Complex approach to robotic automation of assembly processes in aircraft manufacturing based on fuzzy logic


Аuthors

Krivtsov V. S., Pavlenko V. N.*, Voronko V. V.**, Vorobjev Y. A.***, Shostak I. V.****

National Aerospace University «Kharkov Aviation Institute», KhAI, 17, Chkalova St., Kharkiv, 61070, Ukraine

*e-mail: pavlenko_vitaliy@mail.ru
**e-mail: vitaliy.voronko@gmail.com
***e-mail: yuriy.vorobyov@gmail.com
****e-mail: iv_shostak@rambler.ru

Abstract

Subject of research

Manufacturing of light jet airplanes for general aviation fleet of both Ukraine and foreign countries is connected with certain problems. These problems are determined by the necessity to manufacture rather large series of airplanes with a huge number of modifications within each series. Further complications are due to the fact that this manufacturing should be of high quality and should be carried out during a limited period of time. Organization of assembly effort is a weak point in manufacturing of light jet airplanes. This is in particular true for the following operations: intercoordinating details and component parts during their installation, fixturing the component parts in a specified position, joining structure elements. Replacement of assembly workers with robotic tools leads to a problem of development of special smart robots, which should emulate the behavior of an assembly worker to a certain degree.
The paper aims at describing the complex approach to application of fuzzy logic apparatus for the synthesis of the appropriate adequate models and methods of control of automated robotic line for aircraft structure components assembly, which uses smart robots.

Methodology of research

The authors used the method of assembly, which is based on virtual datum surfaces, as a methodological basis for organization of manufacturing processes within the automated robotic line for the assembly of light jet airplanes. The work describes a complex approach, which consists of two stages. The first stage consists in the synthesis of a typical fuzzy model, which can be used for the decision-making by smart manipulation robots during estimation of the surfaces of the matched component parts in the process of assembly. The second stage consists in developing a fuzzy model for coordination of actions of a group of smart manipulation robots, which function within an automated robotic section of the aircraft structure component assembly line.

Results of research

The paper presents a two-stage approach to robotic automation of a section of the airplane structure components assembly line that suggests synthesis of world models for both separate smart robots and a group of robots, which function within an assembly line section, on the basis of fuzzy logic. The work describes a typical fuzzy model of a smart robot, which estimates component parts surfaces on the basis of virtual datum. It also adduces a rough outline of the fuzzy model of coordination of a group of three manipulation robots, which function within a section of airplane structure components assembly line. The functions of these robots include component matching according to the method of virtual datum surfaces.

Conclusions

Intensification of production of light jet airplanes implies robotic automation of the line assembly of aircraft structure components. Such automation can be carried out, in particular, on the basis of the method of virtual datum surfaces. It is rational to use a two-stage approach to implement robotic automation of the assembly effort in aircraft manufacturing. The first stage consists in gradual development of a typical world model for an individual smart robot. The second stage consists in developing a behavior model for a group of smart robots, which function within an assembly line section. At that fuzzy logic proves to be an efficient mathematical tool for synthesis and implementation of world models of smart manipulation robots during aircraft structure component assembly.

Keywords:

aircraft manufacturing, general aviation, light jet airplanes, virtual datum surface method, line assembly, robotic automation, smart robot, fuzzy model, coordination

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