The manufacturing industries are undergoing a digital transformation worldwide, spurred by the COVID-19 pandemic, which is speeding up the adoption of Industry 4.0. This shift to digital is fueling advances in smart sensors that not only capture sensing data, but also interpret that data into actionable insights for a variety of applications in the Industrial Internet of Things (IIoT) space.

Dean Bartles
Chief Executive Officer and President,
Manufacturing Technology Deployment Group
Jeffrey Case
Director of Design Engineering and NPD,
PCB Piezotronics, Inc.
Aric Prost
Senior Global Director, OEM,
Stratus Technologies
Brad Walters
Founder and CEO,

The smart sensors market is expected to grow at a CAGR of 19 percent over the forecast period (2021-2026), according to Market Research Future. What’s driving the escalating demand for smart sensors and which industries will expect to see the greatest demand for sensor technology in the coming years? Tech Briefs posed questions to four industry experts to garner their views on the future outlook for smart sensors and IIoT.

Our roundtable participants include Dean Bartles, Chief Executive Officer and President,Manufacturing Technology Deployment Group , Jeffrey Case, Director of Design Engineering and NPD, PCB Piezotronics, Inc. , Brad Walters, Founder and CEO, Monnit , Aric Prost, Senior Global Director, OEM, Stratus Technologies .

Tech Briefs: The use of “smart” sensors is becoming more prevalent as the IIoT and Industry 4.0 are more commonplace in manufacturing. How are smart sensors being used to improve manufacturing?

Dean Bartles: A great example of how smart sensors are being used to improve manufacturing is a program my company has with the DOD to establish a prototype additive manufacturing supply chain. There is a huge desire to adopt metal additive manufactured parts in the aerospace and defense markets. Advantages include complexity of design, speed in production, light-weighting, etc. However, the variability currently found in metal additively produced parts from machine to machine and even part to part is still a major impediment to adoption. Using sensors and an IoT edge device, we are collecting real-time process data during the printing process such as laser energy, scanning speed, hatch spacing, chamber humidity, etc. and then providing this data to the customer along with the parts produced. The customer is then able to interrogate the data file to ensure all parameters were maintained within a specified range throughout the build process, thus providing a higher level of confidence in the integrity of the parts.

Jeffrey Case: Smart sensors are being deployed in manufacturing facilities across all industries to collect critical information that, with the correct analysis, can create solutions that reduce or eliminate unplanned downtime (part replacement costs, manpower, and lost opportunity costs); increase safety by substituting permanently mounted sensors for measurements requiring human intervention; and improve productivity through precise feedback control and the monitoring of variations in the production process, ensuring manufacturing stability.

Brad Walters: Driving greater efficiency is a top benefit of integrating a platform of smart sensors into manufacturing environments. Smart sensors create smarter factories where you can monitor, control, and improve virtually every aspect of operations with real-time data-driven insights; predict equipment maintenance and quickly trigger protocols before malfunction or failure; automate data logging for streamlined trend analysis, record-keeping, and regulatory compliance; and be alerted of environmental and equipment problems. Sensors that connect people, machines, equipment, and inventory to the empowering capabilities of the IIoT enable manufacturers to produce with greater transparency, efficiency, and overall quality.

Aric Prost: The considerable decrease in the cost of sensors and transmitters coupled with improvements in wireless technology have made it feasible for OEMs, machine builders, and operations teams to install sensors and collect data previously inaccessible. This is the industrial edge where data is being generated, and the ability to measure more process variables more accurately grants better insight and achieves the promise of IIoT and Industry 4.0. The opportunity is a leap forward in monitor and control to drive desired outcomes such as higher quality products, less downtime, or yield improvement.

Tech Briefs: Sensor data fusion provides the ability to combine different sensor technologies in one application. What are the challenges manufacturers face in managing — and effectively using — the increased volume of data collected?

Dean Bartles: The proliferation of sensors in manufacturing is critical to take full advantage of the efficiency that Industry 4.0 promises. However, as sensor technology becomes ubiquitous in manufacturing shops everywhere, the ability to make optimal use of the data that is generated can be severely handicapped unless the data from the various sensors can be harmonized in a common language format. Standards will be the key to make such harmonization possible. One such standard that has already become widely adopted is MTConnect. With uniform data, developers and integrators can focus on useful, productive manufacturing applications rather than translation, which will be key to successful sensor data fusion going forward.

Jeffrey Case: Challenges for sensor fusion include synchronizing the different sensor types and sensor systems, especially when there is time dependency, and ensuring compatible communication networks. In addition, edge computing is becoming more and more critical at the sensor level to minimize the amount of data collected and analyzed, affecting both processing power and data storage requirements.

Brad Walters: Sensor data fusion is a key benefit of the IIoT because decisions made from multiple data points are higher-value decisions. But it can be a challenge when manufacturers source different sensor systems from various vendors and aggregate all the data themselves. You can effectively manage data volume by having a single sensor platform that incorporates sensor types combined with data aggregation, filtering, fusion algorithms, and redundant data deduplication at the edge. The most valuable data volume reducer you can have is edge processing and filtering via a gateway at the sensor level. It’s ideal for sensors to immediately report events and threshold breaches when they detect preconfigured conditions, rather than constantly reporting trivial data at frequent intervals. This way, a sensor system with an edge gateway can quickly fuse relevant data from all sensor types and use a robust set of APIs to simultaneously mix and match data from other analytics systems.

Aric Prost: Manufacturers face a few challenges because of the volume of edge data being created. First, data in a typical plant or facility comes from sensors manufactured by multiple vendors that use different communications protocols. That data must be collected and integrated. Second, edge locations — even the factory floor — face bandwidth and latency issues when transmitted to the control room, much less to the cloud. The ability to analyze this edge data and translate it into insight is predicated on its availability and reliability. Predictive analytics or AI applications rely on these full data sets. Any communications gaps in data or equipment downtime can disrupt those advanced models. To address these challenges, including sensor data fusion, organizations deploy edge computing to collect information close to equipment, provide processing and historization to avoid downtime and data loss.

Tech Briefs: If facilities are utilizing multiple connected sensors and systems, how do they ensure that they are secured properly to guard against unwanted outside access?

Dean Bartles: The most secure way to guard against unwanted outside access is to “airgap” everything. In other words, avoid the use of Wi-Fi sensors and instead deploy hard-wired sensors and hard-wired IoT edge devices and have all data route through a cybersecurity appliance that both encrypts and tokenizes everything leaving the facility. As OEM’s continue to drive “transparency” into their supplier’s manufacturing operations, technology solutions will be paramount.

Jeffrey Case: While there is no silver bullet when it comes to industrial cyber security, network segmentation is a cornerstone to protecting private networks from potential vulnerabilities. Sensor systems should be configured on a network isolated from internal systems, and access to the sensor system networks should be limited to the minimum required. We encourage all our IIoT customers to follow cyber security best practices on their internal sensor system networks and/or our sensor systems, leveraging industry standard technologies.

Brad Walters: Security must be sustained at all communication points between sensor, gateway, network, network controller, and the cloud. A robust IoT device and data security governance initiative to enforce policies can help protect a company’s sensor network and data. You also can’t put all of your safeguards in strongholds like firewalls but leave the temperature sensor on the lobby’s fish tank vulnerable. If you use one sensor management system, you limit outside entry points. Regardless, every system needs to be vetted for security individually, then as a whole system.

Aric Prost: Cybersecurity is front and center for operational technology, and the notion of air-gapped assets is less and less realistic as more equipment is connected. By deploying edge computing platforms with built-in virtualization, OT and IT teams have the means to run cybersecurity software close to critical equipment alongside other industrial software applications. In this instance, the edge computing platform running security software sits between the sensors or PLCs and the rest of the network.

Tech Briefs: In what industries do you expect to see the greatest demand for sensor technology in the next five years?

Dean Bartles: Significant progress has already been made by large corporations in aerospace, defense, automotive, food, medical, chemical processing, etc. So, I don’t think the question should be “what industries” as much as “who” inside the various industries where we’ll see the greatest demand. Clearly, the small and medium manufacturers (“SMM’s”) have the most to gain by adopting sensor technology into their manufacturing operations. A recent survey conducted by the Manufacturing Leadership Council of the National Association of Manufacturers ranked “Taking end-to-end supply chain visibility, transparency, and predictability to the next level” as the second most important thing for 2022. To provide OEMs with the transparency, visibility, and predictability in their supply chain that they desire, SMM’s will need to deploy far greater sensor technology than they have to date.

Jeffrey Case: As sensors become more mainstream with improvements in sensing technology, edge computing, artificial intelligence, and the proliferation of Industrial 4.0 communication networks, the greatest demand for sensor technology will be across all manufacturing operations in almost all markets/industries. Both preventive maintenance and process automation applications are driving this unprecedented demand in industrial manufacturing. A wide variety of sensing technologies are being deployed in the process automation market to facilitate tighter control on manufacturing processes. While sensors have traditionally been deployed in these applications, Industry 4.0 is providing internet-connected sensors that are able to collect, transfer, and display data via established digital highways with minimal human intervention. This infrastructure can easily satisfy a company’s ROI and will significantly drive sensor sales over the next five years and beyond.

Brad Walters: It’s easy to see that predictive maintenance, remote monitoring and control, and autonomous systems in virtually every industry will continue to depend heavily on advancements in smart sensor technology. For example, innovators in oil and gas, agriculture, energy and power production, chemical and mining, and transportation lean on wireless sensors’ far-reaching capabilities that deliver long-range, low-power, and long battery life. As manufacturers, health care, and smart cities look to be more efficient, sensing solutions that expedite 4G LTE and 5G functionality, eliminate frequency interference, and enable multi-access edge computing will be highly valuable. Industries that effectively integrate smart sensors will help propel the IIoT evolution into the next industrial revolution.

Aric Prost: We see the greatest demand for sensor technology coming not from specific industries but from specific use cases within industries where assets and processes are remote or inaccessible, critical to measure, high velocity, and where safety is a significant factor. Sensor technology will be essential to scale automation and remote management in these cases. There are a range of examples which cut across including Discrete Manufacturing — complex packaging machines, robotics, metal fabrication; Water and Wastewater — remote and unmanned pumping stations, flowmeters; Power Generation – solar arrays, wind farms, and substations; Oil and Gas — pumping stations, flow metering stations, production platforms, and many others. For these assets and use cases, the abundance of sensor technology and limited connectivity requires a “brain” on site to process and store data, ensure uptime availability, run cybersecurity agents, and potentially provide monitor and control without human intervention. Edge computing platforms provide these capabilities and thereby the means to harness sensor data to realize Industry 4.0 capabilities.

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