Supply Chain Design for Vaccine Manufacturer
GlaxoSmithKline (GSK) was the world’s sixth largest pharmaceutical company in 2014. The company was launching a new vaccine product on a new market that needed a distribution network different from what they had before. Therefore, the company needed to design a new supply chain and align manufacturing processes with it.
The supply chain of a vaccine is a complex system because it is geographically extended globally, and it uses a large amount of resources, including manufacturing plants and warehouses.
Production and distribution start with the preparation of “bulk”, where many different components are used. This stage is then followed by the “filling” step, where many containers, such as syringes and vials, have to be managed. Then the product goes to final packaging (with specific requirements for all different regions, in compliance with local laws). In addition, in the GSK case, the vaccine could only be produced and released for distribution in batches, which made further supply chain planning even more difficult.
A specific issue for the company was how to handle large amounts of components with specific expiration dates, while complying with quality control procedures (both internal and external at “single dose level”), and commercial rules. In addition, GSK implemented various inventory management policies using corporate transactional systems, including SAP. Above all, their supply chain faced a large amount of specific settings and balancing problems.
All of these special traits were the reason that GSK choose dynamic simulation as a decision-support tool for the vaccine supply chain design. Fair Dynamics Consulting developed the supply chain’s simulation model for the company using AnyLogic.
The model designed by Fair Dynamics simulated GSK’s supply chain, including the manufacturing and the distribution parts of it.
Process Logiс in the Model
The manufacturing part was based on the discrete-event modeling method and it simulated business processes involved in the vaccine production. These included three levels of processes that could be intervened by each other:
- Manufacturing processes
- Quality control processes (product testing)
- Quality assurance processes (production process control)
The model had to take into account the different policies the company implemented and production constraints. For example, the model included shifts of human operators at the plant, their operation times depending on experience, as well as different sourcing policies that affected the production schedule.
The manufacturing part of the model was integrated with the distribution part that simulated the US market supply chain, orders to the manufacturing part, and received goods from it.
The supply chain in the model reflected the real-world supply chain design, and included warehouses replenished from the main European distribution center, wholesalers (product distributors), and hundreds of clients, all with defined geographical locations. Clients ordered goods from wholesalers, but were supplied directly from GSK’s warehouses, due to the sensitive nature of the product and to avoid delays caused by intermediaries’ participation.
One of the important metrics taken into account was maintaining high service levels, because the product’s selling proposition was guaranteed 24 hour delivery.
The model was able to simulate both the steady state of the supply chain, and situations with disruptions and emergencies, to see how “what-if” scenarios would affect supply chain performance.
The model allowed GlaxoSmithKline to determine the optimal vaccine supply chain design from the standpoint of costs and service level.
The model also served as a part of an operational decision-support tool for the supply chain planners. The tool allowed them to determine optimal production/distribution policies for the next week/month.
The uniqueness of this project was the combination of manufacturing and distribution processes in one simulation model, which was possible due to the multimethod modeling techniques available in AnyLogic. This approach gave GSK the ability to achieve more accuracy in simulation, thus allowing for more precise forecasting and more profitable decision making.
More Case Studies
Selecting the Best Inventory Policy Using GojiiExisting supply chain and S&OP tool sets do a great job of managing supply to meet a selected "forecast." However, there is no single "correct forecast" of future demand, and existing tools are not designed to select the best demand level for the business. There is a "tool gap" between forecast inputs and selection of the best demand signal (aka "forecast") to drive your S&OP system. Gojii is the tool created by DecisioTech that fills that gap.
Maximizing Push Boat Fleet’s Net Voyage RevenueInterBarge, a first-class waterway operator, affiliated with SCF Marine, a part of Seacor Holding Group, operates freight along the HPP Waterway (Hidrovia Parana Paraguay, located in Argentina, Paraguay, Brazil, and Uruguay) on a dedicated contract carriage. The company’s challenge was to use the boat capacity free from dedicated contract commitment as a fleet, maximizing net voyage revenue.
Customer-Centric Transportation Network ModellingThe public transportation company employed PwC Australia to develop a solution that could provide a customer-centric view of their railway infrastructure and help the company understand the current incident effects on rail network operations and how to improve the situation. PwC consultants decided to build a model of the transportation network that would simulate train movements, incidents, and customers at stations and in trains.
CSX Solves Railroad Operation Challenges with and without AnyLogic Rail LibraryCSX is a US railroad company that operates about 21,000 route miles (34,000 km). AnyLogic allows the railroad industry users to simulate line-of-road, terminal, and yard problems. The following three projects, completed by CSX in 2014, covered a variety of tasks that were solved using AnyLogic software.
Preventing “Bus Bunching” with Smart Phone Application ImplementationIn public transport, bus bunching refers to a group of two or more transit vehicles (such as buses or trains), which were scheduled to be evenly spaced running along the same route, instead running in the same location at the same time. Dave Sprogis, Volunteer Software Developer, and Data Analyst in Watertown, MA, used AnyLogic to confirm his thesis that preventing "Bus Bunching" would improve the experience of public transit bus riders.
Emergency Evacuation Planning: Minimizing Gridlock and Improving Public SafetyA typical rush hour impedes the mobility of individual vehicles and significantly slows the overall flow of traffic. This phenomenon is compounded by events of mass mobilization, such as during an evacuation due to a hurricane or other event. When this occurs, traffic can reach a state of gridlock. ITS researchers sought to understand how public safety could be improved during such events by incorporating communication among a percentage of the vehicle population.
Apparel Company Chose Location for New Distribution Center Using Simulation ModelingFruit of the Loom (FOTL) is one of the largest US apparel manufacturers and marketers. The company was expanding, and the executives wanted to know if it would be beneficial, in terms of shipping costs, to add a new distribution center (DC) on the east/west coasts of the US, or to redistribute products to a pre-existing DC. The contractors decided to simulate the whole supply chain in order to visualize DC locations on a GIS map, and the supply network between them.
Improving Mining Outbound Logistics with Agent-Based Simulation ModelingOne of the largest resource companies in the world, with over $80 billion in sales, decided to enter a new market. It was planning to build a new potash mine with 90% of the resources exported. They wanted to design a reliable supply chain, with a high speed of supply replenishing, and the ability to recover from natural disasters and man-made crises benefiting from such volatility. Amalgama and Goldratt companies contracted this project to design the potash mining operations and a full supply chain of outbound logistics.
Simulation of the Construction of a Tunnel with a Tunnel Boring MachineThe cost of one hour of down time of a tunnel boring machine is usually high and project managers have to do their best to avoid unnecessary delays in construction. The aim of the simulation project, which was carried out at Ruhr University Bochum in Germany, was to create a simulation model that would be capable of determining the bottlenecks in tunnel building processes in order to minimize the possible monetary losses.