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Departments: Quality Applications

Simulation Modeling Helps Bring Pain Reliever to Market


Data Analysis Software Integrates with Shop-Floor CMM



Simulation Modeling Helps Bring Pain Reliever to Market

Pharmacia’s Searle plant in Caguas, Puerto Rico, produces more than 20 brands of pharmaceuticals. Faced with the responsibility of undertaking a launch of the new prescription drug Celebrex, Searle Caguas had the daunting task of producing launch requirements in three months, plus packaging and shipping the capsules in a timely manner. Searle assembled an ad hoc task force—the Celebrex Readiness Team—to manage the introduction and commercial production of the new product.

The team searched for a simulation- modeling solution that was affordable, user-friendly and had animation capabilities. The company had never used simulation technology before; buying a tool that does what had previously been done in Excel spreadsheets would be difficult to justify if the tool were expensive. It also had to be easy to understand and use because of the short amount of time available to complete the project. Additionally, it had to be powerful enough to handle different process details without losing model credibility and validity. The animation feature was necessary in order to depict the process operation for the team members to verify model logic in operation.

Searle Caguas turned to ProcessModel for all these reasons. “There are a few tools within this niche for simulation modeling at a macro process level.” Says Santos Sanabria, system improvement engineer for the Searle Caguas plant. “However, the best-in-class is ProcessModel.” Sanabria presented ProcessModel to the Celebrex Readiness Team.

ProcessModel Inc. is a Utah-based company and inventor of the ProcessModel tool that creates a computerized version of a business process using a flowchart interface. ProcessModel provides a detailed statistical report, which allows the user to compare existing processes with proposed fixes. The model then uses data to determine how the process will perform under various scenarios. It allows the user to examine the effect of two important factors present in most businesses: randomness (or fluctuation) and interdependence (dependent events). Searle’s manufacturing process for the drug launch needed to be evaluated using these factors.

The manufacturing process includes six basic steps: receiving raw materials; packaging components and testing samples that ensure their suitability and purity for the manufacturing process; granulation; filling the capsules; testing samples of the drug at the analytical laboratory; and bottling, packaging and shipping worldwide.

The entire manufacturing process was input to ProcessModel, and because of the short timeline, Sanabria suggested a top-down approach by developing a macro-level simulation model of the whole process using existing data. Submodels were developed adding more information as needed. This approach could facilitate handling the simulation effort by breaking the process in manageable segments and obtaining quick results at each stage of the process. The receiving operation at the warehouse was the first area to be modeled.

The existing warehouse was reasonably utilized, but with production volumes doubling, a new warehouse would need to be built. Management wanted to avoid such an expensive expansion, so inventory models were developed and tested with ProcessModel to determine their adequacy to guarantee the material supply for the new product. The inventory models assumed a kanban replenishment mode, which dramatically reduced the inventory levels at the site. Procurement practices for the existing products represented a reduction of more than $1 million in the site’s inventory-carrying costs and avoided the expansion of the warehouse.

ProcessModel was then used to determine the resources needed for a full receiving process of the different components and raw materials. Detailed receiving schedules were prepared and validated with the vendors. The warehouse simulation scene was ready to integrate the whole Celebrex process in a single simulation model.

The model included all stages, starting at the receiving warehouse and ending at the shipping warehouse, all located in Caguas. When the full production schedule was input into the model, the capsule samples taken from the encapsulated lots started to accumulate in a long queue at the laboratory, waiting for approval. Laboratory calculations had been made in Excel, and no unexpected delays were factored into the calculations. Excel assumed a fixed daily average arrival rate of samples to the laboratory. ProcessModel considered random variability in the arrival pattern and concluded that three shifts of chemists working seven days a week were needed in order to cope with the demand of the production schedule.

Based on the successful results obtained from the application of simulation modeling at Searle Caguas, the management team is supporting and requiring process simulation analyses as part of its regular decision-making process. New products being introduced at Searle Caguas are subjected to the scrutiny of simulation modeling in order to “test drive” process capabilities ahead of time and take preventive actions early on.



  • Helps analyze critical processes
  • Allows users to experiment
  • Improves actual operations