Programación de la producción para la sección de formado y lijado en una empresa de fabricación de cepillos profesionales para peluquerías

La programación de la producción se entiende como el proceso que tiene una empresa para la toma de decisiones respecto a la fabricación de sus productos. En este proyecto se estudiará el problema de programación de la producción para la Etapa 2: formado y lijado, la cual se identificó como cuello de botella en la empresa Irca Ltda. Como principal objetivo, se desarrollará un aplicativo en Microsoft Excel ®. El cual se apoyará en un algoritmo genético que logre reducir la sumatoria de las diferencias entre el tiempo de terminación de un trabajo y la fecha de entrega del mismo; entendida como la minimización de la tardanza total. Se tomaron restricciones propias del sistema, las cuales están relacionadas con máquinas en paralelo, elegibilidad de máquina, permutación e interrupción de las órdenes de producción. Este algoritmo genético aplica un enfoque de variabilidad logrando hallar una solución factible y de calidad para el problema. Este enfoque comienza utilizando reglas de despacho como SPT, LPT, EDD y LIFO para el caso de la población inicial, para la selección de padres una probabilidad asociada al de menor tardanza, para el cruce se utiliza aleatoriedad en las particiones a intercambiar y en la mutación se presenta la probabilidad que los tipos de cabo se agrupen para reducción de tiempos de alistamiento. Respecto a los resultados obtenidos es posible evidenciar como el algoritmo propuesto mejora la tardanza en un rango entre el 40-90%, además de mejor solución en comparación con la programación actual de la compañía, al igual que con las reglas de despacho evaluadas.Scheduling is understood as the decision process that a company has to make regarding the manufacture of its products. This project will study the production scheduling problem for Stage 2: formed and sanding, which was identified as a bottleneck in the company Irca Ltda. As an objective, an application will be developed in Microsoft Excel ®. Which will be based on a genetic algorithm that reduces the sum of the differences between the time of completion of a work and the date of delivery of the same, Understood as the minimization of total tardiness. The constraints of this system were applied, this are related to parallel machines, machine eligibility, permutation and interruption of production orders. This genetic algorithm applies a variability approach to find a feasible and quality solution for the problem. This approach starts using dispatch rules such as SPT, LPT, EDD and LIFO for the initial population case, for the selection of parents a probability associated to the lesser delay, for the crossing is used randomness in the partitions to be exchanged and in the Mutation we present the probability that the types of cable are grouped for reduction of enlistment times. Regarding the results obtained, it is possible to show how the proposed algorithm improves the Total Tardiness in a range between 40-90%, as well as a better solution in comparison with the current schedule of the company, as well as with the dispatch rules evaluated.Ingeniero (a) IndustrialPregrad

Flexible jobshop scheduling problem with resource recovery constraints.

Objectives and methods of study: The general objective of this research is to study a scheduling problem found in a local brewery. The main problem can be seen as a parallel machine batch scheduling problem with sequence-dependent setup times, resource constraints, precedence relationships, and capacity constraints. In the first part of this research, the problem is characterized as a Flexible Job-shop Scheduling Problem with Resource Recovery Constraints. A mixed integer linear formulation is proposed and a large set of instances adapted from the literatura of the Flexible Job-shop Scheduling Problem is used to validate the model. A solution procedure based on a General Variable Neighborhood Search metaheuristic is proposed, the performance of the procedure is evaluated by using a set of instances adapted from the literature. In the second part, the real problem is addressed. All the assumptions and constraints faced by the decision maker in the brewery are taken into account. Due to the complexity of the problem, no mathematical formulation is presented, instead, a solution method based on a Greedy Randomize Adaptive Search Procedure is proposed. Several real instances are solved by this algorithm and a comparison is carried out between the solutions reported by our GRASP and the ones found through the procedure followed by the decision maker. The computational results reveal the efficiency of our method, considering both the processing time and the completion time of the scheduling. Our algorithm requires less time to generate the production scheduling (few seconds) while the decision maker takes a full day to do it. Moreover, the completion time of the production scheduling generated by our algorithm is shorter than the one generated through the process followed by the decision maker. This time saving leads to an increase of the production capacity of the company. Contributions: The main contributions of this thesis can be summarized as follows: i) the introduction of a variant of the Flexible Job-shop Scheduling Problem, named as the Flexible Job-shop Scheduling Problem with Resource Recovery Constraints (FRRC); ii) a mixed integer linear formulation and a General Variable Neighborhood Search for the FRRC; and iii) a case study for which a Greedy Randomize Adaptive Search Procedure has been proposed and tested on real and artificial instances. The main scientific products generated by this research are: i) an article already published: Sáenz-Alanís, César A., V. D. Jobish, M. Angélica Salazar-Aguilar, and Vincent Boyer. “A parallel machine batch scheduling problem in a brewing company”. The International Journal of Advanced Manufacturing Technology 87, no. 1-4 (2016): 65-75. ii) another article submitted to the International Journal of Production Research for its possible publication; and iii) Scientific presentations and seminars