visible return.
For sales"Hui'er" is an accelerator for order grabbing, making quotations faster and more accurate;
For technology"Hui'er" is a successor of experience, ensuring that craft knowledge is never lost;
For the plan"Hui'er" is a wise co-pilot, allowing scheduling decisions to calmly cope with all changes.
Driven by the dual engines of "AI + Industry," Fangtian's "Hui'er" is helping Chinese manufacturing enterprises break through the ceiling of traditional management and build a core competitiveness in flexible manufacturing with data as its lifeblood, algorithms as its nerves, and intelligence as its brain. The future is here; embracing "Hui'er" means embracing the intelligent future of manufacturing.