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Title: Production planning and scheduling with applications in the tile industry

Authors: Armindo Soares; Carina Pimentel; Ana Moura

Addresses: Grés Panaria Portugal, S.A. Zona Industrial de Aveiro, Apartado 3002, 3801-101 Aveiro, Portugal ' GOVCOPP, DEGEIT, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal; UNIDEMI, Faculty of Science and Technology, Universidade NOVA de Lisboa, 2829-516 Caparica, Portugal ' GOVCOPP, DEGEIT, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal

Abstract: In this paper we consider the medium to short-term production planning and scheduling (PPS) process of a ceramic tile industry. The PPS process encompasses three problems: 1) the development of a master production plan that determines the medium-term production needs; 2) the development of a biweekly production scheduling plan that minimises the production time required to complete the set of products, so as to meet customer orders within agreed due dates and ensure the filling of connected firing kilns; 3) the available-to-promise problem (or jobs order acceptance/order selection, and delivery date establishment problem). The production scheduling problem (PSP) was addressed as an identical parallel machine problem, with machine eligibility constraints, family and subfamily setups and minimum production lot sizes. A specific heuristic and a mixed integer programming model are proposed to solve the PSP. A model-driven decision support system, applying and manipulating quantitative models, that improves the quality and time expenditure of the PPS process, is also presented.

Keywords: production planning and scheduling; PPS; constructive heuristic; decision support system; DSS; mixed integer programming; MIP; tile industry; master production schedule; MPS; available to promise; ATP; production scheduling.

DOI: 10.1504/IJOR.2022.123035

International Journal of Operational Research, 2022 Vol.44 No.1, pp.58 - 79

Received: 10 Oct 2018
Accepted: 24 Jul 2019

Published online: 23 May 2022 *

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