Abstract

The process of one-parameter selective assembly of two parts is considered. Methods for reducing the probability of sorting errors are given. It is suggested to perform the sorting process according to the values of the parameter estimates. For this estimate, a recursion algorithm (the Kalman filter) is used in each cycle. In the environment of GPSS World, a simulation model of selective acquisition and assembly of two parts for determining the parameters of the assembly process is constructed. Comparative modeling results are presented that prove the effectiveness of the algorithm for estimating parameters for selective assembly. The variants of using the algorithm and the prospects for further research are suggested.

Highlights

  • The process of one-parameter selective assembly of two types of parts by parameters xi ( i = 1, 2 ), manufactured by N - batch of parts, is considered

  • The control of the details is accompanied by random errors, the appearance of which leads to the fact that instead of the true value of the parameter xk,i in the measurement process, a value zk,i usually associated with the initial dependence becomes known: z= k,i xk,i + δ k,i, (1)

  • Where δk,i − random component of the measurement error of the i-th parameter, k - the cycle number corresponding to the serial number of the part in the batch ( k = 1, N )

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Summary

Introduction

The probability of obtaining such events will be less, the smaller the magnitude of the measurement error δk,i , i.e. more proximity of the actual value of the parameter to the true value Reduce this probability in several ways: 1) by choosing the accuracy of the means of measuring technology, which provides the measurement error required for the given criteria; 2) the use of methods for the optimal evaluation of the parameters of parts in the presence of a priori information. The purpose of this work is to modify the simulation model of selective assembly of two parts by implementing the sorting algorithm based on the values of the parameters obtained as a result of their recurrent evaluation

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