How Industrial IoT enables the factory of the future
Trillion-dollar projections on the expanding size of the market are urging companies to capitalize on the Industrial IoT. For many, however, it remains unclear how industries should apply IIoT to begin making the hyper-efficient and agile factory of the future a reality. Fabio Bottacci, founder and CEO of VINCI Digital and Industrial IoT Expert Contributor at the World Economic Forum and at the Brazilian Development Bank (BNDES), shares his insights on how Industrial IoT is already increasing operational efficiency, saving time and reducing cost.
As the Fourth Industrial Revolution transforms manufacturing and material handling, enterprises continue to look for ways to create value from converging technologies. But what are the steps that companies need to take to put together an effective agenda of action? Fabio Bottacci finds it essential that the implementation of industrial internet is incorporated into the company’s strategy and business development. In other words, chief executives must embrace change. “In order to advance decision-making on the correct level, CEOs must be included from the very beginning, possibly as initiative main sponsor. IT officers alone cannot drive real digital transformation,” says Bottacci.
Bottacci advises manufacturers to initiate the transformation by defining a specific set of goals, to be assessed and validated initially on a pilot project, before the implementation at scale of an end-to-end Industrial IoT solution. The next step is to deploy an industrial internet pilot in one facility, or on a specific production line, which will be used as a case study for learning how IoT works in this particular industrial environment. The pilot facility is then reworked and developed according to observations. After the test phase, it is easy for a company to apply the same principles, with proper adjustments, at scale to other facilities.
Bottacci uses the concept of flexible infrastructure to refer to how transformation can be simpler in certain contexts. “It is easier to justify large investments in industrial internet in environments where industrial internet is incorporated into production by transitioning directly to automated, advanced IIoT environments. The transition phase is less complicated when the existing infrastructure is light, because there are fewer things that must be accounted for in applying new solutions,” he explains.
A case in point is Romania, where the internet infrastructure is now top of the class in Europe. The Romanian infrastructure was created rather recently compared to more affluent European countries, and therefore, the entire web is more modern than that in Finland, for example.
Industrial internet in practice
“IIoT coupled with AI or ML turns maintenance into a dynamic, rapid and automated task.”
Bottacci emphasizes that applications of industrial IoT are already a reality. According to him, there are dozens of different use cases of IIoT in enterprises. “Companies are already developing IoT applications that work, and they have started making a difference. For example, transportation and warehousing benefit from automated vehicles and asset tracking. In manufacturing, predictive maintenance and asset performance management are key areas where industrial internet boosts value creation.”
Predictive maintenance keeps assets up and running, decreasing operational costs and saving companies millions of dollars. Data from IIoT-enabled systems – sensors, cameras, and data analytics enabled by powerful artificial intelligence (AI) or machine learning (ML) algorithms – helps to better plan maintenance, allowing manufacturers to service equipment before problems occur. “Data streaming from sensors and devices can be used to quickly assess current conditions, recognize warning signs, deliver alerts and automatically trigger appropriate maintenance processes. IIoT coupled with AI or ML thus turns maintenance into a dynamic, rapid and automated task,” Bottacci explains.
“Other potential advantages include increased equipment lifetime, increased plant safety and fewer accidents with negative impact on environment,” he adds.
The importance of edge analytics
“Companies have been proactive in moving the processing of IIoT to cloud services,” Bottacci notes. However, in his opinion, it is not necessarily a wise move to have everything in the cloud. During critical stages of the manufacturing process it is crucial that decisions can be made instantaneously. Here, manufacturers can benefit from edge analytics.
“Edge computing enables real-time analytics. Edge analytics is an approach to data collection and analysis where automated analytical computation is performed on data at a sensor, network switch or other device instead of waiting for the data to be sent back to a centralized data store. IIoT can be supplemented with Arduino-based, open-source computer hardware and software applications that allow some of the processing to take place on site, at the edge of the network and near the source of the data. Edge computing helps ensure that the right processing takes place at the right time, in the right place,” Bottacci explains. “Edge computing is a preferable option for the cloud in terms of security, as proprietary data is kept within the company firewall. Moreover, edge computing becomes vital when you need real-time analysis and automated action to save critical-mission production lines or facilities from potential heavy damages.”
Creating value with Industrial IoT
“There’s no value in the data without advanced algorithms of machine learning.”
Bottacci says that value can be created in surprisingly simple ways by putting data to work. As an example of enhancing safety and efficiency in material handling, he refers to a fleet management system in Silicon Valley. “Peloton Tech’s truck platooning system is a case study that illustrates how IIoT is already creating value. The system uses vehicle-to-vehicle communication to connect the braking and acceleration between two trucks. The lead truck controls the simultaneous acceleration and braking of the whole fleet, reacting faster than a human or even a sensor system could. What follows is a reduction in aerodynamic drag, which leads to companies saving around seven per cent in fuel cost. In terms of annual savings, this is a remarkable number,” says Bottacci.
In Europe, trucking companies such as Scania and Volvo Trucks have adopted IIoT fleet thinking. “It still takes courage to adopt innovations like these,” Bottacci admits. However, he recommends getting started quickly by building a case study of industrial internet and then working towards expanding IIoT to cover more and more of the industrial realm. “Companies should start seeing emerging technology like Industrial IoT not as a threat but as the only way to survive in a matter of a few years. That’s two or three years if you are an optimist, five to ten if you are more conservative,” estimates Bottacci.
In Bottacci’s view, the simple capacity of devices to seize data is not what the Industrial Internet of Things is essentially about. “Even if you have all the infrastructure and the technology to get the data – sensors, WiFi, the gateway, the cloud – and the capacity of analyzing the data, there’s no value in it without AI, more specifically advanced algorithms of machine learning.”
“IIoT is about AI or ML analyzing data in real time so as to make decisions and act, most of the times several days or even weeks before a potential issue. This process results in actual business outcomes,” Bottacci states. “Prescriptive analytics react autonomously, real-time: In a mission-critical situation, a prescriptive system will autonomously decide what to do. This is where edge analytics is imperative,” he explains. “My point is: You can’t consider industrial internet standalone. The real value comes from how companies use AI and ML-enabled IIoT solutions in analyzing and processing data.”
Fabio Bottacci works as an independent advisor. He is founder and CEO of VINCI Digital and an Industrial IoT Expert Contributor at the World Economic Forum and at BNDES, the Brazilian Development Bank.
Unifying industrial IoT technologies with monitoring
While the majority of industrial companies have multiple systems and technologies managing various components of their operations, only a few have been able to aggregate the data from all of these systems together to drive business prosperity. When brought together, the data from these disparate systems can produce insights across all aspects of the business.
“The teams and upper management of these industrial organisations could – with a unified monitoring tool – see every link in the supply chain and their products’ evolution from early stages right through to delivery,” Paessler AG’s APAC sales director Andrew Timms told IoT Hub. Besides operations-wide oversight, monitoring tools can also be used for the management of particular components of the value chain.
Read more about aggregating data from RFID, SCADA, IT and other sources at: https://www.iothub.com.au/news/unifying-industrial-iot-technologies-with-monitoring-458258
Looking for the human-machine touch
Digital technology is fast changing the way vehicles are built, but the pace of change varies according to different manufacturers and production processes. Above all, the importance of human workers has been central to the decision process for new technology – and looks set to remain so in the future.
According to Automotive Logistics, experts who spoke at automotiveIT Forum – Production and Logistics, which took place during the recent Hannover Messe, stressed that digitalization starts on the shop floor. Implementing logistics automation and support technology needs to be done with workers in mind – including their safety and comfort, but also their skills. For instance, Dr. Sabine Pfeiffer, professor of sociology at the University of Hohenheim, noted that the industry tends to focus on university graduates or consultancies, “but if you work with the experience and skills on the shop floor, you will get great results.”
Read more on how to begin disruption at the shop floor level: http://automotivelogistics.media/intelligence/looking-human-machine-touch
Image credit: Zapp2Photo / Shutterstock.com
Pushing IIoT predictive maintenance forward: two challenges to overcome
Enabled by wireless technology and connected devices, communication between machines and human technicians is fueling a shift from preventative to predictive maintenance. To push IIoT predictive maintenance technologies up the slope of enlightenment and spark mainstream adoption and success, two major challenges must be overcome: the challenge to obtain high quality data from industrial machines, and that to fuse sensor data with maintenance activities.
An article in Reliabilityweb offers solutions ranging from deep learning algorithms to tapping into the intuitive human capacity of sound-based diagnosis.
Read more about ways to overcome IIoT maintenance challenges and combine deep learning and human input: http://reliabilityweb.com/articles/entry/pushing-iiot-predictive-maintenance-forward-two-challenges-to-overcome
Image credit: Zapp2Photo / Shutterstock.com
How the Internet of Things impacts supply chains
Enterprise resource planning and supply chain management (SCM) have gone hand-in-hand for quite some time, but the IoT revolution will allow those solutions to be enhanced by intelligently connecting people, processes, data, and things via devices and sensors.
“Think of it as SCM 2.0,” writes Udaya Shankar, Vice President and Head of Internet of Things for Xchanging, a business process service provider for the global insurance industry. According to Shankar’s article in Inbound Logistics, this deeper intelligence can come to life in many different ways when it comes to supply chain data and intelligence – from the automation of the manufacturing process to improved visibility within the warehouse.
One area that Shankar believes will play a prominent role in the future supply chain, as it’s impacted by IoT, is in-transit visibility. “The logistics ecosystem has many players, and thus, many moving parts. Products are handled and transferred between the manufacturer, suppliers, the distribution center, retailer, and customer.”
Read more about how IoT can help supply chain professionals at:
Image credit: Lightspring / Shutterstock.com
How to use plant floor data to make smart strategic business decisions
In the case of HK Metalcraft, a manufacturer specializing in precision metal stampings, IoT has made possible the harnessing of plant floor data. “Connecting the plant floor to HK’s business operations through cloud ERP turned that data into actionable information,” according to an article published by Industry Week. The piece is based on a White Paper published by US software company Plex.
When coupled with what happens on a plant floor, a cloud ERP solution enables “the kind of insight and control manufacturers need to make critical business decisions.” Cloud ERP has allowed HK Metalcraft to manage the downtime of operators and see everything from the direct overhead down to the specific amount of time that each operator has spent doing a specific job. “Now not only does HK Metalcraft know exactly what caused the downtime but they also have actionable data to improve processes and overall equipment effectiveness.”
Read more about how HK Metalcraft turned data into actionable information at: http://www.industryweek.com/cloud-computing/how-use-plant-floor-data-make-smart-strategic-business-decisions
Image credit: Pavel L Photo and Video/ Shutterstock.com
Top 10 ways integration will transform manufacturing in 2017
“Enabling a faster pace of innovation in manufacturing starts by using systems and process integration as a growth catalyst to profitably grow,” writes Louis Columbus, Vice President of Marketing at iBASEt.
In Columbus’ article for Enterprise Irregulars, he highlights the importance of real-time data for both manufacturers and customers. He also mentions how the integration of traditional IT and manufacturing systems are vital in order for the potential advantages of Industry 4.0 to be fully realized.
“The key to revitalizing existing production centers and getting them started on the journey to becoming smart factories depends on the real-time integration of IT and manufacturing systems,” Columbus continues. Manufacturers should also expect the importance of IoT generated sensor data, combined with advanced analytics, to keeping increasing in 2017.
Read more about how integration powers manufacturing innovation at:
IoT spending 2017-2020: Internet of Things industry drivers and investments
According to i-Scoop, manufacturing, transportation and utilities are the industries “poised to invest the most in IoT until 2020”. Though currently we are seeing a lot of investments in Consumer Internet of Things (CIoT), it is expected that by 2020 these investments will decrease. The article highlights aspects of the IDC Worldwide Semiannual Internet of Things Spending Guide.
“In the leading IoT industry, manufacturing, operations by far represent the main spending use case ($102.5 billion in 2016 on the mentioned total of $178 billion), outperforming other manufacturing IoT use cases such as production asset management and maintenance and field service. The only exception is the EMEA region, where freight monitoring (transportation) is the main use case, followed by manufacturing operations,” according to the IDC report.
Read more on IIoT investments and patterns per industry and cross-industry at: http://www.i-scoop.eu/iot-spending-2020/
Image credit: Hamik / Shutterstock.com
Making the shift from smart factories to living services
The Industrial Internet of Things (IIoT) is transforming the way manufacturers approach matters such as resource allocation, production processes and the workforce. In time, companies will gain even more benefits from the highly automated, end-to-end production integration of intelligent products and services made possible by the IIoT. Edy Liongosari, chief research scientist and managing director at Accenture Labs, talks about critical trends and uncovers advantages that have yet to be widely discussed.
Operational safety and efficiency are two of the most clear-cut advantages the IIoT brings from the outset. Edy Liongosari believes those are the obvious ones because the return on investment of such initiatives is much simpler to calculate and measure. “When we talk about new products and services, however, the business cases are typically built with a lot of assumptions. Therefore, the confidence on those business cases is lower. But that’s exactly where the big opportunities are.”
Liongosari says that safety and efficiency are just part of the first of four waves of IIoT adoption. The next wave – which he believes has greater transformational impact – consists of the creation of smart products and smart services. “It’s vital to consider how you are going to be able to use the physical products that you have and to think about the product as a way – as a channel if you will – to sell and deliver what we call living services,” he shares.
Living services are contextually aware digital services designed to anticipate and respond to customer needs in real-time through the channel that you have. Liongosari mentions one example that emerged from the IOT Solutions World Congress in 2016: Bigbelly is a connected trash bin that knows exactly when to compact waste and when to unload it. He also cites Claas, the German agricultural machinery manufacturer that has partnered with the free field mapping service 365FarmNet. Together the two use their respective fields of expertise to bring about precision farming, in turn driving the future of agriculture.
A universal standard
In a manufacturing setting, thanks to the convergence of Operational Technology and Information Technology, manufacturing equipment is increasingly connected with larger enterprise systems – from manufacturing execution systems, production management, logistics and enterprise resource planning systems – to allow manufacturers to plan, monitor and adjust their production in real-time.
Liongosari, however, is of the opinion that a universal standard to allow equipment from multiple vendors to communicate and collaborate will not become the norm, at least not in the short term. “It’s primarily because of the diversity of the use cases, environmental conditions, and laws and regulations that fall under the IIoT. For example, the diversity of IIoT infrastructure requirements such as energy consumption, computing and bandwidth availability, mobility and security makes it very hard to have just one sole industry standard,” he explains. However, there are plenty of efforts to make specific IIoT standards to interoperate – to the extent it can be reasonably done – through a variety of testbeds.
“You can see the borders between various industries slowly disappearing because a lot of newcomers are coming to your game very, very quickly. The possibility is really big.”
According to Liongosari, there are four key trends impacting the IIoT. The first deals with automation and artificial intelligence (AI). Our ability to automate or augment work processes using machine intelligence can now be done at the unprecedented scale and precision through the use of AI techniques.
In an automotive manufacturing plant, for example, cameras can be used to learn and detect refined defects in a product. Rather than wait for a batch run to be completed before defects are found, those can be detected in real-time. “Sometimes you don’t realize the presence of small defects until much later on, resulting in a significant loss of work,” he explains, adding that in many cases, existing surveillance cameras can be repurposed for defect prevention in quality assurance by embedding some intelligence in them. “This is what we call the next generation of automation.”
The second key trend is about human and machine interaction. “The industrial workforce itself is changing significantly,” he says. A human workforce is augmented with wearable computing capabilities to significantly increase their efficiency as well as agility, allowing them to take on new tasks at the speed like never before. In addition, collaborative robots – or cobots – that have been used for hospitality and concierge services, are now being expanded to perform simple and repetitive tasks on the factory floor, such as those in Amazon’s warehouses.
The third comprises platforms and ecosystems. “One critical element of smart products is their ability to sense, configure, and respond based on the needs of the customers,” states Liongosari. “It’s not just selling your products and services but the ability to turn the product itself into a platform – just like in Android or iOS – to allow others to build upon it and use it to build a set of rich and interconnected living services provided by a lush ecosystem of business partners.”
The last key trend is cybersecurity, which is rising in importance due to vulnerabilities to attacks, espionage and data breaches brought about by increased connectivity and data sharing. Liongosari brings up the denial of service attack by a Mirai-based botnet that affected IoT devices in September 2016 as a reminder of the importance of cybersecurity in this highly interconnected world.
“In addition to security, privacy and data ethics are increasingly critical especially given the vast amount of customers’ and employees’ data that companies now have access to. In some cases, the concept of data ownership in an organization is being seriously questioned as ownership implies that the organization can do whatever it wants with the data,” says Liongosari.
The use of such data is highly dependent on many factors beyond data privacy laws and regulations. For example, organizations need to factor in the original intention of data when it was provided or captured, ethical interpretation of the analyzed data, and how the results are being used and shared ethically. “How are you going to interpret data uniformly across different countries, laws, interpretations and usages? The meaning of data ownership may change or the term may completely disappear.”
Seizing the opportunity
In order for manufacturers to chart a path of growth through the IIoT, Liongosari offers sound advice. “You can start small in a sense that you can focus on operational efficiency – that there is a specific return on investment that you drive toward. But at the same time, you need to think big because the opportunity is a considerable one,” he says.
“You can see the borders between various industries slowly disappearing because a lot of newcomers are coming to your game very, very quickly. The possibility is really big.” To seize the opportunities of the Industrial Internet of Things, Liongosari sums it up with this mantra: “Start small, think big, and iterate fast.”
Edy Liongosari works as chief research scientist and managing director at Accenture Labs
Image credit: Zapp2Photo / Shutterstock.com
A wider view gives more accurate results
Taking a step back and analyzing processes from a larger perspective might take you to surprising places, such as a dinner table in a Chinese household, says Petri Asikainen, Director, Product Development at Konecranes. According to Asikainen, to get the most out of your production processes, having a wide view of the process in hand is crucial. By seeing the processes as a whole, monitoring them as widely as is possible and by adjusting the production facilities’ metrics accordingly, noticeable boosts can be gained in the total output.
Industrial monitoring is going through big changes. From the variety of ways in which equipment in an industrial setting can be monitored, to the new possibilities in remote monitoring and -operation, operators in facilities have gained new ways to operate efficiently. A great example of this can be found in the context of waste processing.
“We were asked to optimize the operating activities in a certain waste management facility. We noticed that once we installed a Remote Operating Station for the crane operators in the power plant’s main operating room, suddenly the old local operating room over the waste bunker wasn’t the number one choice for working anymore,” Asikainen says.
Having all the personnel operate the plant from one location allows for better communication between the operators in charge of different parts of the facility. It also offers noticeable savings for companies, as there’s no need to build additional local operating rooms just to be physically present for the operation of the cranes anymore.
Monitoring everything there is to be monitored
In many industrial operations, the crane is in the center of the production process. This unique position allows for the possibility to gain deep insight of the production process.
“The entire material flow in the facility might be dependent on the crane, and this gives us plenty of opportunities to create different types of insights for customer’s needs. One example, found in the context of the paper industry, is that we can better identify where reject appears. This is valuable information for the manufacturer, and if it can help to improve the material efficiency of the manufacturers process by half a percent – it might already cover the cost of the crane data gathering capability and analysis work with extremely short pay-back time,” Asikainen explains.
The cranes’ movement patterns can also be tracked in the production facilities, so that the biggest bottle necks can be found. This tracking also helps map the actual material flow. If a load is moved from one place to another several times back and forth, the whole process slows down.
“Existing manufacturing facilities continuously face the need to respond to the global race for lowering costs and improving efficiency. A thorough analysis of the material flow can help improve production. Through it, we can find out what kind of crane setup would suit the client’s process, a result which is based on the actual measured data. When one is considering rebuilding an existing facility, this kind of efficiency analysis is a good tool to define the profitable targets to invest in.”
As to why Asikainen ended up practically monitoring how a household dines, he uses it as an example of how processes can be optimized in various, wider ways.
“We discovered that the loaders used in the waste facilities in China were continuously moving heavier loads compared to their European counterparts. One reason for this was that the households use a large amount of oil in cooking. The residue ends up in the trash and then to the waste processing facilities. This has an effect on the raw material, making it finer and increasing its energy density,” Asikainen explains.
This has a direct effect on how the whole process is set up and the crane is optimized. When the operators have a better view on the type of waste coming in to the facility, the effect that the differences in waste have on the energy output can be taken into account better.
Benefits of monitoring
When asked about the benefits the increased monitoring brings for companies, Asikainen brings up the similarities between lift trucks and cars. Both have similar concerns, such as tire leaks. For both, leaks can be monitored and fixed faster through monitoring. Early reaction to low tire pressure decreases extensive wearing and improves safety.
The operability of cranes develops in similar trends as cars – functionalities which 15 years ago could have been sold only to extreme needs, are now common even in the most value-focused cranes.
“Snag prevention is an example of this. It automatically stops crane movement if a hook, a sling or a load accidentally gets caught on something. Having real-time information on both the environment in which the crane is operating as well as the loads that they are moving, has made it possible to halt the crane if something gets caught in the way”, Asikainen says.
Hook centering is also an effective technology to improve efficiency and safety. If you lift a load and the hook isn’t centered, the load starts to swing as it’s lifted off the ground. The hook centering positions the crane above the hook, eliminating a possible human error. The hook is where it is supposed to be before lifting the load.
Maintenance by demand
Another way in which the increased monitoring can be utilized by companies is by making maintenance more effective. When you have sensors measuring thousands of points of data, you can efficiently both prevent halts as well as optimize maintenances routes.
“With the increased amount of information, technicians can focus their attention to issues needing extra care. The crew can also receive info on which manuals, tools and parts they must have with them beforehand,” Asikainen says.
All in all, maximizing the improvement through monitoring is dependent on two things – both the gathered data and the insights. Through having both, companies can achieve a more holistic view of their process, one which is based more on the actualities of the operating environment, and not just on subjective, professional guesses. This makes the whole manufacturing process more reliable and transparent.
Petri Asikainen works as Director, Product Development at Konecranes.