Browsing by Author "Dolgui, Alexandre"

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Access status: Open Access ,
A transfer line balancing problem by heuristic methods: industrial case studies
(2008) Guschinskaya, Olga; Dolgui, Alexandre
The paper deals with the problem of optimal configuration of a type of transfer lines which are equipped with transfer machines. Such machines perform operations with standard modular spindle heads which are activated sequentially. All operations assigned to the same spindle head (block of operations) are executed simultaneously by a set of tools fixed at the spindle head. The quantity of machines and spindle heads used to produce a part with the given productivity rate defines the final cost of the transfer line which must be minimized. To minimize this cost, a combinatorial problem of operations assignment to blocks and machines must be solved. The solution must provide a desired productivity (cycle time), it must also satisfy precedence and compatibility constraints. In this paper, we suggest improved versions of FSIC heuristic algorithm in order to help line designers to solve real-scale industrial problems. Results of computational experiments obtained for industrial cases are presented.
Access status: Open Access ,
Optimizing modular machining line design problem with mixed activation mode of machining units
(2007) Belmokhtar, Sana; Dolgui, Alexandre; Delorme, Xavier; Ignatenko, Ivan
A modular transfer line designing problem is investigated. The problem is to find the best subset of modules (machining units) from a given set and to assign them to different stations so that technological constraints and cycle upper limit are respected and the line cost is minimal. The investigated lines have a mixed activation mode for the machining units of each station, i. e. the units of each station are arranged into a series of stages such that each stage is composed of several units activated in parallel. A mixed integer program approach is proposed to model and solve the corresponding design problem. Improvements are suggested in order to reduce the model size and speed up the computations.