IIoT: Acting on All Big Data
By Rachel K. Carson, MarCom Analyst for Process Industries
When data comes to mind, what do you think of? It might be definitional, such as facts and statistics. For others, data might seem like a complicated scientific term for confusing numbers and industry jargon. Whichever way you see and define data, it is important to know that data is what drives today’s industrial success. This is especially true in the refining industry. Today, refiners are relying more and more on IIoT, or the Industrial Internet of Things, to help connect operations, collect better data, analyze that data, and act upon it to make better overall business decisions.
The industrial Internet of things (IIoT) plays an important role in the operation of a refinery today. The falling cost of connectivity and data storage, processes across the entire Oil & Gas value chain are now able to gather more data from more devices, assets, operations and processes than ever before. Refiners in particular, stand to gain value quickly because the existing IT infrastructure is more mature compared to extraction (upstream) and distribution (midstream) processes. The foundation of this operational perspective starts with the basic principle of the closed loop process – Connect, Collect, Analyze and Act.
Why IIoT is needed now…
The age of the customer is radically changing the dynamic between businesses and their customers. Just as the abundance of readily available information has inflated the expectations of I&O’s customers, it has also inflated the expectations of their current and future employees. In 2015, Millennials (ages 18 to 34) surpassed Gen Xers (35 to 50) as the largest demographic in the US workforce. By 2025, millennials will become the majority. However workforce evolution is not the only driving cause of immediate IIoT implementation. Other factors driving IIoT implementation include the:
- Desire for increased variants & shorter lifecycles
- Need for cost reduction
- Increasing regulations
- Adaption to digitalization
With IIoT software implementation, these capital constraints yield to overall operational efficiency.
Cutting-edge software solutions help bridge the gap between unused data and profitability
Big Data allows the collection of large amounts of data. But the problem that arises with Big Data is that more than half of the collected data is not utilized; it is forgotten about or turns in to Dark Data. By collecting, visualizing, analyzing, and contextualizing the data, it can be acted upon for overall operational benefit. We call this closing the loop between operations and creating a unified IIoT solution across the entire supply chain.
The principle of a closed-loop process is fundamental to performance improvement. Improving a process requires the monitoring of the key performance indicators (KPIs) and detecting of any deviation from the target; understanding the process context to assess various options; making a decision on the most appropriate corrective action (provided one has the authority to do so); and finally ensuring that the decision actually gets executed or acted on.
Reducing latency – i.e., compressing the time taken to close the loop – is the journey to becoming a real-time business. The four steps in the information management loop (connect, collect, analyze, act) as illustrated represents the technology-agnostic software framework for analyzing problems and designing solutions across the entire business process hierarchy. This also ensures that all big data is acted upon.
Industry-specific closed loop solutions with IIoT bring about the following benefits:
- Reduced operating cost
- Agile process control
- Increased uptime
- More productive, empowered personnel
- Greater environmental and personnel safety
- Increased profitability
Other industry-related successes include of smarter assets, internet reliability, cyber security solutions, data integrity, as well as, actionable data.
Why IIoT is not going away…
IIoT investment is growing in process engineering and refineries at a rapid rate. The oil and gas industry spent $3.5B on big data-related projects in 2015 with projected annual growth of 31% by 2020. This growth is driven by oil producers’ ability to capture more detailed data in real time at lower costs to drive operating efficiencies and reduced downtime. In 2015, the energy market spent $7B on IoT solutions. Projected compound annual growth rate of this spending is expected to climb to $22B in 2020. McKinsey Global Institute Research also projects a period of aggressive growth, estimating that the impact of the IoT on the global economy might be as high as $62B by 2025.
Among trends in the oil and gas industry, the growing use of IoT-enabling technologies can be attributed to a few principal influencers:
- Accelerated use of mobile human machine interface (HMI) technologies via smart phones, tablets and wearables, combined with IP access to data and information are making operators and service personnel more productive.
- Affordable access to cloud technology, which requires only a browser and internet access to connect, makes mobile access and working from the field or off-site and sharing that information easier than ever.
- Refinery operations are using increasingly diverse data sources—from sensors to flow meters, temperature and pressure gauges, actuators and controllers, along with improved analytics applications.
Ready to learn more about IIoT? Read the whitepaper…
The Delivering Closed Loop Business Operations for the Refinery Enterprisewhitepaper outlines the importance of IIoT, closed-loop operations solutions, and why these solutions allows operators to efficiently act on that data to make more time efficient decisions. Download Now.
Come back for Blog #3 on the trending topic of IIoT and how it is playing a powerful impact within refinery operations.
Livia Wiley is the Sr. Product Marketing Manager for SimSci software at AVEVA. She is primarily responsible for expanding SimSci’s brand awareness and marketing of its design, simulation & training, and optimization software. She has more than 20 years of experience in process simulation; assisting clients model, troubleshoot, and optimize their processes through technical and economic studies. Prior to joining Schneider Electric in 2014, she worked for suppliers of process simulation and automation technology, including Honeywell, Aspen Technology, and legacy SimSci. Livia holds a B.Sc. in Chemical Engineering from Queen’s University, and a M.Eng in Chemical Engineering from the University of Houston.