Pharmaceutical manufacturers face growing pressure to move beyond isolated automation islands. They need fully connected, plant-wide systems instead. Biophorum’s Digital Plant Maturity Model makes it clear: Level 3, the connected plant, is now table stakes to compete. yet many companies still struggle to make the leap. Data stays fragmented across systems. Operator interfaces vary wildly. Lean teams make efficiency harder to maintain.
The path forward requires more than simply linking existing equipment. It demands intentional system design, open standards like OPC UA, and software architectures that enable seamless data mobility from the plant floor to business systems.
In the following Q&A, Bruce Greenwald, DeltaV Platform business development sales director at Emerson, discusses the key challenges manufacturers face in automation integration, the evolving role of distributed control systems and MES platforms, and lessons learned from facilities that have successfully made the transition.
What are the biggest challenges manufacturers face when trying to move beyond isolated automation islands to plant-wide or facility-wide integration?
Looking at Biophorum’s Digital Plant Maturity Model, the key goal for many organizations today is reaching level 3, the connected plant. Today, the connected plant is effectively table stakes to participate in the market. Electronic batch records and review by exception reporting, two key competencies to be able to keep up with the industry, need that level of connectivity to be successful.
The key challenges to reaching the connected plant goal are data contextualization and harmonization of operations. First, teams are facing down many different islands of automation across their facilities and need to bring data together. When data is trapped across multiple systems in multiple formats, teams face delays as they try to gather insight from that information. Not only must they find a way to collect and collate the data, often via time-consuming manual collection, but in many cases, they also need to transform the data for use in other systems. Moreover, collecting data from many different systems and bringing it together manually typically means leaving critical context behind.
In addition, teams also struggle to maintain consistency and efficiency of operations when each silo of data has a different interface. Personnel are far less efficient when they must learn and remember how to navigate several different systems to accomplish their goals. Today’s lean teams are looking for ways to standardize operations across all their systems. The ability to train personnel once and have them then be effective on all systems makes it far easier for individuals to work across connected systems to drive more efficiency.
Figure 1: Accelerate technology transfers throughout drug development lifecycle with centralized monitoring and control using standardized product definitions and structures.
How is the approach to automation architecture evolving to support greater connectivity between previously siloed systems?
Companies must embrace building from the plant floor all the way up to business systems using the right tools. Integrating skids is an important strategy, but it is a starting point and not the whole picture. Tools like a distributed control system (DCS), and manufacturing execution system (MES), real-time scheduling (RTS), and process knowledge management (PKM) software are empowering teams to do more with less, making them a critical part of the operational chain. Teams must build their systems intentionally, designing for integration among all the software that drives their operations and business.
Seamless data mobility among systems lets teams optimize their schedules and processes to start moving toward real-time release. They can also identify issues faster, and then intervene by planning maintenance more effectively, and by adjusting process parameters to avoid deviations and material losses.
As plants are asked to operate at peak efficiency with increasingly lean teams, automation solutions designed to integrate seamlessly with all these capabilities are needed. The software solutions necessary to solve these complex issues are designed to operate on a foundation of a seamless data fabric that connects the systems automatically out-of-the-box, while preserving the critical context necessary to turn data into actionable information. For example, DeltaV™ DCS, MES, RTS, and PKM are all designed to help teams avoid unintentionally building a network of data silos. Eliminating silos creates efficiencies by default, reducing engineering effort and streamlining operators’ tasks.
Figure 2: Reaching level 3 of Biophorum’s Digital Plant Maturity Model, the connected plant, is effectively table stakes for entry into the modern life sciences marketplace.
What role do open standards and interoperability play in enabling broader automation integration?
Nearly every organization prioritizes flexibility of engineering and operation, so forward-thinking teams are choosing seamlessly integrated solutions built around open protocols like OPC UA. By selecting systems built around open protocols, teams can bring their systems online more quickly, while maintaining the flexibility to incorporate a much wider array of equipment. The best modern automation solutions can support this flexibility—while still offering a foundation built on secure, out-of-the-box, and seamless connectivity—helping teams drive ease of use and maintenance.
Can you share an example of a facility that successfully scaled from isolated automation to a more unified approach, and what lessons came from that transition?
One large biopharmaceutical manufacturer opted to move from an isolated approach with islands of automation interconnected by the MES to a more unified approach controlled from the top-down with the MES integrated into the DCS. Their goals were to improve consistency, gain better access to data across all batches, and harmonize their operator experience.
The key lesson they learned from the transition was the importance of standardization. It is important to have good standards not just defined but also applied. From naming conventions to operation modes to the look and feel of graphics, the organization needed to consider how it would select best practices and most effectively standardize them via automation solutions.
We are even seeing a surprising number of original equipment manufacturers (OEMs) moving skids with proprietary control systems over to the DeltaV DCS for ease of use and better data mobility. In fact, today many skid vendors are offering solutions with native and integrated DeltaV DCS already built in to help streamline this process.
For R&D and lab environments specifically, what does the path from semi-automation to fuller integration typically look like?
In the development phase, there is often a lot of manual effort as teams run individual experiments across their many bioreactors and other equipment. Many teams have expressed an interest in a more top-down control strategy to allow them to download design of experiment parameters to the system, instead of having to manually set everything up for each experiment. Leveraging an integrated DCS across the process development labs can help teams accomplish these goals, while also setting them up for easier technology transfer as they move closer and closer to full-scale commercial manufacturing.
Bruce Greenwald
A more harmonized, top-down approach with seamlessly integrated automation software also makes it easier for the teams running the experiments to have a unified experience, with all their data collected in one place. Such an approach not only improves efficiency and reduces wasted effort, but it also empowers teams to start exploring optimization and process analytical technology earlier in the process so they can build these features into their systems more effectively.
About the respondent
Bruce Greenwald is the DeltaV Platform business development sales director for Emerson, located in Austin, TX. In his current role, Greenwald assists customers in understanding the features and benefits of DeltaV to improve their automation experience. He is a 1979 graduate of the University of Kansas with a degree in Chemical Engineering. His four decade-long career has been focused on process control.
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