3.2 Process Data Object Definition
Object-oriented method is a software development method that constructs software systems by using concepts such as objects, classes, instances and inheritance. The basic principle is to implement a natural segmentation of the problem domain, and to identify and define related entities in the objective world according to the way humans understand the objective world. Therefore, it is a more intuitive, natural and easier to understand conceptual model method circle. In recent years, object-oriented technology has been widely used in modeling complex enterprise systems. Combined with the above analysis of the process preparation process data, the object object of the process preparation process is defined by object-oriented technology.
The process preparation process data object definition is shown in Figure 3. Data objects fall into two broad categories, support data and result data. Some data objects in the supporting data are the common basis for the process preparation tasks, such as product characteristics, production conditions, policy standards, etc.; and some data objects are the basis for the execution of a specific task, such as the material characteristics of the process design, Typical examples are in process design and the like. Process knowledge is a special set of data objects that are both support data and result data in the process preparation process. According to the object-oriented method, the process knowledge objects can be divided into four types according to functions: manufacturing objects, technology objects, resource objects and decision objects, and the process knowledge objects involved in the process preparation process can be summarized into one type. Each specific object can be divided into two levels: the object layer and the method layer. The object layer includes four elements: an object class set, an object property set, an object property constraint set, and an object instance set; the method layer describes the operation method name, related objects, and relationships that solve the problem.
3.3 Establishment of process information model
Combined with the previous analysis of the process preparation process data and the definition of data objects, according to the role of data in the process preparation work, the process preparation process data model is divided into three sub-models: process basic data model, process result data model and process knowledge. model.
The process basic data model is an abstract description of the process-related basic theoretical data and enterprise-related standard data on which the various tasks are performed in the process preparation process;
The process result data model is the result data generated by the process preparation task execution. The result data here is the result in a broad sense, including some data guiding the production data and the management process preparation process;
The process knowledge model is the basis for ensuring rapid, efficient and comprehensive access to process knowledge during process preparation and applying knowledge to the actual process preparation process.
The process basic data model is in the same form as the process result data model, and the process result data is usually taken from the process basis data or the processing result thereof. The process basic data should be versatile and not limited to a specific product, so the model should be based on the product object; the process result data is directly used to guide the production of the product, and the organization of the model. The unit should be the component of the product processing, that is, the part object. All three models use an object-oriented ER diagram representation method.
With the continuous development of PLM technology and enterprise management mode, if these technologies can be fully utilized to meet the needs of enterprise informationization, the application effect of process informationization will inevitably be greatly improved. However, the process standard is not very standardized, not very comprehensive, and further research is needed. In addition, the implementation of the PLM solution is a complex system engineering, which requires a scientific implementation strategy as a guideline for the implementation process of enterprises, suppliers and software. In the respective positioning, a scientific, practical and effective implementation method was developed.
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