From Big Data to Smart Data: an Industrial Automation strategy

In today’s environment of automated industrial engineering, there is a massive amount of generated data. Sensors and control systems continuously measure pressure, speed, flow and vibration. Millions, sometimes billions of data points are collected from many sources: from 2020 to 2025 IDC forecasts new data creation to grow at a compound annual growth rate (CAGR) of 23%, resulting in approximately 175 zettabytes of data creation by 2025 (a zettabyte equals to one trillion gigabytes, i.e. one thousand billions gigabytes).

If unused, this overwhelming amount of information remains “dumb”, but if properly collected, processed and analyzed could become “smart”, providing exceptional value. Especially in the Oil and Gas industrial automation field. But what kind of technology could transform this incredible amount of raw Big Data in Smart Data?

What is Big Data

First and foremost, what does Big Data mean? The concept refers to data sets that are too large or complex to be dealt with by traditional data-processing application software.

A helpful way to understand Big Data is using the “five Vs”: volume, velocity, variability, veracity and value. These refer to the fact that the raw data elements constituting Big Data are generated at a massive volume, which are transmitted at near instantaneous speeds, come from many different sources, constitute a complete set for reliability and provide precious value that is impossible to get otherwise.

Extracting Big Data

In industrial Oil & Gas settings, data streams could be generated from the entire production process, but identifying useful data sources is just the start of the collection process. An organization must build a pipeline that moves data from generation to enterprise locations, where the data will be stored for organizational use.

Most commonly, this data ingestion process involves three steps: extract, transform and load. “Extraction” means that data is taken from its originating location; during the “transformation” phase, data is cleaned and normalized for business use; “loading” means that data is moved into a database, data warehouse or data lake to be accessed for use. Data management teams face additional tasks at each of these steps, such as how to ensure the data they have identified is reliable and how to prepare it for use.

Why Big Data is so important

Modern Oil & Gas plants are becoming increasingly complex and interconnected, creating new challenges that automation, driven by Big Data, can address. Such data comes from Smart Sensors, in particular within the Industrial Internet of Things (IIoT) networks.

The large amounts of data produced by the Internet of Things (IoT) and modern computer systems have enabled intelligent factories to quickly boost their efficiency and make significant gains in terms of reduced errors, increased uptime and accelerated production. The possibilities of interconnection, facilitated by the IoT, have created very large and complex information networks. Applied effectively, Big Data analysis can be leveraged in an automated industrial setting to fully understand root cause issues, improving performance.

Big Data helps to integrate previously isolated systems, meaning that companies can picture a complete visualization of the manufacturing processes. In addition, it automates data collection and analysis, facilitating a better understanding of the status of each system, both together and separately. Oil & Gas companies can combine this vast amount of information to develop a highly focused business intelligence model.

Therefore, Big Data is becoming one of the most vital elements in the manufacturing industry. It plays a primary role in the fourth generation of ERP (enterprise resource planning) systems, with the aim to transform outdated manufacturing facilities into highly automated and efficient plants.

The information is analyzed in three layers of perspectives including data from the past, present and future, and allows for a complete view and moreover projections. One one hand, this data-based integrated supply chain management approach increases value and efficiency in the manufacturing process, on the other hand, it helps in reducing inventory and capital requirements in the medium to long term.?

The challenge of transforming Big Data in Smart Data

Transforming Big Data in Smart Data is not easy. Most of the data is “dumb”, hard to find, impossible to connect with other data, and hard to comprehend. Information takes time and money to collect, compile, manage and analyze.

In this process, industrial automation companies face challenges such as: identifying and managing all the data held by the organization, accessing all the required data sets and breaking down internal and external data silos, achieving and maintaining good data quality, selecting and properly using right tools. Industrial automation companies have to find enough skilled professionals for the level of work required to meet organizational objectives and protect all the collected data, in compliance with privacy and security regulations.

An Industrial Automation Strategy

Key Solution Srl is an international consultancy firm in the field of Oil & Gas, where we have a proven track record of successful experiences. Since we started as field service engineering, we know how to deal with all the phases of the projects. We generally work in any type of plant, but during more than ten years of projects we now have a good experience in a specific industrial sector, where we can be considered specialists and can add our experience in the discussion of the logic plant control. That’s why we focus on Oil & Gas industry.

Key Solution Srl can develop and design from the beginning, focusing on specific task of it such as software implementation, hardware delivery, service engineering. As a Company working in the Automation and Information Technology sector, Key Solution is always following the quality process based approach cycle Plan, Do, Check and Act. We are certified ISO 9001, 14001 and 45001.

From our experience on the field we designed HIERARCHY 4.0 , a web-based application developed to support the analysis and activities in different lifecycle stages of a plant. Developing this innovative tool, our multidisciplinary team poured in their expertise and background in engineering, commissioning, maintenance and operation. Therefore, this product gets all the features tuned and optimized in every step of the project, from the beginning to the normal operations.

Why is HIERARCHY 4.0 approach - for transforming Big Data in Smart Data - so different compared to the other tools? Our web-based application gives an easy and immediate visualization of the data as a diagram, with readings in real time provided in a “hierarchical” view that allows a deep understanding of the system strategy.

Additionally, the diagram view is much more advanced and detailed than the simple matrices of other available systems on the market, allowing you to simulate and optimize industrial or internal processes (maintenance and engineering), saving time and improving the overall efficiency.

Engineers can use Key Solution’s web app during the design phase to verify the correct assignment of the elements, variables and logic directly on the hierarchy diagram: a diagram that shows a schematic safety logic plant, supporting the engineers to browse interactively and dynamically through the complex interactions of causes and effects. As a result, the engineering team can easily optimize the control system configuration, increasing its performance, security and reliability.

In order to reach its highest performance, the web app is best used in combination with a real-time data acquisition system, so that users can view the actual status of causes, effects and interlocks. The HIERARCHY 4.0 server receives real time data from the plant, with a scan time defined by the client, using a Web API.

All live data (such as status, activation, faults, force and blocks, bypass, MOS and override active on the control system) will be displayed on the diagram and every faceplate, providing operators with both an overview and a detailed view of the plant’s status. This feature is specifically meant to support the operators in decision-making, taking into account both the safety and the operability of the asset.

In conclusion, HIERARCHY 4.0 represents a very innovative tool for the engineering team to easily upgrade and optimize the control system configuration, increasing its performance, security and reliability. The result is improving the efficiency of the plant’s industrial automation by the use of raw Big Data transformed in precious Smart Data.

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2nd edition 2022 of Technical Bulletin of Society of Petroleum Engineers - SPE Italian Section

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