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Abstract
The presented method is used to construction of the shortest assembly schedules of multi-option products. The specific characteristics of assembled products are regarded, for example additional elements (e.g. a handle), different parameters (e.g. a power of the engine), and other properties that determine appearance of a product (e.g. a color of a casing). Schedules are constructed for hybrid flow shop systems. This systems consist of assembly lines with parallel assembly machines. The intermediate buffers with limited capacity are located between assembly stages. In these buffers products are waiting to perform the next assembly operations. The unidirectional flow of multi-option products is regarded – for a fixed or an alternative assembly routes. The monolithic (an one level) approach to construction of assembly schedule is used. The task of assignment of assembly operations to machines and task of scheduling are simultaneously solved. The shortest schedule is fixed. The mathematical models of integer programming are constructed. A fixed assembly routes and an alternative assembly routes are regarded in the mathematical models. The monolithic approach and the integer programming ensure the construction of an optimal schedule. The constructed structure of input parameters and variables and formulated mathematical relationships (constraints) regard multi-option products. There are basic operations (the same for the type of product) and additional operations (differentiating products of a specified type). The structure of input parameters and constraints, and structure of constraints formulated for mathematical models favourably affect the complexity of computing. The results of computational experiments with the proposed method are presented. These experiments have been carried out not only in order to verify the method, but also to make it possible to compare the length of schedules for the fixed and the alternative routes.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)
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