Three Real-World Case Studies for How Manufacturers Can Maximize Edge Computing

The manufacturing industry is producing more data than ever before as sensors become readily available. 

Surprisingly, very little of that data is leveraged to improve better real-time decision making. Rich data sets are rendered useless if they aren't seamlessly incorporated into an organization's analytical platform. To produce usable data insights, organizations must make sure everyone is speaking a common language through the data.

This is where edge computing comes in. Edge computing can collect, process and make sense of data to enable preventive maintenance, improve performance and drive new applications for efficiency.

Rather than sending all data for processing to corporate or cloud data centers, manufacturers can provide compute closer to the data, which decreases latency, improves response time and saves costs, particularly when considering the massive data footprint of most large manufacturers.

But while edge hardware and infrastructure are necessary to optimize rich data sets, they are simply a cost to service providers. The true value — where service providers will make money — lies in the applications that run on top of this infrastructure.

Therefore, no matter the industry, it is important to consider key use cases and the related applications that are most likely to gain market traction.

Organizations should identify and prioritize specific use cases that will create value for the organization before diving deep into which algorithms or platforms should be used. Data-driven insights should help companies answer larger questions that inform strategy and goal setting, such as "How are our teams performing and how effective and high-performing is our culture?"

Some of the manufacturing use cases most likely to deliver the greatest return on investments, according to research commissioned by WWT, include cobotics, autonomous on-site vehicles, and deep sensor networks for predictive maintenance, asset performance management and quality control. 

Let's take a look at a few real-world examples with a company WWT works with, QiO Technologies, which provides AI-infused analytical applications that predict and prescribe actions to unlock trapped productivity and efficiencies across a variety of industries, including manufacturing and utilities.

World's largest tableware manufacturer increases production while saving money.

For instance, ARC, the world's largest tableware manufacturer, produces five million pieces of glass every day across two production lines and was able to create a dynamic Energy Efficiency Index (EEI) for each of its furnaces to help forecast energy consumption and efficiency through scenario planning. Using QiO's Foresight Energy product, ARC was able to improve line production throughput and rescue energy by 8 percent per furnace annually. 

Construction engineering firm reduces ship fuel consumption, saves more than $200,000 per year.

Lloyd's Register was commissioned by a British ship operator to analyze fuel consumption. The operator required a software-based solution that could ingest high-frequency sensor data in real time, provide on-board analytics and bespoke visualizations, scale rapidly across the operator's fleet, and be delivered as a low-cost service.

Marine vessels are equipped with sensors that produce massive amounts of data at different frequencies and output in different formats. The data was manually retrieved in batches at the completion of the journey and analyzed using legacy tools like MATLAB. Reports—in PDF—took several weeks to complete. The significant lag time severely limits the ship operator's ability to optimize fuel consumption, resulting in increased cost.

QiO teamed with Lloyd's Register to build and deploy an end-to-end data ingestion, visualization and correlation solution in just four weeks. The mobile device compatible application was deployed in a secure cloud environment and provides the ship operator with drag-and-drop, dynamic dashboards and customizable charts based on real-time sensor data. More than 45 million data points across approximately three million rows from 50+ channels streaming in at 20kHz were ingested, standardized, augmented with external data sources, calculated and visualized.

In the end, Lloyd's Register was able to detect anomalies that drive excess fuel usage, mapping to historic, current and predictive insights for a single ship or across the entire fleet, achieve up to 8 percent improvement in fuel efficiency for every voyage and save approximately $200,000 per ship each year in the process.

Global oil and gas engineering firm develops flagship digital pipeline integrity service.

Penspen has been providing engineering, project management, asset management and integrity services to the energy industry worldwide for over 65 years. During its history, Penspen has undertaken over 10,000 projects, becoming one of the world's most trusted assessors of oil and gas pipeline integrity. 

Penspen believe the future of pipeline integrity is in making their world leading expertise more accessible to all pipeline operators.

The THEIA application consolidates Penspen's years of expertise, industry knowledge and quality assurance using QiO's Foresight Maintenance technology to enable clients to take control of the integrity of their pipelines using industry standards and trusted methodologies whilst ensuring maximum security for all their critical data.

With QiO Foresight Maintenance, Penspen:

• Digitized its integrity assessment analytics expertise.
• Created a service allowing clients to pro-actively manage their pipelines, to address defects and prevent failures.
• Provided clients with results and reports in seconds rather than weeks.

Conclusion

Adopting a more data-driven culture and harnessing the power of data analytics can be a game changer for companies looking to begin or speed up their digital transformation journey.

The more seamlessly data can be analyzed, models built and insights integrated into day-to-day workflows, the more rapidly organizations can innovate and make decisions on the fly.

However, investment alone doesn't lead an organization to a more data-driven culture. Critical to adopting a more data-driven decision-making culture is understanding the end game.

Commercial innovation — the identification of new technologies and incorporating them into the business enterprise-wide — is hard, particularly when many of the use cases that will truly transform the world are not yet fully developed or even thought of yet, as is the case with edge computing. 

Before service providers can tap into the new value being created at the edge, they must identify and understand vertical use cases and related applications most likely to gain market traction.

WWT, which works with 70 of the top Fortune 100 companies across a range of commercial sectors, is in unique position offer service providers a first-hand view of emerging vertical use cases.

By combining our partnership with organizations like QiO and our extensive capabilities and deep experience serving enterprise customers, WWT can help service providers develop and execute on edge strategies to achieve results that will deliver transformational experiences to end customers.