Problem Context:
In this article from Interfaces on Capacity planning they discuss the challenges of estimating capacity of production for AstraZeneca Pharmaceuticals and discuss. The model was designed by professors at University of Delaware. They use Microsoft Excel-based optimization tool (VBA add-in OpenSolver) to solve the linearized formulation of the problem. The toll which they developed plans capacity for tablet production over a wide span of time ranging from several months to years.
The key questions that the AstraZeneca Pharmaceuticals would be able to answer after the capacity planning tool were as follows:
1. Is the sufficient capacity available to meet forecasted demand over time?
2. Are they having minimal production time?
3. Are …show more content…
Decision Variables(From Article):
Xijk –Number of production cycles of k consecutive batches of product i using route j.
Gijk –Granulation time for k consecutive batches of product I using route j.
Sijk –Press setup time for k consecutive batches of product I using route j. This time always include major setup
Rijk –Press processing time for k consecutive batches of product I using route j.
Tijk –Number of tablets produced by k batches of product I when using route j.
Objective Function:
Objective function is to determine the production Xijk of k consecutive batches which uses route j to satisfy demand for product I, in order to minimize the total production time.
Constraints:
The constraints formulated in the problem ensure that the product demand is satisfied along with that it also keeps check that production resource capacity is not exceeded. The major three constraints used are as follows:-
• Demand constraint- di – Demand for product …show more content…
However the number of major setups required is fixed i.e. after a specific number of consecutive batches and the time also varies for different products. This further complicated the matters.
They had to calculate the production time in sequence dependent setups which made the calculations more complex and complicated. The numerous possible production-route, product- variants and various combinations, combined with limited capacity of production resources, makes the production planning quite labyrinth. The problem constraints ensures that each product’s demand is satisfied and resource capacity is not exceeded.
The AstraZeneca Formulation group, could easily compute the production capacity after implementing this model. The obscure scenarios for production became transparent and factual. The capacity planning time also decreased drastically from hours to minutes. Forecasting the capacity of the production helps in numerous ways. Various other parameters and constraints in production became transparent and hence eliminating errors and hence easy to maintain. This model also assists management in making major decisions relative to capacity planning in the plant and hence elevating the potential for improving the facility.
Lessons
In this article from Interfaces on Capacity planning they discuss the challenges of estimating capacity of production for AstraZeneca Pharmaceuticals and discuss. The model was designed by professors at University of Delaware. They use Microsoft Excel-based optimization tool (VBA add-in OpenSolver) to solve the linearized formulation of the problem. The toll which they developed plans capacity for tablet production over a wide span of time ranging from several months to years.
The key questions that the AstraZeneca Pharmaceuticals would be able to answer after the capacity planning tool were as follows:
1. Is the sufficient capacity available to meet forecasted demand over time?
2. Are they having minimal production time?
3. Are …show more content…
Decision Variables(From Article):
Xijk –Number of production cycles of k consecutive batches of product i using route j.
Gijk –Granulation time for k consecutive batches of product I using route j.
Sijk –Press setup time for k consecutive batches of product I using route j. This time always include major setup
Rijk –Press processing time for k consecutive batches of product I using route j.
Tijk –Number of tablets produced by k batches of product I when using route j.
Objective Function:
Objective function is to determine the production Xijk of k consecutive batches which uses route j to satisfy demand for product I, in order to minimize the total production time.
Constraints:
The constraints formulated in the problem ensure that the product demand is satisfied along with that it also keeps check that production resource capacity is not exceeded. The major three constraints used are as follows:-
• Demand constraint- di – Demand for product …show more content…
However the number of major setups required is fixed i.e. after a specific number of consecutive batches and the time also varies for different products. This further complicated the matters.
They had to calculate the production time in sequence dependent setups which made the calculations more complex and complicated. The numerous possible production-route, product- variants and various combinations, combined with limited capacity of production resources, makes the production planning quite labyrinth. The problem constraints ensures that each product’s demand is satisfied and resource capacity is not exceeded.
The AstraZeneca Formulation group, could easily compute the production capacity after implementing this model. The obscure scenarios for production became transparent and factual. The capacity planning time also decreased drastically from hours to minutes. Forecasting the capacity of the production helps in numerous ways. Various other parameters and constraints in production became transparent and hence eliminating errors and hence easy to maintain. This model also assists management in making major decisions relative to capacity planning in the plant and hence elevating the potential for improving the facility.
Lessons