	Data analytics software and machine learning capabilities give pharmaceutical manufacturers new tools to move beyond preventive maintenance into predictive and prescriptive maintenance, which promises to be more effective and save time and money. 

spoke with Dennis Belanger, director of Operational Certainty Consulting at Emerson, about these new methods. 

What is the difference between preventive, predictive, and prescriptive maintenance? What do you see as the trend in maintenance of equipment in pharma manufacturing?

Today, prescriptive maintenance is being adopted by best-in-class pharma manufacturers to drive better production through more informed decision making. Prescriptive maintenance uses Big Data analytics to find patterns or anomalies in large amounts of seemingly unrelated data-understanding and evaluating the performance of a process or system rather than measuring the condition of a single piece of equipment. Finding these indicators can help organizations identify areas of good and bad performance that might be impossible to identify through standard monitoring procedures. The prescriptive element comes in when organizations can associate a corrective action or adjustment to the anomalies and provide specific actions to take to minimize or stop the failure.

	Many organizations still use preventive and predictive maintenance, and there is an important distinction between them. Preventive maintenance tasks are performed on a fixed schedule or a metric such as run hours or cycles. Preventive tasks inspect assets or bring them back to a certain condition and typically require a scheduled system shutdown. Preventive maintenance tasks should only be used when it is not possible to detect failure modes in a timely manner with predictive monitoring solutions  because they provide only few weeks’ notice of potential failure. Filter changes, leak inspections, and alignment checks are good candidates for preventive maintenance.

	Predictive maintenance uses technology to monitor and trend an asset to detect change in conditions that might indicate a future problem. Maintenance data are collected regularly while equipment is running, through manual rounds or through devices installed at the collection site. Predictive maintenance eliminates the need to schedule a shutdown and provides a better indication of the actual condition of equipment. Predictive technologies have become quite popular because they can provide early indication of potential asset failure-typically allowing many months of advance warning, which supports organizations’ planning of turnarounds and scheduled outages to minimize overall downtime. Vibration analysis, infrared testing, and condition monitoring are all common examples of predictive maintenance technologies widely used today.

What are some best practices for using predictive maintenance?

One of the best practices a pharma organization can apply is to perform a maintenance strategy analysis using a failure modes and effects analysis (FMEA). This analysis would typically incorporate critically ranking information and will ultimately show an organization where best to apply the resources of a predictive maintenance program to have the strongest impacts. Often, organizations view predictive maintenance as a costly expense and use it only sparingly on their most critical assets, but applying it more widely can result in much higher savings if the application is properly targeted. Top quartile performers typically use vibration analysis on 80–90% of their rotating equipment. These organizations know that predictive maintenance is approximately 50% less costly than preventive maintenance, while still providing a much better indication of potential failure. Moreover, online predictive maintenance can also provide earlier detection of issues, making it easier to plan repairs, which typically cuts repair costs by 40–50%.

How are models for maintenance developed, and how can they be best used?

Common assets and systems typically have common problems and impacts on a business. Emerson uses these commonalities as a starting point to develop models that can be used hundreds or thousands of times across many clients with minimal customization. Organizations can use these models to effectively and efficiently simulate common assets such as compressors, distillation columns, heat exchangers, pumps, valves, generators, and turbines, making advanced analytics more achievable and sustainable. 

	Many models for high-impact, known problems can be applied across industries or organizations because the models are built for common equipment. As Emerson expands solutions to address business problems for complex systems and processes, more specific models are possible and will be useful to target a company or plant’s unique environment. When individual systems begin to vary greatly in configuration, engineering design, age, and monitoring techniques, there are more complex custom solutions that can be built from scratch and can deliver end user-specific insights. 

What is the importance of detecting and addressing issues in real time?

The importance of detecting issues in real time is linked to the duration between the detection of a failure mode and the onset of a problem. For example, some electrical failures occur in a matter of minutes. Such a failure would require real-time or near-real-time detection to provide enough time for maintenance to intervene. On the other hand, failure modes such as bearing deterioration may take months to go from detection to failure. When the time to failure is that long, more intermittent monitoring may be appropriate. 

	While monitoring every piece of equipment in real time would be nice, an organization would need to be able to handle the volumes of data such monitoring would generate. Understanding that time to failure dictates real-time detection in only a handful of cases, most organizations opt to monitor many assets in near real-time or even using periodic readings, which still allows them plenty of time to react to problems.

	If you are going to spend the effort and resources setting up and maintaining infrastructure to detect issues in real time, then you also need to be able to act in real time. Detection is only a part of the picture. Organizations also need to examine the established work management process so that significant lead time translates to timely and precise action. 

	Examples of addressing equipment failures

Can you give some examples of detecting and addressing equipment failure modes in pharma manufacturing?

There are many examples of varying size and scope, but three examples in particular stand out. Emerson worked with one organization to develop a machine learning system that could detect sensor drift on a temperature sensor for a heat-treat skid. That implementation detected an aberration 60 days in advance, which allowed the organization to save a batch worth over $1 million.

	Another organization used vibration analysis to detect misalignment and bearing failure on a chilled water system pump for a system performing batch experiments that require constant temperature. That system detected a failure 120 days in advance, saving batch experiments that, if lost, could have wasted months of time.

	In one innovative example, a pharmaceutical organization used machine learning to capture knowledge and monitor systems with the objective of minimizing the impact of a potential loss of 25% of the organization’s workforce due to expected retirements. 

	What all successful examples have in common is that decision makers closely examined critical points of failure in the organization and developed solutions that gave the organization the time it needed to react efficiently but thoughtfully, to drive more positive outcomes overall.

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Predictive and prescriptive maintenance improve pharmaceutical manufacturing equipment effectiveness. 

Data Analytics Technologies Help Reduce Equipment Failure

	Pharmaceutical manufacturers must adhere to cGMP no matter what their batch size, but producing small batches in aseptic fill/finish has particular challenges. 

spoke with Robert Popilock, Packaging and Production segment manager for DWK Life Sciences, about some of these challenges and possible solutions using ready-to-use components.

What are some of the considerations and challenges for fill/finish and packaging that are specific to small-batch manufacturing? 

For small batch entities, the most notable considerations are related to capital investment (processing equipment and physical plant space), internal competency development (standards interpretation, process implementation, maintenance, and review), workflow or production capacity (hand filling, semi-automated, or high-speed lines), and meeting regulatory guidelines.

	Common ways to produce an aseptic drug include internal preparation of sterile components or procurement of sterile components. The selection of one method over the other is often based on production run rates, batch frequency, and operational constraints. Small batch entities are typically constrained to plant space, capital investment, and personnel competencies. Small batch processors may be limited in their ability to dedicate space for automated cleanroom operations with high-efficiency particulate air (HEPA) environments. They may also have limited ability to make the capital and process investments to achieve 

<71> (sterility) (1–3) as well as environmental monitoring requirements. Of interest, the capital outlay for equipment to wash, autoclave, and irradiate can exceed $1 million, and required process verifications and content integrity evaluations can be time consuming.

	To overcome these economy-of-scale limitations, small batch manufacturers seek alternatives to in-house processing by procuring or contracting components and processing services or through the use of ready-to-use  components or kits.

	Although the option of procuring components and processing services does allow the small batch operator to select foundational packaging components, such as clear and amber vials, aluminum seals, and stoppers, this option is associated with operational and capital investment challenges. One limiting factor is that the required production demand may be below the minimum order quantity threshold of both the component manufacturer and processing agency. Another challenge is related to the lead time and fulfillment cycle for processing services, which can create forecasting and planning challenges for ad hoc and small batch consumption scenarios.Unplanned demand is typical, as small batch processors desire to minimize on-hand stock of processed products given that the products have a finite shelf life and desire to reduce capital deployed.  Together, such issues have driven interest in ready-to-use (RtU) packaging components.  

	RtU component packs from DWK are available in quantities from 200–230 units and accompanied by a certificate of analysis (CoA) supporting off-the-shelf use. The small quantity packs consisting of clear or amber vials, aluminum seals, lyophilization stoppers, coated stoppers, and straight plus stoppers help to reduce scrap and management of opened sterile inventory and are ideally suited for small batch and compounding entities. RtU configurations consist of inventory-matched vials, stoppers, and seals available in off-the-shelf kitted quantities from 200–1200 units. The kits minimize risks associated with inventory shortages by assuring matched quantities of sterile components being available in a single kit and limit scrap through small batch pack formats.

	As can be seen, small batch manufacturers can match their batch rates, batch frequency, and operational preferences or governances to maximize workflow, investment, and risk. 

What challenges do you see in fill/finish at compounding pharmacies? 

Compound pharmacies create medications tailored to the specific needs of the patient by combining and mixing ingredients, then packaging them for delivery and use. Typically compounding is a small batch or ad hoc [as needed] production scenario. While compounding is becoming increasingly common, there is a large portion of compounders who may struggle to comply with regulations, including the demonstration of consistent production of clean and sterile parenteral packaging components. Despite the fact that there are guidelines for industry and sterile drug products that require conformance to aseptic processing (cGMP) and 

Pharmaceutical Compounding-Sterile Preparations 

(4), ongoing problems have led to intensified efforts by FDA to assure safety of compounded drug products. 

	In addition to regulatory compliance, compounders who use sterile vials and closures are also challenged by physical plant space to host sterile processing equipment, capital investment in expensive washing and sterilization equipment, and analytical capabilities to assure compliance to published standards, along with personnel required to implement, maintain, and audit processes and procedures to assure compliance. Like fill/finish operations, compounders are challenged in coordinating the purchase of raw components and contracting processing services at minimum order quantities. They also face challenges associated with navigating the processor’s schedule and processing backlogs. This makes RtU solutions a viable alternative through off-the-shelf and small pack quantities accompanied with CoA and traceability documentation. 

	The regulatory environment can be quite complex. So much so, that we are seeing a trend in the number of manufacturing projects being outsourced for large batches to contract manufacturing organizations (CMOs). CMOs typically have dedicated staff who perform such compliance activities and are extremely efficient and less prone to complications that may delay production. In the case of small batch manufacturing and compounding entities, however, their volumes don’t align with such outsourcing agencies, so they must rely on their own compliance person. Knowledge of particulate cleaning, final water for injection rinse, total organic carbon levels, depyrogenation, autoclaving, irradiation, surface treatments, sterile bagging methods, CoA handling, and keeping up with compliance standards pose obvious challenges. A common misconception is that RtU components and kits are associated with a cost premium. However, when balancing against non-compliance risks, adding regulatory headcount, and annual training and processor audits, the convenience of filing the CoA becomes desirable.

<788> “Particulate Matter in Injections” (US Pharmacopeial Convention, Rockville, MD, July 1, 2012 ).	

<85> “Bacterial Endotoxins Test” (US Pharmacopeial Convention, Rockville, MD, July 1, 2012 ).	

<71> “Sterility Tests” (US Pharmacopeial Convention, Rockville, MD, July 1, 2012).	

<797> "Pharmaceutical Compounding-Sterile Preparations" (US Pharmacopeial Convention, Rockville, MD, 2008).

Ready-to-use components help compounders and manufacturers of small batches overcome economy-of-scale limitations in aseptic GMP manufacturing.

Equipment and Processing Report-12-18-2019

Data Analytics Technologies Help Reduce Equipment Failure

Challenges for Compound and Small-Batch Aseptic Manufacturing