Startups and Disruptors within the Plant Industry: Predictive Maintenance Technology

by Yunki Jo | August 29, 2023

Continuing from the startup companies that I introduced last week, which specializes in industrial safety via wearable equipment, I'd like to shift our focus this week to startup companieswhic offers predictive maintenance technology.

Startups involved in the development of plant maintenance technologies aim to address the following needs: boost productivity and at the same time, prevent accidents.

Problem that can be addressed by maintenance-related technologies: Just as all machines experience deterioration with time, equipment in plants faces an elevated probability of issues arising, accompanied by increased frequency. As a result, scheduled maintenance occurs at set intervals. However, unexpected complications not only trigger factory downtime and equipment repair expenses, but also encompass losses equivalent to the duration of plant shutdown. Furthermore, if problems with individual equipment or systems escalate into accidents, they can yield not just property damage, but also human casualties. Hence, the maintenance technologies presented by the upcoming startups hold indispensable significance for the industry.

Prediktas - Predictive Maintenance (IoT)

Solution:

Prediktas delivers predictive maintenance technology that identifies shifts in equipment energy, anticipating potential issues and delivering solutions. Employing sensors capable of recognizing energy fluctuations on each device, the system sends immediate notifications to workers' smartphones upon detecting abnormal factors, enabling rapid interventions. Prediktas focuses its technology on equipment responsive to energy flow monitoring, including compressors, fluid-controlling pumps, and current-regulating transformers.

Prediktas is gaining notable industry momentum with its integrated solution, encompassing IoT sensors, hardware, software offering equipment status updates and report generation, and a service that links maintenance experts directly with customers.

Neuron Soundware - Predictive Maintenance - AI, IoT

Solution:

Neuron Soundware provides technology that enables diagnostic and predictive maintenance by analyzing sound patterns from machines. The process for analysis and diagnosis using sound involves the following steps:

① Installing IoT devices on the machine and connecting them to the internet to initiate recording.

② Recording common sounds and other relevant data from the machine to generate a dataset.

③ Activating user’s account on Neuron Soundware's analysis and monitoring portal.

④ Using the recorded data to calibrate and verify algorithms developed by Neuron Soundware.

⑤ Redeployment of the refined algorithms to the IoT devices installed on the machine.

⑥ As more data is collected, the algorithms become more robust and are used to analyze and diagnose issues with the machine.

Drawing inspiration from skilled workers and engineers who rely solely on sound to identify machine anomalies, another startup named Orelia (www.orelia.fr) has also adopted this sound-based technology. Orelia provides technology similar to that of Neuron Soundware.

CorrosionRADAR - Predictive Maintenance - Sensors

Solution:

In many industrial facilities, piping materials and pressure vessels, which are crucial for fluid flow, are often encased in insulation materials. This serves the dual purpose of providing thermal insulation and personal protection (PP) for workers. However, when these components are hidden beneath insulation, the assessment of corrosion caused by fluid leaks or moisture becomes a challenging task. This often requires the removal of insulation to inspect corrosion. The process can be streamlined by enabling corrosion assessment without the need for insulation removal. This not only reduces unnecessary labor but also mitigates equipment damage resulting from corrosion.

CorrosionRADAR designs and offers Corrosion Under Insulation (CUI) monitoring technology, presenting a management solution enabling the early detection of corrosion on piping materials and pressure vessels concealed by insulation materials.

The attached sensors can be fine-tuned for sensitivity based on the equipment's environment and risk level. It also offers flexibility in mounting on diverse surfaces, making them suitable for intricate structures and a range of field conditions.

Roboplanet - Maintenance - Robotics

Solution:

Roboplanet possesses an array of robotic technologies designed for conducting inspections. Particularly noteworthy is their offering, ALTISCAN, which traverses walls at a speed of 12 meters per minute to gauge thickness and autonomously generate reports. They also provide the TaurUS, an industrial drone that conducts ultrasonic inspections while flying around structures, and the HERMINE, a portable corrosion scanner capable of swiftly assessing extensive metal surfaces for signs of corrosion.

Roboplanet, a French company, is a startup with specialized technology in the field of Non-Destructive Testing (NDT), to the extent that it has been employed for non-destructive inspections within the French Navy.

Predictive maintenance appears to be the hottest innovation in the plant industry. The reliance on skilled workers/engineers for anomaly detection and analysis of equipment is being replaced by AI technologies such as machine learning, made possible by the accumulation of operational data and advancements in computing technology. This shift not only shields workers from perilous environments but also facilitates heightened precision in issue identification and analysis.

Next week, I will provide information on how big data and AI. I'll also discuss how these technologies contribute to enhancing the competitiveness of various plants.

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