Consumer market will drive industrial Internet of things for manufacturing

Technology Update: The same disruptive activities are at work for the industrial Internet of things (IIoT) as when the personal computer changed the way businesses operated.


Monitoring the performance of manufacturing equipment, such as this Gleason gear lapper, improves productivity. Courtesy: Viewpoint Systems Inc.It's official. The entire world knows about the Internet of things (IoT). A recent article in the Wall Street Journal described the efforts of businesses built around producing and consuming data measured by devices. These businesses are based on the thought that smart machines will help market products to the consumer. Your egg carton will tell you when the eggs are old. Your refrigerator will tell you when it's time to buy milk and will eventually tell you which supermarket has the best price. And, with Google's purchase of Nest, it's clear that consumer-based companies want to merge all that data from your cell phone (location, Web browsing history, and so on) with data from your home.

Engineers in the machine condition monitoring world have been gathering data from machines for decades. Early data collection from remote machines was done over dedicated phone lines and modems. Supervisory control and data acquisition (SCADA) systems archived the data for historical review. And, as more programmable logic controllers (PLCs) were involved, the realm of machine to machine (M2M) appeared, where a local PLC could react to data from a remote machine to improve control and safety.

So, if machine condition monitoring engineers have been active in M2M for years, why would they care about the buzz around IoT? The reason is that we are all going to benefit from the huge amount of development being done for that consumer-based market. Remember how the personal computer changed the way businesses operated? The same disruptive activities are at work here. Let's explore some. 

Hardware enablers

Cell phones have caused a 42% increase in the number of U.S.-based cellular towers in the past five years, and Internet data traffic being carried just on U.S.-based wireless (not including wired traffic) is around 1500 petabytes per year. Internet data consumption has grown at around 43% per year on average during that last five years, with video streaming consuming almost half of the entire data throughput in recent years. And, microprocessor designs and miniature micro-electromechanical systems (MEMS) sensors originally developed for cell phones are being considered for industrial machine monitoring. This push is making impacts on traditional sensors and controllers. Companies are seriously considering making their machines "smarter" because costs to do so are dropping as the infrastructure becomes ubiquitous. Even companies that might not see an immediate benefit are joining the Smart Machine revolution because they are worried about being left behind.

Some examples of the infrastructure being developed are IMI's accelerometer in TO-8 package, wireless capability for traditional accelerometers from Lord MicroStrain, the Imp module for integrating Wi-Fi and the cloud into products from Electric Imp, powerful and fast FPGA-enhanced sbRIO controllers for complex machine monitoring and control from National Instruments, the Zynq-based MicroZed that combines ARM processor technology with FPGA capabilities, and the low-power Waspmote from Libelium with eight options for integrated wireless technologies.

Interestingly, cellular providers, such as AT&T and Verizon, have developed business units around M2M, so that data produced by measurement hardware can be connected to the world. Clearly, they see opportunities to increase business by carrying the huge amount of data being produced by machines. And, machines can produce enormous amounts of data. While not typical, the CERN LHC Collider is illustrative of possibilities: one "machine" has collected over 100 petabytes in the past four years. 

Software enablers

The data generated by all the machine monitoring devices and sensors is the industrial version of the big data topic widely discussed in the past few years.

Big data is not new to engineers. For example, engineers have been performing condition monitoring on machines for decades; traditional SCADA historians are the original big data management tools.

Such historians are still widely used, but their tag-based data model can be restrictive in some cases and, in my opinion, a growing number of cases. Certainly, the ability to graph and analyze one or more tag values as a function of time yields huge benefits. Data from transient events can be monitored and analyzed to understand how to improve the reliability of a system. Long-term trends help predict future problems and allow proactive scheduled maintenance. And, of course, traditional process control monitoring and tuning benefits from data collected in SCADA systems.

However, the ability to consume and use multiple data sources from disparate sensor types and machines has been a difficult problem for decades. Traditional SQL-based databases have yielded custom solutions that have worked well for specific industries. For example, tools used for condition monitoring on rotating equipment have traditionally pushed RMS (root-mean-square) vibration levels into SCADA systems, but the actual vibration waveforms were lost.

These waveforms contain valuable information for diagnosing heightened vibration levels. (Is it a bearing? Is the fault on the inner or outer race?) Consequently, custom applications were developed to merge these vibration waveforms with SCADA historical data to allow vibration engineers to identify quickly that an issue is occurring, perhaps through alarm levels on the SCADA data, and then locate the archived vibration data for further detailed analysis.

Rather than building custom applications, companies have begun to leverage emerging technology to help simplify the aggregation of multiple types of data, such as vibration waveforms and tag-based scalars. Some of that technology has been leveraged from Web tools, such as RDF and other NoSQL databases, and some from the enhanced interconnectivity available between computers that simplifies the creation of distributed systems.

Unstructured advantages

Typical components used to connect remote monitoring equipment across the Internet. The gear symbols represent machines, and the configuration at each of the N sites is usually different, depending on the actual machines being monitored. The remote accessAll these tools can handle unstructured data, as opposed to the tabular structure imposed by relational databases. Not only do traditional relational databases complicate the creation of linkages between disparate data, they also restrict data types to a finite set (unless you count BLOBs) and are not flexible when changes are required to the schema.

The newer unstructured databases are no longer restricted to certain types of data. Furthermore, this lack of structure allows arbitrary connections between data entities and adaptability when new entities are introduced or old ones are removed.

Some worthy examples of tools to manage arbitrary data sources are VantagePoint, which is part of Rockwell Automation FactoryTalk; GE's Industrial Internet tools; Digi International cloud-based solutions; the Aperio database framework from Viewpoint Systems for making connections between any arbitrary data; and the Thingworx platform for visualizing and connecting arbitrary data sources. Even low-level tools, such as NoSQL databases, are being widely used now.

Deployment and configuration

An often overlooked aspect of monitoring multiple assets is the need to manage the suites of devices performing the data collection. A typical scenario has perhaps hundreds to thousands of devices deployed in the field across multiple geographic locations. Each device has certain channel configurations (sensor types and counts) and applications (software running on the device controller performing the analysis and managing the local data storage). Over time, changes are made to these devices. Perhaps a new version of the application software is needed for some new analysis or a new sensor has been included.

Ideally, the deployment of the new application or setting up the new channel configuration management can be done remotely. The large number of devices begs for tools to help automate the deployment. Automation helps assure successful deployment and helps manage the available configurations with each deployment. This automation is still an emerging topic that will include device-type dependent tools and some generic configuration management tools. 

Commercial tech helps industry

By leveraging all the technological developments arising from the consumer world, the industrial world is leveraging huge gains in infrastructure and product platforms for the purpose of monitoring remote machines. Engineers have more tools than ever to collect and analyze data from those machines, and make informed decisions about asset utilization and predictive maintenance.

- Jim Campbell is president of Viewpoint Systems Inc., a Control System Integrators Association member based in Rochester, N.Y. Edited by Mark T. Hoske, content manager, CFE Media, Control Engineering,


See related articles at bottom of this posting. 

Key concepts

  • Focus on M2M, remote monitoring, data visualization, and management systems.
  • Why use these versus traditional SCADA historians, touching on asset monitoring?


The Top Plant program honors outstanding manufacturing facilities in North America. View the 2015 Top Plant.
The Product of the Year program recognizes products newly released in the manufacturing industries.
Each year, a panel of Control Engineering and Plant Engineering editors and industry expert judges select the System Integrator of the Year Award winners in three categories.
A new approach to the Skills Gap; Community colleges may hold the key for manufacturing; 2017 Engineering Leaders Under 40
Doubling down on digital manufacturing; Data driving predictive maintenance; Electric motors and generators; Rewarding operational improvement
2017 Lubrication Guide; Software tools; Microgrids and energy strategies; Use robots effectively
The cloud, mobility, and remote operations; SCADA and contextual mobility; Custom UPS empowering a secure pipeline
Infrastructure for natural gas expansion; Artificial lift methods; Disruptive technology and fugitive gas emissions
Mobility as the means to offshore innovation; Preventing another Deepwater Horizon; ROVs as subsea robots; SCADA and the radio spectrum
Power system design for high-performance buildings; mitigating arc flash hazards
Research team developing Tesla coil designs; Implementing wireless process sensing
Commissioning electrical systems; Designing emergency and standby generator systems; Paralleling switchgear generator systems

Annual Salary Survey

Before the calendar turned, 2016 already had the makings of a pivotal year for manufacturing, and for the world.

There were the big events for the year, including the United States as Partner Country at Hannover Messe in April and the 2016 International Manufacturing Technology Show in Chicago in September. There's also the matter of the U.S. presidential elections in November, which promise to shape policy in manufacturing for years to come.

But the year started with global economic turmoil, as a slowdown in Chinese manufacturing triggered a worldwide stock hiccup that sent values plummeting. The continued plunge in world oil prices has resulted in a slowdown in exploration and, by extension, the manufacture of exploration equipment.

Read more: 2015 Salary Survey

Maintenance and reliability tips and best practices from the maintenance and reliability coaches at Allied Reliability Group.
The One Voice for Manufacturing blog reports on federal public policy issues impacting the manufacturing sector. One Voice is a joint effort by the National Tooling and Machining...
The Society for Maintenance and Reliability Professionals an organization devoted...
Join this ongoing discussion of machine guarding topics, including solutions assessments, regulatory compliance, gap analysis...
IMS Research, recently acquired by IHS Inc., is a leading independent supplier of market research and consultancy to the global electronics industry.
Maintenance is not optional in manufacturing. It’s a profit center, driving productivity and uptime while reducing overall repair costs.
The Lachance on CMMS blog is about current maintenance topics. Blogger Paul Lachance is president and chief technology officer for Smartware Group.
The maintenance journey has been a long, slow trek for most manufacturers and has gone from preventive maintenance to predictive maintenance.
Featured articles highlight technologies that enable the Industrial Internet of Things, IIoT-related products and strategies to get data more easily to the user.
This digital report will explore several aspects of how IIoT will transform manufacturing in the coming years.
Maintenance Manager; California Oils Corp.
Associate, Electrical Engineering; Wood Harbinger
Control Systems Engineer; Robert Bosch Corp.
This course focuses on climate analysis, appropriateness of cooling system selection, and combining cooling systems.
This course will help identify and reveal electrical hazards and identify the solutions to implementing and maintaining a safe work environment.
This course explains how maintaining power and communication systems through emergency power-generation systems is critical.
click me