Many companies have cybersecurity policies that inhibit their ability to send data outside of company networks. These days, companies are struggling to maintain operations with the current constraints of remote work, reduced staff, or both...

Throughout the lifecycle of an industrial installation, information about that installation is shared through various diagrams. Even in today’s digital world, that installation knowledge is locked away in analog formats such as legacy, paper..

The engineering, procurement, and construction (EPC) industry face new challenges as technology adoption begins to separate winners from laggards. Many EPC companies see the vast opportunities they can achieve by implementing an overall digital..

Vast amounts of valuable information exist in industrial diagrams and document images which are vital to a number of areas in industrial operations, such as project planning and design. In this area, tabular information typically contains inventory..

In traditional reliability programs, the focus is generally to prioritize those assets that are most critical for the operation of your business. With machine learning and advanced analytics, new opportunities are arising to complement traditional..

In this second article of the Transitioning from R&D to Reality series, we focus on an industrial machine learning (ML) application: digitization of the engineering schematic diagram. Schematic diagrams are the bread-and-butter of the industrial..

In this video, I’ll explain to one of my colleagues, Nadia, why security is so important in the industrial internet of things (IIoT). As I’m out with our customers on a regular basis, I get several questions about security. Here I’ll go through my..

In this article, I discuss how you can identify the best use cases for the application of machine learning (ML) in industrial operations, from the perspective of technical feasibility and value generated. I recommend a strategy searching for common..

As an increasing number of industrial companies gain experience with advanced analytics, the term "anomaly detection" is becoming more common in discussions across a range of engineering and operating roles. People in a variety of jobs, ranging from..

Today’s oil and gas production engineers face several challenges to ensure that their wells are achieving optimal production. Companies are now looking at digital technologies and state-of-the-art data science to solve these challenges.

The Shale..

It’s easy to get carried away with the hype around digital twins. The term has been thrown around for a few years now and has also been in Gartner’s Top 10 Strategic Technology Trends in 2017, 2018 and 2019. However, what’s a digital twin? How can..

Recent advancements in digital tools allow us to dig into the vast amounts of data we have available and reveal patterns we weren’t able to detect earlier. We are able to build richer analytics and create digital solutions enabling us to monitor and..

The benefits of software as a service (SaaS) software are well documented, but can be challenging to achieve in the emerging area of industrial data-driven products. A few guiding principles can help.

Ah, the sweet promise of design-driven SaaS..

With the advent of the era of "Big Data" and the subsequent explosion of interest in applying data science techniques to all manner of problems, it has come as no surprise that heavy industry has been exploring these areas in recent years. The..

Your SCADA system is growing in complexity and capabilities, producing more data than ever before. However, we have reached a point where the issue is no longer an absence of data. On the contrary, there might be too much for the operators to..

As we’ve talked about earlier, industrial companies now have the ability to interact with physical equipment like never before. You’ve probably also heard that there’s an urgency for you to get started with your digital transformation. However, you..

If you work with natural gas, chemicals, or other industrial processes, it’s likely you deal with compressor systems. These systems tend to be complex, fit-for-purpose, and expensive. However, due to their role in maintaining phase states,..

The proliferation of alarms in control rooms and in the field can cause “alarm fatigue” for some operators. IIoT applications for human-in-the-loop decisions often involve additional alerts and notifications. Choosing the right problem to solve is..

We’ve all seen how successful internet giants have been at deploying artificial intelligence (AI). Now companies in many different sectors want to do the same. In this video, I’ll talk with Carola about the challenges many organizations in..

Predictive equipment maintenance is the ultimate goal of many digital initiatives in heavy industries. However, the reality is much more difficult than operators may anticipate. In this article, I discuss the path to predictive maintenance,..

There’s been a shift happening and it has a name. You definitely know it and have probably used it already. Depending on your point of view, this name strikes fear or excitement - digitization.

You’re tasked with the digitization of your assets and..

There's a growing trend for the need for edge technologies when implementing an industrial internet of things (IIoT) solution. Here I'll explore how the impact of edge can be increased through the adoption of edge analytics models. Taking it beyond..

There’s an emerging trend using machine learning (ML) in industrial applications. However, transitioning a solution from a research and development (R&D) setting to actual use in industry is not without hiccups. In this first article in our series, ..

CO₂ emissions are a major concern for many sectors and people in general. The major CO₂ emitters are well known: energy production, agriculture, live-stock rearing, industry, and transportation. However, few associate pumps with CO₂ emissions. In..

Big data, data lakes, cloud computing. Well-recognized terms that have generated a lot of hype in recent years. Many industrial internet of things (IIoT) companies hope to recreate the wild success of the big data giants using their data to generate..

Are you considering data-driven solutions to improve or create new business outcomes, and/or business models? Do you need to consider how such a solution would fit within your infrastructure? As I architect solutions at Arundo, I’m often asked to..

Have you considered starting an industrial data science initiative but don’t know where to start? Keep on reading and I’ll tell you 4 important things you should know.

1. What kind of operational challenges can data science address?

Machine..

Referring to their internal digital program, a customer once said: "On Artificial Intelligence (AI) we have more pilots than a major airline". This is a common pitfall companies struggle with as they move from proof of concepts (PoC) to actual value..

Maybe you’ve heard this type of story before: an industrial company announces the start of a major digital initiative. Time goes by, but nothing seems to happen. After many months, and many meetings, there is little to show for the efforts.

..

For industrial companies, the ability to interact with physical equipment has never been easier. Now you have the ability to access vast amounts of data from a variety of sources in order to make meaningful business decisions. Many of your..

There’s currently debate among industrial leaders, digital evangelists, academic scholars and business researchers whether Chief Digital Officers (CDOs) are making a difference; if they’re needed going forward; and if so, what should their focus be...

Setting out the best strategy to implement data analytics solutions in an industrial environment can be a roller-coaster ride. In theory, the key to solving many of the challenges that your business is facing is simple: Data – the more, the better...

Today’s oil and gas production manager faces a myriad of challenges in ensuring that wells are consistently producing at their highest possible potential. The advent of shale, and its high-volume drilling process, means that onshore production..

Over the last few years, the utilization of data science and machine learning techniques in asset-heavy industries have taken off. Digital transformation is moving from proofs of concept into an ecosystem of fully-fledged data science applications...

Few people realize how unlikely it is that their industrial analytics initiatives are going to deliver real bottom-line value. In this post, I’ll share some statistics you need to be aware of. I’ll then talk about some of the reasons why the odds..

Most companies have started or planned to start a digital program. One they hope will transform their business, deliver improved results and move their company to higher levels of performance and shareholder value. So far, very few have seemed to..

Solving problems for the asset-heavy industries can be challenging due to the nature of the work. Blue-collar employees, lots of manual labor, old expensive assets, and extremely high-risk situations. Where do you begin to build a solution for an..

If you’re an engineer, operator, adviser, or executive working in heavy industry, odds are high you’ve heard more and more about trends, buzzwords, and ideas suggesting software and data science will radically transform your business. However, the..

In the world of the Industrial Internet of Things, or IIoT, we talk about the impact enterprises can derive from combining their Information Technology (IT) with their Operational Technology (OT). There’s an obvious linear relationship between..

In this article, I explain how tag-based data contracts simplify the time and effort required to create tangible business value from local operating data.

It’s sometimes hard to remember in these days of touchscreen human-machine interfaces, but the..