A model-driven decision support system for reallocation of supply to orders under uncertainty in ceramic companies

In ceramic companies, uncertainty in the tone and gage obtained in first quality units of the same finished good (FG) entails frequent discrepancies between planned homogeneous quantities and real ones. This fact can lead to a shortage situation in which certain previously committed customer orders...

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Detalles Bibliográficos
Autores: Alemany Díaz, María Del Mar|||0000-0002-0992-8441, Ortiz Bas, Ángel|||0000-0001-5690-0807, Boza, Andres|||0000-0002-5429-0416, Fuertes-Miquel, Vicente S.|||0000-0003-3524-2555
Tipo de recurso: artículo
Fecha de publicación:2015
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/65507
Acceso en línea:https://riunet.upv.es/handle/10251/65507
Access Level:acceso abierto
Palabra clave:Decision support system
Mathematical programming models
Lack of homogeneity in the product
Shortage planning
Uncertainty
Ceramic companies.
ORGANIZACION DE EMPRESAS
MECANICA DE FLUIDOS
Descripción
Sumario:In ceramic companies, uncertainty in the tone and gage obtained in first quality units of the same finished good (FG) entails frequent discrepancies between planned homogeneous quantities and real ones. This fact can lead to a shortage situation in which certain previously committed customer orders cannot be served because there are not enough homogeneous units of a specificFG (i.e., with the same tone and gage). In this paper, a Model-Driven Decision Support System (DSS) is proposed to reassign the actual homogeneous stock and the planned homogeneous sublots to already committed orders under uncertainty by means of a mathematical programming model (SP-Model). The DSS functionalities enable ceramic decision makers to generate different solutions by changing model options. Uncertainty in the planned homogeneous quantities, and any other type of uncertainty, is managed via scenarios. The robustness of each solution is tested in planned and real situations with another DSS functionality based on another mathematical programming model (ASP-Model). With these DSS features, the ceramic decision maker can choose in a friendly fashion the orders to be served with the current homogeneous stock and the future uncertainty homogeneous supply to better achieve a balance between the maximisation of multiple objectives and robustness.