Design of condition-based maintenance framework for process operations management in pharmaceutical continuous manufacturing

Ganesh, Sudarshan; Su, Qing; Vo, Le Bao Dan; Pepka, Nolan; Rentz, Benjamin; Vann, Lucas; Yazdanpanah, Nima; O’Connor, Thomas; Nagy, Zoltán K.; Reklaitis, Gintaras V.

doi:10.1016/j.ijpharm.2020.119621

Cited by 26 publications

(13 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In a similar fashion, PSE researchers are also looking to quantify parameter uncertainty and its impact on product and process performance [74,75]. From an operational standpoint, many groups are developing using digital twins for the design of optimal operating setups, optimisation profiles [76][77][78][79], and smart controllers [80][81][82] that can operate bypassing measurement unavailability.…”

Section: Assisting Digitalisation In Pharmaceutical Industry Via Procmentioning

confidence: 99%

Emerging Challenges and Opportunities in Pharmaceutical Manufacturing and Distribution

et al. 2021

View full text Add to dashboard Cite

The rise of personalised and highly complex drug product profiles necessitates significant advancements in pharmaceutical manufacturing and distribution. Efforts to develop more agile, responsive, and reproducible manufacturing processes are being combined with the application of digital tools for seamless communication between process units, plants, and distribution nodes. In this paper, we discuss how novel therapeutics of high-specificity and sensitive nature are reshaping well-established paradigms in the pharmaceutical industry. We present an overview of recent research directions in pharmaceutical manufacturing and supply chain design and operations. We discuss topical challenges and opportunities related to small molecules and biologics, dividing the latter into patient- and non-specific. Lastly, we present the role of process systems engineering in generating decision-making tools to assist manufacturing and distribution strategies in the pharmaceutical sector and ultimately embrace the benefits of digitalised operations.

show abstract

Section: Assisting Digitalisation In Pharmaceutical Industry Via Procmentioning

confidence: 99%

Emerging Challenges and Opportunities in Pharmaceutical Manufacturing and Distribution

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Data-driven applications for equipment condition monitoring have been suggested outside pharmaceutical manufacturing . Tailored sensors for predictive maintenance (e.g., vibrational analysis) are often installed in production facilities . Installing such new sensors in a running pharmaceutical facility, however, could be cumbersome due to the GMP requirements for registration and validation of any changes within the manufacturing facility.…”

Section: Introductionmentioning

confidence: 99%

“… 13 Tailored sensors for predictive maintenance (e.g., vibrational analysis) are often installed in production facilities. 14 Installing such new sensors in a running pharmaceutical facility, however, could be cumbersome due to the GMP requirements for registration and validation of any changes within the manufacturing facility. The extra costs for the revalidation process are also an additional burden that could deter the application of changes to an operating process.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Approach toward Long-Term Equipment Condition Assessment in Sterile Drug Product Manufacturing

et al. 2022

View full text Add to dashboard Cite

A two-stage data-driven methodology for long-term equipment condition assessment in drug product manufacturing is presented with a case study for a commercially operating aseptic filling line. The methodology leverages process monitoring data. Sensor measurements are partitioned using process information and maintenance schedules that are available on different databases. Data is processed to tackle heterogeneity in sources and formats. The data is cleaned to remove the effects of short-term variabilities and to enhance underlying long-term trends. Two approaches are presented for data analysis: first, anomaly detection using independent component analysis (ICA), where clusters of outliers are identified. The frequency and timing of such outliers yield important insights regarding maintenance schedules and actions. The second approach enables condition monitoring using principal component analysis (PCA). Long-term operational baselines are identified and shifts therein are linked with different process and equipment faults. This approach highlights the impact of equipment deterioration on shifting operational data baselines and shows the potential for the combined application of ICA and PCA for equipment condition monitoring. It can be applied within predictive maintenance applications where the installation of new specialized sensors is difficult, like in the pharmaceutical industry.

show abstract

“…While time-based PM schedules maintenance actions at fixed time-intervals, CBM reacts based on available information regarding the condition of a given component [9]. Due to its advantages many researchers have recently focused on CBM application to several fields [10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

On risk-based maintenance: A comprehensive review of three approaches to track the impact of consequence modelling for predicting maintenance actions

Leoni

Carlo

Paltrinieri

et al. 2021

Journal of Loss Prevention in the Process Industries

View full text Add to dashboard Cite

The integrity of the gas distribution network is crucial to guarantee the safety of human beings and the environment, while avoiding significant financial outlay. Since gas plants are progressively increasing near urban areas, a comprehensive tool to conduct maintenance and reduce the risk arising from the operations is required. To this end risk mitigation strategies have played a pivotal role during the last decades. In this paper, a comparison of three Risk-Based Maintenance (RBM) methodologies able to point out the most critical components, is presented. The first developed technique is a four stages Probabilistic Risk Assessment (PRA), characterized by a Hierarchical Bayesian Network (HBN) to perform the occurrence analysis and a Failure Modes, Effects and Criticality Analysis (FMECA) to assess the magnitude of the adverse outcomes. The HBN is adopted to overcome the limitations of traditional probability analysis approaches such as Fault Tree (FT), Event Tree (ET) or Bow-Tie (BT). To define a risk metric the total cost of failure is estimated and subsequently the Cost Risk Priority Number (CRPN) is calculated for each equipment. The second approach is a Quantitative Risk Analysis (QRA) carried out via a software named Safeti (by Den Norske Veritas -German Lloyds DNV-GL). By exploiting standard frequencies and modelling the losses of containment through Safeti, the most compelling devices are determined based on their estimated risk integral percentage. At last, Synergi Plant (another software developed by DNV-GL) is adopted for the third methodology. The software provides a Risk-Based Inspection (RBI) plan, through which the components are ranked. The proposed study can provide asset manager a concrete aid to focus maintenance efforts on priority apparatus, while assisting them in adopting the most appropriate methodology to their context. To demonstrate the applicability of the approaches and compare the obtained rankings, a Natural Gas Regulating and Measuring Station (NGRMS) is considered as case of study. The results proofed that all the proposed approaches can be implemented for practical application and the choice of the method strongly depends on the available data.

show abstract

Design of condition-based maintenance framework for process operations management in pharmaceutical continuous manufacturing

Cited by 26 publications

References 38 publications

Emerging Challenges and Opportunities in Pharmaceutical Manufacturing and Distribution

Emerging Challenges and Opportunities in Pharmaceutical Manufacturing and Distribution

Data-Driven Approach toward Long-Term Equipment Condition Assessment in Sterile Drug Product Manufacturing

On risk-based maintenance: A comprehensive review of three approaches to track the impact of consequence modelling for predicting maintenance actions

Contact Info

Product

Resources

About