Reasignación óptima del inventario a pedidos en empresas cerámicas caracterizadas por la falta de homogeneidad en el producto (FHP)

Abstract

Reasignación óptima del inventario a pedidos en empresas cerámicas caracterizadas por la falta de homogeneidad en el producto (FHP) La Falta de Homogeneidad en el Producto (FHP), se define como la carencia de la homogeneidad requerida por el cliente en los productos. La FHP aparece en empresas en las que los productos finales obtenidos no son homogéneos, dando lugar a la existencia de diferentes referencias (subtipos) de un mismo producto final. Esta falta de homogeneidad supone un problema cuando el cliente requiere ser servido a través de unidades homogéneas de un mismo producto y sus pedidos se comprometen en base cantidades planificadas, cuyas características de homogeneidad finales se desconocen en el momento de adquirir los compromisos con el cliente. Las constantes discrepancias provocadas por la FHP entre las cantidades planificadas y las realmente obtenidas y disponibles, pueden impedir servir pedidos comprometidos previamente. Para resolver este problema, se propone un modelo de programación matemática que permite reasignar el inventario en empresas caracterizadas por la FHP que fabrican contra almacén (Make to Stock: MTS) que combina varios objetivos. El modelo matemático propuesto se ha validado mediante su aplicación a un caso real de una empresa cerámica. El análisis de los resultados indica la obtención de mejoras considerables en la cantidad de pedidos completados a tiempo y en los ingresos por ventas.M Palabras clave: Asignación de inventario, disponible a prometer (ATP), falta de homogeneidad en el producto (FHP), fabricación contra stock (MTS), modelo de programación matemática, múltiples objetivos.Optimal inventory reallocation to customer orders in ceramic tile companies characterized by the lack of homogeneity in the product (LHP)The lack of homogeneity in the product (LHP) is defined as the lack of uniformity required by the customer in the products. The LHP appears in companies where the final products obtained are not homogeneous, leading to the existence of different references (subtypes) of the same product. This lack of homogeneity is a problem when the client needs to be served through homogeneous units of a product and commit orders are based on planned quantities, whose final homogeneity characteristics are unknown at the time of acquiring the customer commitments. The frequent discrepancies caused by the LHP between planned homogeneous amounts and those actually obtained and available, can prevent the delivery of committed orders. To solve this problem, we propose a mathematical programming model for the reallocation of inventory in Make to Stock (MTS) ceramic tile companies characterized by the LHP that combines multiple objectives. The proposed mathematical model has been validated by its application to a real case of a ceramic company. The analysis of the obtained results indicates significant improvements in the number of orders completed on time and in sales revenue achieved. Vol 52, 1, 31-41, Enero-Febrero 2013 iSSn 0366-3175. eiSSn 2173-0431. doi: 10.3989/cyv.42013 Keywords...

Simulation to reallocate supply to committed orders under shortage

“…D: deterministic; U: uncertain; RS: real stock; PP: planned production; DA: delays allowed; POL: partial deliveries of order lines; MP: mathematical programming; SD: system dynamics. Alemany et al (2013a) formulated a mixed-integer linear programming (MILP) model for solving the SP problem in LHP contexts. The model reallocates only existing stocks of multiple products to multiple-line orders, while ensuring homogeneity between the units of product that comprise each order line.…”

A Model-Driven Decision Support System for Reallocation of Supply to Orders Under Uncertainty in Ceramic Companies

“…This paper also contemplates the reallocation of uncertain future homogeneous quantities of subtypes in the master plan lots. Reallocation of supply to customer orders is very difficult, and LHP makes it even more complex given the larger number of references managed (subtypes) and the number of possibilities when assigning supply (Alemany et al 2013a). Thus in a real situation, finding not only an optimal solution, but also a feasible one to the reallocation problem is very hard given the huge volume of committed orders, each with several order lines, different subtypes and homogeneous sublots.…”