(233n) Fault-Tolerant Control Design and Risk MAP Based Resiliency Analysis of Continuous Solid Dose Manufacturing | AIChE

(233n) Fault-Tolerant Control Design and Risk MAP Based Resiliency Analysis of Continuous Solid Dose Manufacturing

Authors 

Su, Q. - Presenter, Purdue University
Moreno, M., Purdue University
Ganesh, S., Purdue University
Giridhar, A., Purdue University
Reklaitis, G., Purdue University
Nagy, Z. K., Purdue University
The recent development and adoption of continuous manufacturing technologies in pharmaceutical industries1-3 has also created the demand for more efficient process monitoring and control techniques. This is particularly the case with solid dose manufacturing processes, in which unit operations, such as blending, milling, etc., that in a classic batch processing are performed sequentially, are now integrated with a higher degree of automation, and operated at steady state with less manual intervention.4-8 It has also become apparent that fast and reliable control strategy design is a requirement for successful continuous manufacturing technology. Hence, in this study, a systematic framework for fault-tolerant control design and resiliency analysis is proposed for continuous solid dose manufacturing processes based on risk mapping, accessing, and planning (Risk MAP).9

First, a risk mapping was designed to characterize the frequency and severity of the potential faults during the design and operation stages, e.g., model-plant mismatch, calibration errors, failing/missing sensors, process disturbances, etc. The three levels of hierarchical control strategies design, which ranges from single proportional-integral-derivate (PID) control loop to plant-wide advanced model predictive control (MPC), were then assessed subject to the potential faults by using control key performance indices (KPIs), such as, time to product (T2P), magnitude to product (M2P), and other control measures, such as Morariâ??s resiliency index (MRI).10 Mitigation planning for severe faults were also suggested, e.g., to activate or decommission a specific control level, or to divert the off-spec products.

The proposed systematic framework for fault-tolerant control design was demonstrated in a pilot plant for continuous dry granulation process11 and was shown to be efficient and robust in handling potential faults and achieving a robust processing line for solid dose.

References

  1. Ierapetritou M, Muzzio F, Reklaitis G. Perspectives on the continuous manufacturing of powder-based pharmaceutical processes. AIChE Journal.2016;62:1846-1862.
  2. Lee SL, Oâ??Connor TF, Yang X, Cruz CN, Chatterjee S, Madurawe RD, Moore CMV, Xu LX, Woodcock J. Modernizing pharmaceutical manufacturing: from batch to continuous production. Journal of Pharmaceutical Innovation. 2015; 10:191-199.
  3. Buchholz S. Future manufacturing approaches in the chemical and pharmaceutical industry. Chemical Engineering and Processing. 2010; 49:993-995.
  4. Vervaet C, Remon JP. Continuous granulation in the pharmaceutical industry. Chemical Engineering Science. 2005; 60:3949-3957.
  5. Teng Y, Qiu Z, Wen H. Systematical approach of formulation and process development using roller compaction. European Journal of Pharmaceutics and Biopharmaceutics. 2009; 73:219-229.
  6. Singh R, Ierapetritou M, Ramachandran R. An engineering study on the enhanced control and operation of continuous manufacturing of pharmaceutical tablets via roller compaction. International Journal of Pharmaceutics. 2012; 438:307-326.
  7. Singh R, Sen M, Ierapetritou M, Ramachandran R. Integrated moving horizon-based dynamic real-time optimization and hybrid MPC-PID control of a direct compaction continuous tablet manufacturing process. Journal of Pharmaceutical Innovation. 2015; 10:233-253.
  8. Hsu SH, Reklaitis GV, Venkatasubramanian V. Modeling and control of roller compaction for pharmaceutical manufacturing. Part II: control system design. Journal of Pharmaceutical Innovation. 2010; 5:24-36.
  9. http://www.fema.gov/media-library/assets/documents/18274.
  10. Morari M. Design of resilient processing plants III a general framework for the assessment of dynamic resilience. Chemical Engineering Science. 1983;38(11): 1881-1891.
  11. Hsu SH, Reklaitis GV, Venkatasubramanian V. Modeling and control of roller compaction for pharmaceutical manufacturing. Part I: process dynamics and control framework. Journal of Pharmaceutical Innovation. 2010; 5:14-23.