Abstract
Purpose
This study focuses on the implementation of a real-time exceptional events management (EEM) framework on a pharmaceutical manufacturing process to demonstrate its efficacy in detecting, diagnosing, and mitigating incipient exceptional events on a continuous process.
Methods
The real-time EEM framework integrates signed directed graph and trend analysis methods for diagnosis. Additionally, fast Fourier transform analyses are performed via a parallel moving window to detect oscillatory behavior. The EEM framework is demonstrated on a partial continuous dry granulation line consisting of two feeders, blender, and roller compactor and is shown to be capable of incipient fault diagnosis. In addition, simultaneous occurrences of different exceptional events are considered in this study, and a protocol is developed for multiple fault identification.
Results
The framework is observed to detect, diagnose, and offer mitigation strategies within 10 s of event inception for the following cases: (1) simultaneous occurrences of different exceptional events in a particular, isolated, equipment, (2) simultaneous occurrences of different exceptional events spanning multiple equipment, and (3) consecutive occurrences of events. Additionally, the EEM framework is capable of limiting the progression of exceptional events originating in an upstream equipment, thus ensuring minimal to no propagation of exceptional events. Once an exceptional event has been determined, mitigation strategies are retrieved from the knowledge base and are either presented to the operator as an advisory or automatically executed to restore normal operating conditions.
Conclusions
The real-time EEM framework is demonstrated to effectively detect, diagnose, and mitigate known exceptional events using built-in process knowledge. In addition, a protocol for handling multiple fault identification is successfully demonstrated on the partial continuous dry granulation line. Finally, quick and effective remediation of an exceptional event as it begins is shown to prevent the propagation of its effects downstream, thus reducing subsequent deviations across the continuous line.
Similar content being viewed by others
Notes
Preema red powder food coloring ingredients: sodium chloride, ponceau 4R (red synthetic colorant), and tartrazine (lemon yellow synthetic colorant)
Normal operating conditions of roller compactor variables were subtracted from actual measurements
Residence time estimates were based on Table 3 using equipment settings described in “Experimental Method for Continuous Dry Granulation Line.”
References
Suresh P, Basu PK. Improving pharmaceutical product development and manufacturing: Impact on cost of drug development and cost of goods sold of pharmaceuticals. J Pharm Innov. 2008;3(2008):175–87.
Crosby T. Designing for the future of continuous processing. 2008.
Lewcock A. Ditch batch: continuous is the future. 2008.
Switchtenberg W. Moving beyond the batch. 2008.
Schneider RE, Cini P. The push for modern manufacturing. 2004.
Preub K, Le Lann M-V, Cabassud M, Anne-Archard G. Implementation procedure of an advanced supervisory and control strategy in the pharmaceutical industry. Control Eng Pract. 2003;11(12):1449–58.
Zulkeflee SA, Aziz N. Control implementation in bioprocess systems: a review. In: International Conference on Control, Instrumentation and Mechatronics Engineering, Johor, Malaysia. 2007
Yu LX. Pharmaceutical quality by design: product and process development, understanding and control. Pharm Res. 2008;25(4):781–91.
Johanson JR. A rolling theory for granular solids. Trans ASME J Appl Mech Ser E. 1965;32(4):842–8.
Hsu S-H, Reklaitis GV, Venkatasubramanian V. Modeling and Control of Roller Compaction for Pharmaceutical Manufacturing. Part I: Process Dynamics and Control Scheme. J Pharm Innov. 2010;5(1–2):14–23.
Hsu S-H, Reklaitis GV, Venkatasubramanian V. Modeling and control of roller compaction for pharmaceutical manufacturing. Part II: control system design. J Pharm Innov. 2010;5(1–2):24–36.
ISA. Management of Alarm Systems for the Process Industries (ANSI/ISA 18.2). 2009. International Society of Automation.
Pariyani A, Seider WD, Oktem UG, Soroush M. Investigation and Dynamic Analysis of Large Alarm Databases in Chemical Plants: A Fluidized-Catalytic-Cracking Unit Case Study. Ind Eng Chem Res. 2010;49:8062–79.
Hamdan IM, Reklaitis GV, Venkatasubramanian V. Exceptional events management applied to roller compaction of pharmaceutical powders. J Pharm Innov. 2010;5(4):147–60.
Ng HT. Model-based, multiple-fault diagnosis of dynamic, continuous physical devices. IEEE Expert. 1991;6(6):38–43.
Watanabe K, Hirota S, Hou L, Himmelblau DM. Diagnosis of multiple simultaneous fault via hierarchical artificial neural networks. AIChE J. 1994;40(5):839–48.
Vedam H, Venkatasubramanian V. Signed digraph based multiple fault diagnosis. Comput Chem Eng. 1997;21:S655–60.
Sesen MB, Suresh P, Banares-Alcantara R, Venkatasubramanian V. An ontological framework for automated regulatory compliance in pharmaceutical manufacturing. Comput Chem Eng. 2010;34(2010):1155–69.
Venkatasubramanian V, Zhao C, Joglekar G, Jain A, Hailemariam L, Suresh P, et al. Ontological informatics infrastructure for pharmaceutical product development and manufacturing. Comput Chem Eng. 2006;30(2006):1482–96.
Hailemariam L, Venkatasubramanian V. Purdue ontology for pharmaceutical engineering: part I. Conceptual framework. J Pharm Innov. 2010;5(3):88–99.
Zhao C, Jain A, Hailemariam L, Suresh P, Akkisetty P, Joglekar G, et al. Toward intelligent decision support for pharmaceutical product development. J Pharm Innov. 2006;1(1):23–35.
Jain A, Kumar P, Joglekar G, Hailemariam L, Suresh P, Zhao C, et al. Integrated decision support tool for pharmaceutical product development. In: 18th European Symposium on Computer Aided Process Engineering, Lyon, France. 2008
Akkisetty PK, Reklaitis GV, Venkatasubramanian V. Ontological informatics based decision support system for pharmaceutical product development: milling as a case study. In: 19th European Symposium on Computer Aided Process Engineering, Cracow, Poland. 2009
Suresh P, Hsu S-H, Akkisetty P, Reklaitis GV, Venkatasubramanian V. OntoMODEL: ontological mathematical modeling knowledge management in pharmaceutical product development, 1: conceptual framework. Ind Eng Chem Res. 2010;49(17):7758–67.
Suresh P, Hsu S-H, Akkisetty P, Reklaitis GV, Venkatasubramanian V. OntoMODEL: ontological mathematical modeling knowledge management in pharmaceutical product development, 2: applications. Ind Eng Chem Res. 2010;49(17):7768–81.
Kramer MA, Palowitch Jr BL. A rule based approach to fault diagnosis using the signed directed graph. AIChE J. 1987;33(7):1067–78.
Maurya MR, Rengaswamy R, Venkatasubramanian V. A systematic framework for the development and analysis of signed digraphs for chemical processes. 1. Algorithms and analysis. Ind Eng Chem Res. 2003;42(20):4789–810.
Maurya MR, Rengaswamy R, Venkatasubramanian V. Application of signed digraphs-based analysis for fault diagnosis of chemical process flowsheets. Eng Appl Artif Intel. 2004;17(5):501–18.
Maurya MR, Rengaswamy R, Venkatasubramanian V. A signed-directed graph and qualitative trend analysis-based framework for incipient fault diagnosis. Chem Eng Res Des. 2007;85(A10):1407–22.
Iri M, et al. An algorithm for diagnosis of system failures in the chemical process. Comput Chem Eng. 1979;3(1–4):489–93.
Acknowledgments
The authors would like to acknowledge the National Science Foundation funding for the Engineering Research Center for Structured Organic Particulate Systems (ERC-SOPS). The authors would also like to thank Girish Joglekar for his expertise and advice in ontologies, and Ryan McCann and Arun Giridhar whose help has been essential to the success of this study.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hamdan, I.M., Reklaitis, G.V. & Venkatasubramanian, V. Real-time Exceptional Events Management for a Partial Continuous Dry Granulation Line. J Pharm Innov 7, 95–118 (2012). https://doi.org/10.1007/s12247-012-9138-6
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12247-012-9138-6