The industrial internet of things, or IIoT, is defined as “machines, computers and people enabling intelligent industrial operations using advanced data analytics for transformational business outcomes”. We are now in the middle of the Fourth Industrial Revolution or Industry 4.0 where smart, connected devices and technologies are transforming how products and equipment are designed, manufactured, maintained and ultimately used.
The application of IoT (the Internet of Things) in the manufacturing industry is called the Industrial Internet of Things (IIoT). This already has revolutionized manufacturing by leveraging much greater amounts of data, at far greater speeds, to drive productivity and efficiency to another level.
How does IIoT work?
IIoT is part of the larger concept known as the Internet of Things (IoT). This network of intelligent devices, machines, computers and objects increases automation in many industries by collecting and sharing huge amounts of data with end users – thus improving operational efficiency, productivity, and time and cost savings. These insights help drive smarter and faster decision making while providing valuable insights in real-time.
Evolve with IIoT:Predictive Maintenance
Monitor your factory floor equipment in real time by using sensors and advanced analytics to predict needed maintenance and reduce unplanned downtime. Intelligent devices can predict when a machine is about to fail and this allows you to better plan for maintenance. For example, a machine on your floor may be sensitive to temperature, velocity or pressure changes. So when these changes occur, this could indicate potential failure and the device would essential “predict” this before any unplanned downtime occurs.
Collect telemetry data from multiple remote devices and control them. Simply imagine your assets having eyes and ears and communicating this back to your dashboard, allowing you to respond to current conditions quickly. For example, a cooling system installed on your clients’ premises can be fully managed through your dashboard. Create automated processes and responses with the ability to schedule, reconfigure and delete devices in your cooling system all through the power of the cloud.
A more tailored and engaging customer experience
The interaction between your company and your customers at every stage of product development, from initial research to sales, can bring invaluable insights to your organization and improve your customers’ experience overall. Through all these touchpoints, data can be analyzed to drive action tailored to the different customer needs and preferences. Also, through historical analysis, future product innovations can be leveraged to offer better-designed products and services.
Improve field service
Sensor data out in the field can greatly save you time and money and increase efficiency before potential issues become a major problem. This data ensures that the right field service technicians and tools are dispatched at the right time while optimizing and automating your scheduling process. Field service had always started with a plan that, in reality, was never realized due to unforeseeable factors and delays that were out of their control. IIoT ensures increased schedule accuracy and delivery – leading to increased productivity and customer satisfaction.
Reducing production costs and eliminating inefficiencies are some of the benefits of transforming your business with the industrial internet of things. There are a number of moving parts that encompass IIoT, but getting started does not have to be complicated. Incorporating the right technology can turn data into valuable insights that help you make more informed business decisions and achieve success in the digital age of manufacturing.
Explore more about intelligent manufacturing with IIoT and learn how the technology of today can support an end-to-end approach that drives new business opportunities and revenues for your organization.
Reaping the benefits of the Industrial Internet of Things (IIoT) is about measuring just about everything in the factory of the future. As we enter the Industry 4.0 era, where computers and automation are coming together in an entirely new way, with equipment connected remotely to systems equipped and ready with machine learning algorithms - the benefits outweigh the concerns in many facilities worldwide.
The Industrial Internet of Things brings together machine-to-machine communication, advanced data analytics, and people through a network of devices that results in systems that can monitor, collect, exchange, and deliver valuable information for smarter business decision making.
Benefits of IIoTIIoT is changing industries and is driving unprecedented levels of productivity, efficiency and performance that allow manufacturers to gain transformational financial and operational benefits.
Optimum Energy Efficiency
One of the largest expenses for manufacturing organizations is the energy bill. IIoT can empower and transform manufacturing leaders to determine when and where they are wasting energy and fixing these areas. The real-time data delivers insights like off-hour consumption and other energy saving opportunities that allows managers to identify operational inefficiencies and waste. Information about attaining higher efficiency from equipment/machines, potential regulatory compliance issues and waste that all offer opportunities for cost savings is provided and leaders can take action sooner rather than later.
Just in Time Manufacturing (JIT)
The Just in Time (JIT) methodology aims at reducing flow times within a production/manufacturing system, response times between suppliers and customers, and increase collective collaboration along the supply chain. Through IIoT, basic metrics are constantly tracked like throughput, uptime, and fail rate, etc… Analyzing this data encourages continuous improvements in manufacturing processes and personnel. Real-time data from IIoT sensors and devices provides information on delivery schedules, manufacturing capacity, staff availability for receiving and loading products and updates on material availability.
Predictive Maintenance (PdM)
One of the main value-adds of IIoT to the manufacturing line so far has been predictive maintenance (PdM). The aim of PdM is first to predict when machine or equipment failure might occur – and to then prevent this occurrence from happening by performing maintenance. In an ideal scenario, PdM permits the maintenance frequency to be as low as possible and prevents unplanned reactive maintenance, creating a more proactive maintenance schedule. This brings about several cost savings like minimizing production hours lost to maintenance, minimizing the cost of spare parts and supplies and the time required to maintain machines/equipment.
While running your machine operation, recording high-frequency sensor data allows you to monitor parameters like vibration, speed and temperature, collecting this data in milliseconds. Repeatability refers to the ability to repeat or duplicate a given set of conditions/circumstances within a specific range or tolerance. IIoT benefits manufacturers with data analytics to offer a faster ROI at a lower cost since. An example of this could be a company that cross-drills holes in a block of steel, monitoring the torque of the motor and referencing this to the data to determine if the holes were crossed straight enough in comparison to the drop in torque.
Fast and more Informed Decision Making
With IIoT, operations managers are no longer uninformed about machine/equipment performance or problems. Like PdM, this transforms a manager’s approach from a reactive one to a proactive one where waste is decreased with an increase in overall visibility. The power lies in the accuracy of the data they have – and the ability to take action based on insights from the data.
Higher product quality, reduced downtime and a real-time competitive edge is what manufacturers of the future are achieving with Industrial Internet of Things technology. The factory of the future aims to be even more efficient, operate with greater profitability and achieve higher customer satisfaction. All the above benefits make IIoT a critical and powerful tool for manufacturing organizations that want to grow and thrive in the digital future.
The introduction of IoT has opened gates for multitude of possibilities of performance upgrades through total control. IoT has moved out from our homes and offices to the industrial segment, and hence known to become IIoT (Industrial Internet of Things). Industrial IoT in Manufacturing industry is a core element of the transformation, and by far it has seen the most investment, which makes for a promising future.
Manufacturing is poised to keep that first position across the globe until at least 2020, even if, in some geographies, this leading position is more prominent. The manufacturing industry is leading in the Internet of Things for various reasons, such as the promising industrial revolution (Industry 4.0) and then there are the many cases of actual IoT deployments that offer rapid return and enable manufacturers to realize digital transformations from several perspectives: efficiency, automation, customer-centricity, competitive benefits and the advantages which are offered by using data across the manufacturing value chain and to tap into new revenue sources, which is a key aspect of industry 4.0 in manufacturing.
Here is a compiled list of Top 7 uses, application and benefits of Industrial IoT in the manufacturing industry:
1. Inventory Management
Monitoring of events across the supply chain is now possible through IoT Application. Using these systems, the inventory is tracked across the globe on a line-item level and the users are notified of any significant deviations from the plans, or even updates. This provides cross-channel visibility into inventories and managers are provided with realistic estimates of the available material, work in progress and the estimated arrival time of new materials. Ultimately this optimizes supply and reduces shared costs in the value chain.
2. Quality Control
IoT sensors collect aggregate product data and other third-party syndicated data from various stages of a product cycle. This data relates to the complete composition of raw materials used, temperature and working environment, wastes, the impact of transportation and more on the final products. Moreover, if used in the final product, the IoT device can provide data about the customer sentiments on using the product. All of these inputs can later be analyzed to identify and correct quality issues, which leads to significant improvement.
3. Enhanced Safety
Big Data analysis is effectively possible with Industrial Internet of Things . Key performance indicators of health and safety, such as number of injuries, short- and long-term absences, illness rates, near-misses, can thus be monitored constantly to ensure better workplace conditions. Lagging indicators like the number of accidents can be addressed immediately.
4. Smart Metering
IIoT has seen to the introduction of various smart meters. These Smart meters can monitor the consumption of resources like electricity, fuels, water etc. Through the use of IoT sensors, manufacturers will know exactly how much is consumed and what for. Through effective management, operational expenditure can be reduced significantly.
5. Predictive Maintenance
Gone is the era of preventive maintenance, with Industrial IoT in Manufacturing we have not only seen a revolution in the machine maintenance system, but also it’s delivery. For the first time, predictive maintenance is delivered through hardware, which takes machine health monitoring beyond cloud computing, into edge computing. This means faster processing and on spot analysis. Infinite Uptime, which is ranked amongst the top 25 IoT solutions provider globally, is the only company providing it through their patented technology. Predictive maintenance (PdM) techniques are designed to help determine the condition of equipments in order to predict when maintenance should be performed or possible breakdowns. This promises cost savings over routine or time-based preventive maintenance, as the tasks are performed only when warranted.
6. Smart Packaging
By using IoT sensors in products and packaging, manufacturers can gain valuable insights into the usage patterns and handling of product from multiple customers. Smart tracking mechanisms can be used to track product deterioration during transit and impact of weather, road and other environment variables on the product. This in turn offers insights that can be used to re-engineer products and packaging for better performance in both customer experience and at times, even the cost of packaging.
7. Digital Industries
IoT enabled machinery can transmit operational information to the partners like OEMs (original equipment manufacturers) and to field engineers. This will enable operation managers and factory heads to remotely manage the factory units and take advantage of process automation and optimization. This makes streamlining the day-to-day work effortless.
Industrial IoT in Manufacturing is indeed empowering the industrial revolution (industry 4.0). Top companies have been the beneficiaries of integrating IoT enabled services, the list of the names include Amazon, Hitachi, John Deere, Komatsu, Maersk and many more.
Agility, visibility and insight are among the core drivers of success for manufacturing plants. These attributes are what enable plants to cut costs while adhering to increasingly stringent compliance standards, boosting overall performance, and delivering more and better-quality products in less time.
Unfortunately, many manufacturers today are hampered by isolated, complicated business systems that slow down processes and impede operations. According to market research firm IDC, companies lose 20 to 30 percent in revenue every year due to inefficiencies. Still, many businesses continue to “get by” with their existing systems and applications even though they are often a performance drag.
Growing supply chain complexity has added to the challenge, making it more difficult to bridge the physical distance between enterprise-level decision making and plant floor execution systems. While the many information-generating systems within today’s plants are vital to the functional areas they support, these systems are typically isolated and detached, restricting company-wide access. A lack of near-real-time visibility across production leads to higher costs, fragmented communication and delayed response to business-critical issues.
Major benefit of IIoT - The path to improved productivityNew control technologies have given manufacturers the ability to make quicker and smarter moves on the plant floor, but rarely is data from these systems converged into a usable, integrated format. While access to plant floor data has long been available, it is often isolated in disparate production systems, limiting its use for timely decision making.
One major trend poised to have a transformative impact on the manufacturing model of the future is the Industrial Internet of Things (IIoT). The term refers to products, machines and devices that typically haven’t had any kind of connectivity—from factory machines and forklifts to shipping pallets and delivery trucks.
Sending instructions to machines is not new, but the IIoT offers the potential to control more devices more effectively (and more affordably) than ever before. The IIoT makes it much easier to gather and manage large volumes of plant floor data not only in an individual plant, but throughout multiple facilities via the cloud. When combined with analytics, organizations can obtain greater insights, enabling them to boost manufacturing performance, improve product quality and carry out preventative maintenance.
To take advantage of the opportunities presented by the IIoT, manufacturers need an ERP architecture that is up to the task. Monolithic mega suites will be replaced by agile, adaptable application infrastructures; focus will shift to the flexible integration of new systems and technologies. Particularly critical are integrated ERP capabilities that can connect devices and process data across all areas. Only by collecting comprehensive knowledge can manufacturing performance be improved and processes optimized. . .
Welcome to the connected world. Virtually every home today has some form of connected device be it a smartphone, Alexa, Google Home, video doorbells, networked sprinkler systems, smart plugs and smart lighting, and yes, networked refrigerators and microwaves. We can start our cars and unlock our doors from thousands of miles away. Today we can connect, control, and gather data from these devices anywhere in the world. Welcome to the Internet of Things (IoT).
IoT is a network of sensors, intelligent systems, and computers that are connected via the Internet to share, control and collect data.
The Industrial IoT (IIoT) has the potential to be much more advanced and of greater financial benefit to manufacturers than the commercial IoT, primarily due to the prevalence of connected sensors in the industrial world. With advances in control and communication technology, virtually any machine sensor can provide data that can then be monitored, reviewed, and reported real time on PCs, tablets, smartphones, and smart watches. No longer is an operator required to constantly monitor equipment or processes or is manual data collection and analysis required as this information can be collected, processed, and exceptions reported on a real time basis.
With 66% of early movers in manufacturing saying that IIoT is now critical in creating a competitive advantage, its beneficial for manufacturers to develop systems that help them get better connected to their data. IIoT uses sensor-based technology to deliver key performance related, safety and operational benefits.
Extensive software packages now exist using machine learning and artificial intelligence for fault finding and analysis of the system components, as well as monitoring and documenting the safety, overall awareness of system health, visibility of equipment status and machine efficiency, can be added to IIoT technology allowing information to be pushed anywhere in the world from a multitude of devices.
Instead of immediately calling on the services of either internal staff or those of the system manufacturer, IIoT devices can first clarify the problem via the Internet, intranet, or mobile data and quickly analyze faults that can be isolated in extensive nets, with the causes being specified. This allows for quick and precise remedial measures to be implemented, meaning that reaction times are considerably reduced and costs for internal and external staff can be optimized.
Key Benefits of IIOT
Safety: users can be alerted to potential safety breaches before they arise. Receive critical information to enhance reporting on safety.
Workplace safety is essential to achieving optimal operation, avoiding substantial production interruptions, and most importantly, protecting employees. With IIoT, you get site wide visibility of your equipment allowing you to view key indicators in not only production, but also in safety compliance. This in turn allows you to be proactive in being able to spot possible safety gaps in your process.
Many processes rely on outdated methods of safety data collection some using pen and paper reporting, and some have no reporting at all. This may give rise to safety standards slipping, delays in reporting data and even senior-level management, who are ultimately responsible for mitigating those risks, receiving biased data on safety breaches.
Awareness: Reduce or eliminate unplanned downtime by moving to planned preventative maintenance.
IIoT gives you the ability to collect and analyze the data from your machines and develop a program for predictive maintenance, as well as pinpointing potential bottlenecks in your process. Previously, when a system failed it could result in costly unplanned downtime and routine inspections resulting in a change of spare parts. With IIoT technology, sensors could continually report data back to the right people and will notify them before critical failure. Reports suggest that 40% of organizations are not using any form of predictive maintenance at all, but that unplanned outages could be cut by up to 50% with IIoT devices.
With IIoT, maintenance is no longer reactive, but proactive, with both real time data as well as historical being made available. Manufacturers working towards zero unplanned downtime can benefit from intelligent insights that will improve efficiency and reduce costs.
Visibility: Gain critical visibility at multiple levels of operation utilizing a wide range of sensory inputs.
By selecting the problems you want to solve, IIoT can track and report on data you need the most. Immediate action can be taken with specific IIoT reports being sent to your PC or laptop, mobile devices and tablets, and even wearable smart devices such as watches. Often in manufacturing, if the correct action is not taken at the right time it can be detrimental to production and result in a disproportionate loss of profits over a planned maintenance. With 82% of asset failures occurring randomly, IIoT devices will indicate how and when the failure occurred and will learn from this event, enabling it to predict future events more accurately.
Efficiency: Reduce disruption to operations and costly workarounds by monitoring efficiency and repairing assets before they fail.
By accessing existing data and presenting it to the right people at the right time, key processes can improve with quality control, reduced downtime and energy efficiencies.
Manufacturers know that their profitability is reliant on having an accurate, high quality and reliable production output. And as, according to Verizon, 60% of early-movers are improving the reliability or performance of products and services with IIoT, being able to pinpoint the issues that can cause a poor-quality product is essential, especially if the problem is caused by faulty equipment.
If your equipment is not calibrated properly, not properly maintained, or not set up correctly, this can lead to issues with the product that could be avoided. IIoT will use the sensors to track and analyze the information and report back to key employees in real-time, who in-turn can stop production immediately to resolve the issues.
If a machine stops working in the middle of a shift and there are no critical spare parts on site, long delays can occur which can be expensive. It has been reported that IIoT devices could eliminate up to 70% of breakdowns by reporting the data back to key individuals, who could take decisive action before critical failure. This will overall improve the efficiency of production as maintenance can be planned and scheduled to specific times.
With IIOT you will get faster and better-informed decision making by unlocking critical data about equipment performance and putting the facts into the right hands. It will pinpoint any system bottlenecking and wasting production “up time” giving you the capability to see the system, but also being modular, it will allow you to further streamline your process for lean manufacture.
1 Verizon: State of the Market with IIoT
2 Enterprise Asset Management and Field Service Management, ARC Advisory Group, 04/17/2015.
4 ARC view, Optimize Asset Performance with Industrial IoT and Analytics, August 2015
5 Verizon: State of the Market with IIoT
6 G.P. Sullivan, R. Pugh, A.P. Melendez and W.D. Hunt, “Operations & Maintenance Best Practices: A Guide to Achieving Operational Efficiency, Release 3.0,” Pacific Northwest National Laboratory, U.S.
Department of Energy, August 2010.
THE PROLIFERATION OF smart things has reached critical mass. Products with wireless connectivity (from lightbulbs to thermostats to smart speakers) are more present in people’s homes today than not—one report suggests that 79 percent of U.S. consumers have at least one connected device at home. But the technology actually has its roots in a world that predates the rise of remote control thermostats: industrial manufacturing.
The Industrial Internet of Things (IIoT) takes networked sensors and intelligent devices and puts those technologies to use directly on the manufacturing floor, collecting data to drive artificial intelligence and predictive analytics.
“In IIoT technology, sensors are attached to physical assets,” says Robert Schmid, Deloitte Digital IoT chief technologist. “Those sensors gather data, store it wirelessly, and use analytics and machine learning to take some kind of action.”
The IIoT is driving unprecedented disruption in an industry that has struggled in recent years due to talent shortages, and this offers hope for the industry’s future. The IIoT can transform traditional, linear manufacturing supply chains into dynamic, interconnected systems—a digital supply network (DSN)—that can more readily incorporate ecosystem partners. As key enablers of DSNs, IIoT technologies help to change the way that products are made and delivered, making factories more efficient, ensuring better safety for human operators, and, in some cases, saving millions of dollars.
The Power of Prediction
One of the greatest benefits of the IIoT is how it can dramatically improve operating efficiencies. If a machine goes down, for example, connected sensors can automatically pinpoint where the issue is occurring and trigger a service request. Perhaps more importantly, the IIoT can also help a manufacturer predict when a machine will likely breakdown or enter a dangerous operating condition before it ever happens.
“Predictive maintenance is a big thing,” says Schmid. “This lets us limit equipment downtime and improve safety by being proactive about a fix.”
The sensors work by analyzing the sound frequencies, vibrations, and temperature of a given machine to tell if it’s working within its normal condition. This process—known as condition monitoring—is time intensive when humans do it manually. By using sensors to collect and quickly analyze data points in the cloud, prediction becomes easier.
Schmid cites a client that makes packaging materials as a great use case for the prediction capability of connected sensors. When the company outfitted its production equipment with IIoT sensors, overall equipment effectiveness (OEE) improved by nine percent. The heightened OEE decreased waste for the company by predicting when machines would need to be maintained before they failed and had to be taken out of service. By decreasing machine downtime, Schmid says the company was able to take better advantage of the factory’s capacity.
“Thanks to the predictive nature of the sensors, the company avoided building another production line, which helped them save $25 million in added capital expenditures,” he says.
Beyond saving money and time, the IIoT can keep workers safe. If an oil well is about to reach a dangerous pressure condition, for example, operators will be warned well before it explodes. Sensors can even be used to manage and monitor workers’ locations in case of an emergency or evacuation.
Location, Location, Location
Another huge benefit of the IIoT is location tracking—the industrial version of a connected fob that makes your keys impossible to lose. Workers can spend a lot of time locating tools, equipment, and finished goods inventory, but the IIoT reduces that time significantly.
“When equipment is built, it goes onto a massive inventory lot that could be three quarters of a mile on each side,” says Schmid. Simply finding equipment on the lot is so time consuming that one of Schmid’s clients saved $3 million per year on each of its production lines once the company’s equipment was outfitted with location-tracking sensors.
Dr. Richard Soley, executive director for the Industrial Internet Consortium (IIC), which works to test and promote the IIoT, has come across similar findings with his clients. Dr. Soley’s group works primarily through “testbeds”—experimental technology implementations designed to measure how well the technologies really work. One of the IIC’s testbeds involved a client with a massive number of tools that kept getting misplaced.
“The client found that its workers spent 47 percent of their time just looking for the right tools,” Dr. Soley says. “But with an IIoT solution, the worker could be told that the tool they needed was 10 meters behind them and to the left.”
This also meant that the workers didn’t have to spend time putting the tool back where it belonged. Thanks to the sensors, the system will always know where the tool is and will tell workers where to find it.
The IIoT and the Leasing Model
While the IIoT is already boosting efficiency, productivity, and safety, the future of the IIoT could disrupt enterprise business models, too. Schmid believes that in the near future we could see the proliferation of high-value equipment—ranging from manufacturing robots to aircraft engines—being leased instead of being sold outright.
“Rather than sell equipment directly, the equipment can be outfitted with built-in sensors and marketed as both a product and a service, where the owner monitors the equipment remotely and delivers maintenance, repairs, and upgrades automatically,” Schmid says.
This will allow manufacturing companies to focus on the work at hand instead of worrying about the condition of the equipment that they use to do it, further increasing productivity and efficiency even.
As the manufacturing industry continues to adopt IIoT technology, these results provide a clear business case—far beyond the sensors that anticipate (and accommodate) or arrival home.
This story was produced by the WIRED Brand Lab for Deloitte Digital.
IIoT refers to a subcategory of the broader Internet of Things.
IoT includes IIoT plusthings like asset tracking, remote monitoring, wearables, and more. IIoT focuses specifically on industrial applications such as manufacturing or agriculture.
In recent years, innovations in hardware, connectivity, big data analytics, and machine-learning have converged to generate huge opportunities for industries. Hardware innovations mean that sensors are cheaper, more powerful, and run longer on battery life. Connectivity innovations mean that it’s cheaper and easier to send the data from these sensors to the cloud. Big data analytics and machine learning innovations mean that, once sensor data is collected, it’s possible to gain incredible insight into manufacturing processes.
These insights can lead to massive increases in productivity and drastic reductions in cost. Whatever is being manufactured, it can be done faster, with fewer resources, and at lower cost.
An example of the potential of IIoT is predictive maintenance. A broken machine in a manufacturing process can mean millions of dollars in lost productivity while production halts to fix the issue.
The past solution was to regularly scheduled maintenance, but this has a few issues. What if the machine breaks before the maintenance? This leads to huge loss of productivity as described above. And what if the machine doesn’t need maintenance? Time, effort, and money is wasted that could be better spent elsewhere.
Predictive maintenance means using more sensors to collect better data on machines, and then using data analytics and machine-learning to determine exactly when a machine will need maintenance. Not too late, which leads to broken machines, and not too early, which leads to misallocated resources.
Predictive maintenance is just one example, and it’s already a reality.
As adoption and advancement of IIoT accelerates, the changes will be profound. Eventually we can achieve an autonomous economy in which supply exactly meets demand, completely optimizing the production process and leading to zero-waste.
And there’s every reason to think that IIoT will accelerate in the near-term…
Adoption of IIoTIn many ways, IIoT is ahead of IoT, and will continue to see faster adoption. Why? A key difference between IoT and IIoT is that, unlike consumer IoT applications, incentives for adopting IIoT technologies are much greater:
“[IoT and IIoT have] two distinctly separate areas of interest. The Industrial IoT connects critical machines and sensors in high-stakes industries such as aerospace and defense, healthcare and energy. These are systems in which failure often results in life-threatening or other emergency situations. On the other hand, IoT systems tend to be consumer-level devices such as wearable fitness tools, smart home thermometers and automatic pet feeders. They are important and convenient, but breakdowns do not immediately create emergency situations.” -- RTI
Another difference between IoT and IIoT is that there are clearer near-term benefits for IIoT vs IoT. Manufacturing companies can reduce costs and increase productivity, meaning more tangible return-on-investment for adopting IIoT solutions. Companies like ThyssenKrupp, Caterpillar, and Thames Water are already reaping benefits from being early IIoT adopters.
But IIoT isn’t without it’s challenges…
Barriers to IIoTTwo of the biggest hurdles are security and interoperability.
Bringing physical systems online generates substantial benefits, but also means that those systems can be potentially compromised. Cyberattacks become scary when they can enable remote control of or damage to physical systems; huge financial losses at best and serious injuries or death at worst. Security is a major concern for IoT in general, and needs to be a big part of the conversation in the coming years.
To collect the data from sensors and make that data useful, everything in the system needs to work together. Lack of interoperability and lack of standards between IoT sensors, devices, connectivity, and communication protocols can hinder the process of connecting everything. This is also a problem for IoT in general.
Considering the Implications of IIoTThe above graph shows an incredible increase in U.S. productivity over the last few decades.
As we head into the future and see accelerated IIoT adoption, the increases in productivity will be even more pronounced. Tesla’s Gigafactory will be highly automated, promising a staggering $100 billion in output with only 6,500 workers. That’s only 1.3 jobs to generate $1 million in manufacturing output.
So what does this mean for U.S. jobs?
On the positive side, this will likely help bring manufacturing back into the U.S. from abroad. Manufacturing moved outside of the U.S. because labor was cheaper in foreign countries, but IIoT solutions will create machines and systems that outcompete this cheap manual labor.
IIoT will also create entirely new industries and categories of jobs to support these high-tech systems. Medical robot designers, grid modernization managers, intermodal transportation network engineers, and more.
However, we should be wary that there may be fewer jobs created than destroyed. As shown above, increases in productivity mean fewer jobs are needed to create the same value, potentially meaning fewer jobs overall.
And even if there is no net job-loss or even a net job-gain, we also need to consider the kinds of jobs being created and destroyed. The new job categories will demand interdisciplinary skills; deep knowledge about specific industries coupled with skills and expertise in new technologies, software, data analytics, system integration, and cybersecurity.
These jobs are not blue collar, the skills will take high-level training and education. How will this training and education be provided? Who’s going to pay for it? I don’t have answers, but these questions are critical to consider as we head into our next Industrial Revolution.
By Calum McClelland
“What's the Difference Between IoT and IIoT (the Industrial Internet of Things)?” IoT For All, Calum McClelland, 31 Jan. 2019.
The Industrial Internet of Things (IIoT) poses large impacts on business models (BM) of established manufacturing companies within several industries. Thus, this paper aims at analyzing the influence of the IIoT on these BMs with particular respect to differences and similarities dependent on varying industry sectors. For this purpose, we employ an exploratory multiple case study approach based on semi-structured expert interviews in 69 manufacturing companies from the five most important German industries. Owing the lack of previous research, our study contributes to the current state of management literature by revealing the following valuable insights with regard to industry-specific BM changes: The machine and plant engineering companies are mainly facing changing workforce qualifications, the electrical engineering and information and communication technology companies are particularly concerned with the importance of novel key partner networks, and automotive suppliers predominantly exploit IIoT-inherent benefits in terms of an increasing cost efficiency.
International Journal of Innovation ManagementVol. 20, No. 08, 1640015 (2016)
Special Issue — 16th
Industrial Internet of Things (IIoTs) is the fast growing network of interconnected things that collects and exchange data using embedded sensors planted everywhere. Several IIoT applications such as the ones related to healthcare systems are expected to widely utilize the evolving 5G technology. This 5G-inspired IIoT paradigm in healthcare applications enables the users to interact with various types of sensors via secure wireless medical sensor networks (WMSNs). Users of 5G networks should interact with each other in a seamless secure manner. And thus, security richness is highly coveted for the real time wireless sensor network systems. Asking users to verify themselves before every interaction is a tedious, time-consuming process that disrupts inhabitants' activities, and degrades the overall healthcare system performance. To avoid such problems, we propose a context-sensitive seamless identity provisioning (CSIP) framework for the IIoT. CSIP proposes a secure mutual authentication approach using hash and global assertion value to prove that the proposed mechanism can achieve the major security goals of the WMSN in a short time period.
Published in: IEEE Transactions on Industrial Informatics ( Volume: 14 , Issue: 6 , June 2018 )
The Industrial Internet of Things (IIoT) refers to interconnected sensors, instruments, and other devices networked together with computers' industrial applications, including, but not limited to, manufacturing and energy management. This connectivity allows for data collection, exchange and analysis, potentially facilitating improvements in productivity and efficiency as well as other economic benefits. The IIoT is an evolution of a Distributed Control System (DCS) that allows for a higher degree of automation by using cloud computing to refine and optimize the process controls.
The IIoT is enabled by technologies such as cyber security, cloud computing, mobile technologies, machine-to-machine, 3D printing, advanced robotics, big data, Internet of Things, RFID technology, and cognitive computing. Four of the most important ones are described below:
IIoT systems are often conceived as a layered modular architecture of a digital technology. The device layer refers to the physical components: CPS, sensors or machines. The network layer consists of physical network buses, cloud computing and communication protocols that aggregate and transport the data to the service layer, which consists of applications that manipulate and combine data into information that can be displayed on the driver dashboard. The top-most stratum of the stack is the content layer or the user interface.
The history of the IIoT begins with the invention of the programmable logic controller (PLC) by Dick Morley in 1968, which was used by General Motors in their automatic transmission manufacturing division. These PLCs allowed for fine control of individual elements in the manufacturing chain. In 1975, Honeywell and Yokogawa introduced the world's first DCSs, the TDC 2000 and the CENTUM system, respectively. These DCSs were the next step in allowing flexible process control throughout a plant, with the added benefit of backup redundancies by distributing control across the entire system, eliminating a singular point of failure in a central control room.
With the introduction of Ethernet in 1980, people began to explore the concept of a network of smart devices as early as 1982, when a modified Coke machine at Carnegie Mellon University became the first internet-connected appliance, able to report its inventory and whether newly loaded drinks were cold. As early as in 1994, greater industrial applications were envisioned, as Reza Raji described the concept in IEEE Spectrum as "[moving] small packets of data to a large set of nodes, so as to integrate and automate everything from home appliances to entire factories".
The concept of the internet of things first became popular in 1999, through the Auto-ID Center at MIT and related market-analysis publications. Radio-frequency identification (RFID) was seen by Kevin Ashton (one of the founders of the original Auto-ID Center) as a prerequisite for the internet of things at that point. If all objects and people in daily life were equipped with identifiers, computers could manage and inventory them. Besides using RFID, the tagging of things may be achieved through such technologies as near field communication, barcodes, QR codes and digital watermarking.
The current conception of the IIoT arose after the emergence of cloud technology in 2002, which allows for the storage of data to examine for historical trends, and the development of the OPC Unified Architecture protocol in 2006, which enabled secure, remote communications between devices, programs, and data sources without the need for human intervention or interfaces.
One of the first consequences of implementing the industrial internet of things (by equipping objects with minuscule identifying devices or machine-readable identifiers) would be to create instant and ceaseless inventory control. Another benefit of implementing an IIoT system is the ability to create a digital twin of the system. Utilizing this digital twin allows for further optimization of the system by allowing for experimentation with new data from the cloud without having to halt production or sacrifice safety, as the new processes can be refined virtually until they are ready to be implemented. A digital twin can also serve as a training ground for new employees who won't have to worry about real impacts to the live system.
Standards and Frameworks
IoT frameworks help support the interaction between "things" and allow for more complex structures like distributed computing and the development of distributed applications. Currently, some IoT frameworks focus on real-time data logging solutions like Jasper Technologies, Inc. and Xively: offering some basis to work with many "things" and have them interact. Future developments may lead to software development environments targeted specifically for creating the software needed to work with IoT hardware. Companies are developing technology platforms to provide this type of functionality for the internet of things. Newer platforms are being developed, which add more intelligence.
The term industrial internet of things is often encountered in the manufacturing industries, referring to the industrial subset of the IoT. The industrial internet of things will enable the creation of new business models by improving productivity, exploiting analytics for innovation, and transforming the workforce. The potential of growth by implementing IIoT is predicted to generate $15 trillion of global GDP by 2030.
While connectivity and data acquisition are imperative for IIoT, they are not the end goals, but rather the foundation and path to something bigger. Of all the technologies, predictive maintenance is an "easier” application, as it is applicable to existing assets and management systems. Intelligent maintenance systems can reduce unexpected downtime and increase productivity, which is projected to save up to 12% over scheduled repairs, reduce overall maintenance costs up to 30%, and eliminate breakdowns up to 70%, according to some studies. Industrial big data analytics plays a vital role in manufacturing asset predictive maintenance, although that is not the only capability of industrial big data. Cyber-physical systems (CPS) are the core technology of industrial big data and they will be an interface between human and the cyber world. Cyber-physical systems can be designed by following the 5C (connection, conversion, cyber, cognition, configuration) architecture, and they transform the collected data into actionable information, and eventually interact with the physical assets to optimize processes.
An IoT-enabled intelligent system of such capability has been demonstrated by the NSF Industry/University Collaborative Research Center for Intelligent Maintenance Systems (IMS) at University of Cincinnati on a band saw machine in IMTS 2014 in Chicago. Band saw machines are not necessarily expensive, but band saw belt expenses are enormous since they degrade much faster. However, without sensing and intelligent analytics, it can only be determined by experience when the band saw belt will actually break. The developed prognostics system is able to recognize and monitor the degradation of band saw belts even if the condition is changing, so that users can know in near real-time the optimal time to replace the belt. The developed analytical algorithms were realized on a cloud server, and were made accessible via the Internet and on mobile devices.
Integration of sensing and actuation systems connected to the Internet can optimize energy consumption as a whole. It is expected that IoT devices will be integrated into all forms of energy consuming devices (switches, power outlets, bulbs, televisions, etc.) and be able to communicate with the utility supply company in order to effectively balance power generation and energy usage. Besides home based energy management, the IIoT is especially relevant to the Smart Grid since it provides systems to gather and act on energy and power-related information in an automated fashion with the goal to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity. Using advanced metering infrastructure (AMI) devices connected to the Internet backbone, electric utilities can not only collect data from end-user connections, but also manage other distribution automation devices like transformers and reclosers.
As of 2016, other real-world applications include incorporating smart LEDs to direct shoppers to empty parking spaces or highlight shifting traffic patterns, using of sensors on water purifiers to alert managers via computer or smartphone when to replace parts, attaching RFID tags to safety gear to track personnel and ensure their safety, embedding computers into power tools to record and track the torque level of individual tightenings, and collecting data from multiple systems to enable the simulation of new processes.
Using IIoT in car manufacturing implies the digitalization of all elements of production. Software, machines, and humans are interconnected, enabling suppliers and manufacturers to rapidly respond to changing standards. IIoT enables efficient and cost-effective production by moving data from the customers to the company's systems, and then to individual sections of the production process. With IIoT, new tools and functionalities can be included in the manufacturing process. For example, 3D printers simplify the way of shaping pressing tools by printing the shape directly from steel granulate. These tools enable new possibilities for designing (with high precision). Customization of vehicles is also enabled by IIoT due to the modularity and connectivity of this technology. While in the past they worked separately, IIoT now enables humans and robots to cooperate. Robots take on the heavy and repetitive activities, so the manufacturing cycles are quicker and the vehicle comes to the market more rapidly. Factories can quickly identify potential maintenance issues before they lead to downtime and many of them are moving to a 24-hour production plant, due to higher security and efficiency.
The majority of automotive manufacturers companies have production plants in different countries, where different components of the same vehicle are built. IIoT makes possible to connect these production plants to each other, creating the possibility to move within facilities. Big data can be visually monitored which enables companies to respond faster to fluctuations in production and demand.
Oil and gas industry
With IIoT support, large amounts of raw data can be stored and sent by the drilling gear and research stations for cloud storage and analysis. With IIoT technologies, the oil and gas industry has the capability to connect machines, devices, sensors, and people through interconnectivity, which can help companies better address fluctuations in demand and pricing, address cybersecurity, and minimize environmental impact.
Across the supply chain, IIoT can improve the maintenance process, the overall safety, and the connectivity. Drones can be used to detect possible oil and gas leaks at an early stage and at locations that are difficult to reach (e.g. offshore). They can also be used to identify weak spots in complex networks of pipelines with built-in thermal imaging systems. Increased connectivity (data integration and communication) can help companies with adjusting the production levels based on real-time data of inventory, storage, distribution pace, and forecasted demand. For example, a Deloitte report states that by implementing an IIoT solution integrating data from multiple internal and external sources (such as work management system, control center, pipeline attributes, risk scores, inline inspection findings, planned assessments, and leak history), thousands of miles of pipes can be monitored in real-time. This allows monitoring pipeline threats, improving risk management, and providing situational awareness.
Benefits also apply to specific processes of the oil and gas industry. The exploration process of oil and gas can be done more precisely with 4D models built by seismic imaging. These models map fluctuations in oil reserves and gas levels, they strive to point out the exact quantity of resources needed, and they forecast the lifespan of wells. The application of smart sensors and automated drillers gives companies the opportunity to monitor and produce more efficiently. Further, the storing process can also be improved with the implementation of IIoT by collecting and analyzing real-time data to monitor inventory levels and temperature control. IIoT can enhance the transportation process of oil and gas by implementing smart sensors and thermal detectors to give real-time geolocation data and monitor the products for safety reasons. These smart sensors can monitor the refinery processes, and enhance safety. The demand of products can be forecasted more precisely and automatically be communicated to the refineries and production plants to adjust production levels.
As the IIoT expands, new security concerns arise with it. Every new device or component that connects to the IIoT can become a potential liability. Gartner estimates that by 2020, more than 25% of recognized attacks on enterprises will involve IoT-connected systems, despite its accounting for less than 10% of IT security budgets. Existing cybersecurity measures are vastly inferior for internet-connected devices compared to their traditional computer counterparts, which can allow for them to be hijacked for DDoS-based attacks by botnets like Mirai. Another possibility is the infection of internet-connected industrial controllers, like in the case of Stuxnet, without the need for physical access to the system to spread the worm.
Additionally, IIoT-enabled devices can allow for more “traditional” forms of cybercrime, as in the case of the 2013 Target data breach, where information was stolen after hackers gained access to Target's networks via credentials stolen from a third party HVAC vendor. The pharmaceutical manufacturing industry has been slow to adopt IIoT advances because of security concerns such as these. One of the difficulties in providing security solutions in IIoT applications is the fragmented nature of the hardware. Consequently, security architectures are turning towards designs that are software-based or device-agnostic.
“Industrial Internet of Things.” Wikipedia, Wikimedia Foundation, 27 Apr. 2019."