SCHEDULING IN THE
PHARMACEUTICAL INDUSTRY
Kristinn Magnusson
Sigrun Gunnhildardottir
IEOR 4405 – Production Scheduling
Pharmaceutical Industry
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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
Real Life Case
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High but uncertain demand
Supplier’s have long lead times
40 different product families
1000 different product variations (SKU’s)
Production Process
Goals and Objectives
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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
Three Level Hierarchical
Framework
Level 1
Level 2
Level 3
• Based on demand forecasts
• Product groups are placed on each machine at each time
• Updated at least every 3 months. Horizon: 1 year
• Plan is adjusted to the orders that have been received
• Updated every week. Horizon: 3 months
• Detailed schedule of prodcution tasks
• Based on confirmed customer orders
• Updated every day. Horizon: 1 month
Level 1: Campaign Planning
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Optimize campaign plan
Fulfill predicted demand
Minimize production time
Helpful for purchasing raw
material
The model is updated
every 3 months
Level 1: Model
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Objective: Minimize
Subject to:
 Allocation
 Sequencing
 Delivery
 Capacity
 Campaign
 Mutually Exclusivity
Level 2: Campaign Planning and
Order Allocation
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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
Level 3: Detailed Schedule
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Actual timing of activities
Objective to minimize late
deliveries
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The model gives:
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Machine/Campaign for each order
for every production stage
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Production sequence of orders
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Start and processing time of tasks
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Setup time required between
orders
Heuristic: Decomposition of Production
Stages
Improving Lower Bounds...
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... 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
Solution Times
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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
References
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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
Any Questions ?