Production planning of biopharmaceutical manufacture.

Multiproduct manufacturing facilities running on a campaign basis are increasingly becoming the norm for biopharmaceuticals, owing to high risks of clinical failure, regulatory pressures and the increasing number of therapeutics in clinical evaluation. The need for such flexible plants and cost-effective manufacture pose significant challenges for planning and scheduling, which are compounded by long production lead times, intermediate product stability issues and the high cost - low volume nature of biopharmaceutical manufacture. Scheduling and planning decisions are often made in the presence of variable product titres, campaign durations, contamination rates and product demands. Hence this thesis applies mathematical programming techniques to the planning of biopharmaceutical manufacture in order to identify more optimal production plans under different manufacturing scenarios. A deterministic mixed integer linear programming (MILP) medium term planning model which explicitly accounts for upstream and downstream processing is presented. A multiscenario MILP model for the medium term planning of biopharmaceutical manufacture under uncertainty is presented and solved using an iterative solution procedure. An alternative stochastic formulation for the medium term planning of biomanufacture under uncertainty based on the principles of chance constrained programming is also presented. To help manage the risks of long term capacity planning in the biopharmaceutical industry, a goal programming extension is presented which accounts for multiple objectives including cost, risk and customer service level satisfaction. The model is applied to long term capacity analysis of a mix of contractors and owned biopharmaceutical manufacturing facilities. In the final sections of this thesis an example of a commercial application of this work is presented, followed by a discussion on related validation issues in the biopharmaceutical industry. The work in this thesis highlighted the benefits of applying mathematical programming techniques for production planning of biopharmaceutical manufacturing facilities, so as to enhance the biopharmaceutical industry's strategic and operational decision-making towards achieving more cost-effective manufacture

Estudio y diseño de una planta multiproducto de bebidas vegetales

Treballs Finals de Màster d'Enginyeria Química, Facultat de Química, Universitat de Barcelona. Curs: 2021-2022. Tutores: Alicia Maestro Garriga, Esther Chamarro AguileraThe current project is focused on the development of several plant-based beverages in a multiproduct plant. The high percentage of lactose intolerant people, the great contribution of livestock to global warming and the increasing cow’s milk allergies makes it crucial to find an alternative to the classical cow milk. Furthermore, people are becoming more aware about their fitness and lifestyle and these types of beverages are perceived as healthier as bovine milk, gaining importance in the market. Other reasons to bet for these types of products are their sustainability and their impact on the environment. As bovine milk needs a lot of water and huge areas of land for its production, plant-based milks don’t require such amounts of water and land. In addition, CO2 emissions are another problem of cow’s milk and another reason why people decided to change to vegetable beverages. This work is based on the development of formulated products, including all steps of this procedure: market study, product conceptualization, quality criteria, product formulation, design the manufacturing process and a scheduling to plan the production. Three different types of plant-based milks have been selected to produce due to their popularity and consumption here in Catalonia. These beverages are soya milk, almond milk and oat milk. There is a general production process for all types of milk but obviously modifications have been made depending on the raw material used and the aims of the present thesis. Two main quality criteria have been stablished to make this product especially appealing, which are their nutritional value and the flavor. When it comes to flavor, lipoxygenase and its oxidation reaction plays an important role when designing the production process and specially the equipment. In the present work one of the aims is to avoid the activation of this enzyme to improve the final flavor of the milk. On the other hand, to launch an alternative to cow’s milk, the substitute must have similar qualities in terms of nutritional value. Depending on the raw material, amounts of these nutrients differ from each other but in all of them there is a specific way to make the addition of nutrients in order to enrich the beverages. Finally, to plan the production and operate properly it has been made a scheduling. Firstly, a batch size of 6000kg is stablished according to the total production wanted per year, the way milks are delivered and considering a production unit of six carboards of one liter of milk each. Afterwards, time required for each stage is estimated to plan the number of batches carried out every month. In this amount of time, it is included not only the main operation but also other operations such as the charging of the product or the cleaning. Taking into consideration the time and the total production to be carried out, it is estimated how to operate in the plan

Optimal batch scheduling of a multiproduct dairy process using a combined optimization/constraint programming approach

This paper presents the optimal batch scheduling of a multi-product dairy process using an approach that combines optimization and constraint programming techniques. A suitable model describing the subprocesses and production rules is developed allowing to obtain scheduling constraints relating the production process and the machines available together with their relative efficiencies. After the scheduling problem has been formulated, the batch scheduling of a real powder milk/yogurt process is obtained in an optimal manner using the proposed approach with the objective of meeting customers’ deadlines considering the efficiencies/costs of available alternative machines. Results using real consumer orders on some representative scenarios corresponding to the dairy production plant used as a case study are provided. This application shows a formulation closer to the engineering problem description thanks to the constraint-based language that facilitates the adaptation of the optimization objectives and constraints to real applications.Peer ReviewedPostprint (author's final draft

Scheduling Multiproduct Chemical Batch Processes using Matrix Representation

Batch process plants are usually designed for the production of specialty and fine chemicals such as paint, food and pharmaceutical to meet specific product requirements as set by current market demand. Batch process plants can be operated as single product in which only one product is produced and multiple products which allow production of more than one product using same batch facility. The economics of the batch process heavily depends on efficient scheduling of the different tasks involved in manufacturing the range of products. The main objective of scheduling is generally to minimize completion time known as the makespan of the batch process. Product sequencing, which is used to set order of products to be produced, has a direct impact on the makespan particularly in the multiple products case. Another effect on makespan is observed for different transfer policies used to transfer the product intermediates between process stages. The generally adopted intermediate transfer policies are (i) zero wait (ZW), (ii) no intermediate storage (NIS), (iii) unlimited intermediate storage (UIS) and (iv) finite intermediate storage (FIS). In the past, the determination of makespan for each transfer policy has been done using a number of mathematical and heuristics approaches. Although these approaches are very efficient and are currently being applied in many chemical process industries but most of them end up with the solution in terms of complex mathematical models that usually lack user interactions for having insights of the scheduling procedure. This motivated the current work to develop relatively simple and interactive alternate approaches to determine makespan. The proposed approach uses matrix to represent the batch process recipe. The matrix is then solved to determine the makespan of a selected production sequence. Rearrangement of the matrix rows according to the varied production sequences possible for the specified batch process recipes enables the makespan to be determined for each sequence. Designer is then provided with the production sequence options with its corresponding makespan from which a selection could be made according to the process requirements

Modeling Industrial Lot Sizing Problems: A Review

In this paper we give an overview of recent developments in the field of modeling single-level dynamic lot sizing problems. The focus of this paper is on the modeling various industrial extensions and not on the solution approaches. The timeliness of such a review stems from the growing industry need to solve more realistic and comprehensive production planning problems. First, several different basic lot sizing problems are defined. Many extensions of these problems have been proposed and the research basically expands in two opposite directions. The first line of research focuses on modeling the operational aspects in more detail. The discussion is organized around five aspects: the set ups, the characteristics of the production process, the inventory, demand side and rolling horizon. The second direction is towards more tactical and strategic models in which the lot sizing problem is a core substructure, such as integrated production-distribution planning or supplier selection. Recent advances in both directions are discussed. Finally, we give some concluding remarks and point out interesting areas for future research

Scheduling of single-stage noncontinous processes

Master'sMASTER OF ENGINEERIN

Planning and scheduling in pharmaceutical supply chains

Ph.DDOCTOR OF PHILOSOPH