## 1 Introduction  
The International Organization of Vine and Wine (OIV) estimates that global wine production reached approximately 221 million hectoliters in 2023 [1]. The wine industry is a highly relevant economic sector, contributing significantly to employment, tourism, and exports in numerous countries [2, 3]. Wine production, due to its specific nature, involves the consideration of multiple critical variables to ensure the quality of the final product [4]. In this context, effective planning and scheduling are essential for wineries, as they directly influence the ability to meet customer demand, maintain high-quality standards, and optimize the use of available resources. The bottling stage, in particular, represents approximately 30% of the total costs of the wine value chain [5]. Poor planning in this phase can lead to production-line disruptions, especially during the filtration stage, which significantly impacts the overall production process [6].  
This study aims to develop and apply an operational model based on mixed-integer programming that optimizes the sequencing of batches on the filtration and bottling lines.  
The proposed methodology integrates sequence-dependent setup times with the objective of minimizing the total processing time for orders and reducing the costs associated with resource usage.  
Although the literature has explored aspects related to bottling planning, the specific constraints of the filtration process have received less attention. In particular, the clogging index which measures the potential of particles present in the wine to obstruct the filtering surface is a determining factor that has not been sufficiently addressed [7]. This index is influenced by the mechanical properties of the particles, such as their degree of deformation and disintegration [8]. The accumulation of solids in the filters reduces the flow and increases the processing time for each batch. If not properly managed, the clogging index can reach a critical threshold, requiring the production line to be stopped to replace the filter, resulting in significant losses of time and product [9]. A robust setup plan could mitigate these risks and ensure the feasibility of the production schedule.  
Currently, many wineries perform planning manually, which is often inefficient and leads to adjustments and rescheduling based on unforeseen circumstances, generating additional costs due to delays in fulfilling planned orders. Existing research mainly addresses these issues from a strategic or tactical perspective by formulating the simultaneous lot-sizing and scheduling (SLS) problem and examining its implications for inventory management and order fulfillment. However, these studies do not exhaustively consider the constraints derived from the filtration process [10].  
To address the challenges within the wine industry and contribute to operational decision-making in daily bottling planning, this document is structured as follows: first, it presents an analysis of the predominant practices in the Chilean wine industry, based on a survey conducted with key companies in the sector. This analysis identifies the mechanisms and tools used in planning, as well as the operational considerations and critical variables involved in production processes. Next, a thorough literature review is provided to establish the state-of-the-art and highlight existing knowledge gaps. The third section details the problem and the formulation of the proposed model, followed by its practical application in a real operational context. Finally, the document concludes with a discussion of the results obtained, the limitations of the study, and potential future research directions that could further optimize these processes in the wine industry.