Scheduling in the Pharmaceutical Industry

1. Scheduling in the Pharmaceutical Industry Kristinn Magnusson Sigrun Gunnhildardottir IEOR 4405 – Production Scheduling

2. Pharmaceutical Industry • Most important driver: time-to-market • Highly Competitive • Very regulated industry • High amount of cleaning and set up time needed between jobs • Life and death: no room for mistakes

3. Real Life Case • High but uncertain demand • Supplier’s have long lead times • 40 different product families • 1000 different product variations (SKU’s)

4. Production Process

5. Goals and Objectives • Determine a campaign plan and schedule customer orders within the campaigns • Provide realistic and accurate models that are solvable within acceptable computational time • General objective of the plans and schedules: • meet the quantity and delivery date of customer orders • minimize the unproductive production time  maximize economic performance of the company

6. Three Level Hierarchical Framework

7. Level 1: Campaign Planning • Optimize campaign plan • Fulfill predicted demand • Minimize production time • Helpful for purchasing raw material • The model is updated every 3 months

8. Level 1: Model • Objective: Minimize Subject to: • Allocation • Sequencing • Delivery • Capacity • Campaign • Mutually Exclusivity

9. Level 2: Campaign Planning and Order Allocation • Actual orders are known • Revise campaign plan • Allocate orders to campaigns • Specify in which campaign each order are produced on every production stage • It gives the latest allowed completion time for the order

10. Level 3: Detailed Schedule • Actual timing of activities • Objective to minimize late deliveries • The model gives: • Machine/Campaign for each order for every production stage • Production sequence of orders • Start and processing time of tasks • Setup time required between orders

11. Heuristic: Decomposition of Production Stages

12. Improving Lower Bounds... • ... by adding valid inequalities • A constraint for the minimum number of campaignes needed for a feasible solution • A constraint for the minimum number of delayed jobs

13. Solution Times • These models have been tested with real data and have been shown to be solvable within acceptable computational time • 1. level: 14 hours • 2. level: 6 hours • 3. level: 6 minutes

14. References • P. Jensson, N. Shah and H. Stefansson, “Multiscale Planning and Scheduling in the Secondary Pharmaceutical Industry”, Published online October 26, 2006 in Wiley InterScience (www.interscience.wiley.com) • N. Shah, “Pharmaceutical supply chains: key issues and strategies for optimisation”, Computers and Chemical Engineering 28 (2004) 929–941

15. Any Questions ?