1. How to understand the data space and what problems to solve?
Create a secure and trusted data space in which enterprises or organizations of any size and industry can share, trade or use their data assets with full data autonomy, and can trace the shared data through the whole chain. Creating a vehicle data space that operates on a consolidated cloud infrastructure, thereby providing a common standard for data exchange between companies along the entire value chain. In order to solve the problems of technology, standards, application and industry cultivation in the trusted circulation of industrial data resources, the China Academy of Information and Communications Technology (CAICT) has jointly initiated the establishment of the "trusted industrial data space Ecological Chain" with the trusted industrial data space as the starting point, aiming to build an ecological cooperation and development platform for the open sharing, analysis and utilization of industrial data and trusted circulation.
Based on the above background, data space should be understood at three levels:
The first layer is the enterprise data space, which focuses on the product as the core within the enterprise and defines the data elements of the product in various stages of the life cycle, such as the concept stage, the detailed design stage, the manufacturing stage, etc. At the same time, it is also necessary to organically link the data elements of different stages to form a continuous flow of product data flow, which we call "product digital main line". Creating the product data space within the enterprise is the key problem to be solved in the digital transformation of manufacturing enterprises, which will provide key data support for the construction of end-to-end data-driven business and artificial intelligence applications within the enterprise, and its ultimate application scenario is the product digital twin, the factory digital twin, and even the enterprise digital twin.
The second layer is the industrial data space, which aims to solve a series of problems such as how to access the industrial chain data space on the basis of the internal digital space constructed by enterprises, so as to build an agile, reliable and reliable digital supply chain ecology. This layer of data space needs to focus on the industrial chain dimension, define the product form and enterprise portrait of the upstream and downstream of the industrial chain, and realize the transformation and upgrading of the industrial chain from the chain supply chain to the network supply chain through the secure and trusted data interface provided by the data space. The industrial data space can not only provide a flexible and reliable supply chain system for upstream and downstream enterprises in the supply chain, but also provide insights and analysis at the industrial chain level for relevant government departments, such as industrial layout, strong chain reinforcement analysis, etc. Its ultimate application scenario is the data-driven, real-time dynamic industry graph.
The third layer is cross-industry chain data space, which is an innovative application scenario that builds data space from a higher dimension, such as smart agriculture, smart parks, smart cities, etc., and is a comprehensive application of the industrial chain such as road/infrastructure, vehicles, and traffic signals. This is also the greatest value of the future data space, including digital twins, meta-universes, and so on.
These three layers of data space complement and promote each other. The enterprise data space is the foundation, providing data support for the other two layers of data space. If the enterprise data space is done well, the data space of the industrial chain and cross-industrial chain will have a steady stream of data support; The innovative application scenarios of the industrial chain and cross-industrial chain will further promote the iterative upgrading of the enterprise data space, thus accelerating the digital transformation within the enterprise.
2. At present, what are the data space practices in the manufacturing industry and what specific results have been achieved?
With the rise of a new generation of digital technology, the manufacturing industry began to realize the value of digital technology to enterprises, and gradually raised the digital transformation to the strategic level of enterprises, setting off a wave of digital transformation and upgrading in the manufacturing industry. In short, the essence of enterprise digital transformation is to solve data problems, that is, to break organizational barriers, eliminate information islands, solve the problem of end-to-end data access within the enterprise, and ultimately help enterprises realize the transformation of product development models or enterprise business models. It can be seen that enterprise digital transformation is to create a product-centered enterprise data space in the enterprise, promote the efficient flow of data in various business links and product stages, and lay a solid foundation for the large-scale application of artificial intelligence and decision innovation in the enterprise.
Combined with years of industry practice, the digital mainline technology based on model and end to end closed loop is proposed, which provides a feasible path for manufacturing industry to create enterprise data space, and has been verified in practice in many leading enterprises in the world. The biggest challenge in the past was how to deliver the engine configuration data of each production batch in real time and accurately to assembly personnel at different stations in various plants around the world, and also to provide real-time feedback and summary of assembly and inspection results. Through the product data flow of product design, process, and workshop station, the assembly procedures, operation guidance/animation, inspection requirements, etc. are pushed to the mobile terminal of the corresponding station in real time and accurately. By using augmented reality and artificial intelligence technology, assembly workers can quickly complete the assembly and inspection work on the mobile terminal, and automatically feed the result data back to the system. Thus, the manual error rate is greatly reduced and the production and assembly efficiency is improved. By building an end-to-end, closed-loop digital mainline, we've reshaped the product development value stream, dramatically improved product quality, and accelerated time-to-market.
3. Ideas and suggestions for promoting enterprise data space?
With the mature application of data space infrastructure, under the protection of data autonomy and transaction mechanism, manufacturing will become one of the important application scenarios of data space, which will further promote the transformation and upgrading of the manufacturing industry chain. Therefore, manufacturing enterprises should actively participate in it, and formulate enterprise data space strategies as soon as possible, and even actively participate in the construction of industrial chain data space ecology and new models, in order to stand out in a new round of industrial chain transformation and upgrading.
For the construction of enterprise data space, the author has the following suggestions:
First of all, the enterprise data space and enterprise digital transformation strategy are combined to think about the digital construction of enterprises from a higher level and dimension, that is, to promote the comprehensive digitalization of products and businesses.
Secondly, it is necessary to pay attention to top-level planning and design, promote construction in different fields and stages, and adopt the promotion idea of agile iteration and small steps to strengthen confidence and determination with quick results.
Finally, strengthen the construction of the standard specification system, formulate a standard service framework agreement for multiple products and multiple fields, and connect the national/international data space protocol on the top, and connect the underlying data source system within the enterprise to support the global security sharing and circulation of product data.
The strategy of data space requires the simultaneous development of technology, system and market. In terms of technology, the systematic technological arrangement that drives circulation, sharing and exploitation is designed. Institutionally, establish a system to crack the data flow; In terms of market, establish a unified data element market. Finally, the value of data can be transformed from resource to asset and capitalization, and finally realize the value of data space.
