The PLM concept implies the use of heterogeneous information resources at different stages of the product life cycle, the joint work of which allows the user to effectively solve the problems of product quality and various costs. According to the principle of isomorphism of complex systems’ regularities, an effective PLM system must have these regularities. Unfortunately, this principle is not often fundamental when designing PLM systems. The purpose of this paper is to develop principles, based on the general theory of systems, for the design, operation and use of PLM systems and the implementation on their basis of the educational framework of a PLM system for threaded connections with the possibility of its effective development, research and study. The multi-agent approach to the development of a PLM system provides the necessary prerequisites for the emergence of system-wide regularities in it. The parallel work of agents is implemented using the actor model and the Ray Python-package. Agents for the logical inference of knowledge base facts, CAD/FEA/CAM/SCADA agents, agents for optimization by various methods, and other agents have been developed. Open-source software was used to develop the system. Each agent has relatively simple behavior, implemented by its rule function, and can interact with other agents. The system can work in interactive mode with the user or in automatic mode according to a simple algorithm: the rule functions of all agents are executed until at least one of them returns a value other than None. Examples of the system operation are given and system-wide regularities such as emergence, historicity and self-organization are demonstrated in it.

The principles of the development of PLM-system for threaded connections of oil and gas equipment are described. In order to ensure efficiency, the PLM-system must be isomorphic to other complex systems and have their laws, in particular, the emergence and “requisite variety”. The proposed system belongs to the class of hybrid multi-agent intelligent systems that combine various methods of knowledge representation and decision making. The system contains a knowledge base with inference rules, an inference engine, a code editor, simulation models of threaded connections, the results of their simulations, and other components. The knowledge base contains facts, in which the factors that affect the reliability and durability of threaded connections, are connected by cause-effect relations “is the cause” and “is the effect”. Facts can have such properties as an information source, dependence of quantities, a simulation model, etc. The rules of inference allow you to get new facts from the knowledge base and simulation models. All system components or their software interfaces are developed in a high-level general-purpose programming language Python, which simplifies the implementation of the system and the integration of components with different types. In particular, any Python package can be easily connected to the system. Classes and individuals of ontology are declaratively described by Python classes and objects, attributes and relationships are Python-attributes. For easy editing, the system code is divided into parts, which are combined before execution.

High-precision tapered threads are widely used in hard-loaded mechanical joints, especially in the aggressive environment of the drilling of oil and gas wells. Therefore, they must be made of workable materials often difficult to machine. This requires the use of high-performance cutting tools, which means the application of non-zero geometric parameters: rake and edge inclination angles. This study is based on analytical geometry methodology and describes the theoretical function of the thread profile as convoluted surfaces dependent on the tool’s geometric angles. The experiments were conducted using a visual algorithm grounded on the obtained function and prove the practical use of the scientific result. They predict the required accuracy of thread made using a lathe tool with a rake angle of up to 12°.