Let’s Discuss "Machine Wearable" Sensor Technology

Sensors Insights by Bryan Christiansen

Thanks to the growing popularity of wearable devices like the Apple Watch and Fitbit, a previously little-known technology has now become mainstream. The Internet of Things (IoT) refers to unique devices that are part of an ever-growing network of objects that connect to the internet and can interact with other internet-enabled devices and systems.

Today, these items are not slowing down in popularity and many industries are taking note. From healthcare to sports with its human wearables, to the business sector with machine wearables, it’s now apparent that the innovative advancements made in this area so far are a but the “tip of the iceberg.” And, the possibilities are endless. This article focuses on the industrial applications of this technology and a few of the benefits to organizations that use them.

 

What Are Machine Wearables?

Former Intel CEO, Brian Krzanich, first used the term “machine wearables” when referring to the practice of fitting machines with sensors to capture data about performance in real-time. The data is then used to identify maintenance needs before they become issues, increase productivity, and lower costs. Although consumer IoT applications still accounts for 63 percent of the wearables market, business/industrial applications are increasing annually giving rise to another category - the Industrial Internet of Things (IIoT).

IIoT Industrial Internet of Things (IIoT) is a subset of IoT, aimed specifically at industrial applications. IIoT is about the inter-connectivity of machine to machine, the resultant data exchange, and its benefits to the industry. But, for these machines to be considered a part of the Internet of Things they need the ability to “talk” to each other. Fortunately, industrial and technology companies have been able to achieve this by creating sensors that connect devices and allow them “talk.”

 

Sensors And Connected Equipment

The IoT is more common than you may realize. For example, every time you access a remote camera from your smartphone you are using IoT. Essentially, the IIoT works in a similar manner but is developed specifically for larger assets and systems. The equipment communicates via sensors that measure:

  • temperature,
  • pressure,
  • environmental conditions,
  • vibration,
  • noise, etc.

The premise behind this setup is that smart machines perform better than humans at capturing, analyzing, and communicating large amounts of real-time data.

 

Applications of Machine Wearable Sensor Technology

Incorporating machine sensor technology with an organization’s equipment can deliver significant improvements in different aspects of their operations. Some ways which businesses are using it includes the following.

Manufacturing:  With IoT technologies, factories are becoming more software-defined. Plant owners are having sensors fitted on conveyor belts, packaging machines, cutting machines, air compressors, etc. to enable automation and remote monitoring and enhance almost every stage of production.

For instance, European aircraft maker Airbus launched its "factory of the future" to streamline operations, reduce errors, and improve workers’ safety. This factory is a digital one with sensors on machines and tools in the plant and manned by staff fitted with wearable technology.

Maintenance Management: Sensors fitted on a physical asset transmit information on how that piece of machinery is operating directly to a data exchange network from where it is interpreted into applicable information. With time, this machine data analysis reveals a pattern of events that are responsible for equipment failure and can warn maintenance personnel of impending problems (downtime).

Based on this timely information, workers can then plan to have equipment maintenance done well ahead of expected failure. This exchange of information and generating of proactive actionable insights is the essence of Predictive Maintenance (PdM).

A major advantage of this kind of IIoT assisted maintenance strategy becomes evident when one considers a business or factory that owns hundreds or even thousands of assets. Imagine that in order to free up the maintenance team and allow them time to focus on mission-critical machinery, such a business concern decides to adopt Total Productive Maintenance or Predictive Maintenance.

Surely in the above scenario, with maybe thousands of assets under the care of different employees, it would be easier to monitor each item and keep them running efficiently. That’s if staff could be alerted on time about equipment failures.

Augmented and Virtual Reality for Employee Training: Companies can achieve faster and improved training results by using virtual reality (VR) and Augmented reality (AR) to simulate real-life training scenarios. Employees, whether new or old, can wear IoT-enabled glasses or visors (and other devices) to get immersive and interesting alternatives to traditional text and book learning methods (figure 1).

Fig. 1: Employees can wear IoT-enabled glasses or visors and other devices.
Fig. 1: Employees can wear IoT-enabled glasses or visors and other devices.

Companies like Walmart have started using this technology successfully to train recruits on several kinds of situations they could face in the workplace.

Artificial Intelligence: Artificial Intelligence (AI) refers to the transfer of intelligence from humans to machines. Electrical and mechanical systems, especially robots, are fitted with sensors that allow them learn tasks and analyze situations for performing specific sequential tasks. These machines can scrutinize data and make accurate decisions based off that data without human intervention. In the manufacturing industry, a common application of this is robots separating good parts from defective ones on the assembly line.

Figure 2

Energy Management: Sensors are being used to reduce the overall power consumption in the built environment. There is a lot of research going on in this regard but so far, one way these energy-efficient sensors can save on energy costs is maintaining a healthy and comfortable indoor air quality. An example is heat exchangers that use differential pressure sensors to balance the indoor climate without the need for the usual external energy sources.

Figure 3

Benefits of Machine Wearable Technology

  • Predictive maintenance. It allows businesses to foresee defects in machinery before they occur and reduce downtime.
  • Flexibility for mobile equipment. Wireless sensors make it easier to move equipment around and reconfigure them since there are no cables involved.
  • Reduced errors. Sensory technology reduces the reliance on humans and the inherent mistakes and costly errors that are bound to occur from time to time.

Challenges of Machine Wearable Technology

  • Amount of data. The rate at which data is generated may become staggering depending on the type of equipment in question. Companies will need to understand this and prepare to handle this.
  • Power consumption. Some sensors are required to transmit data in limited cycles, so the power requirements would be low. But, for systems and assets that generate large amounts of data continuously, the power demand can become considerable.

As more companies strive to remain competitive, it’s obvious that no matter their industry or size, they can use machine sensory technology to improve their bottom line in one way or the other. From large scale factory-wide applications, to just managing the power consumption in a single building, professionals in every sector will do well to investigate how best their organizations can benefit from this technology.

 

About the author

Bryan Christiansen is the founder and CEO of Limble CMMS. Limble is a modern, easy to use mobile CMMS software that takes the stress and chaos out of maintenance by helping managers organize, automate, and streamline their maintenance operations.