Batch sequencing for resource management in manufacturing environments
- Autores: Santiago López de Haro
- Directores de la Tesis: Pedro Sánchez Martín (dir. tes.), Andrés Ramos Galán (codir. tes.)
- Lectura: En la Universidad Pontificia Comillas ( España ) en 2011
- Idioma: español
- Tribunal Calificador de la Tesis: Fco. Javier Carrasco Arias (presid.), Efraim Centeno Hernáez (secret.), Francisco Javier Conde Collado (voc.), Rafael Ruiz Usano (voc.), Donald B. Rosenfield (voc.)
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- Resumen
This research is based on scheduling problems that arise in two real world manufacturing environments that belong to the automotive industry.
It first evaluates the context of a final assembly process that is considering switching its scheduling strategy from mixed to multi model. This change of strategy has the potential to provide significant labor savings. However, in order to find an accurate quantitative estimate of these savings, the line needs to balanced considering the constraints of this new approach and the restrictions of the manufacturing process. The author suggests and studies the results of an MIP CP-based Assembly Line Balancing approach that can be run efficiently on this context. The analysis of these results suggests that, even though the new strategy might be promising in other scenarios, it does not reduce labor requirements here.
Secondly, it studies the case of a tier-1 supplier of this industry that is struggling with the schedule of one of its machining processes. The carrier machining process is subject to significant unscheduled downtime and its demand is also stochastic, as a result, it is difficult to manage product inventories and often leads to starvation of the downstream processes. The author provides a new approach to generate and validate new schedules. It is based on a new type of visual representation of schedules and an estimate the probability of starvation. It assumes stochastic supply and demand and a predefined schedule sequence based on batches of different sizes.
Finally, based on his analysis of the state of the art, the author suggests an extension to the taxonomy of manufacturing environments from the scheduling perspective
