ARCHIVE FOR THE ‘artificial-intelligence’ CATEGORY

Tieto announced recently that it is one the first Nordic companies to join the European AI Alliance, a newly-formed forum for artificial intelligence (AI) stakeholders to come together to push European competitiveness on AI research and development and its impacts on industry and society.

The AI Alliance, established by the European Commission, brings together a diverse set of leading AI actors, including companies, consumer organizations, trade unions and other representatives of civil society bodies across Europe to share best practices. The AI Alliance aims to directly contribute to the European debate on AI and impact the Commission’s AI policy-making.

To achieve that, the AI Alliance works in close collaboration with the High-Level Expert Group on Artificial Intelligence (AI HLEG), a group the Commission has also established, with 52 members from academia, business and civil society such as Bayer, BMW, Bosch, Fraunhofer Institute, Google, IBM, Nokia, Siemens, Telenor and University of Oxford. The AI HLEG advises the Commission on AI’s opportunities and challenges, and supports it in the implementation of the European strategy on AI. The AI HLEGwill also prepare AI ethics guidelines covering issues such as fairness, safety and transparency as well as the impact on our fundamental rights, including privacy, dignity and consumer protection.

The AI Alliance will complement and support the work of the AI HLEG in particular in preparing AI ethics guidelines and ensuring Europe’s competitiveness in AI. Tieto and other members of the AI Alliance can provide direct feedback on specific questions and draft documents prepared by the AI HLEG.

“As one of the first Nordic companies involved in the AI Alliance, this is a great opportunity for Tieto to facilitate the development of artificial intelligence in Europe. We are excited to join forces with other AI Alliance members to foster AI innovation while also ensuring the highest ethical and sustainability standards in the development of AI. We will work alongside other leading members to build strategies that accelerate AI research and industrial applications,” says Dr. Christian Guttmann, Vice President, Head of Artificial Intelligence and Data Science at Tieto.

“As a Nordic leader in AI, we have already established a Tieto wide AI ethics certificate and are already recruiting new talent in this area, including AI ethics and transparency engineers and AI Trainers to teach our AI systems,” Guttmann continues.

AI and advanced data analytics are an integral part of Tieto’s vision for future growth and success, and Tieto has recently developed several innovative AI and data-driven projects, including the trial with the City of Espoo. Tieto will have six representatives in the AI Alliance, each with deep scientific and industrial experience in AI, including AI’s sub-categories such as machine learning, deep learning, multi-agent systems, knowledge representation, machine perception and AI ethics.

---

 

Be social and share

Aly Pinder outlines how the growing trend for connected products is set to revolutionise the way we approach service...

What is the value of a connected product or asset? Some might argue, connected products allow a manufacturer to capture a wealth of product data which can be used to make better products in the future.

Others might state, connected products open a window into customer usage data which can help manufacturers and sales teams target customers more effectively driving increased revenues.

These are two important use cases and show some of the promise of the Internet of Things (IoT) and connected products.

But I think there is an even more impactful area of value from the ability to connect to products – field service.

Now you may be thinking, of course, it’s all of field service, as you peruse the articles of Field Service News. But even if I am preaching to the choir, the impact that connected products can have on the ability for manufacturers to transform the way they deliver field service and customer support is not necessarily a given.

However, as more products and assets are connected I believe there is a real opportunity to see great leaps in field service and the transformation of the way manufacturers interact with the end customer.

Three opportunities, in particular, jump out as big wins for the future of field service as a result of data captured from connected products and equipment:

 

Finally, predict and not react

The journey from reactive field service to proactive and predictive persists for many manufacturers. I don’t think this is necessarily a battle which will ever reach a state of 100% predictive service, and nor should it.

But I do think there is a great opportunity to take the volumes of data being captured in real-time to make smarter decisions in field service which can lead to a different balance of reactive, proactive, and predictive support.

Also, data gleaned from connected products can help make reactive service calls more valuable and efficient as a technician should have the answers to the issue without having to guess or lean on gut-feel.

 

Service without a truck roll.

As noted in recent IDC research, by 2020, 50% of global OEMs with connected service offerings will have incorporated augmented service execution and/or remote management thus improving service margins by up to 30%.

The ability to resolve issues remotely or to utilize a centralized expert to help a customer solve a problem can be transformative for field service. This type of model could help service leaders allocate their seasoned technicians to the most complex problems as opposed to just an issue within their geographic footprint.

Connected products enable a manufacturer to know what is wrong in advance of a response and ensure the right response is the one scheduled for a scarce set of resources.

 

Focus on the value of the human interaction.

When we think about the negatives associated with the rise of the machines (i.e., Terminator), we often miss something.

This should be an opportunity not a threat.

Connected products which ‘talk’ to each other provides an opening for field technicians to focus on the humans while they are on site as opposed to spending time looking for information, turning wrenches, or filling out paperwork.

Obviously, this will mean manufacturers and service leaders will need to train their technicians on a new set of skills and activities. But as the workforce and economies evolve, the skill of interaction will be in more demand and provide more value in the customer relationship.

And manufacturers which leverage connected product data to have their field teams focus on the customer will succeed.

The promise and value gained from connected products is more than just additional data points.

As manufacturers look to transform their organizations and teams, connected products should be the catalyst for a journey of new ways of delivering value to customers and not the end result of a technology investment.

Field service should be the aspect of the business which sees the biggest gains from connected products and equipment.

The possibilities are endless, and I look forward to seeing where manufacturers take this technology as it extends beyond IT and engineering to the field.

---

Aly Pinder is Program Director - Service Innovation & Connected Products, IDC Manufacturing Insights

---

 

Be social and share...

We are undoubtedly entering a new era of technology, automation and innovation, but in a world of rapid industrial evolution how will regulations also adapt? 

Oliver Rickett, Solicitor, and Caroline Churchill, Partner, at law firm Womble Bond Dickinson  share their insights on this crucial topic... 

---

"Everything is true… everything anybody has ever thought." Philip K. Dick – Do Androids Dream of Electric Sheep

---

It is impossible to escape from the fact that technology, and increasingly artificial intelligence (AI), has transformed everyday life.

It all started with how we play our music, but Apple's Siri and Amazon's Alexa (along with other similar "virtual assistants") now have a daily interface with many of us. We are also, increasingly, now daily users of the Internet of Things (IoT) – connecting up smart fridges, boilers and alarm systems, each controllable from a smartphone. The "everyday" form of AI is almost unavoidable in the modern home, but, while not necessarily as obvious to you and me, there is also an ongoing, yet unseen growth in AI in the manufacturing sector.  What is still lacking, however, is concrete regulation in place for the use and development of AI in the industry.

This article looks at where AI regulation might be implemented and, specifically, what impact both AI has, and its regulation would have, on the manufacturing industry and what role the UK might have in this ever-changing sector.

 

What is "Industry 4.0" and how is AI related?

The term "Industry 4.0" is not a new one.  It relates back to discussions in 2012 of a forthcoming "Fourth Industrial Revolution", the idea being that the current trend of automation would increase, with technology enabling "smart factories". These factories take existing automated assembly line structures and include a cyber element, allowing for the underlying manufacturing machinery to communicate with one another and with the wider factory system as a whole via an IoT setup – increasing efficiency.

Machines with autonomy

The whole process is, and would still be, overseen by a human element, who the machines can also communicate with.  But one of the main goals of Industry 4.0 is to have the machines operating in a decentralised way and with as much autonomy as possible save only where exceptions, interferences or conflicting goals require additional input.

 

How is AI being used currently?

"So far, so sci-fi" you might think, but Industry 4.0 is alive across our manufacturing industry and there are already plenty of examples of manufacturers using this kind of technology across the sector.  Developments are being pioneered by high-end technology companies such as Tesla, Intel and Microsoft on an international scale, some through mere investment or others through actual manufacturing and application.

AI efficiencies and cost savings

Siemens has been using neural networks for a number of years in monitoring the efficiencies of their steel plants.  Siemens is now using this prior experience to make waves in the manufacturing AI sector, using AI to monitor variables (e.g. temperature) on their gas turbines which then adjusts the operation of the machine for increased efficiency and without unwanted by-products.

Others use system masters to spot potential problems and possible solutions, often before a human operator would notice such issues.  The use of this technology has resulted in positive improvements across their smart factories, reducing maintenance costs, as AI can now detect wear on machinery long before it becomes unmanageable.

 

The UK's role in AI and plans for regulation

In the UK, The Manufacturer's Annual Manufacturing Report 2018 conducted a survey on the possibility of a more widespread use of "smart factories" - 92% of senior manufacturing executives believe that digital technologies (including AI) will enable them to increase productivity levels.  Yet, the UK is generally seen as "lagging behind" many other developed countries when it comes to implementing AI in the manufacturing sector.  Is this an example of the UK "traditional mindset"?  With estimates on global turnover of the "smart manufacturing" market soaring to a projected $320bn by 2020 – let's hope not!

Sector-led regulation

Despite technology advancing at a rapid pace, regulation of AI is yet to emerge.  Whilst some commentators have theorised a Skynet-style AI uprising if the sector remains as unregulated as it is today, the UK government has provided a more pragmatic voice. According to the House of Lords Select Committee's report on AI[1], the UK "is in a strong position to be a world leader in the development of artificial intelligence" and with this comes some required element of regulation.

The report "AI in the UK: Ready, Willing and Able?" makes several recommendations as to how the law may need to be updated to account for these new technologies, but also states that "blanket AI-specific regulation, at this stage, would be inappropriate". The Lords instead believe that a sector-specific approach should be taken, with three new governmental organisations (the Centre for Data Ethics and Innovation (CDEI), the AI Council and the Government Office for AI) each taking a lead role in developing regulatory policy going forwards.

Manufacturing sector

For the manufacturing sector, this is expected to cover a number of areas. A key area of focus is likely to be the availability of data access.  AI systems are notoriously expensive and this could clearly impact on the revenues of SMEs struggling to compete financially with international corporations if they were to be further bolstered by AI. A possible solution suggested by the Lords is to implement an "Open Banking" style model where some data can be made public in order to make the sector, as a whole, more competitive.

Safety concerns

Terminator references aside, safety is also one of the primary concerns in this new technology. The current law is a long way from Asimov's "Three Laws of Robotics" and currently fails to address liability issues if, for example, a worker was to be injured by a machine malfunction. As with all policy issues at the moment, the spectre of Brexit looms large and is specifically referred to in the Lords' report as an area of concern since many of the UK's AI initiatives are run jointly with EU counterparts.

Impact on workforce

Finally, aside from direct regulation, businesses across the sector must prepare themselves for potential changes in personnel. Much has been made of how AI will "cost jobs" but the reality is that work in this field is expected to create as many as are lost. It will be more a matter of retraining current staff to deal with the new equipment, and each business will have to assess how much of an impact this will have on their own operation.

AI promotion of innovation and growth

The use of AI in manufacturing will inevitably increase over the short-to-medium term before becoming the "norm" and with an encouraging approach taken by the Lords, aligned with UK Government – who are committed to regulation "that promotes innovation and the growth of new sectors while protecting citizens and the environment", it is likely that we can expect domestic investment in AI as well as the inevitable international investment.

Sustainable regulation required

As with all rapidly growing technologies, the focus should be on sustainable regulation (such as the recent developments in UK law on the use of drones).  However, while the regulatory forecast is still uncertain, what is becoming clear is a real sense of opportunity.

AI - an opportunity for all

With the possibility of the UK being front-and-centre of the new age for manufacturing, there is huge potential for our manufacturing and technology clients:

• those that embrace the change and move towards a technology-focused approach away from the traditional "industrial" style will surely benefit from the efficiencies that come with that change, and
• for the smaller UK SMEs and start-ups out there – dream big!  With the AI sector in such an early stage of development and with many larger corporations lacking the technological know-how (for the time being) to trail-blaze the industry, UK start-ups, with the technological background, have the opportunity to partner or contract with large industrials and have their say on what the future of the manufacturing sector looks like.

Womble Bond Dickinson takes a sector-based approach in all work that we do for our clients and are particularly strong in both manufacturing and technology.  If you have any comments or queries in relation to this article, AI in general, or questions about how we can help your business grow and embrace this new landscape, please get in touch.

Approximately one in three companies (32 per cent) believe the business use of artificial intelligence will be commonplace within the next decade, new research from TomTom Telematics has revealed.

The study found that 22 per cent believe virtual reality will be in common usage, while around one in five anticipates the prevalence of in-vehicle working due to the development of autonomous vehicles.

However, almost a third (32 per cent) fear they may struggle to keep pace with the rate of technological change. Furthermore, one in two (49 per cent) believe those that fail to embrace digitalised processes and the Internet of Things are at greater risk of going out of business.

“Complacency can sound the death knell for businesses,” said Beverley Wise, director UK & Ireland at TomTom Telematics.

“Companies should be mindful of the pace of change and keep a close eye on the solutions and processes that will help ensure a competitive future – from smart mobility and connected tech to advanced manufacturing and design systems. Many of today’s new emerging technologies will disrupt and revolutionise commerce, and in the process become the standard for tomorrow.”

Almost half of companies (46 per cent) believe remote working has or will become, the norm within the next 10 years. Remote working is currently proving more prevalent among larger companies (58 per cent) than their SMEs counterparts (37 per cent).

“The onus is on businesses, both large and small, to adapt to this new era of hypermobility and connected working that is being ushered in by advancements in areas ranging from telematics and the connected car to iPaaS and blockchain solutions,” added Wise.

“Such connected technologies and unified communication systems are unshackling workers from traditional working patterns - an empowering development that is set to significantly impact productivity and business efficiency.”

---

Be social and share

If there is one industry that should be leveraging data in every way possible, it’s telecommunications. The telecommunications industry services billions of people each day, generating massive amounts of data. Though not many telecom companies are leveraging this data, the introduction of data science, machine learning, and artificial intelligence in this industry are inevitable.

A study by McKinsey, Telcos: The Untapped Promise of Big Data, based on a survey of leaders from 273 telecom organizations, found that most companies had not yet seriously leveraged the data at their disposal to increase profits. And only 30 per cent say they have already made investments in big data.

So while there is certainly debate within telecom companies about whether the return on investment is worthwhile, there is no doubt that data science, machine learning (ML), and artificial intelligence (AI) are inevitable when it comes to the industry’s future. Those that figure out how to leverage these techniques and technologies will thrive; those that don’t will be left behind.

By using data science, machine learning, and artificial intelligence strategies, telecommunication companies can improve four areas of their services.

The importance of data science, ML, and AI to the telecom industry will likely present itself in these four areas in particular, which this paper will take a look at individually:

 

1. Troubleshooting:

One of the major challenges for telecom providers is being able to guarantee quality service to subscribers. Analyzing call detail records (CDR) generated by subscribers at any given moment of the day is key to troubleshooting. However, CDRs are challenging to work with because the volume of data gets massive and unwieldy quickly. For example, the largest telecommunication companies can collect six billion CDRs per day.

With data science, machine learning (ML), and artificial intelligence (AI), companies can instantaneously parse through millions of CDRs in real-time, identify patterns, create scalable data visualizations, and predict future problems.

 

2. Fraud Detection: 

Verizon estimated in 2014 that fraud costs the telecom industry upwards of $4 billion a year. However, the faster that telecom companies analyze large amounts of data, the better off they are in identifying suspicious call patterns that correlate with fraudulent activity.

Cutting-edge ML and AI strategies like advanced anomaly detection make it much easier for telecommunication companies to identify “true party” fraud quickly.

 

3. Marketing:

The high churn rate in telecommunications, estimated at between 20-40% annually, is the greatest challenge for telecom companies. Telecommunication companies can use data to build better profiles of customers, figure out how to best win their loyalty (in the most scalable and automated way), and adequately allocate a marketing budget. With improved data architecture, they are able to harvest and store a greater diversity of data that provide insights into each customer such as demographics, location, devices used, the frequency of purchases, and usage patterns. By combining data from other sources like social media, they can have a stronger understanding of their customers.

Using machine learning gives a more accurate picture of which channels are most responsible for customer conversions for better ad buying as well.

 

4. Customer Experience: 

Telecommunication companies can enhance their services by analyzing the millions of customer complaints they get every year to figure out which types of improvements will have the greatest impact on customer satisfaction and thereby increase customer retention. They can also leverage data at a larger and more automated scale to gain insights into the performance of their technicians.

The more that telecommunication companies can analyze data on customer calls, the more they can begin to recognize which types of problems are most likely to lead to unwarranted “truck rolls” and put in place measures to prevent those calls. Given the number of calls and the depth of analysis required, this necessarily dictates a machine learning approach - more specifically, a deep learning approach. Because analyzing the calls themselves means dealing with lots of unstructured data, it’s the perfect place to expand into ML and deep learning for big gains.

 

The future of data in the telecom industry

Data science is already a big part of the telecommunications industry, and as big data tools become more available and sophisticated, data science, ML, and AI will all continue to grow in this space.

In the coming years, companies that succeed will be those that figure out how to best use the massive number of data points that are flowing both through their network and around it to reduce labor costs, develop better technology and, to better understand what the seven billion potential customers around the world want to do with their smartphones and computers.

To learn more, download the whitepaper White Paper: Top 4 Growth Areas of Machine Learning in Telecommunications.

---

 

Be social and share

In this episode of The Field Service Podcast, Field Service News Editor-in-Chief talks to Kevin McNally, Sales Director for Asolvi about how technologies such as Cloud, Mobile, Artificial Intelligence and IoT have enabled smaller companies to not only meet the service standards of their larger peers but in some instances exceed those standards...

Did You Know? You can now subscribe to The Field Service Podcast on iTunes! Check it out here and subscribe to get the podcast straight to your phone, desktop or tablet as soon as they are released! 

Want to know more? Field Service News have published a white paper sponsored by Asolvi that explores this topic in further detail. This white paper is available exclusively for fieldservicenews.com subscribers.

If you are not yet a subscriber and are a field service professional you can apply for a complimentary subscription below (after reading our T&Cs here first) and we will send you a copy of the white paper as soon as we receive your application.

Click here to apply for your complimentary industry subscription to fieldservicenews.com and access the white paper now!

Note: Please do take the time to our T&Cs (available in plain English at fieldservicenews.com/subscribe) and note that this content is sponsored by Asolvi)
be social and share

Atos, a global leader in digital transformation today announces that it has been identified as a ‘Leader’ by global research and advisory firm NelsonHall in its latest Vendor Evaluation & Assessment Tool (NEAT) for Cognitive IT Infrastructure Management...

Atos supports businesses in their digital transformation by providing the tools, services and consulting to enable them to successfully implement next-generation IT infrastructure and workplace services, such as those which use Artificial Intelligence (AI), cognitive, machine learning, deep learning, virtual agents, advanced analytics and robotics.

Atos’ brand new Codex AI Suite, announced recently, supports businesses and research institutes in the development, deployment and management of AI applications. It offers an easy-to-use, efficient and cost-effective solution to rapidly build and deploy AI applications, better extract value from data and develop new business opportunities.

Atos’ end-to-end Digital Workplace offering includes a range of intelligent solutions to enhance the user experience.Atos’ end-to-end Digital Workplace offering includes a range of intelligent solutions to enhance the user experience. This includes the Atos Virtual Assistant (AVA), which leverages Cognicor’s next-generation AI engine, to offer help and support for users, resulting in reduced downtime, increased user productivity, and cost reduction.

Commenting on this ranking, John Laherty, Senior Research Analyst at NelsonHall, said: “Atos is driving digital transformation across both infrastructure and service desk to improve business outcomes and end-user experience; it is embedding automation into all its standard infrastructure managed services offering for clients.”

Elaborating on Atos’ role as a leader in Cognitive IT Infrastructure Management services, Peter Pluim, Head of Infrastructure & Data Management at Atos, said: “We are delighted to be recognized as a Leader in Cognitive IT Infrastructure Management by NelsonHall. We offer an end-to-end approach to automation and robotics, thereby reducing costs, increasing quality, and creating differentiation with real-time insight for our clients.”

Be social and share

Kris Oldland, Editor-in-Chief, Field Service News talks to Scott Berg, CEO at ServiceMax about why IoT has so far failed to hit the heights it really is capable of and what we more should be expecting from connected assets in the near future...

When I sit down with Berg, he has just given a highly well-received presentation at Field Service USA, perhaps the biggest event in the global field service calendar. He managed to hit the two big topics that dominated conversation over the four days of the conference, namely preventative maintenance and IoT.

However, whilst many of his peers have spent the time still talking about why these are essential topics for field service companies today, Berg is already looking towards tomorrow.

“There is a big move towards predictive service, which a lot of us have talked about wanting to do. I think IoT has arrived on the scene and that might be what finally enables it. One of the things I’ve seen as we’ve come deeper into GE and seen what some of the other assets are around us from a technology standpoint is that the asset performance management concept is really unique,” he opens.

“As a field service guy I didn’t even know that this stuff was out there- I didn’t know that it was possible. That, of course, makes sense as it was used in process manufacturing, chemicals, oil and gas so it just wouldn’t occur to bring that over to field service, but this linking of the predictive analytics fed by IoT allows us to create a closed-loop process.”

“Frankly, now that I know these APM guys better within the GE company, it was one of the first epiphanies we had last year where we said you send that work to me, I’ll send you this back, arm the technician with the predictives that say ‘here’s why your here today.’”

“Another theme is also that this whole IoT thing is making me scratch my head a little bit and I’ve been talking to more and more people lately about this.,” Berg admits.

For me as a technology salesperson by trade it really gets good when someone can see real obvious value articulated, experience it and it becomes a bit of a no-brainer, I don’t think IoT has reached tha“$2.9Trillion dollars is going to get spent on IoT by 2020. Now this is not to say that many companies including a number of our customers haven’t experienced value, but it it’s still not quite fulfilling the full potential that it had - so what is the problem? For me as a technology salesperson by trade it really gets good when someone can see real obvious value articulated, experience it and it becomes a bit of a no-brainer, I don’t think IoT has reached that.”

It is a question I have raised myself in these pages. So what does Berg think is holding everyone back from seeing the true potential of IoT?

“I think it’s a combination of things,” he replies, considering the question. “Firstly, people are still drowning in data - and I do think that is still a problem. We see it even in GE businesses, there is so much more data by our own creation that it just gets harder and harder, and so now you’ve got things like Edge computing as opposed to sensors feeding data to Clouds, which is way to slow and far away, so that’s one thing that is changing rapidly.”

“And yes, there are people who have got the benefit but so far I see it as just a one and done benefit. We’ve had good examples of our customers, where they’ve identified a failure pattern, in one case a company were able to identify that they were fixing something too early, they could’ve gotten two more weeks out of it, so that leads to a modification of a service protocol or procedure, but it is still a one-off benefit.”

“It’s big don’t get me wrong. But it doesn’t do anything for you next year and it didn’t uncover the next problem. In fact, it may be even pushing a problem further downstream and so then another one surfaces.”

“That’s what is so exciting about the whole conversation around AI and Machine Learning - in that it offers continuous learning. The ability to model risk and put that into a plan - maybe that is the final way to bring IoT to its full potential in terms of service management and to create a pretty cool closed-loop process really.”

“I don’t mean to push IoT to a back seat, don’t get me wrong, there are so many side benefits that are game changing but it is a bit like you’ve planted something and then your like when is it going to come out of the ground, when am I going to see a flower and then to continue that analogy when that fruit first comes out, you don’t want to pick it and then that’s if you want it to be a constant crop."

It is interesting to hear Berg’s view that there is so much more to come how we implement IoT in a field service context. Particularly given ServiceMax’s role as an earlier pioneer within the space. When he speaks on the topic he invokes a clear belief in the scientific method - i.e. that each hypothesis is subject to continuous testing and re-evaluation.

“We were early partners and integrators with things like PTC and the ThingWorx products, launched connected field service and we’ve had some customers who have seen some real benefit - but why didn’t it sustain, why didn’t it evolve, why didn’t it grow - why wasn’t it everywhere?” He asks.

“I think it is because people were just a bit stalled looking for that extra piece of the puzzle,’ he continues answering his own questions.

One of the reasons we didn’t call Connected Field Service our IoT API is because the notion of connecting field service was not only getting the device to give up its data but also in the mobile device then arming the technician with why are you here“In fact, one of the reasons we didn’t call Connected Field Service our IoT API is because the notion of connecting field service was not only getting the device to give up its data but also in the mobile device then arming the technician with why are you here.”

“What was the reading that led to this? But let’s take that further, let’s get an understanding of what the is device doing right now so they know what it was doing yesterday when they were summoned, but also me what it's doing now, how has that changed.”

“I think that’s that notion of equipment centricity. The cool thing about GE is that it is the world’s largest field service company and it is also at it’s core a completely asset-centric group of engineers, the machine is everything they worship the machines - there are pictures of machines all over our office.”

When I last spoke to Berg, ServiceMax had only recently become part of the GE family, but even then he spoke of an early affinity between the companies and of a kindred spirit at each companies core. Fast forward some 18 months and it is clear that the relationship is proving to be even more symbiotic with benefits flowing both ways.

“I was in a meeting recently where one of the innovations another team was pushing in APM was maximising the performance and predicting the health of a set of assets. By that I mean not just one isolated machine but for example think of a wind-farm, maybe there are a thousand of assets within that fleet. We were trying to establish how we can comprehend the collective health of those assets and how they work together.”

This is just another example of how Berg, ServiceMax and now the wider team within GE are not satisfied with pushing the envelope today but are dedicated to understanding how they can continue to stay at the vanguard of innovation for many, many years to come.

Be social and share