What is process historian database?

Despite the fact that process historians have been available for over two decades, an astonishing number of businesses are yet to recognize and leverage their numerous advantages. Empowered Automation Solutions has identified this gap in adoption and is helping companies successfully transition into modern process monitoring tools that can be used to streamline operations and enhance efficiency.

Process historians are essential for understanding the way business’s function. They are able to track the production flow and provide details about how a task is being executed. Investing in process historians could be worthwhile as it can lead to better data analysis and provide detailed insights into a business's workflow.

It is vital to have an understanding of process historians and time-series in order to get back to the basics. Process historians are systems that record data over time and time-series are the sequences of data points collected at successive points in time.

Process historians are a kind of non-relational SQL database that stores and handles industrial data based on the time it was created. It also processes, examines, and produces results from the stored information. AI’s capacity to trace data points over time is incredibly beneficial for a variety of sectors and applications, including utilities, energy, manufacturing, and process engineering. This capacity makes them invaluable for analyzing and making decisions.

A time-series database and a process historian may sound similar, however they each have different functions. A time-series database stores data points over a period of time, while a process historian records information about how processes are run over a certain amount of time.

Not exactly. A process historian is a specifically designed 'time-series database' made for the process control sector. This kind of database is also used in other areas such as finance (like tracking stock prices over time) and IT (for monitoring server usage over time). Tech giants such as Google, Facebook & Amazon have revolutionized the data storage space by developing their own NoSQL databases. These databases have the ability to process millions of data points from millions of internet users at a very fast rate.

Data from manufacturing and industrial operations can be recorded, stored, and tracked. This includes production data such as order details, inventory levels, production output measurements and more. Furthermore, this information can be used to analyze performance and assess trends in the workplace.

The possibilities are endless when it comes to the data items (or tags) that could be stored and processed:

• The total amount of defects that occurred during a particular shift.
• Production lines often rely on motor fans to help operate efficiently. These fans produce vibrations which can be disruptive, but are necessary for the machine to run properly.
• Water treatment plants need to keep their pH levels in a specific range in order to ensure the water is safe for consumption and other uses.
• Conveyors are built with various speeds depending on the purpose they serve. The speed of a conveyor can be determined by how quickly it can move a certain material or item down its track.
• When data was entered by a human being
• The sum of all the ingredients placed in a batch recipe.

It is possible to view and analyze the data across different time frames, be it past, present or future, and in real-time for better insights into operations. Through the accumulation of historical data over time, operational supervisors can develop models or spot trends to locate potential issues that could arise in the future and refine existing protocols accordingly.

Our operations have been collecting data for some time now. What can a process historian do to facilitate real-time data analysis?

Without an organized and effective approach to data analysis, all the data that is available in the world will be of no use because it cannot be interpreted in a meaningful way. That's why it is so vitally important to have a detailed strategy for understanding and interpreting data in order to derive meaningful insights and information.

Despite the availability of advanced technology, some businesses still resort to manual data logging on paper. This could be using spreadsheets or SCADA (Supervisory Control and Data Acquisition) to monitor trends. Historians have immense capabilities in analyzing large amounts of data over an extended period, which provides a comprehensive perspective on different timeframes. Operations managers & CIOs can identify patterns that may lead to failure events with the help of spreadsheets, though this information becomes available only after the event takes place. Historians have the ability to identify trends, irregularities and other signals that can notify production managers of potential issues before they arise. This sort of pattern recognition is developing the groundwork for machine learning applications. AI technology is currently being utilized in the manufacturing industry to minimize any errors and improve the overall quality of products & services.

IoT technologies are providing businesses with a chance to optimize their operations, reduce the risk of mistakes and positively influence their profits. The quantity of data that industrial plants have to deal with is increasing exponentially and the sheer amount of it will make it useless if the system isn't able to store, process and convert it into useful insights. This emphasizes the necessity for an advanced database for any company in order to remain competitive in today's business environment.

The database industry has seen a remarkable rise in the popularity of time-series databases over the past two years, with more and more developers and businesses opting to use them due to their advantages. Nowadays, there is a vast selection of time-series databases available on the market, so users have more choice in terms of features, scalability, cost and performance.

Many organizations are now turning towards enterprise data historians as a way to improve their operational performance by leveraging the power of historical data. These systems are used to store, organize and analyze large amounts of data which can then be used to inform decisions, identify areas for improvement and optimize processes.

In this day and age, many open-source data historians exist with the same scalability & processing power of that of Google. A few examples are Influx, Grafana, & Elasticsearch. We will discuss the advantages and disadvantages of enterprise process historians and open-source time-series in detail in an upcoming blog post.

Staying up to date is essential- transitioning from process historian to time-series databases allows you to be more efficient and access more data in real-time. The change improves data management and ensures better accuracy of results.

Gathering and examining production data is an essential ingredient of success for manufacturers wanting to stay ahead in the competition. This allows them to make the best possible decisions based on accurate and up-to-date information. The tech behemoths of the web have revolutionized the time-series technology landscape. It is more powerful, user-friendly & a drastic improvement compared to what has been around for the past 4 decades.

Businesses that are able to successfully leverage the power of Internet of Things (IoT) technologies are in a great position to gain a major competitive advantage over their rivals. As more companies adopt such innovative and cutting-edge technologies, those who have implemented them in a successful manner, and managed to reap the maximum benefits from them will stand head and shoulders above the rest.

A key factor to unlocking the potential of data analysis is having all the data organized in one place. It can be challenging to find this 'single source of truth', but with diligence and effort it is achievable. We plan to explain the concept of data warehousing & dimensional modelling in an upcoming blog post. This is a great way to ensure that you have a reliable single source of truth.