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Abstract
The impacts of manufacturing cannot be overstated. Apart from trees, mountains, and oceans, most things around us were manufactured at some point through a process that few ever think about. Pharmaceutical products, specifically, improve, extend, and save the lives of human beings around the planet and their manufacturing is of significant importance. Apart from determining the quality and cost of the products, the output of the manufacturing process also impacts the availability of the drugs in pharmacies and hospitals. As such, the planning of pharmaceutical production must ensure that the manufacturing output of all products is sufficient to meet demands. The flexible operation of manufacturing facilities allows for adjustments of the allocation and utilization of the process to satisfy varying demands. However, the operation is limited to throughputs below the installed capacity. Pharmaceutical companies must therefore plan their capacities such that future demands can be satisfied. Capacity planning involves the expansion and reduction of existing facility capacities and the construction of new facilities to meet long-term demands. A strong link exists between capacity planning and production planning, as capacity changes impact the future throughput of the entire manufacturing system. As a consequence, the integration of decisions in capacity and production planning can bring significant benefits.
Production planning must consider a set of manufacturing features to provide feasible production targets for each facility. Often, the production of an active pharmaceutical ingredient takes place over multiple stages with shipments of stable intermediates between facilities on each stage. The facilities themselves consist of multiple manufacturing lines where each line is capable of producing multiple products. When going from the production of one product to another, a line must be thoroughly cleaned and as a result the lines operate in campaign mode where products are produced over long periods. The campaign production on each line must therefore be considered when developing manufacturing targets to ensure that enough product is made at the final stage and that production on each line is supported by a sufficient supply of intermediates and raw materials.
Capacity expansions of existing lines can be achieved through the implementation of retrofit projects that influence the capacities of the various products on a line differently depending on the product-process similarities. Capacity planning must therefore consider both the lines and products to determine where, when, and how much capacity to expand. During project implementation, the throughput of a line can be affected and ultimately production on the line may have to be stopped. As such, the production plan must ensure that the downtime of the line does not lead to a mismatch of supply and demand.
The integration of capacity planning and production planning involves the consideration of various features within each problem and related to their integration. These features can be described through mathematical models, and various formulations based on mathematical programming have been presented in the research literature. However, few of these formulations consider the complex systems described and the relationships between capacity expansions, product capacities and the impacts of retrofit projects on the line operation. It is therefore clear that the development of new mathematical formulations is needed.
The variety of model formulations in literature additionally points to the need for a method that states how a general problem in capacity and production planning should be tackled. These problems start with challenges in a specific system that must be solved through the generation of plans and recommendations for decision-making support. One or several models can be used for the solution of each problem, which requires that the method considers model development as well as model solution.
The main contribution of this thesis is the development of a systematic framework that integrates general representations, models, methods, and tools for the solution of capacity and production planning problems. The developed framework is generic and can thus be used to solve a wide range of problems in various system types. The framework has been applied to several case studies inspired by or coming from industrial primary pharmaceutical manufacturing. As a result, several novel deterministic and stochastic MILP models have been developed. The solution of the case studies through the developed models has demonstrated the ability of the framework to provide data-driven decision-making support for systems of industrial size and complexity.
Production planning must consider a set of manufacturing features to provide feasible production targets for each facility. Often, the production of an active pharmaceutical ingredient takes place over multiple stages with shipments of stable intermediates between facilities on each stage. The facilities themselves consist of multiple manufacturing lines where each line is capable of producing multiple products. When going from the production of one product to another, a line must be thoroughly cleaned and as a result the lines operate in campaign mode where products are produced over long periods. The campaign production on each line must therefore be considered when developing manufacturing targets to ensure that enough product is made at the final stage and that production on each line is supported by a sufficient supply of intermediates and raw materials.
Capacity expansions of existing lines can be achieved through the implementation of retrofit projects that influence the capacities of the various products on a line differently depending on the product-process similarities. Capacity planning must therefore consider both the lines and products to determine where, when, and how much capacity to expand. During project implementation, the throughput of a line can be affected and ultimately production on the line may have to be stopped. As such, the production plan must ensure that the downtime of the line does not lead to a mismatch of supply and demand.
The integration of capacity planning and production planning involves the consideration of various features within each problem and related to their integration. These features can be described through mathematical models, and various formulations based on mathematical programming have been presented in the research literature. However, few of these formulations consider the complex systems described and the relationships between capacity expansions, product capacities and the impacts of retrofit projects on the line operation. It is therefore clear that the development of new mathematical formulations is needed.
The variety of model formulations in literature additionally points to the need for a method that states how a general problem in capacity and production planning should be tackled. These problems start with challenges in a specific system that must be solved through the generation of plans and recommendations for decision-making support. One or several models can be used for the solution of each problem, which requires that the method considers model development as well as model solution.
The main contribution of this thesis is the development of a systematic framework that integrates general representations, models, methods, and tools for the solution of capacity and production planning problems. The developed framework is generic and can thus be used to solve a wide range of problems in various system types. The framework has been applied to several case studies inspired by or coming from industrial primary pharmaceutical manufacturing. As a result, several novel deterministic and stochastic MILP models have been developed. The solution of the case studies through the developed models has demonstrated the ability of the framework to provide data-driven decision-making support for systems of industrial size and complexity.
Original language | English |
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Place of Publication | Kgs. Lyngby |
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Publisher | Technical University of Denmark |
Number of pages | 229 |
Publication status | Published - 2023 |
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SUPPLY - sustainable Upstream Production Planning for Lot-sizing and Yield Evaluation
Lindahl, S. B. (PhD Student), Sin, G. (Main Supervisor), Gernaey, K. V. (Supervisor), Babi, D. K. (Supervisor), Langfrits, M. T. (Supervisor), Pinson, P. (Examiner) & Barbosa-Póvoa, A. (Examiner)
01/01/2021 → 07/05/2024
Project: PhD