Capacity and Inventory Optimization for Pharmaceutical Industry 
                            by 
                         Huong Thi Dang 
             Bachelor of Business Administration, National University of Singapore, 2013 
                            and 
                        Brett Anthony Elgersma 
                   Bachelor of Science, Iowa State University, 2016 
                              
               SUBMITTED TO THE PROGRAM IN SUPPLY CHAIN MANAGEMENT 
              IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF 
                MASTER OF APPLIED SCIENCE IN SUPPLY CHAIN MANAGEMENT 
                           AT THE 
                   MASSACHUSETTS INSTITUTE OF TECHNOLOGY 
                              
                          May 2020 
              © 2020 Huong Thi Dang & Brett Anthony Elgersma. All rights reserved. 
       The authors hereby grant to MIT permission to reproduce and to distribute publicly paper and electronic 
        copies of this capstone document in whole or in part in any medium now known or hereafter created. 
                                                   
       Signature of Author: ____________________________________________________________________ 
                                 Department of Supply Chain Management  
                                             May 1, 2020 
                                                   
       Signature of Author: ____________________________________________________________________ 
                                 Department of Supply Chain Management  
                                             May 1, 2020 
        Certified by: __________________________________________________________________________ 
                                           Dr. Nima Kazemi 
                        Postdoctoral Associate, Center for Transportation and Logistics 
                                           Capstone Advisor 
       Accepted by: __________________________________________________________________________  
                                           Prof. Yossi Sheffi 
                              Director, Center for Transportation and Logistics 
                               Elisha Gray II Professor of Engineering Systems 
                               Professor, Civil and Environmental Engineering 
                              
                              
                              
                              
                           Capacity and Inventory Optimization for Pharmaceutical Industry 
                                                                 by 
                                                           Huong Thi Dang 
                                                                 and 
                                                       Brett Anthony Elgersma 
                                        Submitted to the Program in Supply Chain Management 
                                              on May 1, 2020 in Partial Fulfillment of the 
                        Requirements for the Degree of Master of Applied Science in Supply Chain Management 
                                                                    
                ABSTRACT 
                The  pharmaceutical  industry  is  subject  to  many  unique  constraints,  due  in  part  to  both  product 
                characteristics and regulatory guidelines. Nevertheless, pharmaceutical companies are expected to be 
                able to serve customers that rely on their products, even as demand can be unpredictable and erratic. 
                Pharmaceutical companies have choices in how they deal with demand uncertainty, but two schools of 
                thought dominate: hold additional inventory or employ additional capacity. Finding the right balance 
                between additional inventory and excess capacity proves difficult given product shelf-life constraints and 
                long production ramp-up lead times. This study develops a mixed-integer linear program that optimizes 
                inventory policy and production capacity policy under stochastic demand scenarios at a single node of the 
                supply chain by minimizing inventory costs, production costs, and anticipated write-off costs. Scenarios of 
                demand uncertainty with different probabilities are simulated to provide insights into key drivers of the 
                model  behavior  and  guide  insights  into  useful  inventory  policies.  Findings  demonstrate  that  in  an 
                environment characterized by long production ramp-up lead times and products constrained by shelf life, 
                neither  additional  inventory  or  excess  production  capacity  alone  is  sufficient  for  hedging  demand 
                uncertainty. Therefore, pharmaceutical companies should consider employing the two strategies together 
                to meet market demand with the optimal cost.                                                  
                                                                                                              
                                                                                                              
                                                                                                              
                                                                                                              
                                                                                                              
                                                                                                              
                                                                                                              
                                                                                                              
                                                                                                              
                                                                                                              
                                                                                                              
                                                                                       
                Capstone Advisor: Dr. Nima Kazemi 
                Title: Postdoctoral Associate, Center for Transportation and Logistics 
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                        ACKNOWLEDGMENTS 
       We would like to thank Dr. Nima Kazemi for guiding us through this process, challenging us to think 
       differently, and pushing us to be the best versions of ourselves. Without his feedback and tutelage, we 
       would still be trying to figure out where to begin. A special thank you is also due to Mr. Nicholas Wigdahl 
       and the rest of the Supply Chain team at F. Hoffman-LaRoche Ltd. We appreciate your guidance through 
       the intricate workings of pharmaceutical supply chains. Finally, we would like to thank our families, 
       friends, and classmates for their patience, understanding, and support throughout this research process. 
        
        
        
        
        
        
        
        
        
        
        
        
        
        
        
        
        
        
        
        
        
        
        
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                                                                  TABLE OF CONTENTS 
                    
                       LIST OF FIGURES                                                                                         5 
                       LIST OF TABLES                                                                                          5 
                   1.  INTRODUCTION                                                                                            6 
                       1.1. Motivation                                                                                         6 
                       1.2. Problem Statement                                                                                  6 
                   2.  LITERATURE REVIEW                                                                                       8 
                       2.1. Inventory Holding Costs                                                                            8 
                       2.2. Production Planning                                                                                9 
                       2.3. Capacity Expansion                                                                                 9 
                   3.  METHODOLOGY                                                                                             12 
                       3.1. Interview and Data Collection                                                                      13 
                       3.2. Scope and Limitations                                                                              16 
                       3.3. Assumptions                                                                                        16 
                       3.4. Mathematical Formulation                                                                           17 
                            3.4.1.  Notations                                                                                  17 
                            3.4.2.  Objective Function                                                                         19 
                            3.4.3.  Constraints                                                                                21 
                   4.  RESULTS, ANALYSIS, AND DISCUSSION                                                                       22 
                       4.1. Simulation Description                                                                             22 
                       4.2. Simulation Parameters                                                                              23 
                       4.3. Simulation Results                                                                                 23 
                       4.4. Model Parameter Sensitivity                                                                        24 
                            4.4.1.   Production Line Dedication                                                                25 
                            4.4.2.   Forecast Error                                                                            26 
                            4.4.3.   Customer Service Target Level                                                             27 
                       4.5. Insights and Management Recommendations                                                            28 
                   5.  CONCLUSION                                                                                              29 
                       REFERENCES                                                                                              30 
                       APPENDIX A                                                                                              31 
                       APPENDIX B                                                                                              33 
                        
                    
                    
                    
                    
                    
                    
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