Introduction: 

In the world of pharmaceutical and life sciences manufacturing, the ability to capture, contextualise, and analyse data in real time is essential. Modern operations depend on reliable, validated data systems that not only meet strict compliance standards but also empower continuous improvement, efficiency, and innovation. Among the leading data historian technologies driving this transformation is Canary Historian, a powerful, scalable solution trusted by manufacturers worldwide.

As specialists in data infrastructure and data analytics, Réalta Technologies works closely with clients to implement historian systems like Canary, helping them achieve visibility, reliability, and data integrity across their operations.

What Is Canary Historian?

Canary Historian, developed by Canary Labs, is a high-performance, enterprise-grade data historian designed to store, manage, and analyse time-series data. Built for speed, reliability, and scalability, it provides life sciences organisations with a secure and compliant platform for collecting data from sensors, control systems, and industrial devices.

Unlike traditional historians that can be complex to maintain or scale, Canary’s architecture is lightweight and efficient, allowing for fast data ingestion and retrieval without compromising integrity or performance. It seamlessly integrates with control systems like Siemens, Rockwell, Emerson, and Ignition front end screens, as well as analytics and reporting platforms such as Power BI and SEEQ.

Key Capabilities of Canary Historian

Canary Historian is built with a clear focus on data integrity, speed, and accessibility, all essential criteria in regulated environments such as pharmaceutical manufacturing.

• Lossless Data Compression:
  Canary’s patented compression algorithms allow massive volumes of process data to be stored efficiently while preserving accuracy. This ensures traceability and compliance with regulatory frameworks like FDA 21 CFR Part 11 and EU Annex 11.
• High-Performance Data Retrieval:
  Canary is optimised for fast query performance, enabling engineers, data scientists, and quality teams to access and visualise data instantly, even across years of historical information.
• Scalability and Flexibility:
  Designed to scale from a single production line to global enterprise deployments, Canary can handle millions of data points per second, supporting digital transformation initiatives across multiple sites.
• Integration with Analytics Platforms:
  Through seamless integration with SEEQ, Power BI, and other modern analytics tools, Canary allows users to move from raw process data to actionable insights. Additionally, Canary can integrate its UNS architecture seamlessly by collecting data in MQTT & SPBv1.0 specifications from MQTT data sources.
  This empowers smarter decision-making and accelerates continuous improvement. 
• Security and Compliance:
  Canary supports role-based access control, data encryption, and full audit trails , critical for compliance in GxP environments.

Use Cases in Life Sciences and Pharmaceutical Manufacturing

For pharmaceutical and biotech manufacturers, data integrity and process optimisation are non-negotiable. Canary Historian plays a crucial role across a range of applications:

• Batch Process Monitoring:
  Ensuring each batch follows the defined recipe and identifying deviations or anomalies early in production.
• Equipment Performance Tracking:
  Continuous monitoring of critical systems such as bioreactors, cleanrooms, and HVAC to ensure operational reliability and product quality.
• Regulatory Compliance and Audit Readiness:
  Providing detailed data trails that demonstrate compliance with GMP standards and regulatory requirements.
• Energy and Utility Management:
  Capturing and analysing utility data, from compressed air to chilled water, to optimise energy consumption and sustainability initiatives.
• Predictive Maintenance and Quality Analytics:
  When combined with advanced analytics platforms, Canary enables manufacturers to predict equipment failures before they occur and improve product consistency through process insights.

Data Collection, Visualisation, and Analytics

At its core, Canary is more than a historian, it is a data foundation for innovation. By centralising time-series data and contextualising it within the manufacturing ecosystem, it enables seamless visualisation and analysis.

Through integrations with platforms like SEEQ, engineers can build advanced analytics models, track key performance indicators (KPIs), and uncover correlations between process parameters and product quality. This real-time visibility leads to more efficient operations, reduced downtime, and data-driven decision-making across departments.

How Réalta Technologies Adds Value with Canary Historian

As a trusted data partner to global life sciences organisations, Réalta Technologies has extensive experience implementing and optimising Canary Historian systems. Our engineers understand both the technical and regulatory dimensions of data management, ensuring that each deployment is compliant, scalable, and future-ready.

Our expertise spans:

• Designing and deploying data historian architectures across multi-site facilities.
• Integrating Canary with control systems and enterprise applications.
• Enabling connectivity to SEEQ, Power BI, and advanced analytics frameworks.
• Supporting validation, testing, and documentation to meet regulatory expectations.

Whether you are upgrading from legacy historians or implementing a new data infrastructure, Réalta Technologies provides a complete solution , from design and deployment to ongoing managed services.

Conclusion

In today’s data-driven manufacturing landscape, the ability to collect, contextualise, and analyse process data efficiently is a competitive advantage. Canary Historian provides life sciences companies with the flexibility, speed, and compliance they need to turn data into real value.

Partnering with Réalta Technologies ensures that this technology is implemented with precision and aligned with your business goals. With proven expertise in data historians, automation, and analytics, we empower organisations to achieve operational excellence through data.

To learn more about how Réalta Technologies can help you implement or optimise Canary Historian, contact our team today.

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Introduction: 

In the age of Industry 4.0, the volume of data generated in manufacturing environments continues to grow exponentially. But data alone doesn’t drive smarter decisions. It’s how you visualise and act on that data that creates real value. For companies in life sciences, pharmaceuticals, and high-volume manufacturing, choosing the right data visualisation tool is critical.

In this blog, we compare three leading tools in the space: Microsoft Power BI, Tableau, and SEEQ, examining their features, benefits, and use cases from the perspective of industrial data analytics.

Why Data Visualisation Matters in Manufacturing?

Before diving into the tools, it’s worth revisiting why data visualisation plays such a key role in manufacturing.

Manufacturers face constant pressure to increase yield, reduce downtime, improve compliance, and optimise performance. Data visualisation tools allow plant teams, analysts, and decision-makers to transform raw operational data into actionable insights. Whether tracking equipment efficiency or identifying production bottlenecks, the right dashboard can be the difference between reactive and proactive decision-making.

Power BI: Scalable, Accessible, and Microsoft-Native

Microsoft Power BI is one of the most widely used business intelligence platforms in the world. It offers deep integration with Microsoft products, scalability, and user-friendly interfaces, making it a powerful choice for companies already embedded in the Microsoft ecosystem.

Key Features:

• Native integration with Excel, Azure, and SharePoint
• Drag-and-drop dashboard creation
• Custom DAX formulas for advanced metrics
• Scheduled data refresh and real-time dashboards
• Strong data modelling capabilities

Strengths:

• Easy to adopt for teams already using Microsoft 365
• Strong community support and regular updates
• Affordable pricing tiers at enterprise level compared to other  visualization tools 
• Suitable for both SME and enterprise scale

Manufacturing Use Cases:

• OEE Dashboards: Track overall equipment effectiveness across multiple plants
• Quality Monitoring: Monitor defect rates and identify trends
• Supply Chain Analysis: Visualise logistics and inventory data

Limitations:

• Can be less flexible for time-series industrial data
• Requires additional configuration for integration with industrial historians like AVEVA PI or OSIsoft

Tableau: Powerful Visualisation and Data Exploration

Tableau is known for its visually rich dashboards and ability to handle large datasets from varied sources. It empowers users to explore data intuitively and supports custom, interactive reporting.

Key Features:

• Rich data visualisation capabilities
• Native support for many data connectors
• Real-time data exploration and drill-downs
• Customisable dashboards with dynamic filters

Strengths:

• Intuitive UI for data analysts and non-technical users
• Excellent at data storytelling and presenting complex trends
• Highly flexible for different data sources and schemas

Manufacturing Use Cases:

• Batch Performance Analysis: Track trends in batch processes over time
• Energy Consumption Reporting: Visualise and compare energy usage across facilities
• KPI Reporting Dashboards: Executive-level visual reporting across departments

Limitations:

• Higher licensing costs than some alternatives
• Not purpose-built for time-series industrial data
• More suitable for data analysts than plant-floor users

SEEQ: Purpose-Built for Time-Series Industrial Data

SEEQ is designed specifically for advanced analytics in process manufacturing industries. Built to work with time-series data from historians like AVEVA PI or Canary, SEEQ enables engineers and analysts to gain insights from complex datasets quickly.

Key Features:

• Native connectivity with AVEVA PI System, OSIsoft, and Canary
• Purpose-built for time-series and event-based data
• Predictive analytics and statistical modelling
• Collaboration features for teams across functions
• Strong integration with Jupyter for advanced data science

Strengths:

• Ideal for engineers and process analysts
• Handles large volumes of industrial data efficiently
• Designed around manufacturing and life sciences workflows
• Short time to value with minimal IT setup

Manufacturing Use Cases:

• Process Optimisation: Identify trends and anomalies in production runs
• Deviation Analysis: Investigate root causes of failures and off-spec product
• Batch Comparisons: Compare equipment and material performance across runs

Limitations:

• Not designed for traditional business metrics (e.g. finance or HR data)
• Requires familiarity with process data structures and tag naming conventions

Choosing the Right Tool for Your Manufacturing Business

The best data visualisation tool depends on your organisation’s needs, data environment, and user base. Here’s a quick comparison:

At Réalta Technologies, we work with clients to implement the right data visualisation solution based on their unique needs. This might be AVEVA PI paired with SEEQ for deep process insights, Tableau connected to AVEVA PI for advanced visual storytelling, or Power BI dashboards for plant-wide KPIs and reporting.

How Réalta Technologies Adds Value

As experts in industrial data architecture, data science, and automation, Réalta Technologies supports clients through every stage of their data journey. This includes infrastructure and historian setup, advanced analytics, and dashboard delivery.

We’ve successfully delivered SEEQ and AVEVA PI solutions across global manufacturing and life sciences clients. Our partnerships with leading technology providers and our in-house data engineering team ensure solutions that are tailored, validated, and built for real-world impact.

Conclusion

Data visualisation is not just about attractive dashboards. It’s about empowering teams with insights. Whether you need plant-level performance metrics, quality trends, or predictive insights, selecting the right visualisation tool is essential.

Power BI, Tableau, and SEEQ each offer distinct advantages. Understanding how they align with your infrastructure, team skillsets, and business goals helps ensure long-term value.

Need help selecting or implementing your data visualisation tools? Get in touch with our team.

Phone: +353 21 243 9113

Email: sales@Realtatechnologies.com 

Introduction

In today’s data-driven world, organisations rely on three crucial roles to extract valuable insights from the vast amounts of data they generate: Data Engineers, Data Scientists, and Data Analysts. While each role serves a distinct purpose, there are key areas where their responsibilities overlap, enabling seamless integration and insight generation. 

This blog explores the differences between these roles and how Réalta Technologies offers a comprehensive range of services that covers all three.

What Does a Data Engineer Do?

Data Engineers are responsible for creating the infrastructure that enables data collection, storage, and processing. Their primary focus is to ensure that data is available, organised, and ready for further analysis by building robust data pipelines and managing databases.

Key Responsibilities:

• Data Architecture: Designing and structuring the framework for data storage and accessibility.
• Infrastructure Setup: Implementing systems to capture and process real-time data.
• Database Management: Overseeing data storage, ensuring its organisation, and handling large datasets efficiently.
• Scalability Solutions: Building systems that can scale with growing data needs.

At Réalta Technologies, Data Engineers specialise in automating connectivity and ensuring smooth data flow using communication protocols like OPC DA, OPC UA, MQTT, BACNet, and various fieldbus communications.

What Does a Data Scientist Do?

A Data Scientist focuses on analysing and interpreting complex datasets to generate actionable insights. They apply advanced machine learning models and algorithms to predict future outcomes, optimise processes, and solve business problems. Their work relies heavily on the infrastructure built by Data Engineers.

Key Responsibilities:

• Machine Learning & Predictive Modeling: Applying algorithms to make data-driven predictions.
• Statistical Analysis: Analysing large datasets to identify trends, correlations, and outliers.
• Algorithm Optimisation: Continuously improving models to enhance their accuracy.
• Data Cleaning & Preparation: Ensuring data quality and preparing it for analysis.

At Réalta Technologies, Data Scientists utilise tools like AVEVA PI, Ignition, and SEEQ to create advanced models that help businesses optimise their processes and improve decision-making.

What Does a Data Analyst Do?

Data Analysts focus on making sense of the data by translating complex findings into clear, actionable insights. They interpret data, create reports, and visualise trends, ensuring that stakeholders can use the data effectively for strategic decisions.

Key Responsibilities:

• Data Querying & Analysis: Extracting specific datasets and interpreting them to uncover meaningful patterns.
• Insight Generation: Turning raw data into actionable insights for business stakeholders.
• KPI Tracking & Performance Benchmarking: Monitoring key performance indicators to track progress.
• Reporting & Visualisation: Using tools to create automated reports and dashboards for easy data interpretation.

Réalta Technologies’ Data Analysts rely on platforms like PowerBI and Tableau to provide comprehensive, interactive dashboards that allow businesses to monitor performance metrics in real time.

Where Do These Roles Overlap?

While the roles of Data Engineers, Data Scientists, and Data Analysts are distinct, they do overlap in important areas:

Integration (Data Engineer + Data Scientist)

Data Engineers and Data Scientists work closely together to ensure that data pipelines are optimised for analysis. Data Engineers provide clean, well-organised datasets, while Data Scientists use these datasets to build and refine models. Together, they focus on:

• Pipeline Optimisation: Ensuring efficient data flow for real-time analysis.
• Data Cleaning Automation: Automating the process of preparing raw data for analysis.
• Real-Time Data Processing: Creating systems that allow for live monitoring and data-based decision-making.

Insights (Data Scientist + Data Analyst)

Data Scientists and Data Analysts overlap in their work of interpreting and analysing data. Data Scientists build models and algorithms, while Data Analysts use these models to generate insights and actionable reports. Together, they focus on:

• Data Querying: Extracting relevant datasets for further analysis.
• Insight Generation: Collaborating to turn analytical results into understandable insights.
• Advanced Data Analysis: Combining machine learning models with business-oriented reporting.

How Réalta Technologies Delivers All Three Services

At Réalta Technologies, we offer a comprehensive range of services that cover all three key roles: Data Engineers, Data Scientists, and Data Analysts. By delivering these services in an integrated manner, we provide businesses with the tools they need to collect, process, and understand their data.

Our Expertise Includes:

• Data Engineering: We design and implement robust data pipelines and infrastructure to ensure your data is always accessible and ready for analysis.
• Data Science: We apply advanced machine learning and statistical techniques to analyse your data and make predictive insights that drive informed decision-making.
• Data Analytics: Our analysts create customised reports and dashboards using tools like PowerBI and Tableau, turning raw data into actionable insights that you can use to improve performance.

Tools We Use:

We rely on a variety of industry-leading tools and platforms to deliver the best possible solutions for your business:

• AVEVA PI, Ignition, SEEQ: For real-time data processing and analysis.
• PowerBI, Tableau: For intuitive reporting and data visualisation that offers comprehensive insights at a glance.

Conclusion

The data lifecycle is complex, and it requires a collaborative effort between Data Engineers, Data Scientists, and Data Analysts to derive maximum value from the data generated by businesses. At Réalta Technologies, we combine these three essential roles to deliver holistic data solutions. From capturing and processing data to generating actionable insights, our experts are here to help you leverage your data for better decision-making, optimised processes, and improved business outcomes.

Contact Réalta Technologies today to learn how we can help you build an integrated data strategy that covers everything from infrastructure to insight generation.

Phone: +353 21 243 9113

Email: sales@realtatechnologies.com

Introduction

Sustainability has become a central focus for industries worldwide, and manufacturing is no exception. With the increasing demand for eco-friendly practices, companies are under pressure to reduce their environmental impact while maintaining efficient operations. One of the most significant challenges in achieving this balance is energy usage, a critical component of both operational costs and sustainability metrics. In this post, we will explore the role of data capture, analysis, and reporting in promoting sustainability in manufacturing and how Réalta Technologies is helping businesses achieve their sustainability goals.

The Energy Challenge in Manufacturing

Manufacturing facilities are energy-intensive by nature, with operations that require large amounts of electricity, gas, and other resources. Energy consumption can account for a substantial portion of a facility’s operational expenses, and inefficient energy use not only impacts the bottom line but also increases the environmental footprint. For companies striving to meet sustainability targets, understanding and optimising energy usage is key.

In recent years, there has been a growing demand for manufacturers to track and report sustainability metrics, such as carbon emissions, water usage, and overall energy consumption. However, the challenge for many facilities lies in the lack of visibility into how energy is used across various operations. Without accurate data, it is difficult to pinpoint areas where energy efficiency can be improved or determine the effectiveness of sustainability initiatives.

The Role of Automation and Data Capture in Sustainability

Réalta Technologies understands the complexities of energy management in manufacturing and offers cutting-edge solutions to help facilities better understand their energy usage. Through automation connectivity and advanced data analytics, manufacturers can gain comprehensive visibility into their operations, allowing them to make data-driven decisions that support sustainability.

Key Benefits of Réalta Technologies’ Data Capture Solutions:

• Automation Connectivity: Réalta Technologies specialises in connecting industrial systems to capture real-time data from various equipment and processes. Using a range of industrial communication protocols such as OPC DA, OPC UA, MQTT, BACNet, and various fieldbus communications, we enable seamless integration across multiple systems and devices, ensuring no data is left behind.
• Data Analysis and Reporting: Once data is captured, Réalta Technologies provides advanced reporting and analytics tools that allow manufacturing sites to break down their energy consumption. This helps facilities determine critical insights, such as energy usage during production vs. non-production times. For instance, a manufacturer can analyse how much energy is consumed during a batch process compared to when equipment is idle, helping to uncover opportunities for energy savings.

Using Data to Optimise Facility Sustainability

The journey towards sustainability begins with understanding how resources are being used. With the right data in hand, manufacturers can take a strategic approach to reducing their energy consumption, improving efficiency, and minimising their environmental footprint.

1. Energy Consumption Patterns

Réalta Technologies enables manufacturers to identify trends in energy consumption by collecting real-time data across all production stages. By comparing energy use during batch runs versus downtime, facilities can pinpoint inefficiencies, such as idle equipment consuming unnecessary power. This type of analysis allows companies to implement targeted energy-saving measures, such as shutting down non-essential equipment during off-peak hours or optimising heating, ventilation, and air conditioning (HVAC) systems to reduce energy waste.

2. Benchmarking for Sustainability

By tracking sustainability metrics over time, manufacturers can measure the impact of their energy optimisation strategies and set realistic goals for improvement. Réalta Technologies’ data reporting tools help companies benchmark their performance, ensuring they meet or exceed sustainability targets. Through continuous monitoring and reporting, facilities can identify areas where additional improvements can be made, contributing to long-term sustainability.

3. Carbon Emission Reduction

Energy usage is closely tied to carbon emissions, and reducing energy consumption is a direct way to lower a facility’s carbon footprint. With Réalta Technologies’ solutions, manufacturers can generate detailed reports on energy usage and its associated carbon emissions. These reports can then be used to develop strategies for further reducing emissions, helping companies meet regulatory requirements and align with corporate sustainability goals.

The Tools Behind Réalta Technologies’ Solutions

Réalta Technologies partners with industry-leading applications to provide manufacturers with the best-in-class tools for data collection, analysis, and reporting. These include:

• AVEVA PI: A powerful data infrastructure that captures and stores real-time data from industrial processes, offering deep insights into energy usage and operational efficiency.
• Ignition: An industrial automation platform that seamlessly connects devices and data across the facility, allowing manufacturers to monitor and optimise their systems in real-time.
• SEEQ: An advanced analytics platform designed to help manufacturers analyse large volumes of data and identify trends and anomalies, essential for optimising energy consumption.
• PowerBI: A business analytics tool that enables the creation of interactive reports and dashboards, helping stakeholders visualise energy data and make informed decisions.
• Tableau: Another powerful data visualisation tool, Tableau helps manufacturers turn raw data into actionable insights, making it easier to track sustainability metrics and energy usage trends.

How Réalta Technologies Drives Sustainability

At Réalta Technologies, we believe that data is the key to unlocking sustainability in manufacturing. By providing manufacturers with the tools and expertise to capture, analyse, and report on energy usage, we empower businesses to take control of their sustainability goals. Whether it’s through automation connectivity or advanced analytics, our solutions help manufacturers:

• Gain visibility into energy consumption across all operations
• Identify inefficiencies and opportunities for energy optimisation
• Track sustainability metrics and monitor progress over time
• Reduce carbon emissions and meet environmental regulations

Conclusion

Sustainability is no longer an option for manufacturers—it’s a necessity. As the world shifts towards more eco-friendly practices, companies that prioritise energy efficiency and resource optimisation will lead the way in reducing environmental impact. Réalta Technologies is committed to helping manufacturers achieve their sustainability goals through data-driven solutions. By leveraging our expertise in automation and data analytics, manufacturing sites can gain the insights needed to optimise energy use, reduce costs, and improve their overall environmental footprint.

Contact Us

Ready to optimise your facility’s sustainability efforts? Contact Réalta Technologies today to learn how our data capture and reporting solutions can help you achieve your energy efficiency and sustainability goals.

https://realtatechnologies.com/contact/

sales@realtatechnologies.com

+353 (0)21 2439113

Introduction

In the rapidly evolving pharmaceutical industry, the need for real-time data collection, analysis, and visualisation have become crucial for maintaining operational efficiency and compliance. Réalta Technologies has demonstrated its expertise in this domain by successfully implementing a High-Availability PI System at a BioPharma site specialising in Fill Finish operations. 

This case study is one example of many full PI System implementations we have completed this year and highlights the advanced systems and technologies integrated by Réalta Technologies and the significant benefits they bring to the site.

Understanding the Customer’s Requirements

The BioPharma site required a robust and reliable system capable of collecting, storing, analysing, and visualising both real-time and historical operational data from various critical areas within the facility. These areas included the Formulations Suite, Component Preparation, Filling & Inspection, Labs, Clean and Black Utilities, and the Building Management System (BMS). The primary objective was to implement a High-Availability PI System that could integrate seamlessly with existing systems and provide comprehensive insights into operational performance.

Systems Integrated

Réalta Technologies expertly integrated a range of systems to achieve the desired outcomes for the BioPharma site:

• • DeltaV Batch System: Facilitates precise control and monitoring of batch processes, ensuring consistency and quality in production.
  • Syncade MES: Provides Manufacturing Execution System (MES) capabilities, enhancing production management and compliance.
  • Siemens & Allen Bradley PLC’s and HMI’s: Critical for controlling and monitoring automated processes and equipment across the site.
  • Desigo BMS: Manages building systems such as HVAC, lighting, and security to ensure a controlled environment.
  • LIMS (Laboratory Information Management System): Streamlines lab operations by managing samples, associated data, and laboratory workflows, ensuring data integrity and compliance.

Technologies Deployed

To meet the complex requirements of the BioPharma site, Réalta Technologies employed a suite of advanced technologies that work in tandem to deliver real-time insights and analytics:

• PI Data Archive: Redundant central repository for all operational data, ensuring secure and efficient data storage.
• PI Asset Framework (AF): Provides a contextualised representation of data, enabling users to easily navigate and analyse information.
• MS SQL Server: Allows redundancy and robust support for the databases used for the PI system’s Metadata
• PI Analytics: Allows for the creation of sophisticated analytics models, providing actionable insights from the collected data.
• PI Vision & Datalink: Facilitates intuitive data visualisation and interaction through dashboards and reporting tools.
• PI Event Frames Generator (EFGen): Generates event frames for tracking process events and exceptions, crucial for batch reporting.
• PI Notifications: Automates alerts and notifications, ensuring timely response to critical conditions.
• RtReports: Enables comprehensive reporting and review by exception, streamlining compliance and quality assurance processes.
• PI Integrator for Business Analytics: Integrates PI System data with business intelligence tools, enhancing strategic decision-making.
• PI WebAPI: Provides programmatic access to PI System data, enabling custom applications and integrations.
• Python: Utilised for developing custom scripts and analytics models, further extending the system’s capabilities.
• PowerBI: A powerful tool for creating interactive and insightful business intelligence reports, integrating seamlessly with the PI System.
• PI Interfaces: Enables reliable collection of data from multiple sources like OPC Servers, PLC, relational databases, Batch Execution Systems

Rationale for the Systems and Technologies Used

Each technology and system integrated by Réalta Technologies was carefully selected to meet the specific needs of the BioPharma site:

• High-Availability and Redundancy: The PI System architecture ensures continuous operation with minimal downtime, critical for maintaining uninterrupted production and compliance.
• Real-Time Data Visibility: Integrating PI Vision, Datalink, and PI Analytics provides stakeholders with real-time access to operational data, enabling proactive decision-making.
• Advanced Reporting and Analysis: Tools such as RtReports, PI EFGen, and PI Integrator for Business Analytics enable detailed reporting, exception-based review, and in-depth analysis of critical process parameters (CPP) and batch performance.
• Seamless Integration with Existing Systems: The PI System’s compatibility with DeltaV, Syncade MES, and various PLCs ensures a smooth integration process, preserving existing investments in technology.
• Customisable and Scalable Solutions: The use of Python and PowerBI allows for the development of custom analytics and reports, tailored to the site’s specific needs, while providing scalability for future expansion.

Use Cases and Benefits

The implementation of the High-Availability PI System has enabled the BioPharma site to achieve significant improvements in operational efficiency and data-driven decision-making. Key use cases include:

• Alarms Notifications and Reporting: Automated alerts and detailed reporting on alarms ensure quick response to critical issues, minimising downtime and enhancing safety.
• Downtime Reporting: Accurate tracking and analysis of downtime events help identify root causes and implement corrective actions, reducing production losses.
• Critical Process Parameter (CPP) Reporting: Continuous monitoring and reporting of CPPs ensure that production stays within defined parameters, maintaining product quality and compliance.
• Batch Reporting with Review by Exception Strategy: Streamlines batch reporting processes, focusing only on deviations and exceptions, which reduces the time required for quality reviews.
• Batch Analysis & Comparison Dashboards: Visual dashboards allow for easy comparison of batch performance over time, helping to identify trends and optimise processes.
• Energy Monitoring Dashboards: Provides insights into energy consumption patterns, enabling the site to implement energy-saving initiatives and reduce operational costs.

Conclusion

Réalta Technologies has once again demonstrated its expertise in implementing advanced technological solutions for the pharmaceutical industry. By deploying a High-Availability PI System at the BioPharma site, Réalta has enabled the site to achieve greater operational efficiency, enhanced data-driven decision-making, and improved compliance with industry regulations. The successful integration of multiple systems and the deployment of cutting-edge technologies highlight Réalta Technologies’ commitment to delivering customised, high-performance solutions that meet the unique needs of their clients.

If you’d like to discuss your challenges or how we can help your data work better for you, contact us today.

sales@realtatechnologies.com 

+353 21 2439113

FAQs

1. What is a High-Availability PI System?
   A High-Availability PI System is a robust data infrastructure that ensures continuous operation with minimal downtime. It is designed to collect, store, and analyse real-time and historical data, providing businesses with actionable insights and ensuring operational continuity.
2. How does the PI System enhance operational efficiency?
   The PI System enhances operational efficiency by providing real-time visibility into critical processes, automating alerts and notifications, and enabling advanced data analysis. This allows businesses to proactively address issues, optimise processes, and make informed decisions.
3. What is the role of PI Vision in the PI System?
   PI Vision is a visualisation tool within the PI System that allows users to create interactive dashboards and displays. It enables real-time monitoring of operational data, making it easier for stakeholders to identify trends, anomalies, and opportunities for improvement.
4. Why is integration with existing systems important?
   Integration with existing systems is crucial as it ensures that the PI System can seamlessly collect and analyse data from various sources without disrupting current operations. This preserves the value of existing technology investments and minimises implementation challenges.
5. How can businesses benefit from energy monitoring dashboards?
   Energy monitoring dashboards provide businesses with insights into their energy consumption patterns. By analysing this data, companies can identify areas of inefficiency, implement energy-saving initiatives, and reduce operational costs, contributing to sustainability goals.