Against the backdrop of the interweaving era wave of the new round of scientific and technological revolution and industrial transformation, intelligent manufacturing has become the core direction for the transformation and upgrading of global manufacturing. Faced with the deep integration of the digital economy and the real economy, as well as the accelerated evolution of industrial chain reconstruction, China's manufacturing industry is standing at a historic critical juncture. As a rising star in the landscape of China's manufacturing industry, Dishan is firmly advancing into the great practice of "Intelligent Manufacturing 4.0", committed to building an efficient, intelligent, green, and sustainable modern industrial system. It not only opens up new tracks for its own development but also devotes itself to contributing innovative forces to the rise of China's intelligent manufacturing in the new era and writing a new chapter in the evolution of industrial civilization.
What is Intelligent Manufacturing 4.0?
Intelligent Manufacturing 4.0 originated from Germany's concept of "Industry 4.0". Its core lies in the deep integration of new-generation information technologies such as the Internet of Things (IoT), Big Data, Artificial Intelligence (AI), Cloud Computing, Digital Twins, and Edge Computing, enabling the intellectualization, networking, and flexibility of the entire production process. The essence of this transformation is to build a "physical + digital" twin ecosystem, endowing production systems with self-perception, self-learning, self-decision-making, and self-execution capabilities. It is no longer limited to automated production but breaks through traditional manufacturing boundaries through the deep synergy of "human-machine-object-system", forming a dynamic, optimized, and agile response intelligent ecosystem.
The technological system of Intelligent Manufacturing 4.0 encompasses comprehensive innovations from the bottom-level equipment to the top-level decision-making. For example, IoT technology enables equipment interconnection and data collection, edge computing ensures real-time response, cloud computing provides massive data processing capabilities, AI endows the system with intelligent analysis capabilities, and digital twins construct a two-way mapping between the virtual and the real world. The integration of these technologies allows manufacturing systems to self-evolve like "living organisms": when market demand changes, intelligent production lines can automatically adjust process parameters; when equipment malfunctions, the system can issue early warnings and independently schedule maintenance resources; when developing new products, virtual simulation can significantly reduce the cost of physical trial and error. This qualitative change brought about by technological integration is redefining the boundaries and possibilities of manufacturing.
For Dishan, Intelligent Manufacturing 4.0 is not merely an iterative upgrade at the technological level, but a comprehensive transformation encompassing management philosophy, organizational structure, business models, and even value chains. It requires enterprises to be customer demand-driven, data-driven, and innovation-driven, to reconstruct production logic, shift from "experience-based manufacturing" to "data-driven manufacturing", and from "closed production" to "open collaboration", ultimately achieving a multiplier effect in value creation. As a senior official responsible for Intelligent Manufacturing at Dishan stated: "Intelligent Manufacturing 4.0 is not an optional question, but a mandatory question concerning the survival and development of the enterprise." The urgency of this transformation stems from the profound changes in the global manufacturing competitive landscape—only by embracing intelligent transformation can we take the initiative in the reconstruction of the industrial chain.
1. Intelligent Infrastructure Upgrading: Laying the Foundation for Transformation
Dishan has set its sights on "equipment networking, data visualization, and control intelligence" as its core goals, driving comprehensive digital transformation of factory equipment. It is as if the factory has been implanted with countless smart tentacles. Tens of thousands of intelligent sensors and industrial internet platforms have been deployed, enabling real-time monitoring, fault early warning, and predictive maintenance of equipment operational status.
In the core workshop, the intelligent sensor network acts like a nervous system, collecting real-time data on temperature, vibration, energy consumption, and other metrics. Through the precise analysis of AI algorithms, equipment downtime rates have been reduced by 40% and maintenance costs cut by 30%. Traditional rigid production lines are gradually transforming into self-adaptive smart lines, as flexible as Transformers. A single line can now produce over a dozen different product specifications, with setup times shortened to the minute scale, greatly enhancing production efficiency and product consistency.
Additionally, Dishan has introduced an intelligent warehousing system. Through the synergy of Automated Guided Vehicles (AGVs) and automated three-dimensional warehouses, it achieves unmanned material handling and precise delivery. Inventory accuracy has been elevated to 99.5%, and space utilization has increased by 40%.
During the equipment transformation process, Dishan has emphasized a "new-old integration" strategy. For high-value legacy equipment, intelligent modules are retrofitted to breathe new life into them. For new production lines, a "native intelligence" design philosophy is adopted, ensuring that equipment is networked and data-interoperable from the very beginning. This incremental transformation approach avoids the high costs of "tearing it down and starting over" while guaranteeing the continuity of technological iteration.
2. Data-Driven Decision-Making System: Building a "Digital Brain"
Leveraging its big data analytics platform and industrial big data center, Dishan has 打通 (broken through) the data flow across the entire value chain, from market demand analysis, product development, and supply chain collaboration, to production scheduling, quality control, and after-sales service. By constructing a "digital cockpit," management can gain real-time visibility into key performance indicators (KPIs) such as order progress, equipment utilization rates, and inventory turnover, enabling visual management and precise decision-making throughout the production process.
For instance, in supply chain collaboration, predictive algorithms analyze market demand fluctuations to dynamically adjust procurement and production plans. This has increased inventory turnover efficiency by 50% and shortened lead times by 20%. Furthermore, Dishan has developed a customer behavior analysis model. By leveraging historical order data and market trend forecasting, it can proactively identify and secure high-value orders, ensuring the precise allocation of production capacity resources.
Data governance has become a core capability of Dishan's intelligence initiatives. The enterprise has established a comprehensive data standard system to ensure data consistency across different systems. Through data cleaning and labeling, raw data is transformed into analyzable "knowledge assets." For example, in quality control, the system can automatically correlate production parameters with inspection data, rapidly pinpoint the root causes of defects, and enable "one-click traceability" for quality issues.
Artificial intelligence empowers quality and innovation: moving towards "zero defects" and "rapid iteration"
In the quality inspection process, Dishan has introduced an AI visual recognition system. By deep learning millions of defect samples, it achieves micrometer-level defect detection in milliseconds, reducing the product defect rate from 0.5% to 0.05%, which reaches an industry-leading level. This system can also autonomously learn new defect types and continuously optimize detection accuracy.
Meanwhile, AI technology has been deeply integrated into the R&D (Research and Development) process. Through simulation and machine learning, it accelerates key links such as new material selection and process parameter optimization. For example, in new material development, the AI system can simulate thousands of formula combinations, screen out the optimal performance scheme, shorten the R&D cycle by 60%, and reduce material costs by 15%.
Dishan has also explored the application of AI in process optimization. For instance, in the injection molding process, the AI system dynamically adjusts parameters such as temperature and pressure by analyzing historical production data and real-time process parameters, increasing product yield to 98% and reducing energy consumption by 12%. This "AI + Process" model is gradually becoming a standard configuration for Dishan's technological innovation.
Building a Flexible Manufacturing System: Resolving the Paradox Between Personalization and Efficiency
For instance, on the consumer electronics production line, the same production line can simultaneously manufacture customized smartphone cases and smart wearable devices. The unit cost only increases by 5%, while the delivery cycle is shortened to 3 days, truly realizing the "mass customization" model. This flexible capability enables Dishan to quickly respond to market changes and seize opportunities in the "long-tail market".
Dishan has also developed a "Modular Production Line Configuration Platform", which allows customers to select product configurations online and view simulated production line scheduling in real time, delivering a "what you see is what you get" customization experience. This platform not only enhances customer engagement, but also significantly shortens the order confirmation cycle.
Green Intelligent Manufacturing: Fulfilling the Commitment to Sustainable Development
Dishan has deeply integrated the ESG philosophy into its intelligent manufacturing system. By leveraging the Energy Management System (EMS) to monitor energy consumption and carbon emissions at all stages in real time, and optimize production scheduling and equipment dispatching, the company has achieved a 25% reduction in energy consumption per unit of output value.
For example, in the painting workshop, the intelligent scheduling system can dynamically adjust the operation status of equipment according to order volume, cutting down the annual energy consumption by nearly 100,000 kilowatt-hours. Meanwhile, clean energy is adopted to replace traditional energy sources. For instance, photovoltaic panels installed on the roof generate electricity that can meet 15% of the production power demand annually.
Dishan has also established a Carbon Footprint Tracking System, which conducts quantitative analysis of the carbon emissions throughout the entire life cycle of each product. Through process improvement and supply chain optimization, the company is gradually moving towards the goal of carbon neutrality. This green transformation not only enhances the enterprise's social image, but also creates new market competitiveness—an increasing number of international customers have incorporated ESG performance into their supplier evaluation systems.
Despite its broad prospects, Dishan still faces numerous challenges in advancing Smart Manufacturing 4.0, which are also a microcosm of the transformation and upgrading of Chinese manufacturing enterprises:
Shortage of high-end interdisciplinary talents: The scarcity of "π-shaped talents" who are proficient in both industrial technologies and digital technologies has restricted the in-depth application of intelligentization. For example, the talent gap for professionals who are both AI algorithm engineers and industrial automation specialists reaches 30%, becoming a bottleneck for technology implementation.
High complexity of system integration: The integration of OT (Operational Technology) and IT (Information Technology) is fraught with difficulties, and the data silos between different systems are in urgent need of being eliminated. For instance, compatibility issues exist between the protocols of the early-built MES system and the newly established AI platform, making data integration a time-consuming and labor-intensive process.
Heavy pressure from initial investment: The high cost of intelligent transformation is unaffordable for small and medium-sized enterprises. Take an intelligent production line as an example, its transformation cost can be as high as tens of millions of yuan, with a payback period of 3–5 years, resulting in significant financial pressure.
Data security and privacy protection: Industrial data is of high value, and thus faces risks of hacker attacks and compliance violations. For example, a cyberattack once led to the leakage of production data, causing losses of millions of yuan and highlighting the importance of security protection.
Resistance to organizational transformation: Conflicts exist between traditional manufacturing mindsets and digital innovation concepts, and the coordination efficiency among departments needs to be improved urgently.
To address these issues, Dishan has adopted a systematic response strategy:
Cultivating talents through industry-education integration: Jointly establishing "Smart Manufacturing Joint Laboratories" with universities and research institutions, offering customized courses, and training an average of 300 engineers per year; setting up a "Smart Manufacturing Talent Pool" to attract top global experts. For example, cooperating with a well-known science and engineering university to launch a "Dual-Degree Program in Industrial AI", where students can not only learn mechanical engineering knowledge but also master deep learning technologies.
Reducing risks via phased implementation and ecological cooperation: Adopting a three-step strategy of "pilot project – promotion – optimization" to avoid reckless and overly hasty progress. For instance, in the pilot phase, high-value production lines are selected for transformation, and full-scale promotion is carried out only after verifying feasibility; cooperating with internationally leading enterprises such as Siemens and Huawei to introduce mature solutions and reduce technical risks.
Building a defense line through data governance and security reinforcement: Establishing a full-process data governance system covering data collection, storage and application; deploying industrial firewalls and blockchain traceability systems; and obtaining ISO 27001 certification. For example, reconstructing the network security system with a "Zero Trust Architecture" to ensure full traceability of data access.
Driving development with dual engines of policy and capital: Actively striving for national special subsidies for smart manufacturing and support from local government industrial funds to leverage social capital investment. For example, successfully applying for the "National-Level Smart Manufacturing Demonstration Project" and obtaining funding support of tens of millions of yuan; setting up a smart manufacturing industrial fund to attract venture capital institutions to participate in ecological construction.
Breaking mindset barriers through cultural transformation: Enabling employees from traditional manufacturing departments to participate in intelligent projects via the "Digital Talent Rotation Program" to cultivate digital thinking; establishing an "Innovation Error-Tolerance Mechanism" to encourage employees to boldly try new technologies and tolerate the cost of trial and error.
Looking Ahead: Building a New Ecosystem for Smart Manufacturing and Moving Toward a New "Smart Manufacturing + Services" Paradigm
Standing at a new historical starting point, Dishan will take Smart Manufacturing 4.0 as its core strategy and map out a more ambitious blueprint:
Building a "Smart Park" to create an industrial collaboration hub: A 1,000-mu smart park will be planned and constructed, integrating a 5G private network, intelligent logistics, and a shared manufacturing platform. It will promote the digital connection of suppliers, customers, and service providers, and build an integrated ecosystem covering "R&D, production, supply, marketing and service". For example, blockchain technology will be adopted to achieve full traceability of the supply chain, helping customers accurately track the full-life-cycle information of products; a shared manufacturing platform will be established to provide SMEs with services such as equipment leasing and capacity sharing, lowering the industry entry threshold.
Exploring the new "Manufacturing-as-a-Service (MaaS)" model: Transform from a pure product manufacturer into a provider of "products + services + solutions". For instance, it will offer intelligent operation and maintenance services for wind power enterprises; through remote monitoring and predictive maintenance, it helps customers cut operation and maintenance costs by 20%. An industrial APP store will be developed to provide innovative services including equipment leasing, capacity sharing, and process optimization, creating a new profit model featuring "hardware + software + services".
Deploying cutting-edge technologies to seize future track opportunities: Focus on key research in frontier fields such as digital twin factories, industrial metaverse, and AI generative design, and build up future technology reserves. For example, in the digital twin workshop, virtual-real interaction is used to optimize production processes, shortening the commissioning cycle by 50%; in the field of industrial metaverse, a virtual training system has been developed, tripling the training efficiency for new employees.
Global deployment to export Chinese solutions: Actively participate in the smart manufacturing cooperation under the Belt and Road Initiative, build overseas smart factories in Southeast Asia, the Middle East and other regions, replicate the Dishan model locally, and help drive the intelligent transformation of global manufacturing. For example, the smart factory built in Thailand adopts a "lightweight intelligent transformation" solution, helping local enterprises achieve digital transformation at low cost; it has partnered with Germany's Industry 4.0 platforms to jointly develop cross-regional collaborative manufacturing solutions.
Building an industry ecosystem alliance: Take the lead in establishing a "Smart Manufacturing Industry Alliance", uniting upstream and downstream enterprises, research institutions and universities to jointly formulate industry standards and promote technological innovation and achievement transformation. For example, it has led the development of a "Smart Manufacturing Capability Maturity Assessment Model", providing a reference tool for industry enterprises in their transformation journey.
Dishan’s pursuit of Smart Manufacturing 4.0 is not merely a technological leap, but a strategic expedition for the future. On this path filled with challenges and opportunities, innovation is the engine, data is the fuel, talents are the cornerstone, and collaboration is the key. From the roaring of intelligent production lines to the flowing data in the data middle platform, from the lush greenery of eco-friendly factories to the prosperity of the industrial ecosystem, Dishan is striding forward steadily to write a legend in the new track of smart manufacturing.
As smart factories continue to be implemented and mature, Dishan will not only build a new highland for "Intelligent Manufacturing in China", but also contribute the "Dishan Solution" and "Chinese Wisdom" to the intelligent transformation of global manufacturing through technology export and model innovation. This journey of innovation is witnessing the historic leap of China’s manufacturing industry from a follower to a leader. The goals are clear: build a world-leading smart manufacturing ecosystem and become an industry leader in the "Intelligent Manufacturing + Services" sector; expand the layout of overseas smart factories to cover 10 countries and regions, and export Chinese intelligent solutions.