Standardization must come first! The key to unlocking digital transformation in smart manufacturing logistics lies here.

To achieve digitalization in smart manufacturing logistics, standardization must come first.

China is advancing along the path of industrial intelligence, with every sector undergoing transformation through intelligent technologies. In particular, logistics permeates the entire spectrum of smart manufacturing and production, and as businesses integrate into various links of the manufacturing industry’s value chain and supply chain, the demand for logistics digitalization is becoming increasingly pronounced. However, achieving logistics digitalization is a long‑term endeavor that cannot be accomplished overnight. On the one hand, the development of industrial intelligence calls for deep, coordinated integration of logistics digitization; on the other hand, the successful implementation of logistics digitalization hinges on the effective deployment of standardized frameworks. Therefore, to realize digitalized logistics in the context of smart manufacturing, standardization must come first.

▍Requirements for Industrial Intelligent Development: Deep Digital Collaboration in Logistics

High‑precision, superior‑quality production of smart products in diverse varieties and small batches is a global trend in manufacturing. The intelligent transformation of industries is driving greater production efficiency and enhanced product quality. As customer demand for personalization, ergonomic considerations, and operational efficiency continues to grow in the era of smart manufacturing, effectively organizing and managing logistics activities—reducing supply‑chain costs and boosting intelligent productivity—has become increasingly critical. The importance of establishing digital logistics management is self‑evident.

As new technologies continue to emerge and their application deepens, logistics‑digitalization solutions are now permeating the entire industrial value chain of manufacturing enterprises, reshaping the industry’s human‑centric environment. Through technological transformation, repetitive, physically demanding, and purely material‑handling tasks—jobs that once exposed workers to occupational hazards such as pneumoconiosis or even finger amputations—are being replaced by palletizing robots, material‑handling robots, and glazing robots. Meanwhile, manufacturing firms undergoing digital transformation aim ultimately to codify human knowledge and expertise within systems, minimizing human intervention and eventually achieving fully autonomous operations. In digitalized workshops, logistics‑digitalization technologies enable the system to automatically optimize the sequencing and batching of materials required for production, selecting the most efficient execution plan—technologies that are just around the corner.

Indeed, without digital logistics, truly intelligent manufacturing remains unattainable. The journey toward logistics digitization is lengthy and cannot be accomplished overnight. It begins with a shift in mindset and awareness: we must recognize that intelligent manufacturing logistics is not merely a technological issue, but rather a systemic, holistic concept. Intelligent manufacturing demands a corresponding logistics infrastructure that aligns with its goals—going far beyond simply introducing automated equipment or deploying software.

Secondly, it is essential to recognize that intelligent manufacturing inherently demands precise material delivery. To enable the automated dispatch of materials with diverse weights and dimensions, standardization of logistics containers is indispensable, as is the standardization of the correspondence between each component and its designated container. Consequently, when placing purchase orders with suppliers, it becomes necessary to require them to deliver components in their smallest packaging units, aligned with this established mapping. This process touches upon a wide array of operations across the entire supply chain. If these foundational steps are either entirely omitted or inadequately executed at the outset, even the most advanced automation equipment in the workshop or warehouse will be unable to support digitalized logistics management.

Therefore, achieving a quantum leap in the digitalization of manufacturing logistics is, in fact, a systemic undertaking—each component is tightly interconnected and requires holistic, systems‑based thinking to coordinate effectively. Without such a systematic approach, merely upgrading isolated points will fail to deliver meaningful results.

▍The prerequisites for advancing logistics digitalization hinge on the implementation of standardization.

The development of logistics digitalization hinges on the standardization of norms. At its most fundamental level, standardization begins with standardized packaging. Only when packaging is standardized can logistics standardization maximize the loading efficiency of on‑line delivery equipment and ensure better compatibility with a wide range of automated and intelligent systems.

In addition, logistics standardization encompasses end-to-end standards across the entire supply chain, service‑process standards, logistics‑operations standards, multimodal transport standards, logistics‑equipment standards, and information‑technology standards, among others.

Among these, standardized logistics equipment—particularly reusable and palletized containers—requires tailored solutions that account for the material characteristics of manufacturing line‑side logistics and the frequency of material feeding at the production line. As for information‑technology standards, beyond the standardization of hardware, two often overlooked or undervalued areas are: the standardization of interfaces between different software systems, and the standardization of logistics service protocols. Internally, logistics, manufacturing, procurement, planning, and process‑design departments must maintain real-time coordination and seamless information exchange with external upstream and downstream suppliers, as well as with logistics and transportation service providers, to enable digital service sharing. The following three aspects merit particular attention.

First, the digitalization of logistics standards—shifting from human readability to machine recognition—requires robust top-level design. Standardization in the digital realm has become an essential component of industrial production and logistics development in response to the global digital economy. To harness the guiding role of standardization, it is imperative to digitize standards. However, the majority of China’s standards remain in paper format, leaving a significant gap compared with standards that are fully machine‑readable.

In addition, there are challenges related to the adoption and adaptability of standards. Technical personnel rely heavily on professional expertise and contextual knowledge when accessing standards, which can lead to misinterpretations during standard selection. Moreover, the inability to monitor compliance in real time makes it difficult to promptly identify shortcomings—such as incomplete or inadequate indicators—in the development and revision of standards. Coupled with the fact that standards encompass national standards, industry standards, group standards, enterprise standards, and internal technical specifications, the volume of existing data is substantial. Standard digitization demands a high degree of disaggregation, necessitating differentiated processing and indexing based on priority levels to lay a robust data foundation and ensure future applicability.

Today, digitalization has permeated every aspect of logistics, and in many application scenarios, automation is already replacing human labor. As a result, enabling machines to interpret standards has become an inevitable trend. When the subject of analysis is a human viewer, it suffices to align video frame rates and resolutions with the human eye’s resolving power. However, video‑encoding standards for machine vision differ from those intended for human consumption; thus, video design must account for both human‑readable and machine‑readable formats. This shift involves not only changes in methodology but also variations in the standards’ content, definitions, underlying principles, and performance metrics, necessitating careful planning and pilot testing before broader deployment. The most effective use case for machine‑readable standards is automated logistics equipment that executes workflows according to these specifications, which can be advanced through targeted pilots based on preliminary strategic planning.

Therefore, the development of digital logistics standards should begin at the design stage, with a strong emphasis on strategic planning; top-level design is particularly critical. Top-level design sets the baseline for ambition, and the planning phase must ensure that a competitive edge is established—failure to stay ahead from the outset risks falling behind. Moreover, without a clear understanding of the industry’s dynamics and external trends, it is all too easy for a project to lag once it is implemented. Only by taking a leading position at the planning level can organizations secure a sustained competitive advantage in practical applications and align with future‑oriented needs.

Second, the digitalization standards framework for smart manufacturing logistics must be aligned with production and manufacturing processes. The production architecture of a smart factory is neither fixed nor pre‑defined; it can dynamically reconfigure the factory’s topology—covering models, data, communication protocols, and computational algorithms—to meet specific market conditions. Consequently, component specifications, dimensions, and weights do not adhere to a uniform standard. Given this, why are non‑standard components still delivered to the production line in a standardized manner, and how is standardized integration into the production process achieved?

First, manufacturing facilities cannot be infinitely large; the final assembly workshop, in particular, should be as compact as possible and must not be used for storing large quantities of components. Instead, component sorting, sequencing, and temporary storage should be moved upstream to the warehouse, and logistics management for these components must be more standardized and precise.

Secondly, market demand is driving increasing flexibility in production. The growing prevalence of customized products makes material management on the production line particularly challenging. Since different products require distinct components, this variability poses significant logistical hurdles. Employing standardized tooling facilitates the rapid reconfiguration of line‑side components to accommodate product changes. Moreover, even when component dimensions vary, they can typically be accommodated within standardized fixtures, enabling efficient identification and retrieval of specific parts.

Third, component requirements under different line‑in modes call for corresponding production‑logistics approaches. JIT parts are typically delivered directly to the line side by suppliers, bypassing internal sorting and kitting at the logistics center and being sent straight to the assembly line. In many manufacturing sectors, this practice has already become standard.

Standardized components are not stored individually but in bulk quantities based on demand, which allows for the effective use of standardized logistics handling equipment. However, manufacturing firms with a high degree of lean management typically require suppliers to pre‑package items in their smallest internal unit sizes. By contrast, companies with a more rudimentary management approach often fail to establish such specifications or requirements, necessitating secondary picking and temporary storage within the warehouse, as well as manual counting of standard parts to verify quantities. When it comes to standard components, if companies and suppliers do not adopt unified packaging and standardized handling tools, not only does logistical efficiency suffer, but costs also increase significantly.

JIS parts (sort‑by‑part) are the most complex. The challenge with sort‑by‑part lies in the fact that, since each product differs, the components required also vary. Ideally, after sorting and staging all sort‑by‑part items in a warehouse near the final assembly line according to the production schedule, they would be delivered to the line side using standardized material‑handling containers, aligned with the production takt time. If the product mix changes or the production plan is adjusted, only the container‑based system needs to be reconfigured. However, many companies today still cannot achieve this; instead, they typically manage sort‑by‑part in much the same way as kanban‑based parts.

Behind this lies not merely a problem with the logistics unit‑handling equipment itself, but rather an issue with the overall integration solution. Since companies fail to define such solutions in advance, on‑site operators naturally do not know which components should be grouped together in a particular handling device or container. Consequently, whether standard logistics equipment is user‑friendly and practical must be evaluated based on each company’s specific circumstances.

Third, digital talent specializing in logistics standards is even more scarce. Logistics digitalization professionals are highly multidisciplinary. Many of those who previously developed standards were deeply familiar with industry rules and specifications, adept at drafting clear, concise standards in standardized language that minimizes ambiguity. However, these seasoned standardization experts may not necessarily be equipped to articulate machine‑readable standards using languages like XML. Meanwhile, IT specialists often lack a thorough understanding of standardization principles and domain‑specific technical requirements. To excel in this field, one must not only master diverse specialties and the nuances of standard‑writing but also be proficient in machine‑readable technologies. In the realm of logistics digitalization, such versatile talent is scarce, making the cultivation of digitally‑oriented logistics standards professionals an urgent issue that demands early attention.

  (China Logistics 100 experts (think tank), Chief Expert at Fabraug Logistics Consulting Co., Ltd.