Modernizing manufacturing with artificial intelligence

April 04, 2018 - 03:00pm

A sensei is a teacher or instructor, usually of Japanese martial arts. Sensai the company offers an augmented productivity platform for manufacturing operations, but transferring knowledge to help people make better decisions is at the heart of the company’s concept, according to CEO Porfirio Lima. “We believe that the most valuable asset an organization has is the knowledge that comes from its people.”

He added that shop personnel make decisions based on their knowledge and can teach a machine to make better decisions about how to maximize throughput. When the machine has enough data and knowledge, it could also help the shop workers make better decisions. “When we talk about augmented productivity, we believe that at some point we will have AI helping people make decisions,” Lima said.

Based in Monterrey, Mexico, and backed by Metalsa S.A. de C.V., a manufacturer of automotive structural components, Sensai launched a pilot program in the U.S. in late March. “We are a manufacturer that started to do software and not the other way around,” Lima said.

The company reports that the augmented productivity platform increases throughput and decreases machine downtime with an artificial intelligence technology that enables manufacturing operations teams to effectively monitor machinery, accurately diagnose problems before they occur and quickly implement solutions.

Lima said AI is a high-level name for machine learning, and machine learning is one of the easiest ways for Sensai to optimize a process. The current focus is primarily on process control and quality control to proactively target a production asset and avoid a major catastrophic failure, for example.

By installing a set of noninvasive and nonintrusive wireless sensors that interconnect through a “smart mesh network of gateways,” Sensai says it collects data through its industrial internet of things hub, gateways and sensors, and instantly sends it to the cloud or an on premise location to be processed and secured.

While many manufacturers gravitate toward big data, Lima said the focus for him is on smart data. “That’s why the smart mesh works, because we only connect the sensors that make sense.”

With a cloud-based approach being effective when processing a large amount of data for complex applications, Lima emphasized that Sensai places a high priority on security and feels confident in its efforts. Nonetheless, the company has many risk-averse customers and can deploy the platform using a local server so no information travels outside a facility and no external information enters.

Manufacturers of varying sizes can participate in the pilot program, Lima said, ranging from those with $1 million to $5 billion or more in annual sales. He added that a modest investment can generate significant results. To connect the software to one asset, the company offers a license for $1,000.

“Through that, you will be able to grasp some of the value that we can develop,” Lima said, noting Sensai can deploy significantly more robust pilot programs.

Related Glossary Terms

  • process control

    process control

    Method of monitoring a process. Relates to electronic hardware and instrumentation used in automated process control. See in-process gaging, inspection; SPC, statistical process control.

  • quality assurance ( quality control)

    quality assurance ( quality control)

    Terms denoting a formal program for monitoring product quality. The denotations are the same, but QC typically connotes a more traditional postmachining inspection system, while QA implies a more comprehensive approach, with emphasis on “total quality,” broad quality principles, statistical process control and other statistical methods.



Alan holds a bachelor’s degree in journalism from Southern Illinois University Carbondale. Including his 20 years at CTE, Alan has more than 30 years of trade journalism experience.


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