1. SCHEDULING IN THE PHARMACEUTICAL INDUSTRY IEOR 4405 – Production Scheduling Kristinn Magnusson Sigrun Gunnhildardottir

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 Level 1 Based on demand forecasts Product groups are placed on each machine at each time Updated at least every 3 months. Horizon: 1 year Level 2 Plan is adjusted to the orders that have been received Updated every week. Horizon: 3 months Level 3 Detailed schedule of prodcution tasks Based on confirmed customer orders Updated every day. Horizon: 1 month

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)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 ?