Simulation and
Optimization of
Pharmaceutical Operations
Simulation and Optimization of Pharmaceutical Operations
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Agenda
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Why simulate?
How to simulate?
Simulation in practice
Conclusions
Simulation and Optimization of Pharmaceutical Operations
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Why Simulate?
Simulation and Optimization of Pharmaceutical Operations
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Why Simulate?
Why do we need to simulate operations?
Because we need crucial figures and…
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System or changes to system do not exist yet
System is too complex for equations and spreadsheets
Field experimentation is too expensive or time consuming
Real-life testing is unsafe, dangerous or leads to disaster
And also because…
› Modern computers are fast, powerful and cheap
› There are many nice software packages out there!
Scheduling for operations is a great source of complexity!
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Why Simulate?
Production scheduling in a pharmaceutical plant can easily
become a threat to mental health…
Multiple products
Multiple packages
Changeovers
Limited footprint
Client orders
Existing equipment
Equipment availability
Best lot sizes?
Best sequencing?
Deliver on time?
Reduce costs?
Cleaning times
… and much more!
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Why Simulate?
What about integrating all system aspects into one model?
› Combination of process expertise and planning know-how
› Faster and error-free calculations
› Convenient way to manipulate schedules and validate feasibility
Oh! By the way…
This is called simulation and it can be used to:
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Select, size and validate new equipment
Identify ongoing operations bottleneck(s)
Reduce/eliminate undesired waiting times
Test alternative production sequences
… (this list is definitely not exhaustive!)
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Why Simulate?
To have a global view on complex industrial systems
Layouts, routes, dimensions,
stationary and mobile
equipment characteristics,
technical data
DESIGN
SPECIFICATIONS
HISTORICAL
SIMULATION
PROCESS DATA
MODEL
Cycle times, schedules,
resource availability, logic,
routing and operational
constraints, reliability
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Performance diagnosis
Effective and ultimate throughput
Equipment utilization rates
Meaningful and custom statistics
Trend and pie charts, histograms
OPERATIONS
KNOWLEDGE
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Why Simulate?
To provide fact-based strategic insights when in matters
ENGINEERING PROJECTS
Conceptual model
Model with basic data
Update model with existing data
Enriched model, “what if” analysis
Troubleshooting with model
Expand or modernize with existing model
De-bottlenecking and fine tuning
Continuous improvement
ONGOING OPERATIONS
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How to Simulate?
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How to Simulate?
Mankind has been creative when it comes to simulation…
Here is a short classification of relevant simulation techniques:
Deterministic
Stochastic
Static
Dynamic
Algebraical equations
Differential equations
Markov chains
(process simulation)
Monte-Carlo
Discrete events
simulation
(operations simulation)
 Dynamic: time-dependant model, decisions based on current system state
 Stochastic: model uses random values and probabilities
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How to Simulate?
Principles of discrete events simulation… in 3 words!
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System updated at countable number of times
Discrete › System states and flows constant between events
› Absence of smooth and continuous transition
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Changes in a state, flow, record, schedule, etc.
› Beginnings and endings of cycles
Events
› Arrivals and departures of resources
› Scheduled activities
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Model evolves from one event to the other
Simulation › An event can create a cascade of upcoming events
› Simulation executes the time-ordered list of events
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Process design
Operations design
FOCUS
 Thermodynamics
 Fluid mechanics
 Heat and mass transfer
 (Bio)chemical reactions
 PID / control loops
 Flow of bulk materials and parts
 Transport and kinematics
 Interactions and variability
 Tasks and resources coordination
 Reliability and maintenance
USEFULNESS
SIMULATION
SIMULATION
How to Simulate?
 Design unit operations
 Establish flows and compositions
 Calculate utilities and requirements
 Find how to ensure unit operations
 Establish overall system throughput
 Assess impact of resources availability
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How to Simulate?
Ingredients of a discrete events simulation model that are
common in the pharmaceutical industry
Components for
mass balance of
fluid/bulk process
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Tanks, pipes, valves, flow control
Conveyors, feeder bins, stockpiles
Batching cycles and filling processes
Changeover, cleaning, queuing for CIP
Components for
logistics, movement
and materials handling
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Trucks loading and unloading
AGV, forklift, and cart deliveries
Staging, palletizing and warehousing
Personnel interactions with process
Plant-wide components
Simulation and Optimization of Pharmaceutical Operations
› Weekly/daily production schedules
› Operators and task coordination
› Equipment reliability & maintenance
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How to Simulate?
Model outputs can be customized and provide decision-ready
facts that are easy to interpret
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Gantt-style effective schedules
On-time order fulfillment scorecards
Equipment utilization rates with breakdown
Filling line throughput
Evolution of work-in-progress inventories
…
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How to Simulate?
A structured, scientific and rigorous methodology is needed to
guide simulation studies:
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DATA & INFO.
COLLECTION
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› Discover assets and operations
› Obtain data and knowledge
MODEL
SPECIFICATION
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› Understand how system works
› Describe how it will be modelled
MODEL
DEVELOPMENT
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Simulation and Optimization of Pharmaceutical Operations
› Implement in simulation package
› Verify and validate model
SYSTEM
OPTIMIZATION
› Test improvements
› Increase performance
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Simulation in Practice
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Simulation in Practice
Production scheduling is crucial to ensure:
› For the Client: on-time order fulfillment
› For the company:
 Maximum use of installed equipment and personnel
 Minimization of waste
The challenge is to answer the basic questions:
› What is the required equipment capacity to fulfill orders on-time?
› What is the maximum volume that can be accommodated?
› What is the optimal production schedule?
Equipment selection and process scheduling are inter-related:
› To select equipment, one needs to know the desired production schedule
› To establish a production schedule, one needs to know what equipment to use
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Simulation in Practice
Simulation-aided iterative scheduling strategy
Obtain client’s
ordered
volumes
Analyze
and interpret
results
EXECUTE
SIMULATION
Edit lot sizes
and production
sequences
Validate
production
schedule
Update
product
characteristics
Update
equipment
specifications
Simulation and Optimization of Pharmaceutical Operations
Traditional
scheduling process
Iterative simulationaided process
yes
Optimization
opportunities
identified?
no
Production
scheduling
completed
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Simulation in Practice
Old School “Simulation” Methods:
› Excel spreadsheets used to schedule unit operations
(both manufacturing and transverse support)
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Simulation in Practice
Old School “Simulation” Methods:
› Include hourly clean and black utility estimates
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Simulation in Practice
Old School “Simulation” Results:
› Hourly utility requirements
› Overall facility utility sizing
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Simulation in Practice
Old School “Simulation” Issues:
› Excel sheets become large with many background calculations (crashing)
› Changes / scenario investigation tedious
 Copy / paste schedule
 Re-align process steps
 Introduce new sheets?
› How many CIPs was that?
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Simulation in Practice
Today’s Simulation Methods:
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Process analysis / optimization
Scenario investigation
Utility sizing
CIP allocation
Comprehensive buffer
& media strategies
› Hourly utility usage
› Multi-product
campaign scheduling
for the year
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Simulation in Practice
Today’s Simulation Results:
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Simulation in Practice
Optimal schedule for installed equipment and fixed demand
 Equipment characteristics, production volumes and deadlines are known
 Use the methodology to determine the best production sequence
 Minimize waiting and down times to reduce costs
Maximize production capacity with installed equipment
 Equipment characteristics are known
 Unknown: how much can be produced
 Increase volumes and optimize schedule iteratively until no more marginal capacity
Modify equipment for fixed demand, maintain optimality
 Future or desired production volumes are known
 Unknown: required equipment to ensure on-time fulfillment
 Add the least equipment possible and maintain schedule optimality
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Conclusions
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The Final Words
Production scheduling is a challenging endeavour
 Designing or modernizing a facility is even more challenging
 Fundamental problem: optimal scheduling and equipment selection are interdependent
Operations simulation supports this optimization task
 Representation of schedules, tasks, flowrates, storage, human interventions, etc.
 Selection, sizing and validation of equipment requirements
 Reduction of waiting and down times
Benefits of simulation for pharmaceutical processes
 Centralized, consensual and cross-discipline model
 Reduced calculation time and risk of error
 Increased decision-making power
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Questions?
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Thank you
for
your attention!
FOR MORE INFORMATION:
Vincent Béchard
Discrete Event Simulation Designer
Office: +1 514-393-8000 #57221
vincent.bechard@snclavalin.com
John Black
Senior Process Engineer
Office: +1 416-422-4056 #52154
John.Black@snclavalin.com
Richard Fecteau
VP, Business Development
Office: +1 514-393-8000 #54406
richard.fecteau@snclavalin.com
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