Recent market changes in terms of an increase in product variety and demand uncertainty have tremendously complicated production planning in process industries, and in response to this, many manufacturing companies in process industries have been forced to adopt hybrid MTS-MTO production planning systems. To address this complication, Several production planning and scheduling approaches have been proposed by researchers. Among these, the simultaneous lot-sizing and scheduling (L&S) problem as one of the most promising approaches has attracted a considerable amount of attention not only from academia but also from many companies in process industries. Over the last two decades, several mixed-integer linear programming (MILP) models have been proposed by researchers for addressing L&S problems. With the latest advancements in modern commercial optimization solvers, researchers have been able to propose complex mathematical models that are more capable of capturing real-world properties. However, these models have primarily been suggested for process industries with MTS production systems, and the implementation of L&S models in process industries using hybrid MTS-MTO production systems has been almost neglected by the literature. This master’s thesis attempts to fill this gap in the literature and propose an L&S model to process industries using hybrid MTS-MTO production systems. In doing so, a mineral water bottling company, within process industries that uses a hybrid MTS-MTO production system is chosen to be studied. The choice of the company enables the research to investigate and observe challenges of production planning inside process industries, and later to test the applicability of the developed L&S model addressing these challenges in the chosen company.