Mixed-model assembly lines balancing with given buffers and product sequence: model, formulation comparisons, and case study
Jan 1, 2020·
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Thiago Cantos Lopes
Celso Gustavo Stall Sikora
Adalberto Sato Michels
Leandro Magatão
Abstract
Asynchronous assembly lines are productive layouts in which products move
sequentially between stations when processing at current station is complete, and
the following station is empty. When these conditions are not verified, downstream
starvations and upstream blockages can occur. Buffers are often employed to minimize
these problems, which are particularly relevant when the line is shared between
a set of different products models (mixed-model lines). If the sequence of such
models is cyclical, a steady-state production rate is eventually reached. However,
determining (and, therefore, optimizing) such steady-state is challenging. This
led to the development of indirect performance measures for mixed-model lines by
many authors. In this paper, a direct performance measure is presented with a mixed-integer
linear programming model and compared to previous formulations. The model is also
applied to a practical case study and to a new dataset (with 1050 instances), allowing
general assertions on the problem. All instances are solved with a universal solver
and solutions are validated with a simulation software. Tests on the dataset instances
confirmed the observations made on the case study: the proposed formulation produced
solutions with higher production rate in 82% of the instances and tied the remaining
ones, not being outperformed a single time. A triple interdependency of task balancing,
product sequencing, and buffer allocation is demonstrated. Cyclical schedules show
how buffers are able to compensate differences between models across stations and
lead to the conclusion that the propagation of differences of models between stations
can generate scheduling bottlenecks (blockages and starvation).
Type
Publication
Annals of Operations Research

Authors
Celso Gustavo Stall Sikora
(he/him)
Postdoctoral researcher
Postdoctoral researcher in Operations Research at Friedrich-Schiller-Universität Jena.
Specialist in exact optimization methods, decomposition approaches, and AI-enhanced
combinatorial optimization, with applications in urban logistics, port operations,
and assembly systems.