Resource Optimisation of Distributed Manufacturing Processes Using Simulation

Abstract

Non-destructive testing processes in the technological cycle of a wagon repair enterprise largely determine safety of railway transport facilities. The most effective ways to control such processes can only be determined through simulation which makes it possible to assess stability of the production system in a wide range of both external conditions and internal factors.The objective of the work is to create a method for optimising the resources of distributed manufacturing processes for non-destructive testing of a wagon repair depot based on simulation to reduce the likelihood of stopping the production cycle and reducing unreasonable costs of the enterprise.The features of non-destructive testing as a stage of the technological cycle of the enterprise are considered followed by the analysis of information on the qualifications of the specialists of the wagon repair company. The positions of non-destructive testing and controlled details are described and analysed within the framework of the queuing theory. To optimise the non-destructive testing division, simulation modelling is used, while mathematical statistics methods and correlation analysis are used to process the simulation results.A built model of a non-destructive testing unit comprises posts at the units for repair of parts of the automatic coupling devices and the wagon bogie, wheel sets. A production personnel management scheme is proposed, which might be a basis for optimising the organisational structure of the non-destructive testing unit.The simulation resulted in formulating requirements for qualification of non-destructive testing inspectors of the wagon repair depot. It is shown that the optimal strategy for development of a subdivision should be aimed at ensuring the universal qualification of employees, in which they have the necessary competencies to perform work at all testing positions. This will increase the average occupancy rate of NDT inspectors from 0,34 to 0,45 and reduce the average delay time of an item at the post from 650 % to 150 % of the standard time.