Vice President of Industrial AI, Maya HTT
Artificial intelligence, machine learning, and deep learning are advancing industries and changing the way people work, live, and create.
The Internet of Things (IoT) refers to the many computing devices globally that are connected to the internet and interrelated, while the Industrial Internet of Things (IIoT) is the use of IoT technology in a business setting. IIoT is increasingly being used by smart companies to attain business gains.
But working with sensors, big data, artificial intelligence (AI), software development, and analytics to measure and optimize industrial processes requires skill and experience. Maya HTT provides computer-aided engineering software to industrial clients — such as renowned companies in the aviation, automotive, and electronics industries — to optimize their design, manufacturing, and operations.
Using data to support your business use case
IIoT implementation begins with data. “Industrial clients, whether they manufacture lithium batteries, cars, or airplanes or operate ships with many different generators, turbines, pumps, and conveyors, have been collecting more and more data over the last two decades,” says Remi Duquette, Vice President of Industrial AI at Maya HTT. He notes that such clients often have significant amounts of data, but limited knowledge on how to leverage it. “Now they’re at a stage where they have enough data to leverage newer technologies like AI, machine learning, and deep learning,” he says.
Data increasingly forms the foundation of successful business strategies, product innovation, and customer satisfaction. From improving efficiency and machinery performance to maximizing asset health, avoiding incidents, reducing product quality issues, creating a more secure manufacturing environment, and optimizing product design, there are countless benefits of IIoT implementation.
Finding the right partnership
Industry has reached the point where a company’s ability to compete effectively hinges on its proficiency in collecting, interpreting, and understanding data.As smart devices proliferate and industrial-grade, reliable high-speed networks become the norm, AI and machine learning technologies are becoming must-have tools. Establishing an AI roadmap and building the skills to cope efficiently with a massive, globally-distributed influx of data will be imperative — as will making the right decision about a service provider to partner with.
“You should ask all your vendors to show examples,” says Duquette. He recommends getting to know a potential provider and asking them about previous projects they’ve done that are similar to your company’s environment. “They should be able to understand the main roadblocks that will come up,” he says.
From the top down
“We need corporate buy-in and the support of upper management to build a roadmap to get to the more sophisticated endeavours and to make sure that they’ll stay the course,” says Duquette. “AI will have successes and failures, so we need buy-in that they won’t stop at the first sign of problems.”
IIoT implementation often requires a company to make a variety of changes, from bringing in new connectivity, networks, technologies, and processes to hiring new people. This is the perfect stage to work with a partner who can deliver an AI readiness assessment and digital transformation roadmap. The right specialist can help organizations ensure a smooth and adaptable transition to a connected future.
“Engineers are very well-placed to leverage these technologies for the problems they face on a daily basis,” says Duquette.