eesti teaduste
akadeemia kirjastus
SINCE 1952
Proceeding cover
of the estonian academy of sciences
ISSN 1736-7530 (Electronic)
ISSN 1736-6046 (Print)
Impact Factor (2022): 0.9
Implementation of a knowledge-based manufacturing on the example of Sumar Tools OÜ; pp. 407–412

Kaarel Kruuser, Jüri Riives, Pavel Tšukrejev, Indrek Kiolein

Higher productivity of an organization is based on modern manufacturing systems and digitizing the manufacturing processes. The problem is how to match together technological capabilities of machine tools (machining centres) with the need to manufacture a product; and how to increase the efficiency of process planning procedures. Injection molds are the products with many different features, with high quality requirements, and variable geometrical parameters. The problem is sophisticated because most of the products are unique and do not repeat. In order to be able to respond quickly changeable situations where sometimes more than 4 different programs are needed on a daily basis, manufacturing systems will have to become more autonomous. For this purpose, it is necessary to take advantages of the possibilities of modern production programs by linking them with know-how of engineers. Manufacturing operations management (MOM) and machine learning are the tools used for developing knowledge-based manufacturing solutions in the company. Framework has been developed to gather data in the company and develop the rules based on data models and information analysis. The designed solutions for feature-based machining (FBM) give high quality technological solutions and increase the efficiency of machining process by computer numerical control (CNC) programming. Product manufacturing information (PMI) model is in development together with integration of the machine learning system.


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