In workshops/factories, automation equipment and systems with different functions from different manufacturers are prevalent, and at the information level, they appear as heterogeneous data distributed at different network levels. The interconnection between heterogeneous systems and equipment is the basis for realizing manufacturing informatization and intelligence, and it is a core issue of digital workshop integration. The key to solving this problem is to establish a normative and consistent information model. In response to the transformation and upgrading needs of the machine tool manufacturing industry for intelligent manufacturing, in order to realize the interconnection between different network levels and heterogeneous equipment and systems in the machine tool manufacturing digital workshop, with the support of the intelligent manufacturing special project, the research group aimed at the lack of digital workshop standards. Based on the research results, the information model of the machine tool manufacturing digital workshop was established, and the machine tool manufacturing digital workshop information management system was developed, and the standard verification was completed. Finally, according to the research results, the GB/T37928-2019 "Digital Workshop Machine Tool Manufacturing Information Model" was drafted and formed the recommended country. standard.
The digital workshop information model is established according to the layer-by-layer decomposition method of "determining the field - analyzing the activities and functions - determining the analysis object - finding the information flow - information classification - establishing the model". In the intelligent manufacturing system architecture, the digital workshop includes three life cycle dimensions of design, production, and logistics, covering three system levels of equipment, unit, and workshop. Its intelligent functional characteristics cover resource elements, interconnection, fusion and sharing, and system integration, such as Figure 1. According to GB/T 25485-2010 "Industrial Automation System and Integrated Manufacturing Execution System Functional Architecture", the core functional categories of the digital workshop should include production operation management, logistics operation management, quality operation management and maintenance operation management. Combined with the production and manufacturing requirements of machine tools, the functional modules of the digital workshop for machine tool manufacturing and processing and the main information flow between them are shown in the figure.
In the information model, the components of the digital workshop are defined as components, the functional modules are defined as functional components, and the production elements are defined as resource components. The data contained in an object is defined by attributes, and the set of all information data contained in each component or object is called its attribute set. According to the static and dynamic nature of information data, attributes are divided into static attributes and process attributes. Static attributes form static attribute sets, and process attributes form process attribute sets. Each attribute set contains attribute data of several information objects, the information objects are described by attributes, and the attributes are composed of attribute elements. The hierarchical structure of the digital workshop information model is thus defined as shown in the figure. The digital shop floor information model is an extensible tree structure that allows nesting between attribute sets and components. In the above definition, attribute set and component set are abstract structural elements that constitute the description of the workshop information model. They are not a mapping of an actual object, do not contain actual content, and are only used to organize the framework and hierarchy of the model.
On the basis of the abstract frame of the information model of the machine tool manufacturing and processing digital workshop, facing its actual implementation problems, taking the Beiyi machine tool digital workshop as an implementation case, a practical information model object is formed. Based on the specific description method and communication mechanism, the completed The instantiation of the information model realizes the organization and storage of the instantiated information model. Based on OPC Unified Architecture (OPC Unified Architecture, OPC UA), an implementation scheme of information model based on OPC UA protocol is proposed. The mapping rules of the information model in the OPC UA address space and the method of realizing information model data storage and interaction based on OPC UA server/client are established. Finally, the verification of the proposed information model and its realization method was completed at the Beiyi machine tool site. By developing the information model server, loader and information management system, the workshop information management and monitoring based on the digital workshop information model was successfully realized. The practicability of the proposed digital workshop information model for machine tool manufacturing is demonstrated.
Finally, on the basis of theoretical research and experimental verification, the recommended national standard for "Digital Workshop Machine Tool Manufacturing Information Model" was drafted and formed. Effective March 1, 2020. This standard is one of the first batch of seven national standards for intelligent manufacturing since the implementation of the intelligent manufacturing project in my country in 2015.
Liping Wang, Zhaokun Zhang, Zhufeng Shao*, Min Wang. Research on the Information Model of Digital Machining Workshop for Machine Tools and Its Applications. Journal of Mechanical Engineering, 2019, 55(9): 154-165. DOI: 10.3901/JME.2019.09.154.
Zhaokun Zhang, Zhufeng Shao*, Liping Wang, Qinzhi Zhao, Yunfeng Zhang. Digital workshop information model and its standardization. Journal of Tsinghua University (Science and Technology), 2017, 57(2): 128-133,140. DOI: 10.16511/j.cnki.qhdxxb.2017.22.003.