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
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How can Industry 4.0 help the global steel industry achieve greater efficiencies?
Taking place in Warsaw, Poland, the Future Steel Forum assembles speakers from academia and the steel industry to examine how technological innovations can revolutionize steel production. Matthew Moggridge, Editor of Steel Times International, talks about the themes and perspectives steelmakers must consider as they shift to a digital manufacturing platform.
According to the 2016 Global Industry 4.0 Survey conducted by the consulting firm PwC, the buzz surrounding Industry 4.0 has moved on from what some had earlier considered as hype to actual investment and real results. This investment, in turn, is translating into increasingly advanced levels of digitization and integration. 67% of respondents from the metals sector, among them companies in the steel industry, say they expect to reach advanced levels of digitization in their vertical value chains by 2020.
Matthew Moggridge, Editor of Steel Times International, shares a similar view. “The steel industry is well prepared for Industry 4.0 and has, for a long time, been at the forefront of industrial technological development,” he says.
“There are companies, such as Primetals Technologies, SMS group, Danieli Automation, Fives, among others, who have been pushing the boundaries of digital manufacturing and partnering with leading steelmakers such as ArcelorMittal, Tata Steel, Voestalpine and many others to develop the concept of Industry 4.0.”
Moggridge adds that in the US, Big River Steel is arguably the first smart steel plant. The company recently partnered with Noodle.ai, a San Francisco-based Enterprise Artificial Intelligence company, to implement Enterprise AI to optimize operations at the former’s scrap metal recycling and steel production facility in Osceola, Arkansas.
“On the one hand, digitization has moved from being an augmenting capability for steel companies to something that is now becoming a disruptive force. On the other hand, it is delivering supply chain agility, deeper process understanding and higher production utilization.”
Efficiencies and challenges
Broadly speaking, Industry 4.0 assists the global steel industry in its quest for greater efficiencies while raising new concerns. On the one hand, as digitization has moved from being an augmenting capability for steel companies to something that is now becoming a disruptive force, the PwC report says that it is delivering supply chain agility, deeper process understanding and higher production utilization.
The report states: “Automation is combining with data analytics to enable much higher flexibility as well as more efficiency in production. Algorithms are linking the physical properties of the materials with production costs and plant constraints to improve efficiency. Processes that were previously separated are now being integrated, leading to reductions of heat loss, energy consumption, throughput time, inventory as well as better price optimization.”
On the other hand, the people aspect also needs to be addressed. PwC states that companies will need to make sure staff members understand how the company is evolving and how they can be a part of the change. From PwC’s interviews with metals companies, the biggest challenges involve issues such as culture, leadership and the economic case for change.
In addition, Moggridge cites Dirk Schaefer, assistant professor of design engineering at the University of Bath, UK, who argues that the development of a new work force will also prove challenging within the context of Industry 4.0. Schaefer believes that investing in workforce education is essential. “Each of the previous industrial revolutions resulted in a surge of unemployment. There is no reason to believe that this will be any different this time around, unless preventive action is taken today,” Schaefer asserts.
— IndIntNow (@IndIntNow) June 14, 2017
These topics will be addressed by experts at the Future Steel Forum in Warsaw, which takes place today and tomorrow. Other discussion points include the impact of smart manufacturing on the steel industry, Industry 4.0 and its implications for plant safety, the future of cooperation between automation and steel manufacturing, and the role of human beings in the factory of the future.
Taking part are speakers from academia, the steel industry and the world of steel production technology such as Dr. Rizwan A Janjua, Head of Technology, World Steel Association; Jose Favilla, Director, Industry Solutions for Industrial Products, IBM; and Professor Chris Hankin, Imperial College London, among others.
Connecting the dots
As for Industry 4.0-related themes that are set to gain ever greater prominence in the coming years, Moggridge, who will deliver the welcoming and closing remarks at the event, has this to share. “Cyber security will always be a big issue that will constantly need to be addressed, but also the role of the human being in an increasingly automated environment, not only in steel but in other areas of industry as well,” he says.
“What people tend to forget about the steel industry is that it is already a very automated environment. In many ways, it’s just a case of connecting the dots before steelmakers can claim to be true advocates of Industry 4.0.”
Matthew Moggridge is the Editor of Steel Times International. The Future Steel Forum takes place in Warsaw, Poland, on June 14–15, 2017. futuresteelforum.com
The future of IoT and machine learning – what role will humans play?
Despite having been around for over two decades, machine learning and its integration into business models is yet to become commonplace. Jari Salminen, Managing Director of Cumulocity, has witnessed the unfolding of machine learning and noted the progress made in its adoption into a wide range of industries over recent years. He says that rather than spend time in building grand strategies then assume that value can immediately be realized, companies should take pragmatic steps to connect their assets and start collecting data.
“What we are seeing today is that there typically exists a bit of a delay when companies start connecting assets and collecting information to be able to rely on machine learning algorithms and their accuracy,” says Salminen. “The training of these algorithms requires large amounts of data and thus time. It takes time for any individual company to move through the cycle of starting with very basic use cases and moving onto more complex algorithms and dependencies, and eventually introducing machine learning.”
At Cumulocity, Salminen deals with several manufacturing and industrial companies. He recognizes companies that require warehouses – or those whose supply chains do – currently expect sophisticated IoT solutions from a production and manufacturing point of view.
“Things are changing at such a pace that it is now very cost efficient even for smaller companies to deploy off-the-shelf IoT solutions for their supply chains.”
Salminen encourages companies who have examined the cost of IoT solutions for manufacturing or supply chain management over recent years to do so again. “Things are changing at such a pace that it is now very cost efficient even for smaller companies to deploy off-the-shelf IoT solutions for their supply chains as the price of hardware, connectivity and software has dramatically reduced over the last 5 years,” he reasons.
Holding algorithms accountable
The accuracy and efficiency at which these solutions can be implemented will greatly depend on the algorithms triggering them. According to Salminen, the more automated these algorithms become, the greater influence they will have not only on supply chains, but beyond them as well.
“Today, most actions are still done by human users and there are several reasons why that is. For example, accountability – in the long-term, we will need to ask how this will change. Will decisions be made based solely on the algorithms that machine learning will make possible? Maybe. However, such questions and their answers go beyond technology itself, as they are concerned with making sure that somebody other than a computer takes responsibility for decisions. It’s a complex domain,” Salminen says.
So, how to legally and ethically approach decision-making when no human is involved in the process? Very similar questions are currently being asked in the automotive industry.
Closely tied to the accountability of machine-to-machine decision-making within IoT projects is the matter that is security. In general, issues surrounding security are never too far away when connectivity, machines and material networks are concerned.
Multilevel security management
“The issue with security is that it exists on so many levels in IoT projects: from hardware – meaning devices, machines and assets – and connectivity, whether that entails using mobile connections or new narrowband IoT solutions, to the backend, meaning the cloud or servers. On top of all that you might have special applications for company users, partners or even consumers. Security needs to be controlled and monitored at all these levels.”
“Often, security breaches take place when more than one area has been overlooked. A most common area attracting hackers and attacks is wherever any connected device exposes ports reachable from the internet. These are being scanned by hackers,” Salminen continues. He reminds companies that if they are dealing with hardware, that they should keep their wide area network ports closed; from a connectivity perspective, they must make sure that everything is fully encrypted in transit.
“If you are providing cloud services on top of hardware and connectivity, make sure that your whole system is robust and secure. Ultimately, there is no single thing companies must consider when it comes to security, but rather, it is an area that must be owned end-to-end by someone in the project.”
Setting future standards
When asked how he sees the future of machine learning and IoT taking shape, Salminen is simultaneously restrained and excited. He sees industries as being past the initial hype. The implementation of more advanced and sophisticated use cases is now becoming a reality.
“The connectivity costs per device are decreasing, and thus enabling many new developments when it comes to industrial solutions. This is happening across widespread assets, meaning that for example, narrowband technologies are becoming more popular. However, what is still lacking from IoT and will need to be addressed in the next few years is standardization.”
While Salminen is adamant that a comprehensive philosophy regarding standardization must be adopted, he does not foresee the use of one single underlying standard that will apply across industries.
“My guess is that there won’t be an overarching standard that will include everything from devices to data structures. There will be so many different IoT use cases that it will be impossible to create something that would cover all of them,” he says. “We see lot of traction with MQTT (Message Queuing Telemetry Transport) as a messaging protocol due to the fact it doesn’t even try to standardize all parts of the IoT stack. For example, it does not deal with message payload format which is left to the developer to decide.”
On the other hand, Salminen believes that standards like Lightweight M2M by Open Mobile Alliance are not being picked up by market players because probably it doesn’t fit many use cases, among other reasons.
Nonetheless, he reminds those looking to initiate IoT projects to certainly consider available standards, but not to be limited by them. He also states that the key thing to ensure is that you are not locked into any standard, but to have flexibility in case your needs change in the future.
“If I were starting an IoT project, I would be looking at the most recent connectivity options, the role of standards, if such exist, and whether or not they are relevant to my business. However, I wouldn’t force any standards at the moment, as there are in fact very few that are relevant,” Salminen concludes.
Image credit: ImageFlow/ Shutterstock.com
How to build Big Data competencies
There are two separate topics to consider when it comes to Big Data. One involves finding a solution to an existing problem or challenge. The second has to do with building something new. Matti Vakkuri, Head of Technology, Internet of Things at Tieto, outlines ways in which companies can build their Big Data competencies. He also discusses the aggregation of unstructured and machine IoT data in a manufacturing context.
“If we narrow the discussion to cover only the data drivers of Big Data, we are going in the wrong direction,” says Vakkuri. As an example, in B2B operations in the maritime industry like port optimization or fuel consumption optimization in vessels, data delivers huge benefits for a shipping business. “Less polluting engines – or ones that generate more power from less consumption – could be designed based on data that is collected. This would affect productivity and competitiveness because shipping is a volume business.”
Vakkuri adds that this data needs to be utilized so that all the information isn’t amassed for the sake of it. “You always ought to build something with or on the data. This brings an opportunity for data-driven firms,” he continues. “In nuclear power plants in Finland, there’s a regulation that data has to be stored for a relatively long period. Before Big Data, it was mainly in passive storage only. With Big Data, however, all data can be online. This means that we can do research based on the data that already exists.” Vakkuri points out that this is one of the paradigm shifts – that instead of having inaccessible passive data, we now have available data from which we can build analysis, business, opportunities and innovations.
Amazon is a good example. “The truly remarkable thing about their business is that they see who is checking their products, putting them in their basket but not buying them. Checking but not buying – taking things out of your basket and not proceeding to check out – these send very significant signals. Big Data allows this to be done, but it must be understood that Big Data is also about analytics and machine learning,” continues Vakkuri. The same kind of implementation that is being applied in webstores can be also be used in brick and mortar retails stores using indoor positioning.
Tieto’s Intelligent Building Product Line is another case of effective Big Data usage. “This allows us to establish who is where in our new headquarters at any given moment. As long as I have given my permission, for instance, I can be followed around the office. Knowing where co-workers are at any time helps us to be more collaborative,” shares Vakkuri. Beyond determining where people are, the company is also gathering data to optimize and remodel how space is used in their offices.
A question of ethics
To CIOs and CDOs keen on building Big Data competencies in their respective companies, Vakkuri offers this piece of advice. “The answer is really simple: multi-disciplined people. You need technology guys who possess not just domain competence but also ethics. There must be somebody who is capable of understanding ethical aspects and good manners not based on gut feeling, but rather on an understanding of the logic behind whatever ethics is used.” Ethics, Vakkuri notes, is vital in technologies such as AI and Big Data.
“Another thing is that you need a team of people in which every person is different, and from a different background, but who are able and willing to build things together. Never hire just one person to be a data scientist, but a team made up of individuals with a variety of experiences, ages and educational backgrounds, and who come from diverse cultures.” He believes that the more heterogeneous your team is, the better.
“Never hire just one person to be a data scientist, but a team made up of individuals with a variety of experiences, ages and educational backgrounds, and who come from diverse cultures”
Combining unstructured and machine IoT data
“Let’s start with instruments: Instrument everything. This means – as Twitter co-founder Jack Dorsey once advised – log, measure and test everything. Store everything, store all relevant data,” suggests Vakkuri. “If you install video cameras in your factory, you don’t need to collect the data of the raw image, but more so the metadata of what is in the image, timestamps, location data, etc.”
He would like companies to forget the notion that storing and analyzing data is expensive – they really are not nowadays. “The paradigm has changed so that infrastructure costs are down, so invest in human capital and in people who can analyze the data. But if you want to conduct a comprehensive analysis, you need to combine the data sets together which has never been done before, so be provocative and think outside the box. While you’re at it, forget the box altogether.” He adds that this also depends on how open-minded and competent your employees are, and what types of ideas they propose. “In the end, it’s all about what innovations you can get to with the data.”
On Big Data and machine to machine implementation
As far as Big Data and machine-to-machine (M2M) implementation are concerned, Vakkuri has this to share with manufacturers. “M2M communication needs to be more standardized. This also means using the right tools for the right purposes. How do you know what’s right? Only by building proof of concepts and then testing,” he explains.
Vakkuri likewise recommends establishing a partnership involving the research side – such as universities and similar institutions – within the ecosystem. “Carrying out a research collaboration usually means that your costs will be lower when developing something new and quite often new innovations come from the applied research side.”
Last, data quality and information security are two other points Vakkuri would like to underline when it comes to M2M communication. “Information security needs will be more complex. The more machines and data are connected, the more challenges will arise in terms of information security.”
Matti Vakkuri works as Head of Technology, Internet of Things at Tieto.
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Managing change in the connected workplace
The move to the digital world has allowed us to create new value inside the workplace, but adopting the IoT on a wider scale poses a few challenges. Alexander Reay, Chief Digital Officer at Sodash and President of the Nordic IT Association, explores the role an organization’s structure and culture play in maximizing IoT’s potential for businesses. He also talks about the leadership issues that need to be addressed during this transformation.
The Internet of Things (IoT) is very transformative and is reshaping business models. This disruption entails a huge amount of internal change that needs to be addressed in an organization. Alexander Reay, Chief Digital Officer at Sodash and President of the Nordic IT Association, believes that the issue is connected to neither technology nor technology maturity. “It’s a leadership one. It’s about understanding the digital economy – or if you prefer, the platform economy – we’re moving into.”
This transformation through technology, he adds, is a cultural matter. “It’s the impact of how the business and the people in it work. When you’re moving systems into the cloud, the major issue is to actually lead or inspire people who are very much used to the traditional way of doing things to adopt this new method.”
Since digital transformation is something that effects every single part of a business, a leader can’t be expected to do this on his or her own and needs to invest into change agents.
Culture of change
“An organization needs to have a culture of proactive change and the individual spearheading it needs to have a completely systematic and holistic view,” continues Reay. “Leadership in larger enterprises, however, isn’t as agile and usually can’t cope with quick, radical change. By far, that is the biggest barrier in adopting new and better ways of doing things along with rigid old hat organizational structures and governance”
As companies are recast as digital enterprises, and organizations continue to adapt to the IoT and the new demands of managing the physical and the digital, this convergence mandates not only new skills but also different ways of working.
The role of chief digital officer (CDO) involves looking for business opportunities that have been enabled by the digital revolution. It also entails focusing on customers and how their needs might change because of technological developments. It is quite different to that of the chief information officer, whose job — though similarly complex — is more about following procedures and keeping a company’s IT systems running. By contrast, the digital role is to head the transformation.
“This is really a leadership understanding of the technology – how to use it, how to drive new value as result – not the technology itself. So forget thinking of IoT and digitalization as just new technologies.”
As Reay stresses, “This is really a leadership understanding of the technology – how to use it, how to drive new value as result – not the technology itself. So forget thinking of IoT and digitalization as just new technologies. For those companies that get it, digital represents an entirely new way of doing business, moving from using technology as a catalyst for efficiency or effectiveness into driving new value or even changes to entire business models, but most important, they are in the process of changing their corporate culture”.
Difference between network and community
To begin the work of digital delivery, the companies recruiting chief digital officers must break down the walls between the independent vertical structures in their organizations. Reay notes that since we’re used to really siloed innovation, “we’re just about starting to realize the potential of open innovation techniques. What we’re talking about is a completely seamless network.”
It’s one thing to have the infrastructure to create a network and fluidity – those are the technical aspects, according to Reay.
“The real value lies in using that network to create and foster a community or to look at it another way expedite a digital culture, and for that people need to be empowered. Being connected to somebody doesn’t mean that that individual is empowered to be able to add value or even inspired to do so, and that’s the difference between a network and a community, it’s about adoption rate – a network informs, where as a community acts. In a community, people are actively contributing and they’re empowered to do so. That’s why change right now is such a headache for large businesses: they are simply too siloed, lacking the ability to adopt new ways of working quickly enough.”
Security and privacy issues
Another barrier, not just in terms of operability or interoperability, involves security issues. Reay brings up privacy, which to him is an area that is very disruptive in itself. “We’ve got the EU coming out with changes and directives very frequently and cyber-attacks increasing in frequency. The move into IoT requires a completely new set of skills that are needed rather urgently, if you fulfill some of the data regulations,” he adds.
These directives, as well as the cyber security issues that result from having these systems over the internet, have yet to be fully understood because IoT is such a new area.
“Since the EU is putting in these directives, when these new things emerge, they do so within the context of a rigid government system that’s been used for eternity. The key in trying to find new ways of mitigating some of these risks is understanding what leadership roles are really needed.”
Reay observes that large organizations are now rolling out compliance managers across their business units. “This is simply not going to do,” he counters. “There needs to be a Chief Privacy Officer, someone who can run the show at a very single level inside the organization on a strategic level, we are not just talking about technology here. These individuals should be rising through the ranks from a legal perspective, and with heavy sanctions and penalties for privacy breaches, this role should under no circumstances be left to the CISO, CSO, CIO, or CDO’s responsibility”.
Collaboration between machine and human
With the usage or the ability to analyze such massive volumes of data, machine learning starts to play a role. Humans can’t analyze that amount of data, and to Reay, what’s interesting is the new value creation made possible by massive volumes of data collected from connected products and devices. This goes beyond efficiency, smart sensors or the ability to use the IoT to create more efficient productive manufacturing lines.
“For example, artificial intelligence (AI) could be used to process that data to provide insight, resulting in better informed rapid decision making. Doing so could organize a lot of these areas, from efficiency and uptime to the utilization of assets. The maintenance and management aspects are, right now, the areas where we’re going to see machine learning really utilized.”
Ultimately, Reay believes that everything comes down to a human-centric approach.
“What really stands out with the use of AI is that it makes us essentially more human. It’s the same as with digital transformations: it’s not the data we’re interested in. It’s how the data influences our decisions. The collaboration between machine and human is where the real innovations are going to start. The utilization of the interface between AI and humans is going to be where we will see how it is utilized to its full potential.”
Again, when we roll out the IoT, machine learning can be used to improve efficiency and uptime. But, as Reay concludes, “the real utilization is understanding how can we use machine learning to create a positive impact for humanity, the workplace and our customers.”
Alexander Reay works as a Chief Digital Officer at Sodash and is President of the Nordic IT Association
Image credit: Wichy / Shutterstock.com
Five steps to digital innovation
First you need to map and prioritize the needs of your organization. Technology comes in second. Ideas arise from inspiration and interaction, but need to be ranked and properly tested before implementation. Marko Yli-Pietilä, the Business Development Director and Managing Consultant at Midagon, walks us through the five stages of successful digital innovation.
“I think that the approach to creating new business through industrial internet and digitalization has been too technology-oriented for a while now. With agile methods the testing process of new ideas can be quite speedy, but as things get faster, we tend to overlook the actual starting point and the foundation on which we should be building,” Yli-Pietilä points out.
According to his view, digital innovation should be a structured process, in which the entire organization should be involved. In the list below he describes the journey of innovation from an idea to reality.
1. Map and prioritize the specific needs of your organization
“Companies shouldn’t rush into making decisions about the use of certain technologies. In the very beginning, one needs to look at the strategic goals of the company, and think about what needs to be done and what needs to be changed in order to achieve those goals. In this primary stage, the technologies are irrelevant. The focus needs to be kept solely on developing the organization and its functions.”
2. Think about how technology can help you
“Once the priorities and needs of the organization have been defined, then it is time to turn the attention towards how things are done. It is very likely, that digitalization provides the tools for streamlining processes. Nevertheless, what needs to be kept in mind is that digitalization is no panacea. Digitalizing existing procedures just for the sake of it rarely leads to the maximum results. In fact, it may even end up adding unnecessary steps in the overall process. Again, ask yourself what it is that you want to achieve. Then let the technology help you get there.”
3. Unleash the creativity lurking inside your workforce
”I’ve been involved in projects where companies try to foster innovation by bringing someone from outside of the organization to implement creative ideas. Personally, I don’t think that’s the optimal way. There are already numerous examples and case stories in the world of digitalization and industrial internet from where to draw inspiration. Your own colleagues have the best understanding of your company, its business and environment. Why not utilize that? Digital innovation can mean different things to different players. So, instead of hiring a stranger to work their magic, see what your people can do. Have them think about the solutions that provide the greatest benefit to your organization.”
4. After background research it is time for internal testing
“As soon as you have a clear view of your company’s strategy, processes and human resources, it is time to put the ideas to test. With agile testing methods you can test, say, twenty out of hundred different ideas in a few week’s period. The main goal in this stage is to quickly get a perception of which ideas have actual potential business-wise and are worth taking further.”
“Interaction between all kinds of people from different parts of the organization enables going through a broader set of perspectives”
5. Ready, set, pilot!
“After the first round of testing, the number of ideas left in the process has usually decreased to a maximum of five. This is when the ideas need to be evaluated against the set business objectives and bring external stakeholders to contribute to the process. Customers, for example, need to really get acquainted with this new thing, a product or a service, to be able to give their extremely valuable feedback. Because the crucial question that needs to be answered is whether this innovation in the making is something that they are actually willing to pay for. So it is not enough just to create something that technically works. That something needs to help the company either increase profit or, on the other hand, decrease costs. “
Anybody who has ever been involved in the process of innovation surely knows that the journey from having just a hint of an idea that could possibly grow into something bigger, to introducing the first prototypes of a given digital innovation is certainly long and eventful. Everything can go according to the plan – until it doesn’t. Even going through all the necessary stages doesn’t guarantee that the result is optimal, or even functioning. Is there something that could be done in the very beginning in order to improve the chances of succeeding?
“Returning to the very beginning of the innovation process, I would say that the more heterogenic bunch of people throwing in their initial ideas and brainstorming together, the better. Interaction between all kinds of people from different parts of the organization enables going through a broader set of perspectives,” Yli-Pietilä contemplates.
And ultimately, who in the organization should be in charge of the process of digital innovation?
“Often it is either the CDO or the CIO of the company. However, in my opinion the process itself is so comprehensive, that it shouldn’t simply be lumped together with traditional information handling. It requires more than that. Therefore I think that it is easier for CDOs to take responsibility and leadership in the overall process. For that reason, companies who want to be innovative in the digital world need to start by appointing a CDO, if they don’t have one yet,” Yli-Pietilä concludes.
Marko Yli-Pietilä works as the Business Development Director and Managing Consultant at Midagon.
Image credit: Rawpixel.com / Shutterstock.com
New professions develop with new business opportunities
The role of the worker in an industrial environment is changing at a rapid pace. There is a large array of new requirements and skillsets that the modern industrial workforce has to adopt to, in order be able to orient themselves in the digital environment of the future, says Martti Mäntylä, Professor of Information Technology at Aalto University.
Many tasks are becoming more oriented towards information work. The changing role of the industrial worker can be compared to that of a prosumer – a consumer that both creates and consumes media content. For the client companies, the information the worker provides can offer valuable insight in how to develop their business. At the same time the worker requires more information to be able to conduct the increasingly digitized tasks.
The education offered by schools must move towards a T-shaped profile, meaning that on top of the specialization one might have, there’s also the need to have a general knowledge of the whole process one might be involved in. This same development can be seen in all branches of education concerning the Industrial Internet.
“We do not have a one-size-fits-all solution for how the education regarding the industry of tomorrow will look like, but as the Industrial Internet is largely an intersectional phenomenon, it is of importance for the students of industrial processes to have a good overview of how the whole process will be affected”, Mäntylä says.
A rise of new professions
According to Mäntylä, digitalization might breed new professions, for example in the field of data quality and collection. One of the new tasks might involve adding value by analyzing the collected data.
“Whatever the task is, there is an added element of creating data and creating additional value through information work”, Mäntylä says.
A large part of the value creation comes in the form of documentation. This practice brings the data to the use of other related systems, and improves the quality of the manufacturing process.
Several companies have appointed a person to be in charge of the digital transformation of their operations. The position, being relatively new, includes a wide variety of different responsibilities and tasks. According to Mäntylä, appointing these digital or data officers is a way that companies aim to find a direction and lead the ongoing change.
“The changing role of the industrial worker can be compared to that of a prosumer – a consumer that both creates and consumes media content.”
“They also aim to empower and network agents on different levels of organizations, and systematically create the needed stimuli for developing the Industrial Internet”.
There is still a notable amount of work to be done, especially in researching the possibilities of the Industrial Internet, and closing the gap between hypothetical possibilities and the concrete targets that companies wish to reach. At the moment one of the more common ways of proceeding for companies is collecting and comparing different cases to figure out in which direction the field is developing.
The added value comes from information
For B2B companies, one of the significant changes has been in the way they’ve had to view their businesses, and shift the focus from products to services. For example, a client might not actually want to purchase a complete welding system, but instead the “product” they wish to have is a guarantee of good welding seams. The added value for the company now offering this service is generated from gathering more data, which is then used to further assist the client in, for example, certifying their welding seams. It may also come from improving quality control, traceability or anything else based on the needs of the client.
“There needs to be a change of perspective, from a B2B approach to thinking about the client of the client. This change is visible in the processes, which utilize a more co-development based approach”.
Another new way to improve processes comes in the form of hackathons. They are an excellent way for an organization to discover what sort of new possibilities digitalization enables for its business. Some of the ideas that come up in hackathons might not fit the current agenda of the companies organizing them, but it is a great way to see the variety of possibilities offered.
“On top of the solutions developed during these events, hackathons offer insight on the type of valuable complementary knowledge there is to be found from outside of the organization. Still, for many companies, there is a threshold in taking extra-organizational personnel on board in developing the companies’ digital toolkits”, Mäntylä says.
One thing that the hackathons aim at, is utilizing information in new ways. This is also what will happen to the roles of many industrial workers. For them, the new solutions regarding IT, maintenance and services will surely have a noticeable impact on how they perform their tasks in the future. That is why schools must adapt a broader view of what it means to work in an industrial environment in the future.
Martti Mäntylä works as Professor of Information Technology at Aalto University
Image credit: everything possible / Shutterstock.com
Production workers of the future move from manual to digital
One of the notable trends in heavy industries has been the move towards digitalization. This has an inevitable effect on the roles of current industrial production and maintenance workers. The change brings about questions regarding company core activities and responsibilities, says Mikko Mäki-Rahkola, the Development Manager IT at Pesmel, an internal logistics solutions supplier.
Digitalization brings its own set of requirements for the workers on the factory floor. The need for manual labor lessens, and at the same time specialization in maintenance and upkeep becomes more relevant. In the future looms the idea of a fully automatic factory, where there might be only one worker in charge of the whole production facility. Still, the need for workers who have specific maintenance insight on the different parts of the automated facilities, will exist for a long time due to lack of self-maintaining or self-repairing equipment in sight.
“Let’s say there were a hundred workers on an assembly line in the beginning of the 20th century. Today, there are only ten assisted by automatic equipment and software. In 2030, a single person may oversee multiple production facilities and lines remotely without any workers participating in the physical production process”, Mäki-Rahkola says.
In contrast to the ever smaller number of workers needed for the production, the amount of maintenance staff will increase, as there are more automatic devices which require professionals to keep them in working condition.
For production facilities where the machinery is custom built for its particular use or for which the maintenance requires more specialized knowledge, this maintenance staff will be increasingly hired from a specialized contractor, most often the equipment provider. The kind of maintenance, which requires only basic knowledge of the equipment or the production process in question could still be handled in-house.
“In 2030, a single person may oversee multiple production facilities and lines remotely without any workers participating in the physical production process.”
“Industrial equipment maintenance will be performed by humans for tens of years to come. Regarding the question of how they receive information for the task at hand and how they will perform the tasks, I believe that we will see significant changes in ways of working”, Mäki-Rahkola says.
The benefits of IoT implementation realize over a lengthy period
The rate at which the aforementioned change becomes topical for companies depends on their speed in investing to new technology. And, Mäki-Rahkola mentions, what works for one company might not work for another – the solutions regarding the Industrial Internet need to be tailored for the needs of the client.
“The maturity of discussion and customer-vendor dialogue around IoT solutions is still quite low today and very technology driven. As a result, the actual IoT solution business integration might get fully left for the client, who then has to find out how they can best utilize the provided tools and information. The fact is, that a solution that brings 100 units of extra benefit for another company might bring none to some other”, Mäki-Rahkola says.
Even though the interest towards the Industrial Internet and the possibilities it brings has grown considerably over the past few years, the actual change happens incrementally instead of sudden huge leaps.
“Many industrial operators are playing it safe at the moment, and waiting to see how the current trends develop. Also, the investment cycles, especially in heavy industry are long and can easily span over a decade or more”, Mäki-Rahkola reminds.
The evident and instant benefits from investing into the research concerning the Industrial Internet cannot always be calculated straight away, and it is always easier to follow other companies’ examples than to be the one doing pioneer work in the field.
“I believe that you have to have faith in your vision, take controlled risks and believe in the fact, that your clients will appreciate the added value when they see it.”
Despite the long cycles, according to Mäki-Rahkola, we are going through an interesting and accelerating period in the development of the industrial business. Even though the digitalization process takes time, if someone develops a truly disruptive operating model or a product, there might occur a sudden surge forwards in the way we understand IoT.
“It would be interesting to see what this kind of a disruption might entail, but as the environment differs radically from the commercial markets, there is a higher threshold for these kinds of disruptions to emerge”, Mäki-Rahkola says.
To sum it up, it is challenging to envision how the factory floor of the not-so-far future will look like, but what is certain is that the role of the workers will certainly be different. The digitalization of manufacturing and maintenance doesn’t remove the human factor from the process, it merely transforms it into something completely different.
Mikko Mäki-Rahkola works as Development Manager IT at Pesmel
Creating new business opportunities means finding the lines that connect the dots
For OEM’s, with Industrial Internet comes the opportunity to gain a competitive advantage by shifting their focus from developing features to identifying completely new service models. According to Alexander Damisch, Senior Director, Business Transformation at Wind River, coping in the ever-intensifying competition requires changing the entire approach to how and where business happens. Using Industrial Internet to data monitoring can help detect aspects that turn out to have a crucial impact on the overall process. However, achieving breakthrough results calls for thorough digital understanding on different levels.
Original Equipment Manufacturers at the forefront
Damisch states that equipment manufacturers are the true ambassadors at the forefront of the Industrial Internet. However, most of today’s equipment manufacturers aren’t making full use of this opportunity, but instead focus on competing on a feature level with the rest of the operators in the market. This is something that Damisch sees as a hindrance.
“Back in the day manufacturing of many industrial components, such as control systems and electrical drives, used to be rocket science, so to speak, but not really anymore. There are multiple smaller players in the field challenging the traditional giants with their offering, meaning that there is a constant pressure to compete on price,” Damisch says.
Lower-cost manufacturers who manage to produce components and services that are basically good enough to fit the needs of the industry put OEM’s in a fairly unpleasant position. Especially for the so-called high-end brands simply lowering the price for individual products is not really an option.
“Cost reduction is anything but straightforward. You don’t just decide to start selling Rolex watches at a cheaper price. You need to either find a way to reduce costs on the operational level, or learn how to scale your products in a different way.” According to Damisch, the key is to focus on creating new opportunities for generating revenue. This is where IoT plays a crucial role. “Basically you need to let your client know that you no longer will sell them a vehicle, but instead you sell them the ability and the know-how to manufacture one faster, better and for lower OPEX than anyone else.”
As an example of a successful change of the entire business model enabled by IoT Damisch recalls how Rolls Royce switched from selling actual jet engines to leasing engine operating hours. As a manufacturer Rolls Royce moved towards a service-oriented business logic, in which customer pays for the expertise that enables them to use the machinery. Hitech is no longer only in the component itself, but in the service system that the engine communicates with informing the service provider of exactly how and how much the jet engine is used, and when it needs to be maintained.
Revealing the unseen
Moving from preventive maintenance to predictive is the classical example of how industrial internet can benefit businesses. Unscheduled halt in any industry can be extremely expensive, and therefore predicting the equipment’s need for maintenance and repair can result in huge cost savings by minimizing downtime.
Furthermore, closer monitoring and detailed communication between different systems and components can help improve the overall production process and increase manufacturing yield.
“Industrial Internet makes us become more aware of the surroundings of a certain process. It enables us to find connections that we didn’t know existed,” Damisch summarizes.
Silicon wafer manufacturing in the semiconductor business is one example of how recognition of a formerly unknown connection can transform the whole production process. Closer monitoring of the surrounding conditions of the manufacturing process revealed that only a two tenth-degree difference in water temperature in the factory had a significant impact to the manufacturing yield.
“Industrial Internet makes us become more aware of the surroundings of a certain process. It enables us to find connections that we didn’t know existed.”
“You would never realize those kind of things by only looking at one element or component of a machine, because it doesn’t show you the correlation between data sets. Getting all the information at once allows us to tweak even the smallest of things at the very beginning of the production chain without huge investments to new machines or major changes to the overall process.”
In addition, getting a clearer view of the entire production process can help companies achieve their aim to optimize their existing efforts, and at the same find new opportunities to maximize revenue. All this plays a major role in production facilities’ future investment planning. With new technology companies have seen the value of investing into IT.
IT/OT convergence for smarter business
Simply getting access to more data isn’t enough to transform entire processes and business models. Companies must of course also know how to make use of it on different levels of the organization, which in practice means fostering open source culture.
CIOs play an important role in helping companies harness digitization and big data, and thus shift towards industrial internet. As the world gets more digital it also becomes more complex, and this requires utilizing different skill sets within organizations.
“The challenge with big data is that if you look at highly complex industrial systems, the collected information is so extensive that converting it into real knowledge usually requires very specific expertise. In my opinion, CIOs tend to have a good understanding of the business decision making systems. However, their knowledge about the operational processes in the production facilities can be limited,” Damisch ponders.
In order to ease the transition towards utilizing Industrial Internet, Damisch’s advice is to integrate the operations technology and IT technology understanding within a company more thoroughly.
“A process controller can’t be shut down if there is doubt of it being infected by a virus. Very different measures apply at the factory floor. There needs to be a mutual understanding between the OT and IT experts inside the company”.
And as standards might change over the years, Damisch also recommends utilizing open source thinking from the beginning.
“Make sure that whatever you build is based on open interfaces or you risk it turning into a graveyard of information at some point. Using open standards, like a Hadoop system for long term data storage, you make sure you stay open to extract the value later on”.
Alexander Damisch works as Senior Director, Business Transformation at Wind River
Image credit: ImageFlow / Shutterstock.com
Equip, utilize, make it actionable – steps to realizing the Industrial Internet
Data doesn’t lie, according to Harvey Shovers, the President of MSI Data. In baseball, for instance, it’s a commonly known fact that all of the teams today analyze huge amounts of data that is produced on the field. In 2013, the Pittsburgh Pirates managed to break their 20 year losing spree by applying sophisticated data analytics to the baseball field. The same idea can be applied to different manufacturing industries like the steel industry.
“With the steel industry being one of the oldest industries out there, you can imagine it is very traditional when it comes to managing. These kinds of industries have been pretty reserved of the idea of managing by data. But the steel industry, just like everybody else, is going to benefit from the capture and analysis of that data”, Shovers says.
If you take the right mix of experience and reliance on the data that you have never been able to act on before, the steel industry, like any industry, is able to make better decisions that can more quickly affect the manufacturing process.
As an example, for service technicians, having the right data means that they can update their old methods of doing maintenance.
“It isn’t beneficial for the service technician, or the customer, to come on site and not be able to identify the problem, and then have to come back again and again. It’s expensive and it doesn’t drive good relationships with the customer. Now, with the proper data, the technician can come and fix the problem before it occurs and come equipped if a problem does occur. With access to machine data, the technician knows exactly what the problem is and how to fix it. This way the first-time fix rates go up and the service technician gets his job done faster, better and more professionally. This improves the relationship with the customers. It’s a win-win-situation,” Shovers says.
Getting everyone on board is key
Speaking on the hot topics in Industrial Internet, Shovers mentions that there’s a difference in the emphasis between the consumer side of the IoT and the Industrial Internet. When thinking about the Internet of Things, people tend to associate it with consumer-type applications.
“For most people, they like to think of things you can do with your smartphone. The Internet of Things makes day-to-day activities for people easier. We now have apps to control the lights in our apartment, to record TV-shows and to change the thermostat. On the industrial side it’s more about collecting big data.”
According to Shovers, the companies on the leading edge are the ones who are already capturing data and are starting to utilize it. The main problems companies face in getting to this point is getting the whole company on board and having a clear vision as to why other companies are already collecting data and most importantly being able to see what the payback is.
Three steps to an Industrial Internet
For Shovers, the implementation of the Industrial Internet takes place in three distinct phases. The first one is making everything internet-enabled. For example, in the auto industry, most cars that ship today are equipped with some kind of data-collection and telematics devices.
“Not all of the data that can be collected from devices is actually used today, but everyone is putting hardware and software into their products,” Shovers says.
The second phase is capturing the big data, and then being able to utilize it.
“That data helps companies drive their business decisions, or manufacturing and design decisions faster.”
The third phase is making that data actionable. The end result might be, for example, that we have a car that drives itself, compared to cars now that can already change lanes for you automatically, or notify you if something negative is about to occur.
What kind of advice would Shovers then give for company CIOs in charge of implementing any of these three phases?
“The point would be to get started now; don’t wait. The technology is already here, and if you wait two or three years for the perfect solution to become available, you’re going to be behind everybody else”
“I’m a big proponent of taking steps to get things started now, because you can talk about these things forever, just like anything else,” Shovers says.
According to Shovers, an ideal scenario for a company would be to come up with a multi-year plan of where the company aims to get to and of the results they aim to achieve with the implementation of the Industrial Internet.
On the way there they should be able to report back to their stakeholders every step along the way, within or outside the organization, of the progress they’re making towards achieving these long-term goals.
“The point would be to get started now; don’t wait. The technology is already here, and if you wait two or three years for the perfect solution to become available, you’re going to be behind everybody else”, Shovers says.
Finally, coming back to baseball, only 20% of the data-collecting teams make their decisions based on it. The ones using data to guide decisions also happen to be the ones leading the surge and becoming the winners in their sport.
Harvey Shovers is the President of MSI Data, a Wisconsin based company that is the leader in field workforce automation software.
Image credit: vetre / Shutterstock.com