Ensuring Worry-Free Operation in Smart FactoriesWi-SUN sensors streamline machine condition monitoring

AI (Artificial Intelligence) and IoT technologies play a crucial role in the creation of smart factories. These enable cost-effective networking of production equipment while minimizing the need for human intervention. Moreover, continuous monitoring of production equipment allows for the early detection of deterioration that can lead to breakdowns, preventing disruptions to the entire production line.

The transition to a smart factory presents several challenges, with cost being a primary concern. Generally, the implementation of a smart factory is perceived as expensive, largely due to the need for cutting-edge equipment to establish a smart production system. This often results in significant upfront investment. What’s more, operating and maintaining such advanced equipment require employee training, adding to the overall expenditure.
Dealing with equipment breakdowns is another issue. Regardless of how sophisticated the system is, there is always a risk of failure. A single equipment malfunction in a factory can potentially halt the entire production line, resulting in significant losses. In addition, the more complex the system, the longer it takes to restore operations, further impacting the bottom line.
This is where preventive maintenance comes into play. Its purpose is to monitor and assess the degradation of machinery, equipment, and components that make up the production line to proactively minimize the risk of breakdowns.

Upgrading Existing Systems for Machine Condition Monitoring

Operating a smart factory safely hinges on real-time monitoring of the factory environment and equipment. Continuous monitoring allows the status to be constantly assessed, helping to prevent failures before they occur. This method is commonly known as condition monitoring, and its successful implementation requires three elements: advanced sensor technology, cutting-edge semiconductor products like power devices and analog technologies, and robust communication technology.
A key benefit of machine condition monitoring is the ability to address equipment issues at a relatively low cost. This is achieved by simply upgrading the existing production line with a monitoring system, bypassing the need for major overhauls. There is no need to invest in expensive technologies such as industrial robots or AMRs (Autonomous Mobile Robots).

Despite the advantages, upgrading production equipment still involves some costs and downtime, which can hinder adoption in some cases. In response, ROHM has developed a solution that significantly lowers this barrier, combining sensors with wireless communication technology. The range of sensors includes accelerometers, color sensors, light sensors, and current sensors. For wireless communication, there are options like low-power Wi-SUN that ensures stable communication even within factories, and battery-free EnOcean.
As both protocols are either low-power or eliminate the need for batteries, the sensor nodes themselves can be made smaller. At the same time, wireless connectivity allows for flexible placement, cutting costs and installation time. ROHM provides a simple, cost-effective method of retrofitting existing factories with wireless sensor systems for machine condition monitoring.

Enhancing Monitoring Accuracy with Cutting-Edge Analog Technology

ROHM’s solution leverages the latest analog technology to boost sensor node performance, resulting in greater monitoring accuracy. For example, a current detection amp IC is combined with a shunt resistor to form a current sensor capable of detecting current flowing through a circuit.
This component boasts two key features. One is high current detection accuracy that maintains ±1% across the entire operating temperature range. This is accomplished by fine-tuning the resistance value of the gain resistor built into the IC to increase gain accuracy. The other is an exceptionally compact design that reduces mounting by approximately 50% compared to the conventional method of combining an op amp IC with discrete semiconductors and passive components (op amp circuit).
Furthermore, a high maximum input voltage of 26V supports current monitoring and overcurrent detection across a variety of applications, including industrial equipment using 24V power systems.

AI Chips for Standalone Smart Factories

ROHM is also pioneering AI solutions for standalone smart factories. While many current endpoint AI systems focus on inference to provide advantages such as reduced network load and power consumption, ROHM’s AI solution ‘Solist-AI™’ goes a step further. In addition to inference, endpoint learning can be carried out without relying on a cloud environment. This unique capability, which significantly reduces development time, costs, and power consumption compared to existing cloud-based and endpoint AI systems, is particularly promising for machine health applications.

Integrating New Solutions into Existing Systems

The common belief that transforming an existing factory into a smart factor simply requires introducing the latest industrial equipment, robots, and AI devices is a misconception. This alone is insufficient. The key lies in effectively utilizing the facilities and equipment to enhance operational efficiency, quality, productivity, and, ultimately, increase added value. Even in established factories, updating production equipment and systems with new solutions can boost cost efficiency while maintaining high safety standards.

*EnOcean® is a registered trademark of EnOcean GmbH.
*Wi-SUN® is a registered trademark of Wi-SUN Alliance.
*Solist-AI™ is a trademark or registered trademark of ROHM Co., Ltd.