Industrial Internet Now

Why collaboration, not competition, is key in a hyperconnected world

Similar to the internet in its early stages, IoT will need to secure a safe and standardized collective environment in which to operate. According to Iain Groves, Solution Owner at Fujitsu UK & Ireland, “communications protocols and service quality definitions are needed to ensure the development of the highly heterogeneous and open environment required.” Due to the nature of the IoT, this environment will represent something that is greater than the sum of its parts. Thus, “a new, dynamic form of network management will be the only effective approach for the IoT,” writes Groves.

IoT undoubtedly presents significant opportunities both for large manufacturers and consumers alike. However, a balance must be struck between collaboration and competition in order for those opportunities to be realized. It is only then, Groves notes, that “we can ensure that the IoT reaches its full potential – and works for everyone.”

Read more about how to create a strong IoT ecosystem at: http://www.itproportal.com/features/why-collaboration-not-competition-is-key-in-a-hyperconnected-world/

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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.

Case examples

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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The problem with IIoT design

As with all trends and innovations in their infancy, there is bound to be some premature efforts deemed as groundbreaking, when in reality they fail to sustain their relevant functionality beyond initial hype. According to EE Times editor Rich Quinnell, this has been the case with IoT design. “All too often the design behind these [IoT] devices is not all that smart. It’s clever, it’s innovative, but IoT designs are also all too often piecemeal and rushed to market. What’s being created is a system of systems, without the system-level design issues getting addressed,” Quinnell writes.

The Object Management Group (OMG) is nonetheless providing a remedy for “correcting IoT’s trajectory.” For his EE Times piece, Quinnell spoke to Matthew Hause and Graham Bleakly of OMG to find make sense of the issues surrounding current approaches to IoT design. “We’re trying to get people away from building the IoT by hacking,” says Bleakley.

Read more on Hause’s and Bleakly’s thoughts at: http://www.eetimes.com/author.asp?section_id=8&doc_id=1331075

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The learning curve: From the Internet to Big Data to IoT

The technological developments born within the boundaries of the IT industry, and conversations that follow outside these boundaries create trends that are greater than the sum of their individual parts. Challenges are becoming less unique to manufacturers of particular products, and opportunities more ubiquitous to a wide range of service providers and manufacturers alike. In other words, technologies, industries and societies will become increasingly related to, and contingent on, one another in 2017.

Mikko Marsio, Vice President of Digital Business and IoT at Empower group, says that what has unfolded over the past two decades and led companies to where they are today can be understood as both an evolution from a technological perspective, as well as a revolution from an industry and business perspective. From the speculative nature of the IT bubble, to the profoundness of the Internet of Things, Marsio explains how consolidating technology with business is now more imperative than ever before.

“I remember a prediction that was made before I attended an MIT Executive Education course on the Internet in 2000. It envisioned the Internet becoming like electricity, meaning something that we don’t even acknowledge when using,” Marsio reminisces. “If you look at what was laid out in 2000 in conjunction with the IT bubble – for example that the best years for the pulp and paper industry were then and there – no one could actually have predicted how many paper mills would be shut down over the following 15 years.

In order for these mills to stay relevant, they must adapt what they are producing. Companies in general need to understand how both digitalization and end-users are causing their businesses to change. Over the past few years, increasingly many have come to recognize this,” he continues.

An affordable evolution

Despite the predictions regarding the impact of the Internet made at the beginning of the millennium, it would have been impossible for companies to imagine the extent of its integration into businesses. Many companies, and even industries, are now at a point where they are faced with a similar integration problem to solve concerning IIoT. For Marsio, integrating the Internet was the first hurdle for businesses to overcome, Big Data and analytics the second, and IoT the third.

“Big Data is the result of an evolution and I’m not sure that IIoT and IoT can, or indeed should, be separated as distinct developments. I say this because what essentially facilitates Big Data are the digital interfaces created for customer connectivity to machines.”

Machine connectivity and digital interfaces. Sounds very IoT doesn’t it? Marsio recalls an early example of this kind of machine connectivity from his time at Hewlett-Packard, when IoT or IIoT terminology had yet to see the light of day.

“In 2006, when I was working for HP, we were working on how to connect all our office equipment, especially multifunctional machines, to the Internet. This made the remote storage and analyses of data possible, and it also allowed the company to deliver a new kind of value for customers. Since 2006, Big Data has evolved to partly define what IoT is today, as we are now able to gain insights from thousands of data points, analyze these insights in real-time and ultimately use them to drive services. Moreover, in 2017 this can all be done affordably.”

From the short to the long-term

The short-term benefits of such insights can already be seen. However, long-term outlooks still require work. According to Marsio, companies must begin to address how they will develop the execution capacity necessary to scale up tangible opportunities not only now, but also in the future.

“In the manufacturing side, we will see less errors and faults in the short-term, which means companies will improve their overall equipment efficiency. Moreover, companies will not only gain insight into processes from, say the control room of a pulp and paper mill, but they will be able to do so remotely. In the long-term what will be more challenging, for example for players in the pulp and paper industry, will be addressing the ‘paper’ part of their businesses.” This is to say that as end-users’ needs change, the customer-value of paper will need to as well.

According to Marsio, short-term objectives and long-term perspectives can be maintained and executed in parallel. This necessitates a systematic management approach to IIoT opportunities and inherently entails considering the future.

“Within the last few years, there has been a change in how companies approach future developments. This means that companies are now anticipating more of a journey with regard to IIoT, as opposed to a project to be tackled, executed and moved on from. Therefore, future trends, developments and opportunities will be considered as a continuous flow of things.”

“Short-term objectives and long-term perspectives can be maintained and executed in parallel. This necessitates a systematic management approach to IIoT opportunities and inherently entails considering the future.”

Not just thinking, but acting ahead

How do companies and organizations evaluate what they could, should and must do now, and what are the potential consequences of those actions, Marsio asks. Part and parcel of a journey mentality is evaluating the future, which can be challenging especially in industries that have been set in their ways for many years, or even decades. When envisaging what a company will be in 20 years, and who and what it will serve, Marsio encourages leaders to think beyond their businesses and consider societies at large.

“Take Tesla. If in the future, we will all indeed have electric self-driving cars, why buy one at all? The same car that drives you could be used by others when you don’t need it. What would happen to companies offering parking spaces in city centers? Or the driving experience itself? German automotive manufacturers typically market the driving experience as the number one thing to consider, but if there is no driver, what’s the relevance of the experience?”

Regardless of leaders thinking ahead, the questions posed above require action in order to gain answers, and that’s what is currently so compelling about IIoT and IoT. The more ordinary and accessible products like Tesla’s become, the more products will be transformed into services, and thus, the more answers companies will have. However, waiting for that to happen, as opposed to making it happen and becoming accustomed to what IIoT allows for, will result in an opportunity lost. As with electricity and the Internet, Marsio holds that companies should aim for such a profound awareness of IoT that it becomes intuitive to corporate mindsets.

“Ultimately, it is essential for companies to consider how they can get to a point where they no longer acknowledge the fact that they are using IoT or IIoT,” he concludes.

 

Mikko Marsio works as Vice President of Digital Business and IoT at Empower Group

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Reinventing traditional industries

New realms and areas of innovation can be daunting for individuals and organizations alike. Navigating through the maze of prospects and opportunities, and then recognizing the viable ones to pounce and build on, makes the Industrial Internet of Things a jungle of locks for the shrewdest of locksmiths to take on. Anja Hoffmann, the Founder of Copenhagen based strategy and innovation consultancy company Sentio Lab, is convinced that industries are full of such locksmiths, however, she holds that too often those clutching the keys don’t have a clear mindset as to what locks they ought to open. For Hoffmann, companies across industries must first focus on themselves, before venturing to capitalize – and make sense of – the countless opportunities made possible by new data and technology.

“As increasingly many industries are becoming tech-driven, I always start by looking at the mindset of the company looking to shift their focus to technology, regardless of their industry,” says Hoffmann, who also works as an Innovation Mentor for High-Tech Companies at Scion DTU. “In general, I think we have a lack of mindset across industries when it comes to understanding both the opportunities, and challenges in developing business models using new technologies,” she continues.

Hoffmann’s call for a more measured approach is far from baseless. She has been working closely with a wide range of industries for several years, thus gaining a unique vantage point. For her, more “traditional” industries often struggle to reinvent their approaches internally, especially when it comes to customer relations. However, there are exceptions.

“The pulp and paper industry, which I’ve been working with for some years, is an interesting example of a sort of hybrid between tradition and innovation. When it comes to the production process they remain very traditional and even historical, but because many of their customers are creative and innovative, they have been forced to think about new ways for longer than for instance the steel industry.”

In the case of the pulp and paper industry, mindsets have thus been revised by partners and other actors within an ecosystem, something Hoffmann feels very strongly about. For her, ecosystems and value chains represent one and the same thing.

“Companies need to look into their ecosystem, meaning their partners and so on, and ask themselves: what kind of an ecosystem will match our business ambitions in the future? Ecosystems are so important not only in regards to discovering and integrating new technology, but innovation in general. If you consider some of the companies who have asked questions, and succeeded in answering them, they are companies which have recognized that they are more of a service company than a manufacturing company.”

“Companies need to look into their ecosystem, meaning their partners and so on, and ask themselves: what kind of an ecosystem will match our business ambitions in the future?”

Reconciling tradition and innovation

Finding a balance between the two is easier said than done. According to Hoffmann, there should nonetheless be no reason why more “traditional” companies and industries wouldn’t be able to successfully implement a tech-driven agenda, and thrive from what the Industrial Internet promises. She mentions German elevator manufacturer ThyssenKrupp as a great example of a manufacturing company looking beyond its own industry, and desiring to be part of something what would traditionally fall outside the operating parameters of an elevator manufacturer.

“Although ThyssenKrupp manufacture what is essentially a technical product, their latest Industrial Internet developments have not been oriented for a traditional elevator business, but instead more for a service business. Because they have built an intelligent ecosystem around their solutions, ThyssenKrupp are transforming not only elevators, but elevator services to be a part of a smart-city movement.”

Living in the present, preparing for the future

Considering the popularity of the phrase “we live in a constantly changing world,” and other variations of it, Hoffmann reminds us that while this certainly remains the case, it’s vital to focus on the here and now.

“If companies pursue interesting and innovative partnerships across corporate investors and start-ups, they can minimize how much they change at once. Sometimes we focus too much on the fact that we live in a fast-paced business world, which is of course true, but we also need to do remember to experiment in the present, especially with already existing businesses. In order to do this, companies must assess how they can change their own DNA by looking into their value chain or ecosystem.”

When it comes to introspection into ecosystems, the role of the Industrial Internet can’t be understated. One prevailing innovation concerning manufacturing companies has been the increasing integration of co-bots – or “collaborative robots” – into joint working environments with humans.

Not too long ago, robots being used in the automotive industry for example, were kept in cages. Since then, co-bots have emerged and are forcing manufactures to rethink the structure and processes of their value chains. According to Hoffmann, this brings the need to question the necessity and future value of certain skills within the entire Industrial Internet landscape.

“When it comes to co-bots, what will be a challenge in the near future not only for the manufacturing industry, but also for the retail industry, is the demand for new skills from workers. The Industrial Internet is affecting business models as well as society, without forgetting the potential drawback of information overload and issues of security.”

Thus, the impact of co-bots should be assessed from a workforce and societal perspective. Co-bot technology will undoubtedly assist in driving profits and quality via reduced margins of error and sustained performance capabilities, however, as Hoffmann notes, companies “will no longer need programmers with specific technical skills to work with these robots.”

Despite new workforce demands and implementation possibilities in terms of what the Industrial Internet offers –  and as long as leaders acknowledge the challenges and opportunities, without “just pushing a certain agenda forward,” – Hoffmann is certain that companies across industries will prosper from IIoT solutions on many fronts.

Anja Hoffmann is the Founder of Copenhagen-based strategy and innovation consultancy company Sentio Lab.

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Think beyond the cloud – How platform players can prepare for the next phase of the IoT

Many companies are already combining advanced automation, cloud computing and IoT services, among others, to transform their operations. In terms of the maturity of industrial ecosystems, however, Marianne Hannula, Head of Service Product Management and R&D at ABB, believes that there is still the need to establish business models that fully support the technology. She talks about what needs to be done to usher in the era of global supply chain ecosystems and how to take full advantage of its build up phase.

“I first came across machine-to-machine communication more than 15 years ago when I was working with mobile internet applications; a lot has happened since then,” shares Hannula. “All this technological advancement has built momentum for the evolution in industrial ecosystems. These now refer to ecosystems that manage and control the performance of multiple pieces of equipment that form the supply chain, not just order-type data transfers.”

The different players in the field have been somewhat focused on their own operations and that has, in certain cases, slowed the development of new ecosystems. According to Hannula, ecosystems that offer a win-win situation for both parties are needed. “In the case of IoT, this should mean win-win-win-win for multiple parties, not just two.”

Data ownership as a matter of agreement

Hannula sees positive signs in that the time has come when these groups – not just the few early adopters and startups – are beginning to be more open to collaboration and data sharing. “That openness is needed to enable global supply chain ecosystems to develop, where data from multiple sources are combined for the improved performance of the supply chain and for the benefit of end users.”

As data ownership is more complex in an IoT context, the topic has given rise to various opinions. Hannula sees it as a question of what has been agreed upon. “Basically all players should own their data. Sometimes access to this data might be the sellable item. The question arises when the data facilitates new knowledge as it is analyzed and/or combined with other data,” she continues. “Who then owns this knowledge? Who should be held accountable for the consequences when it is used and something adverse occurs? I view this as a matter of agreement, but the responsibility has to be clearly defined between the stakeholders.”

‘Don’t wait for tomorrow’

With regard to IT and OT convergence, Hannula advises companies to not wait for tomorrow. “Use your existing IT structures and find the connectivity means to combine the data available from multiple devices and systems to enable better business decisions now. With that you will learn and find out where the biggest benefits for your business are.”

In addition to the ability to perform predictive maintenance, Hannula believes that the other clear-cut benefits of the Industrial Internet involve the optimization of performance and quality as well as reliability.

“With real-time data turned into knowledge and insights, we are able to detect topics where the process productivity can be improved and become more efficient. Just saving a second or two in some repetitive process can translate to considerable additional revenues,” she explains. “If that happens in one part of the supply chain, the benefits that can be available at the supply chain level can be even greater. Another example could be automatically combining data from various sources and using that to fine-tune equipment performance. This could lead to savings and better quality.”

“When one talks of the IoT, you often only hear the word cloud. But you also have to consider how these clouds can start talking to each other. Then apart from these clouds, there are storms, sunshine and stars.”

Advice for platform players

Hannula believes that there will be a major build up phase for IoT ecosystems during the next five years. “More and more industrial companies will get involved, there will be more and more cloud solutions, and connections between different cloud platforms will become available. The technological knowledge collected over the years and currently stored in documents – or even only in the heads of experts – will turn into a more automated format, making it scalable and useful to business.”

To take full advantage of these changes, she says that companies should focus on three things. “First is that the future starts today. Start using what is available now and learn from it. The next thing to remember is that IoT is not a game of solitaire: Experiment and collaborate with other players. The third and last is don’t wait to be disrupted. Be open to the idea of adopting new business models and remember the human aspect of all this. Instead of considering something as a threat, embrace it as an opportunity and be curious from a technical perspective.”

Above all, Hannula recommends that platform players widen their general outlook. “When one talks of the IoT, you often only hear the word cloud. But you also have to consider how these clouds can start talking to each other. Then apart from these clouds, there are storms, sunshine and stars,” she concludes. “The cloud is a simplification of a technical aspect, but to gain the full benefit of IoT a broader view is needed.”

Marianne Hannula works as Head of Service Product Management and R&D (Portfolio Management, Development, IoT) at ABB.

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Integrating IT, OT and security: convergence to collaboration

“OT and IT are working towards the same goal, uptime,” writes Daniel McGinn of Schneider Electric.  “Whether that means the comfort of building occupants and business continuity or the specific needs of safety and security.” In part one of a two-part blog entry, McGinn highlights the integration of IT and OT, and what that means for security. Companies developing IoT solutions must consider the implications these new systems, applications or even platforms have in terms of security.

“Keeping buildings operational, IT running and security systems up, depends on the availability of the network and server platforms they are running on, and these systems are only as available as the power supporting them. Because these systems are increasingly connected and open, the departments themselves must come together as well,” notes McGinn. “This is where safety and security now begins for any structure that requires active monitoring and access control.”

Read more about the risks and management challenges of IT environments at: http://blog.schneider-electric.com/datacenter/power-and-cooling/2017/01/04/integrating-it-ot-security/

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Trends and themes from the Industry of Things World USA Survey Report 2017

Findings from the Industry of Things World USA Survey Report 2017 reveal that compared to Europe, the US is very advanced on the software side and IoT platforms, analytics tools, as well as AI approaches. Maria Relaki, Group Production Director at we.CONECT Global Leaders, the organizer of the Industry of Things World conference series, talks about the key results that shed light on the current state of the American IoT market.

A clear majority of the cross-industry IoT and Smart Manufacturing managers that participated in an online survey by Industry of Things World – conducted from August to October 2016 – considers Smart Manufacturing as the main driver and contributor for US manufacturing competitiveness.

“One interesting fact from this year is that 71% of the respondents actually have industrial IoT or Smart Manufacturing systems in their organization, compared with 41% who rated the importance of IoT project implementations in their companies as very important last year,” states Maria Relaki, Group Production Director at we.CONECT Global Leaders.

Relaki adds that another key finding is that access to necessary infrastructure is rated as the biggest challenge to implementing IoT within companies (53%), followed very closely by cost (46%). “The positive news is that in 2016 the biggest challenge was ‘uncertain ROI/ lack of business case’ – so here it seems we have had some significant progress. The business case is now a given and it’s a matter of making it happen,” she says.

The survey also reveals that Smart Manufacturing systems are not applied only on a machine (32%) or plant level (43%), but they are being more and more integrated across all levels (36%) within a business.

Challenges and opportunities

By far the biggest opportunity that IoT offers has been recognized as the increased efficiency (68%) that comes with smart manufacturing systems. “As the second biggest opportunity, respondents listed the competitive advantage that IoT can offer as well as, very interestingly, that it can increase product quality,” continues Relaki.

Access to necessary infrastructure is rated as the biggest challenge to implementing IoT within companies.

According to survey participants, some of the biggest challenges they face involve the lack of standards and interoperability, and costs associated with the integration of new systems. They also cited security breaches – that IoT needs a new security approach rather than the traditional one, for instance – and management buy-in as other factors that affect the implementation of industrial IoT technologies in their organizations.

Trending topics

Relaki believes that the industrial IoT landscape is going through a transition. Shifting industry boundaries are changing competition, and businesses need to be aware of that. “Traditional competitors need to look beyond their universe and keep an eye on how IoT technologies can enable other businesses to eat away parts of their market share.”

The interoperability of connected devices in the world of IoT is still a big issue, one that is subject to discussion. “How far away are we from a universal standardization? Discussing the implementation of open source and open standards might be a way to move into a direction with fast results,” offers Relaki.

While robotics is a theme that is becoming more and more relevant, she says that the human factor in all of this must not be forgotten. “The Internet of Things involves new ways of thinking about how humanity and technology can cooperate differently when ‘things’ get smarter. Augmented reality and virtual reality in manufacturing simulation, as well as M2M and Artificial Intelligence for improved productivity, will be discussed throughout the conference.”

Industry of Things World USA 2017

Organized by we.CONECT Global Leaders Industry of Things World USA is an international knowledge exchange platform where over 500 high level Industrial Internet of Things executives will meet. Scheduled to take place in San Diego, California from February 20 to 21, 2017, this year’s two-day program aims to encourage and inspire participants to rethink their technology and business strategy for scalable, secure and efficient IoT, from cloud, robotics and automation to standards, interoperability and security.

“We will have the pleasure of hearing from Alex Tapscott, a blockchain expert, on the impact of Blockchain on the Industrial Internet and how this will change the way we do business. Jeff Burnstein, President of the Robotic Industries Association, will discuss how robots in a smart factory can use self-optimization, self-configuration and artificial intelligence to complete complex tasks in order to deliver vastly superior cost efficiencies and better quality for goods or services,” shares Relaki.

At the same time, the event will attempt to demystify the complexity of getting started with integrating robotics into an IIoT network. “Small and medium sized companies in particular may be overwhelmed by jargon, fears about cost and the difficulty of knowing how to apply these technologies, so these talks will hopefully be of use to them in understanding how to explore robotics and IIoT further.”

To find out more about the agenda and speakers of Industry of Things World USA 2017, visit http://industryofthingsworldusa.com/en/.

Download the full survey report:

http://industryofthingsworldusa.com/cms/media/uploads/events/3755/dokumente/formular/Industry_of_Things_World_USA_2017-Survey_Report.pdf

Maria Relaki works as Group Production Director at we.CONECT Global Leaders and is responsible for the Industry of Things World global event series.

Image credit: we.CONECT Global Leaders

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/

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Mass customization in manufacturing – enabling customer-centric value creation

Traditionally, manufacturing has been defined by supply chains geared towards maintaining production costs as low as possible, with ultimate emphasis placed on output and distribution. These supply chains have largely been both enabled and limited by the hardware systems at their core. As companies are beginning to introduce data-driven, software enabled supply chains, manufacturing will increase in efficiency and mass customization will follow suit. In terms of distribution, platforms and apps are becoming the preferred medium and should be grabbing the attention of material handling industry as well.

Frank Piller, Professor of Management and Scholar of Mass Customization & Open Innovation, shares his thoughts on the intersection of the Industrial Internet and mass customization.

“Manufacturing will really begin to drive business models,” says Piller, who has been leading the Technology and Innovation Management Group at RWTH Aachen University for a decade. Rather than regarding the Industrial Internet solely as an enabler of new business models, Piller sees the technological developments made possible by IIN and IIoT as “drivers of business models.” According to Piller, mass customization plays a pivotal role making this paradigm shift that manufacturing industries are already experiencing, more customer-centric.

“I see the question of manufacturing and the Industrial Internet being defined by two stems of debate; enabling operational excellence on a larger scale on one hand, and using Industrial Internet technologies to drive new business models on the other.” What mass customization makes possible via these two defining principals, is for manufacturing, supply chains and the business model inherent to them, to become more customer oriented. “The ultimate goal of mass customization is for manufacturers not only to become customer-centric, but more so customer-driven, to exploit the heterogeneity of customer demand,” says Piller.

According to Piller, manufacturers will often see the high variety of demand as a challenge, a cost driver and ultimately as a hindrance to maintaining a truly customer-centric manufacturing process. However, what mass customization does, notes Piller, is turns this assumption on its head.

“We should instead see high variety of demand as a profit driver, and do so by allowing for the input of each individual customer at the beginning of the value and supply chains. This doesn’t entail reinventing engineering to order process or craft customization, but doing this with an industrial efficiency that the latest Industrial Internet technologies make possible.”

For material handling, the integration of automated and semi-automated robots into production lines is a big driver for coping with higher degrees of variety, says Piller, who also sees mass customization as something already being utilized in material handling equipment. “A lot of material handling equipment is already engineered to order, meaning it’s highly modular and therefore can fit into existing plant layouts, as well as be integrated into planning and production. Deploying this in larger volumes is the next step.”

“A lot of material handling equipment is already engineered to order, meaning it’s highly modular and therefore can fit into existing plant layouts, as well as be integrated into planning and production. Deploying this in larger volumes is the next step.”

From prediction to action

Closely linked to the paradigm shift taking place in manufacturing are the opportunities that predictive analytics opens up. Piller sees these opportunities as something material handling companies should be taking advantage of and implementing in their systems. “As the basic premise of predictive analytics is that we must guess less, and know more, an implication for a material handling company could be making better forecasts of the incoming flow of material.”

A consumer goods company will traditionally do some market research or extrapolations of the first few weeks of sales, in order to see how sales will develop for the rest of the season. “Now they can get access to much more unstructured data from social media conversations or purchasing behavior in key stores, and thus better predict the operational planning necessary to meet the demand,” says Piller.

However, as with most new data related developments, predictive maintenance and analytics don’t come without potential pitfalls. Piller appropriately sums up the paradox surrounding predive analytics and maintenance, by stating, “the better we are with predictions, the worse we become in executing.

“Imagine a huge plant that has many material handling systems across the globe, and let’s say they are all assessed using predictive maintenance. The plant manager will then know ‘ok, in a weeks’ time, 20 out of my 1000 pieces of equipment will breakdown, and I only have 2 repair teams. How do I allocate them?’ Therefore, action as opposed to prediction is the ultimate goal.”

First an app, then a platform

Another significant development that will only increase the capacity of the Industrial Internet to create new customer-driven business models, is the emergence of the platform economy. However, according to Piller, traditional industries should not be looking to immediately develop a platform as the likes of Amazon and Uber have. For instance, the transportation and material handling industries would benefit by starting off with an app.

“Of course, managers think that ‘we will become a platform,’ but this requires a big mental shift in companies, a shift towards openness. However, I think that traditional industries should first acknowledge the possibilities an app introduces to their business. In a connected world, an app can be a piece of equipment and shouldn’t be limited to the notion of a smart-phone app,” Piller notes.

Becoming a platform-based industry certainly doesn’t happen overnight. What Uber or Amazon managed to do on a consumer level, would be extremely difficult to successfully execute in the industrial world, simply because of the level of openness it requires. For Piller, more companies need to recognize the benefits of an app.

“Established B2B companies are very conservative when it comes to putting their data in a platform, so even if a platform is created by an established player, filling it with meaningful data is a question on its own. Therefore, in terms of market entry, being an app on a platform has a lot of advantages. My advice would be to learn how to become the preferred app, like the Angry Birds of material handling.”

Experimenting for future solutions

Piller is confident that companies experimenting even with more left-field utilizations of the Industrial Internet will ultimately drive innovation, and do so in a customer oriented way.

“Take the Amazon Dash Button, a solution which costs the consumer $4.99. At that price point, even a small established company can start experimenting by asking, for example, ‘what could we do, if we managed to increase the connectivity between equipment that allows you to monitor actions and actives?’”

According to Piller, the issue some managers and CIOs face is making sense of the huge pile of possible things to do – and sometimes they end up doing nothing.“Therefore, I think it’s always better to start experimenting and testing assumptions in order to get real feedback, instead of making huge PowerPoints,” he concludes.

Frank T. Piller works as Professor of Technology & Innovation Management at the Business School of RWTH Aachen University, Germany

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