Case Study: Contamination of a Bulk Manufacturing Facility

Goal: to determine the best response to a plant contamination in a network of production facilities.

High level summary

• Analysis of a network of production facilities when facing a contamination event in a single plant.
• Model demonstrated the impacts of contamination on inventory levels of life saving drugs
• Showed best responses for different contamination scenarios to prevent product stock-outs using other plants in the network
• Analysis guided a large biopharmaceutical manufacturer in strategic decision making for possible contamination risks.

The Brief

The lifesaving nature of the drugs requires careful inventory management. Given the considerable changeover times between drugs in a plant, long- range planning is necessary to prevent a stock-out of drugs. Campaigns running from a few months to half a year are slotted back to back to make the most use of a plant's capacity.

A major threat to any long-range planning schedule is a lengthy facility shut-down due to equipment contamination. To mitigate the impacts on production during a contamination event, excess capacity in a network of production plants can be utilized. Bioproduction Group was asked to create a simulation model of a production plant network and determine the best response to a facility shut-down in order to avoid stocking out of critical drugs.

How We Did It

Bioproduction Group's approach was to develop a detailed facility-network simulation model. Working closely with plant managers and engineers, the model was designed to accurately depict the production process of every facility in the network.

Through discussions with subject matter experts and key members of the scheduling department, Bio-G determined several possible reactions to a facility contamination to prevent product shortages. "When our client says 'no patient shall go without treatment,' it is not corporate rhetoric: they mean it," says Principal David Zhang. "There is an intelligent way to utilize available network resources to keep production flowing while avoiding unnecessary disruption to the supply chain."

Bio-G's strategic model was used to evaluate a number of possible contamination scenarios, depending on the severity of the contamination event. Low severity (2 month recovery time), medium severity (4 month recovery) and high severity (6 month recovery) were each considered, to determine the range of effects on the supply chain network. The diagram above shows the range of possible responses to the adverse events, depending on its severity. Backup facilities were used in more severe contamination cases to ensure stockout would not occur. The Simulation System aided planners in quickly evaluating the best response in each case.

Results

Bio-G's strategic model provided a decision support tool that allowed the quantification and mitigation of risk for strategic decision-making. The results showed that stock outs would occur with some of the response strategies considered by the manufacturer. More importantly, this tool was then used by the client to determine the best responses amongst all possible scenarios. This approach significantly lowered the time to make a decision, increasing confidence the manufacturer had sufficient agility to respond to adverse events.