When manufacturing enterprises embrace industrial AI, they generally face multiple challenges, such as difficulties in integrating business and technology, prominent problems of data silos and production management, shortage of compound talents, and difficulty in organizational culture transformation.
How to make a precise breakthrough?
The core of industrial AI landing lies in — trusted technology, scenario adaptation, and sustainable operation.
Relying on a complete technology stack and profound industry know-how, Luculent deeply "domesticates" general AI into an industrial-level "expert" capability that understands the industry, processes, mechanisms, equipment, and craftsmanship. It independently researches and develops an industrial-level operating system, enabling AI to truly take root in the factory site, solve practical problems, and create multi-dimensional value.
Based on High-Value Scenarios to Solve AI Landing Difficulties
Many enterprises tend to fall into the misunderstanding of "technology for technology's sake" when promoting AI applications and do not know where to start.
Luculent believes that industrial AI is not an isolated technical tool, but a systematic project oriented by value delivery, anchored by business scenarios, and centered on agile and reusable AI capabilities.
First of all, it is necessary to take root in the front line of business, accurately decompose AI value into implementable and measurable business scenarios, and make AI capabilities reusable and scalable, thereby reducing the threshold for enterprises' intelligent transformation.
Based on the unified technical base — Suchang Industrial Internet Platform, Luculent focuses on industrial application scenarios with "strong strategic significance, high economic benefits, and close connection with people's livelihood", such as safe operation, operation optimization, energy management, quality management, and asset performance. It builds a full-link product matrix covering industrial large models, industrial APPs, industrial intelligent agents, and high-quality industrial data sets, and implements a number of benchmark cases reaching "international (domestic) leading level", promoting enterprises to strategically upgrade from "business scenario pilot" to "full-domain AI empowerment".
In the power industry, it breaks through the closed-loop control of intelligent applications such as intelligent monitoring and operation optimization, improves unit reliability through predictive maintenance, and extends the equipment life cycle; in the coal mining industry, it integrates multi-dimensional diagnostic technologies such as process, vibration, oil, current spectrum, and AI to improve the accuracy of component-level equipment fault diagnosis, and expands the scope of intelligent care from large fixed equipment to core production equipment in coal mining working faces; in the chemical industry, it realizes visual management and accurate traceability of the entire production process, optimizes inventory levels, and improves equipment utilization efficiency; in the iron and steel industry, it starts with large model-driven equipment fault early warning and energy consumption management to help save energy and reduce carbon, with a comprehensive power saving rate of 10%–15%.
Truly high-value scenarios directly affect enterprises' costs, efficiency, quality, safety, and benefits. From "looking for technology" to "looking for scenarios", and from "doing pilots" to "building capabilities", this is the industrial AI development path that Luculent adheres to.
Building a "Cloud-Edge-End" Integration to Consolidate Industrial Intelligent Resilience
The future industrial AI must shift from the one-way thinking of "data aggregation" to an intelligent system of "cloud-edge-end" collaboration. This is not only the sinking of technology, but also an inevitable path to build a resilient industrial AI.
Cloud-side intelligence aggregation forms a "strategic command center". Data from different production lines and factories converge, correlate, and analyze here, driving algorithm models to iterate and optimize independently, thus creating strategic algorithm models that optimize the entire production value chain.
Edge-side intelligent control is a key link to undertake the power delegated by the cloud. It processes data in real time at the source of generation, runs localized AI models for reasoning, sinks the cloud evolution capability without loss, and performs agile closed-loop control on on-site equipment.
End-side perception turns every terminal into an intelligent "execution terminal". It is not only the "five senses" for perception, but also the "hands and feet" that can make preliminary judgments and take independent actions, building a closed loop of "perception — analysis — decision — execution" and consolidating the solid line of defense for system resilience.
As an organic living body that is "never tired, fully perceived, and independently decision-making", the "cloud-edge-end" integration makes the production and operation of the factory "smarter"!
"Three Major Strategies" to Accelerate the High-Quality Development of Industrial AI
Luculent takes the three major strategies as the main starting points to fully integrate industrial AI into the gene of enterprise development.
—— Internationalization Strategy
Deeply integrate into the global industrial ecology and let industrial AI technology stride onto the world stage. Relying on long-term accumulation in the domestic market, Luculent's business has covered more than 20 countries along the "Belt and Road", and has fully launched the global layout of industrial AI. The company's core team has a global perspective and overseas practical experience, carries out localized adaptation according to local needs, and gradually moves towards management output, knowledge output and even cultural output from product output and service output.
—— Ecologization Strategy
Cultivate a fertile ground for the "AI + manufacturing" ecology and promote the inclusive sharing of industrial AI technologies, tools and experiences. Luculent gathers ecological partners for collaborative innovation, builds a virtuous cycle of "platform capability improvement — application ecological prosperity — customer value multiplication", jointly creates industry-leading solutions through professional division of labor and complementary advantages, expands the market hand in hand, and improves the overall collaboration efficiency and value creation capacity of the industrial chain.
—— Talents Strategy
Talents are the primary resource, and mechanism is the primary productive force. Externally, through school-enterprise cooperation, on-the-job training, scenario-based training and other methods, it cultivates compound talents with both industrial business and AI technology, providing talent support for industrial transformation; internally, it implements the mechanism of "competing for projects and selecting the best", builds a multi-level AI talent echelon and a full-cycle capacity growth system, implements a special innovation incentive mechanism, promotes excellent practical experience, and makes the "drip irrigation" industrial AI culture prevail.
As Wu Aibin, Chairman of Luculent, said: "We must truly transform technology into a new quality productive force for enterprises to 'reduce costs, increase efficiency, improve quality, and achieve green development'."
Adhering to the original intention and forging ahead with practical work, let the "light of industrial AI" illuminate the path of leapfrog development of the entire industrial chain and consolidate the hard core strength of building a manufacturing power.
