Key Takeaways: Entry Points for the Intelligent Transformation and Upgrading of Traditional Factory Logistics

For existing factories, a systematic diagnosis and assessment are required to identify their current challenges, opportunities, and constraints, enabling the selection of appropriate entry points for logistics transformation and optimization. The following sections present and share successful experiences and case studies from the transformation and upgrading processes of manufacturing enterprises.

 01  The Basic Model of Transformation and Upgrading
Logistics is a core component of factory transformation and upgrading, with its basic model and content illustrated in the figure. As shown in Figure 8-6:

Figure 8-6 Existing Factory Logistics Transformation and Optimization Model

( 1) Supply Chain, Logistics Strategy, and Value Orientation
It is necessary to define the enterprise’s supply chain, logistics strategy, and value orientation in order to achieve a clear focus in its development direction and foster consensus and coordinated action across the organization. In managing a manufacturing facility, factors such as delivery, cost, quality, service, speed, and efficiency must all be balanced; these elements influence, constrain, and reinforce one another. Therefore, enterprises should, in light of both the industry environment and their own unique characteristics, prioritize the key factors that will most effectively enhance their competitive edge. For example, a certain company operates in a market environment characterized by severe product homogenization, low gross margins, and widespread high inventory levels among industry players. Following analysis, the company has identified supply chain and logistics responsiveness and delivery performance as key levers, thereby establishing… A 3–5-year supply chain and logistics strategy is underpinned by the following logic: by ensuring rapid responsiveness, it both enhances delivery service levels and boosts customer satisfaction, while continuously reducing inventory across all channels, thereby keeping costs and gross margins at industry‑leading levels and gradually building a competitive edge that sets the company apart in the sector. In addition, the strategic framework should clearly define the direction of factory digitalization and intelligent transformation, articulating a medium- to long-term vision to foster consensus and coordinated action across all departments.
( 2) Establish an integrated and collaborative planning management system
Establish an integrated, collaborative planning management system to achieve seamless coordination among sales and production plans, manufacturing schedules, procurement plans, logistics plans, and shipping schedules. The ultimate measure of planning capability is the ability to swiftly identify and respond to market fluctuations. Therefore, the planning system must be dismantled. A “pass-the-flower”–style cascading mechanism establishes an interconnected system centered on supply chain planning. When a condition changes, the system can swiftly identify risks and discrepancies, guiding other plans to make informed judgments and adjustments.
( 3) Entry Points for Planning and Improvement
Identify appropriate entry points for planning and improvement, using these as levers to transform and optimize end-to-end logistics. Whether the focus is on inbound logistics, intra‑facility logistics, or finished‑goods logistics, the transformation process must consistently align with the value‑chain perspective: every node in the logistics chain serves as a critical link, with changes at one point cascading throughout the entire system. Therefore, it is essential to adopt a holistic and systematic way of thinking. At this stage, it remains essential to continuously focus on enhancing and advancing areas such as organizational structure, processes, packaging, informationization and visualization, facilities, teams and talent, as well as emergency logistics.
( 4) Seek breakthroughs
Building on the progress achieved in the first, second, and third phases, the focus is on achieving breakthroughs in automation, digitalization, and intelligence, with particular emphasis on the phased implementation and upgrading of intelligent modular design, the deployment of automated logistics systems, the integration of AI‑driven technologies, the digitalization of humans, machines, and materials, the digitization of logistics scenarios, the intelligent optimization of logistics planning, and the development of logistics information platforms.

02  Basic Principles of Transformation and Upgrading
In the process of logistics transformation and upgrading, existing enterprises should pay attention to the following principles:
( 1) Principle of Differentiation
Develop differentiated logistics strategies tailored to specific products, materials, production lines, suppliers, customers, and other factors, and design solutions that align with their unique characteristics. For example: For nearby suppliers and materials that are bulky, with stable supply and quality, inventory should be tightly controlled, and a just-in-time delivery strategy should be adopted. In contrast, for distant suppliers and smaller‑sized materials that are relatively scarce, it is appropriate to maintain slightly larger inventories and implement a batch‑delivery approach. As for products with high versatility and steady sales, Under the MTS (Make-to-Stock) model, products with stable demand are manufactured in advance, while those that are highly customized or subject to significant demand fluctuations are produced under the MTO (Make-to-Order) model. Accordingly, the logic and mechanisms for demand forecasting and collaboration with corresponding customers must also be tailored to each approach.
( 2) Principle of Standardization
By standardizing products, packaging, processes, equipment, data, and business operations, we aim to minimize logistical complexity. For example, when material packaging is not standardized, aspects such as the placement of material labels, the configuration of data‑collection points, the specifications of logistics equipment, and warehouse‑space planning all lack uniformity. As a result, the entire logistics system becomes exceedingly complex, making automation and intelligentization significantly more challenging.
( 3) Principle of Task Simplification
During the process of mapping out logistics operation workflows, the approach adopted is… The ECRS principle seeks to simplify tasks and processes as much as possible; ECRS stands for Eliminate, Combine, Rearrange, and Simplify. For example: reduce unnecessary material repackaging through packaging standardization; minimize redundant inbound and outbound handling via cross-docking; replace manual inventory counts with automated counting; simplify or eliminate handover procedures by adopting unitized materials; and establish continuous flow to eliminate logistics bottlenecks and excess inventory.
( 4) Principle of Collaborative Interconnection
Enable collaboration across business units, between enterprises and suppliers, and between enterprises and customers in areas such as planning, data management, and operations. Specifically, during the logistics planning process, communication methods, communication protocols, and collaboration mechanisms should be defined through workflows, and these should be implemented via the integration of information systems. “Online” collaboration. For example, in the production planning process, it is necessary to coordinate with customer demand (orders), supplier production, and upstream processes; moreover, key information such as plans, orders, inventory, and demand must be shared across all departments within the enterprise and effectively interpreted among the enterprise, its customers, and its suppliers.
( 5) Principles of Process Control
Logistics is a dynamic process composed of multiple nodes, and logistics management emphasizes the dynamic management of planning, standards, execution, and variances throughout the logistics process. Therefore, it is essential to emphasize end-to-end visibility and risk early warning throughout the logistics process. For example: not only should inventory data at each node be presented in real time, but it should also be dynamically monitored against established inventory benchmarks to ensure reasonableness; not only should the routes and locations of delivery vehicles be tracked in real time, but they should also be integrated with the logistics plan to proactively identify potential material‑shortage risks; and key logistics performance indicators—such as labor productivity, equipment utilization, equipment failure rates, logistics‑plan fulfillment rates, and material‑kit completeness—should all be subject to real-time analysis and visualization.

03
Develop a logistics strategy
Enterprises need to develop a detailed strategic implementation plan; only on the basis of a logistics strategy can they proceed with the subsequent system‑building process. For specific guidance on strategy formulation, please refer to… 3.4.2 Logistics Strategy in Conceptual Design. This section presents only the key components and presentation formats of the logistics strategy for a specific manufacturing enterprise.
This manufacturing enterprise is an industry leader, with its overall operational capabilities, supply chain management, and production efficiency serving as benchmarks across the sector. Transforming and upgrading its logistics has long been a core strategic priority; after more than a decade of continuous optimization, the company has achieved a high level of excellence in internal logistics infrastructure, facility layout, workflow streamlining, delivery systems, automation, just-in-time operations, and logistics information technology. Against this backdrop, the company seeks to achieve greater breakthroughs in its supply chain and logistics operations and has formulated a new logistics strategy. “The Five-Year Plan,” as shown in Figure 8-7.

Figure 8-7 Logistics Strategic Planning for a Certain Enterprise

First, the plant conducted a comprehensive logistics review and diagnosis. Based on customer‑needs research and analysis, it concluded that the primary bottleneck in its logistics lies in the inbound logistics process. Significant gaps remain between factories and suppliers in areas such as logistics standardization, coordinated logistics planning, efficient utilization of logistics resources, emergency response mechanisms, seamless integration of logistics information systems, and real-time monitoring of logistics processes. “Management does not extend beyond the factory gate,” resulting in insufficient support from inbound logistics for production stability. Accordingly, a new logistics development strategy has been formulated, taking inbound logistics as the entry point to establish a revamped logistics operations and management system—aiming to build a logistics framework characterized by strategic synergy, seamless interconnectivity, and rapid responsiveness. Compared with the current state of factory logistics, at least three breakthroughs are required:
1. Leaving the factory gate, Engage in deeper and broader collaboration with suppliers, including providing guidance on their production, logistics, and other operational capabilities.
2. Oriented toward efficient delivery, Its core value proposition is to better meet customer needs by enhancing supply-side capabilities.
3. Incorporated interconnectivity into the strategy. and translate this into concrete actions to build interconnected processes and information networks.
Secondly, the factory defines A development strategy characterized by “two strands, three models, and four features.” The two streams refer to tightly managing the two logical chains of information flow and physical material flow—ensuring seamless connectivity within each while synchronizing them in real time—thereby guiding the plant’s logistics planning, process optimization, and system upgrades. The three models involve an inbound logistics approach that combines supplier‑direct delivery, cyclical pickup, and centralized consolidation, with a strong focus on continuously integrating resources such as throughput, vehicles, personnel, warehouses, and facilities at the inbound logistics stage. The four characteristics represent the fundamental principles that must be consistently upheld throughout the transformation: adopting differentiated strategies for different suppliers and materials; striving to achieve coordinated collaboration across departments and with suppliers through logistics planning; emphasizing end‑to‑end monitoring and visibility of the logistics process; and prioritizing real‑time management and rapid response. Moreover, the planning and implementation of this transformation are firmly anchored in a future‑oriented roadmap of digitalization and intelligent iteration, clearly defined… The implementation approach of “one-time planning, phased execution.”
Third, the factory has defined five core capabilities as strategic pillars—essentially, strategic initiatives that require sustained commitment and focused investment to achieve the organization’s objectives. The proposal clearly identifies five key capability-building pillars—logistics planning, standardization, large-scale integration, emergency response mechanisms, and system development—as essential to the entire logistics transformation process. Only by establishing these capabilities can we effectively support the execution of our strategy and tactics.
Fourth, clearly define the strategic priorities for logistics planning and operations:
1. By achieving logistics balance through production leveling and supply consolidation, we ultimately ensure production stability and cost-effectiveness. Before systematic planning was implemented, production and procurement schedules failed to account for logistics requirements, resulting in significant fluctuations across time periods, suppliers, routes, workshops, and assembly lines. These fluctuations are a major cause of uneven workload distribution and efficiency losses. To ensure that logistics capacity can meet demand, additional resource allocation and capacity deployment are necessary to handle peak requirements; however, this approach leads to low utilization rates across all resources. Around 50%. Therefore, during the planning process, it is essential to ensure system-level balance—for example, maintaining relatively stable alignments between products and production lines or workshops; keeping the types and quantities of suppliers and supplied materials fairly consistent; and establishing appropriate correspondences between logistics routes and workshop layouts. Of course, all these arrangements are based on demand‑driven principles and reflect a relatively optimal logical plan derived from comprehensive analysis. Meanwhile, fluctuations arising from actual demand changes must be addressed through robust information systems, flexible planning adjustments, and rapid response mechanisms.
2. Enhance the utilization rate of logistics resources through systematic logistics planning. Before the implementation of a structured plan, suppliers deployed a large number of personnel—drivers, on‑site escorts, and factory‑based staff—whose presence was scattered across various operational stages, making effective oversight virtually impossible. This resulted in significant safety risks and resource wastage, while also leading to extremely low utilization rates. For example, one supplier maintained a permanent presence at the plant for… Five service personnel are assigned to the supplier; they are employed when deliveries arrive but remain idle during periods of no incoming shipments. For example, drivers spend their days shuttling between the supplier and the company, often waiting while unloading—time that generates no value. This inefficiency extends beyond supplier‑related resources: in‑plant staff, unloading areas, warehouses, handling equipment, and loading/unloading facilities, as well as external delivery vehicles, all suffer from underutilization due to a lack of integrated planning, driving up overall operational costs. Whether these costs are borne by suppliers or absorbed by the enterprise, they ultimately translate into higher raw‑material procurement prices and increased product costs. By establishing a third‑party logistics organization—whether a dedicated third‑party logistics provider or a collaborative venture with suppliers—companies can achieve substantial integration benefits through unified planning, execution, and management of logistics operations across multiple suppliers and manufacturing sites.

04
Strengthen the logistics infrastructure
Intelligent logistics in existing factories is a relatively long-term goal, driven by continuous improvement. For most established manufacturing facilities, the immediate priority is to center on logistics, fostering coordinated operations across the supply chain—both upstream and downstream—and aligning inbound logistics, intra‑plant logistics, and outbound finished‑goods logistics to enhance overall operational efficiency. Here, The logistics transformation of a factory should not focus on digitalization or intelligence per se, but rather on streamlining logistics management logic and strengthening the underlying logistics infrastructure—this is the essential step on the path from today’s factories to intelligent operations. “A must‑take course.”
When a factory is caught in a cycle of frequent stockouts, the priority is to establish effective coordination between logistics planning and production scheduling, advance refined inbound logistics management, and ensure stable production. When factory capacity falls short of market demand, the focus should be on enhancing logistics responsiveness and speed, implementing a just-in-time material supply system, and freeing up additional floor space for production expansion. When inventory piles up to unsustainable levels, the task is to develop sound, efficient inventory strategies that keep stock levels within an appropriate range. When finished‑goods inventory remains stubbornly high while stockouts occur frequently, it is essential to streamline customer demand forecasting and order management, and to establish collaborative mechanisms across production and logistics to enable effective order‑priority management. Finally, when in‑house component inventories are excessively high and tie up substantial production space, the solution lies in aligning internal value streams—achieving physical or planned integration—to reduce internal logistics bottlenecks.
On the other hand, many of the fundamental challenges facing existing factories are not inherently linked to digitalization or intelligent technologies. When a factory consistently experiences discrepancies between book records and physical inventory, leading to management chaos, what is needed is the continuous refinement of the bill of materials to enhance the consistency and synchronization of both physical and information flows. When material packaging at the factory is diverse and quantities are inaccurate, resulting in issues such as improper receipt, internal handoffs, counting errors, frequent changes in packaging, and on‑line production line disarray—along with associated waste—the solution lies in establishing standardized, modular, and universal material‑packaging criteria. And when a factory faces chaotic logistics operations across all stages, low efficiency, and an inability to effectively monitor processes, what is required is the development of standardized logistics operating procedures and workflows for each stage, ensuring that logistics operations… “There is law to follow, and violations can be exposed.”

05
Eliminate logistics bottlenecks
The focus of logistics planning is to establish a continuous flow and lay the groundwork for rapid throughput. As shown in the figure. As shown in Figure 8-8, taking logistics as the central thread and viewing the value stream from an end-to-end perspective, the essence is to deliver a high level of service at a reasonable, lower cost. In such a complex system, overall equilibrium is more important than local efficiency, and global coordination is more important than individual node-level execution. Value-stream optimization centered on logistics should be driven by planning coordination, enabling the rational management of lead times and inventory levels. Its objective is to respond accurately to customer demand, shorten delivery cycles, and reduce inventory. Therefore, A holistic plan for the logistics process is required to achieve end-to-end visibility. “De facto balance.”

Figure 8-8 Value Stream Map with Logistics as the Main Thread

The reason it is described as a de facto balance is that enterprises cannot… “Struggling” over an ideal balance or a theoretical equilibrium. The end-to-end logistics process is akin to a continuous-flow production line; for a true production line, IE engineers use stopwatches to meticulously record cycle times, precisely define operations to shorten processing cycles, and employ workstation balancing techniques to establish an optimal line‑balancing ratio. In theory, this approach can enable each line to achieve 90% or even higher of its theoretical output. However, actual performance falls short of this ideal, as numerous disturbances arise during operation: workstations exhibit varying degrees of operational variability, and workers differ in skill level and pace. As a result, much of the effort invested by engineers to achieve production balance may ultimately prove futile. In fact, if variation and disturbances cannot be eliminated, the more balanced a production line is, the poorer its output performance may become.
For a production line with a balance ratio close to the ideal, if the effective output of each workstation is At 90%, the entire production line’s output will be 90% raised to the power of N, where N is the number of workstations on the line. Therefore, even more critical than striving for second‑by‑second workstation balancing is, on the basis of proper workstation balancing, building in adequate time buffers—such as reserving roughly 20% of capacity at stations prone to frequent disruptions—establishing inventory as a buffer, and effectively managing (and reducing) disturbances and variability, all to maximize the overall output of the production line rather than maximizing output at each individual station. As for the logistics sector… For a “production line,” maximizing effective output across the entire line requires measures such as planning coordination, routing optimization, and buffer allocation to achieve overall efficiency improvements.
( 1) Coordination of the plan
First, effectively balance supply and demand through supply chain planning; second, leverage strategic master planning to establish appropriate buffers for time and inventory across the entire logistics chain; third, establish coordinated, responsive linkages between logistics planning and production planning. Planning serves as the engine of both the supply chain and logistics operations, and robust planning management is a fundamental prerequisite for optimizing the value chain.
( 2) Planning of logistics models and routes
For the inbound logistics process, it refers to the planning of receiving modes and inbound logistics routes; for in-plant logistics, it involves designing internal material flow paths and ensuring continuous production flows, with efforts to minimize breakpoints between production and logistics operations; and for finished‑goods logistics, it entails planning the logistics network and routing strategies.
( 3) Deployment of the buffer
To address various disruptions in the logistics process, it is necessary to establish inventory and time buffers where needed. For example, due to factors such as the number of injection‑molding machines, changeover times, economic batch sizes, and production takt time, the injection‑molding workshop cannot establish a direct physical connection (continuous flow) with the final‑assembly line. Therefore, it is necessary to maintain an appropriate inventory buffer between the two workshops. , and the size of this inventory level, in turn, depends on the required buffer time; if the appropriate buffer time is If the lead time is one day, the inventory in this buffer must cover the production demand for the next day. For the entire logistics chain, inventory serves as a vital link connecting upstream and downstream nodes; not every node needs to hold inventory, nor can every node operate without it. For instance, if Node A maintains inventory, Node B may choose not to. The optimal allocation requires systematic planning and the establishment of standardized inventory levels at key nodes.

06
Develop specialized capabilities
Establish a logistics management organization and develop specialized capabilities. Logistics requires end-to-end thinking, while production is… The “precision‑strike” mindset means that production personnel typically struggle to manage logistics effectively; therefore, factories should establish a dedicated logistics management organization. Define specialized logistics management roles, with particular emphasis on talent development and position design in areas such as logistics planning, logistics processes, inventory management, logistics standardization, and logistics automation, digitalization, and intelligentization. For guidance on the organizational development of logistics management, please refer to Chapter 6. 6.2 Organization of Logistics Management in Smart Factories).

07
Logistics Technology and Facility Applications
Logistics automation, digitalization, and intelligent solutions and technologies exhibit broader applicability and greater maturity. Improving the automation and intelligence of production systems requires customized, non‑standard design tailored to the specific manufacturing processes of each product. Particularly when dealing with customer‑specific products, the process for almost every product category—and even for each individual product—varies significantly. Since production equipment varies across industries and enterprises, it cannot be widely standardized or universally adopted, making the implementation of automation challenging. This often requires custom‑designed, non‑standard automated systems and costly intelligent devices. However, although logistics systems are complex—handling large and small items, full‑unit inbound and outbound flows, mixed‑batch inbound and discrete‑item outbound operations, sorting and direct‑delivery tasks, and materials and product units of diverse sizes and specifications—once material packaging and logistics workflows have been standardized, the key equipment, core components, control systems, and logistics information systems in these systems will exhibit strong versatility across different industries, enterprises, and product categories. Even for non‑standard systems, the differences typically amount to variations in external dimensions, while the underlying core functions remain consistent. “Conveying, sorting, inbound and outbound handling, picking, grasping, palletizing, positioning, and reading,” among others—precisely because of this, the associated technologies and equipment have steadily matured through continuous application, creating ideal conditions for advancing intelligent logistics in factories.
On the other hand, when existing factories undertake intelligent logistics upgrades, it is not necessary to make a full-scale investment all at once; instead, they can proceed in phases according to… The “one-time planning, phased implementation” approach. Horizontally, pilot projects can be launched first and then scaled up, thereby minimizing investment risks to the greatest extent. For example, one could first pilot a single product line; after it is successfully implemented and lessons have been learned, the approach can then be replicated and scaled to other product lines or other workshops—such as automated high‑bay warehouses, conveyor systems, RGV and AGV systems, among others, are also built on a modular architecture, offering strong scalability and iterability. They can be deployed in phases and ensure compatibility across different technological stages. From a vertical perspective, it can be implemented sequentially or in parallel across one or several stages. For example, you can first implement layout planning and then proceed with automation upgrades; focus on upgrading the factory itself before extending these improvements to suppliers; and prioritize optimizing internal logistics before addressing inbound and finished‑goods logistics. As long as the logistics system is planned with sound logic, you can flexibly adjust the implementation pace based on your company’s specific circumstances and pilot results, keeping risks at a manageable level.
During the planning and upgrading of logistics intelligence at existing factories, it is essential to maintain a constant focus on… Guided by the value proposition that “planning is for better operations,” we will leverage the logistics automation implementation analysis model and other relevant tools outlined in Chapter 3 to select key nodes for pilot projects and subsequent scaling, rather than striving for a one‑step, all‑at‑once approach.
The development of logistics automation, digitalization, and intelligent systems is key to enabling factories to achieve a significant leap in value. When a factory has a clear logistics framework and a solid foundation in logistics management, it can progressively advance the implementation of logistics automation and digitalization. Logistics facilities generally exhibit strong versatility and flexibility, with well-established technological applications for transportation, material handling, loading and unloading, storage, order picking, last‑mile delivery, and workstation integration. In the process of implementing logistics automation, the following points should be taken into consideration:
( 1) Select appropriate upgrade points by leveraging logistics automation analysis models, For existing plants, not all process nodes are suitable for automation upgrades, or in other words, some nodes simply do not offer sufficient return on investment.
( 2) By analyzing and selecting appropriate logistics technologies and facilities, It is necessary to conduct a detailed analysis that takes into account material characteristics, throughput, and environmental factors. For instance, one may deploy logistics automation solutions at varying levels—mechanized, semi‑automated, automated, or intelligent—and make informed choices among such modes and technologies as continuous conveying versus discrete conveying, standalone storage versus high‑density storage, pallet‑based storage versus bin‑based storage, and fully automated picking versus semi‑automated assisted picking.
( 3) Whenever possible, opt for vertical automated connections. , select a specific area—such as a particular factory, workshop, or production line—to manage material unloading. - Material receiving - Material inspection - Material putaway - Material storage - Material picking - Material delivery - Material line‑side supply - Empty container recovery: the entire process is systematically automated and piloted. Of course, prior to the pilot phase, comprehensive planning remains paramount to ensure that, based on the pilot, the system can be scaled and iterated.
( 4) Abandon the traditional notion that automation simply means “replacing humans with machines,” The core value of logistics automation lies in end-to-end integration, enabling rapid material flow, reducing storage, waiting, and breakpoints in the material-handling process, shortening throughput times, and lowering overall physical inventory levels.

08
Logistics Digitalization
Logistics digitalization is an inevitable step in the intelligent transformation of logistics, and logistics intelligence must be built upon a foundation of logistics digitalization. The fundamental manifestation of logistics digitalization is the full digitization of the entire logistics process. “Online” operations, paperless workflows, automated data collection and transmission, automatic data analysis, automated risk and anomaly alerts, and visualization—these are all key components. In essence, logistics digitalization is the process of embedding factory‑level logistics management logic, experience, and expertise into information systems. The prerequisite for logistics digitalization is “Element onboarding” requires leveraging RFID or barcode technologies to digitize materials, as well as associated equipment and personnel. For example, sensor-enabled material tags, equipment tags, document tags, and personnel tags enable all people, machines, and materials to achieve automated dynamic data collection and two-way communication. The foundation of logistics digitalization encompasses the digitization of materials, storage locations, routes, facilities, personnel, and other related aspects.
( 1) Material Digitization: The digitization of materials is typically achieved through the digitization of packaging containers. Each material must be assigned a unique container and a specified fill quantity at every stage of the process, achieved by affixing a barcode to the container or embedding one within it. RFID technology enables the writing and acquisition of material information. When selecting and designing material packaging containers, it is essential to integrate barcode‑reading technologies and data‑collection methods, clearly define the placement of material tags, and establish standardized specifications to ensure efficient data capture throughout the material handling process.
( 2) Warehouse Location Digitization: Here, “storage location” refers to storage locations in a broad sense—namely, the points where materials are stored or temporarily held during their flow, such as unloading‑yard parking spaces, unloading buffer zones, inspection‑awaiting areas, warehouse zones and storage bins, repackaging areas, picking‑and‑putting‑together zones, and line‑side storage locations. These physical locations must be definable within the information system and virtually identified using spatial positioning technologies, for example: UWB (Ultra-Wideband) technology. And Positioning and labeling are implemented for each zone and storage location to facilitate identification and localization during logistics operations. By establishing both physical and virtual connections among these zones, a digital representation of logistics routes is created.
( 3) Digitalization of Facilities and Personnel: An intelligent logistics system is, in essence, the interconnection and interaction among people, machines, and goods, requiring bidirectional communication among them; accordingly, both facilities and personnel must also… “Going online” enables continuous management and minimizes offline workflows. For example, mechanized equipment such as forklifts and tractors must be clearly marked to identify their identity. RFID cards facilitate the scheduling and management of equipment. Each device should be equipped with a display terminal that shows its specific tasks and instructions, as well as a reader to enable information exchange with materials and inventory, thereby achieving digital collaboration among people, machines, objects, and locations. Personnel should also carry fixed ID cards with defined identities and use handheld or mobile terminals to receive and issue commands. Since both facilities and personnel are fitted with RFID tags, their movement paths, timing, and other data can be analyzed to enable more precise planning and dispatching.
( 4) Digital Foundation: In addition to having a solid data-driven foundation, Logistics digitalization should be progressively achieved across three dimensions: data collection, data application, and data intelligence. Data collection aims to establish end-to-end data‑capture capabilities across the entire logistics process, enabling dynamic, automated data acquisition through scanning devices, sensing technologies, and image‑recognition systems. Data application involves defining a robust data‑management framework and logic, developing data models aligned with key logistics‑control priorities, and embedding domain expertise and institutional knowledge into systems and applications via these models, thereby supporting automated analytics, early warning, and decision‑making. Data intelligence requires building a logistics control tower and a centralized logistics management platform; leveraging big‑data insights, it seeks to achieve autonomous capabilities in logistics planning, scheduling, optimization, coordination, and variance management, progressively advancing toward full智能化 (intelligentization).