Getting Results with Simulation in the Life Sciences Industries
The Life Sciences industry is quick to recognize and use key technologies that can reduce new plant capital project schedules or reduce variation and risk in the operation of the process. The industry has recognized the business benefits of simulation systems for automation system testing and is one of our greatest markets for our Mimic Simulation Software. The business benefits of using simulation as part of the validated system project execution are proven.
Success with Simulation at Lilly
In the September 2009 Issue of Chemical Processing, Ryan Iannucci from Eli Lilly and Company, shows how the use of Mimic Simulation Software can be an integral piece of automation projects in the Life Sciences industry. The article, Novel Approach Enhances Control System Upgrade, describes the use of simulation and other methods for successful control system modernization at a Lilly API plant in Indianapolis. The article is a great read but there are a couple points in particular of interest. Ryan described how the simulator (I verified with Ryan that they did use Mimic) was used to:
- Allow the plant automation engineer to “…assess the software using the simulator and suggest some changes”. Mimic Simulation is an effective tool for reviewing and testing control strategies.
- Then, “…the process team examined the software via the simulator”. Mimic allows the user to accept and review the control system configuration in a safe off-line environment.
- And “...the software was formally tested with the process simulator. This served to minimize any surprises during commissioning and qualification”. Mimic is a proven, effective tool to reduce the time and expenses required for control system application software validation.
Figure 1 of the article shows a rough project timeline that was followed, allowing the plant to separate the software development from the hardware development. This is the optimal approach for modern process automation projects and is almost impossible to achieve without the use of dynamic process simulation software for control system testing.
Ryan described the operator training that was done before startup where each operator “…attended roughly 40 hours of training courses that used a process simulator”. Training exercises included running simulated “…production batches using manufacturing tickets and SOP. These simulations included non-routine events, to give operators experience in this type of event handling”.
Finally, Ryan notes that “…the familiarity the process team and operations personnel has developed with the software led to an relatively uneventful qualification”. The use of Mimic simulation on greenfield projects or control system modernization reduces the risk of the entire automation project.
The article is a great summary of the value of using simulation for Life Science projects. The problems faced in the Life Sciences industry are common across users, in API and Biotech plants.
The Problem is Schedule
Time to market requirements, in the Life Sciences industry, is as significant as any other process industry. By the time a drug is ready for manufacturing and release, two thirds of the patent protection life has expired. In addition, the capitalized development cost to get the drug to that state can reach in the billions of dollars. Technology that can reduce the overall process automation project schedule can easily pay for itself by moving startup in by days. One of the greatest risks, to project schedule and the reliability of the automation system, is hidden defects in the application software or system configuration.
Common defects in automation system application software that can impact project schedule include:
- Incorrect IO or bus register addressing in control modules.
- Incorrect scaling or engineering units
- Timing issues in sequence or batch control modules
- Incorrect alarm handling
- HMI screen elements incomplete or linked to the wrong control modules
- Data addressing or timing problems between automation systems and subsystems.
The Cost of Application Software Errors
The opportunity cost in startup delays due to defects like the ones listed above is significant. The decade rule of cost of software defects states that the cost of software defects increases by a factor of 10 at each subsequent stage of a project. In other words, defects uncovered in system testing that cost $1000 to identify and correct will cost $10,000 to identify and correct during system commissioning or startup. Because of the fixed capital costs and procedural requirements of the validated industry, this decade rule may be a gross understatement of the actual cost of addressing software defects on site.
In addition, studies have shown that between 15% and 30% of the quality deviations found during Functional Testing (FT), Installation Qualification (IQ), and Operation Qualification (OQ) are due to application software errors. In comparison process and mechanical issues have historically accounted for 5% to 15% of the deviations. The use of simulation systems to identify deviations and test application software can result in a significant reduction in errors during startup and commissioning of the automation system. The identification and remediation of errors can be moved back to the design or testing phase of the project by using simulation. This reduction can reduce time to market and reduce project and process risk.
The business case for the use of simulation in the validated industries is proven. These same project execution practices can have great business results when applied across all process industry automation projects.
Other Resources to Review
We look forward to your comments, questions, or suggestions.
Hope to hear from you soon.
Mart Berutti, 10/13/09