Digitalization in the Automotive Industry
The automotive industry is changing rapidly, as new technologies, customer demands, and players emerge. We see the industry move away from the traditional role of hardware provider and embrace the role of provider of connected mobility and transportation solutions, ranging from new digitally enabled services to the software-driven, battery-operated, artificially intelligent, autonomous vehicles of the future. While new offerings emerge, value creation and profit pools shift from incumbents to fields in which tech challengers may have an edge. At the Center for Digital in Automotive we see digitalization as a catalyst, facilitator, and enabler for automotive and mobility companies.
DRIVING DIGITAL TRANSFORMATION IN AUTOMOTIVE
Automotive businesses will need a digital strategy to define their digital ambition and shape their approaches to new opportunities and challenges.
The Center for Digital in Automotive engages with companies from automotive and automotive-related industries around the globe to help them find answers to the questions that arise from the many opportunities and challenges of digitalization. We work with clients across functions to develop new competitive advantages, launch new businesses built on the evolving technical possibilities of digitalization, and establish the infrastructure and capabilities needed for success.
We invite you to explore our approach, meet our experts, read our publications, and learn more about our impact with clients.
Digital transformation in the construction industry: is an AI revolution on the way?
Whilst digital technology has transformed everything from hospitality and banking, to healthcare and e-commerce, the UK’s construction industry has been slow to adopt this change. But is an AI revolution on the way?
The majority of industries have begun their digital transformation journeys. Digital transformation in the construction industry, however, has been slow. Perhaps, this failure to adopt digital technology has been based on a systemic resistance to change?
Indeed, this desire to adopt new technology is being hindered by almost all construction organisations overlook the importance of a technology partner in enabling training and up-skilling, according to a new report by Zen Internet. It found that, as is so often the case with traditional industries, culture is a significant barrier to embracing this necessary change.
Despite this, it appears that there is a willingness to embrace the digital future in this industry and the report reveals that digital transformation has now laid its foundations firmly within the construction industry, with many organisations already working with new technologies such as AI.
Is the construction sector finally embracing artificial intelligence?
Industries are embracing technologies like artificial intelligence on a greater scale than ever before, and construction is no different. CTOs take note. Read here
Artificial intelligence is laying its foundations in construction, but integrating a digital transformation project requires cultural change
• More than half (55%) of large construction firms (over 250 employees) and a third (28%) of smaller organisations (under 250 employees) are already using artificial intelligence.
• Over half (51%) of construction firms surveyed see cultural change as a barrier when implementing a digital transformation project.
• Almost all (86%) construction firms surveyed overlook the importance of a technology partner.
There is an appetite to change, with the construction industry looking at a range of technologies, on top of AI, that could help them in the future, with virtual reality (28%), cloud computing (24%), software defined networking (20%), blockchain (19%) and Internet of Things (17%) all seen as key to future development by those in larger organisations.
According to Tech Nation’s 2018 report, technology is expanding 2.6 times faster than the rest of the UK economy, and yet the construction industry has been slow to implement digitalisation strategies that could bring increased efficiency and collaboration as well as reduced costs.
Disrupt, transform or die. It’s time to enjoy the digital ride
How should businesses look to overcome some of the key challenges of operating a business in the digital age?
Disrupt or die
We only have to look to Mark Farmer’s landmark 2016 report, ‘Modernise or Die’, which warned that failure to innovate poses a serious threat to the UK construction sector.
This was recognised by the Construction Leadership Council, which published its construction sector deal with a focus on transforming the industry through a ‘bytes and mortar’ approach to smart construction.
Digital business requires a change in mindset and not just technology – Gartner
A technology shift that isn’t backed up by a corresponding cultural shift puts the success of a digital business initiative at risk. Read here
Culture change: the biggest barrier
Zen’s report suggests that digital transformation appears to be a strategic priority for the leaders of construction firms, with CEOs (52%), CIOs and CTOs (32%) amongst the biggest drivers of such projects.
This top down approach, crucial for driving change in any business or industry, is still not having the desired results. Cultural change (51%) is cited as one of the biggest challenges to implementing a digital transformation project, highlighting the need to get company-wide buy-in. Nearly all (89%) companies surveyed, who claimed to have already completed a digital transformation project, note that cultural changes are needed from within to make it a success. According to the report, overcoming cultural resistance is only topped by the importance of communicating the value of digital transformation to key stakeholders and investors (62%).
James Albiges, general manager — Network and Communications at Zen, commented: “Initiatives such as training and up-skilling will help tackle cultural change from within a business. This coupled with clear objectives and a formulated strategy will go a long way in making your digital transformation project a success.”
Failed projects can cost an average of $655,000 to the bottom line, yet despite this, almost all (86%) construction organisations surveyed overlook the importance of a good technology partner as an enabler of an effective digital transformation
Digital transformation: it’s a no brainer
The majority of the construction firms surveyed said they have either completed a digital transformation project or have one currently underway — over half (61%) noted improved efficiency and reduced operational costs (58%) as direct advantages. On top of this, following the initial investment, two-thirds (66%) of companies noted a subsequent reduction in costs as a result of the new technology deployed and a third (33%) reported an increase in sales.
The benefits of implementing a digital transformation project can also go beyond the organisation itself, with half of respondents claiming it has enabled increased collaboration within the ecosystem, stemming from streamlined communication and networking — the report concludes that when progressive technology is fully embraced, a more streamlined approach to conducting business across the supply chain can be achieved.
“It’s fair to say that the construction sector has traditionally been slow to adopt change, but things have clearly moved forward in recent years, with digital transformation now a key consideration for the sector,” said Albiges.
“But it is important to note that a digital transformation is not just a means to an end. It’s an ever-evolving process to deliver profound change, fundamentally altering much of the world around us. It is important for construction organisations of all shapes and sizes to understand what digital transformation is, and how a business can benefit from it. There’s no one size fits all approach and there are different solutions for different business needs. With the amount of technologies and number of vendors to choose from, knowing where to start can be a real challenge. That’s why it can help to find a provider that will put your organisation’s success top of the agenda and one that has the right expertise and experience in delivering successful digital transformation projects within the construction industry.”
What is digital transformation in business:
Digital Transformation For The Food & Beverage Industry
In May 2019, Lux Research released a report on the digital transformation of the food and beverage industry. In their press release, Harini Venkataraman, the lead analyst of the report noted:
“More than in other industries, digitalization in food will be a common thread across the entire agrifood ecosystem to enable industry players to address consumers’ future needs. The fact is, food companies that resist the digital conversion will not be able to keep up with more digital-savvy innovators, and will face higher R&D costs, longer product development timelines, and shrinking market share.”
We couldn’t agree more. And clearly first level food processors agree, as we have seen an increased interest in our satellite crop monitoring capabilities in the past year.
The Lux report evaluates the value of digital transformation for the food and beverage industry by its ability to achieve one or more of the six enabling core outcomes and we are proud to have worked with customers across the globe to achieve success in each of these six areas.
Uncover Invisible Insights
As defined by Lux Research: Find an insight by analyzing a signal or set of signals that humans can’t easily interpret.
This is likely the most difficult outcome – finding something that can’t easily be interpreted – but this is at the core of everything we do at Geosys. We’ve frequently discussed how the advantage of satellite imagery is its ability to let us see what’s happening in a field before it’s visible to the human eye. The greatest risk factor to farming is weather. The timing and degree of severity of a weather event can cause drastically different outcomes. Satellite imagery provides data based on signals the plant is sending – it reads the health of the plant in the moment. The plants send invisible signals often before visible signals can be seen.
Even when visible signals are obvious – such as the current wind damage to fields across the Midwest from the recent derecho – there are still factors that cannot be seen with the human eye. Monitoring the NDVI of these crops helps us understand if they will recover and to what degree.
To learn more about the science behind how we use satellites to monitor plant health, be sure to check out Understanding and Evaluating Satellite Remote Sensing Technology in Agriculture.
Predict the Future
As defined by Lux Research: Determine the most likely outcome of a future situation – a particular type of invisible insight
No Magic 8 Balls here. We pride ourselves in using scientific-grade data to run our proven analytics. Applications like our Agriquest tool provide a powerful combination of satellite and weather data with daily updates and a historical database that goes back at least 25 years. This enables us to compare a variety of datasets to best understand what is currently happening in the field and how that compares to past yields. This empowers analytics for our customers for yield and quality forecasting in addition to harvest planning.
As defined by Lux Research: Find optimal setpoints given a set of constraints – a particular type of invisible insight.
When we combine customer data with our data analytics, we often find that 1+1=3. We can do this by integrating customer data into our existing tools, powering a customer’s platform with our Geosys APIs, or building a customized platform to meet the specific needs of a customer. This enables logistics fine-tuning.
We can also help customers answer specific questions, such as identifying the “right” place to grow specific crops. Whether it’s utilizing existing analytics or working to create, test and apply to new analytics, our team is ready to help your business optimize.
As defined by Lux Research: Grant humans a skill they didn’t have before.
We have worked through our 30+ year history in precision agriculture to upskill agronomists, and in commodities trading to upskill analysts. The needs of these groups are parallel to that of the food and beverage industry.
It’s helpful to have production estimates for key growing regions but Geosys takes it to the next level by telling companies exactly what will be collected at a farm level and when. Wherever the contract production is localized, we monitor it for production, quality and timing metrics – delivering insights to support logistics decisions at the plant or procurement, as well as to field support staff so they can focus their efforts where it matters most.
Make Information Accessible
As defined by Lux Research: Make information visible and apparent.
No one really enjoys syphering through endless rows of Excel data and trying to create pivot tables to make sense of it all (okay, we all know that one person who geeks out over these things, but you get our point). This is why we make data visual – so it is quick and easy to consume and understand. Dashboards, APIs and cloud-based applications make our data and insights available globally in a consistent manner, yet adaptable to local context.
Insights are published for internal use while specific metrics can also be published for the benefit of consumers – such as sustainability metrics – to provide the level of transparency expected by all parties.
As defined by Lux Research: Eliminate or reduce human involvement in a process, task or decision.
High quality, accurate data can power a wide variety of analytics to automate processes. Automating data collection and insights calculations are the first steps to go through. We offer ready-to-go tools (such as Croptical) or corresponding APIs to build weather alerts or vegetation index change detection, which can be connected into third party applications such as CropTrak for anyone who is ready to start.
Start Your Digital Transformation Today
The movement towards digital transformation in the food and beverage industry has already begun. Now is the time to start future-proofing your business. Contact us to learn how we can help empower your digital transformation or learn more about our capabilities.
Digital transformation in the manufacturing industry: challenges and accelerators
The manufacturing industry is one of the industries which moved rather slow from an enterprise-wide and certainly ecosystem-wide digital transformation perspective.
Several driving forces of digital transformation in the manufacturing industry are relatively similar to those in other industries. Moreover, industry initiatives and national initiatives across the globe such as Industry 4.0 (Germany and parts of the EU) or the Industrial Internet (Consortium) accelerate transformations with the Internet of Things and the integration of IT and OT as key components.
Industry 4.0 offers multiple benefits – enhanced productivity is just the beginning (The Boston Consulting Group)
The changing expectations of consumers impact the entire supply chain as various manufacturers obviously depend on each other so even manufacturers which don’t produce consumer goods are impacted by these consumer changes. Moreover, manufacturing decision makers also have different expectations as, in the end, we are all consumers. It leads us to the data-intensive and (semi-)autonomous evolutions in Logistics 4.0 where speed and connectivity, with again IoT and cyber-phsyical systems being key.
Digital transformation in manufacturing: evolving towards the ‘as a service’ economy
Other drivers include traditional digital transformation goals on the level of enhanced efficiency, cost reduction and, in more mature stages, innovation and the development of new revenue sources in an age where data – and how it is leveraged – is the currency of automation, optimization and profound transformation at the core where new business models in an ‘as a service’ economy are sought.
The manufacturing industry obviously is a broad industry with giant multinationals and smaller manufacturers; and with industrial manufacturers which produce for industrial partners and manufacturers of goods that are closer to the consumer.
Just like many other industries, the manufacturing industry is diverse and moving at different speeds. While in general digital transformation strategy has been missing and initiatives have been ad hoc, things are changing in some areas but as we’ll see a holistic picture is still missing and the goals remain relatively traditional and isolated.
The similarity between digital transformation and Industrial Internet drivers
Regarding the areas where change is happening one can, for instance, only notice the key role of IoT in the manufacturing industry, advanced data analytics, digital twins and the various components of the Industrial Internet or Industry 4.0 space with an obvious place for, among others, advanced data analytics, industrial robots and collaborative robots, a.k.a cobots.
As mentioned previously, manufacturing is not just the largest industry from an IoT spending perspective, it is also at the center of the Industrial Internet of Things (IIoT).
Some even say that the Industrial Internet of Things only is about the manufacturing industry. Although that is not correct, it’s easy to see why this is the case, if we look at the main Industrial IoT players and at the areas where most IIoT spending occurs.
The reasons why the manufacturing industry is so active in Industrial IoT are threefold and directly relate with manufacturing industry challenges and digital transformation challenges or, more positively, opportunities.
Three large challenges in the manufacturing industry
Economic, geo-political and consumption uncertainties – the need for efficiency
Looking at the end of 2016, 2017 and probably the years beyond, a challenge that hasn’t maybe been the most pressing in past years but clearly has become crucial for the future: geo-political and macro-economic conditions.
The manufacturing industry is going through extremely uncertain times and unpredictability regarding consumer spending/confidence on one hand and the larger geo-political and macro-economic picture on the other is high. There is the protectionist climate in the US whereby manufacturing is one of the key focus points of the new presidency. In other regions similar protectionist risks are present.
European manufacturers are rallying to drive the Industry 4.0 vision forward, amidst the growing uncertainty (and let’s not forget the Brexit uncertainties) even faster than before. Also in other parts of the world initiatives are taken in an undeniable reality where globalization has gone from an evidence for many to a source of distrust for many others.
It is clear that in such conditions the push to automate and save costs, while increasing efficiencies (enhance time-to-market, digitize and digitalize to maximize revenue, etc.) becomes even higher. It is most certainly here that we see an even faster than expected uptake of the Industrial Internet of Things whereby the initial drivers are the same as in the initial digital transformation drivers: increase agility and reduce waste, bring down costs and enhance efficiencies, from manufacturing operations and business processes to maintenance and services.
The customer factor: from speed to better products, services and customer experience
Once these efficiencies and the rather process-oriented and internal-facing Industry 4.0 or Industrial Internet objectives we’ve just mentioned are achieved, new opportunities arise and efforts are done, looking more at customer-facing optimization and innovation.
Note: obviously, in practice, these various goals can be and are sought at the same time (it is not a gradual processes although de facto prioritization is essential). Automation, optimization and the efficiency- and cost-driven goals do have a customer-centric goal as well.
In the end, speed and information-rich, streamlined process optimization efforts don’t just bring down costs but also are what both end customers and the many partners in the manufacturing ecosystem seek. In an increasingly complex and connected value chain (which is another challenge and opportunity for manufacturing) and in the optimization of industrial and business processes, data/information and the Industrial Internet of Things plays an inevitable role. At the same time both are key components of the ability to work in a more customer-centric way in various regards: the improvement of services (towards consumers or industrial partners as is illustrated in the story of how ABB Robotics could offer far better services to its customers, buyers of industrial robots, thanks to the Industrial IoT), the production of goods which are better tailored to customer demand through actionable data and insights, customer experience enhancement through collaborative models and data regarding quality, the list goes on.
Competition and the disruptive impact of manufacturers who have transformed at the core
A third element and also an inevitable consequence of the first two is closer to digital transformation at the core – in the business models and in the detection of new information-driven and connected revenue opportunities in the ‘as a service’ evolution.
By 2020, Manufacturers Will Capture 20% More Aftermarket Revenue by Using Product and Service Quality Measures to Enhance Customer Experiences (IDC, see below)
The old concept of the extended enterprise is pushed much further in the development of new revenue sources, built around services and information, often in collaboration with a-typical partners. Moreover, it’s also key to see how digital transformation initiatives and innovations can be realized in the more traditional ecosystem context of manufacturers with, for example, retail, transportation and logistics etc.
It’s in the dimension of innovation regarding information-based services and ‘products’, that the most mature manufacturing industry players shift business models or at the least find new ways to increase profitability.
It’s also here that leading manufacturers become ‘disruptive’, which obviously then is an additional – competitive – challenge for other manufacturers who haven’t reached the same levels of maturity or ‘innovative disruption’.
In this context it’s important to point out research of The Boston Consulting Group, released end 2016, that many manufacturers see Industry 4.0 as a priority (many also weren’t familiar with the term which influences the outcomes no doubt) but relatively few look at the possibilities to tap into new revenue sources, let alone increase revenues to begin with. There is still a lot of emphasis on productivity optimization and a holistic approach/strategy lacks.
It’s the same picture we see popping up over and over in other industries too and shows how we can’t keep stressing the importance of digital transformation strategy and of a holistic digital transformation perspective enough. More on the research of BCG below this post.
Digital transformation and Industry 4.0 challenges to address in manufacturing
On top of these three challenges and opportunities in manufacturing (and the industrial Internet) are several other manufacturing challenges.
The traditional manufacturing skills gap challenge has close to everything to do with the integration of IT and OT (operational technology) and the other technological and customer/service/innovation evolutions mentioned above.
So, to summarize and, reading between the lines of our three Industrial IoT and at the same time digital transformation drivers, we have the following drivers/challenges/opportunities for digital transformation and manufacturing:
- An uncertain macro-economic and geo-political context where risk needs to be managed and cost reductions and enhanced efficiencies are inevitably (read: automation).
- A more complex and connected supply chain where data/information and speed are key.
- The need to better understand the possibilities and benefits which can be achieved. While that is a strategic and information matter, it also requires manufacturing companies to understand technological enablers of new opportunities such as digital twins, robotics, artificial intelligence and 3D printing to name a few – within their benefit, use case and holistic context.
- A changing customer with an increasing need to be not just more customer-centric but also be more customer-adaptive and innovative.
- A highly competitive landscape in which faster movers are poised to gain advantages and even become disruptive.
- The need to diversify and tap into new revenue sources, leveraging new ecosystems, and (connected) data, to thrive and in some cases survive.
- A lack of clear vision and of a strategic holistic approach to tap into the revenue growth and new revenue source potential of Industry 4.0.
- The human talent dimension in an altering reality where technology and innovation play more profound roles and the talent in many of the mentioned areas (data, industrial IoT, convergence of IT and OT, new business models etc.), nor the culture are present to take the necessary steps.
Industry 4.0 and the changing face of work in manufacturing
Regarding the human talent and skills gap dimension, it’s clear that as Industry 4.0 arrives and the digital transformation of manufacturing continues, the work reality changes.
According to IDC (data end 2016, more below), by 2020, 60 percent of plant floor workers at G2000 manufacturers will work alongside automated assistance technologies such as robotics, 3D printing, AI and AR/VR.
Moreover, let’s say it as it is, the ongoing automation, optimization and transformation, comes with a human cost. From a sheer business perspective this is a challenge as well.
We need add the human consequences, as they MUST be addressed in times when people see fast digitalization as a threat. Each organization, and in manufacturing it is certainly a key element, must realize the impact of automation and that it has a role in society, whereby overlooking human costs can lead to further erosion of brand equity and trust and declines in consumer confidence and buying ‘power’.
More resources on Industry 4.0 and the digital transformation of manufacturing in 2017 and beyond
Of course we didn’t tackle all manufacturing challenges and digital transformation opportunities nor the evolutions in specific manufacturing industries.
Below are a few additional sources you can check out regarding digital transformation in manufacturing in 2017 and beyond:
10 Predictions for the Manufacturing Industry.
In this blog on IDC Manufacturing Insights, Kimberly Knickle, gives an overview of the main 10 predictions which IDC published end 2016, for the coming years.
The post essentially contains the 10 predictions – with data – as you can find them in the report (and of which we mentioned a few) and some more challenges in the manufacturing industry such as more integrated IT and operations (the convergence of IT and OT we’ve mentioned), business security and the need to rethink the future of work in manufacturing.
Sprinting to Value in Industry 4.0.
As mentioned earlier, The Boston Consulting Group released a report about the evolutions in Industry 4.0 and the implications for the US manufacturing industry.
On top of detecting challenges regarding the gaps between the perceived needs to move (faster) in Industry 4.0 among manufacturing professionals and the lack of strategic vision and speed to do so with a far too restricted focus on optimization and not enough focus on generating more revenues, let alone, the identification of new sources of revenues.
Digital Transformation: The future of downstream
Machine learning is an incredibly exciting innovation — the ability to understand when something is going to fail, before it fails — says Craig Hayman, CEO of AVEVA
Digitalisation is a hot topic these days, especially in the refining and petrochemicals industry around the world. The discussion in downstream today has moved quickly from why digitalisation to how quickly can organisations transform.
Digital technology has all the buzzwords — big data, cloud, Industrial IoT, machine learning, augmented reality, virtual reality, etc. — which are all horizontal technologies. All these technologies are being deployed at scale in both midstream and downstream industries. For example, using data that is collected across hundred thousand, or may be even million data points in an operational facility, and providing visualisation in an operational way. Another great example of disruption is how machine learning is being applied to predict unplanned downtime. This is really where the current state-of-the-art is in terms of the digital transformation in the worldwide downstream industry.
Digital transformation of the industrial world
AVEVA, Virsec collaborate to boost defence against targeted cyber attacks
AVEVA has committed itself to the role of digital transformation in the industrial world. The company has doubled in size in the last twelve months by combining the heritage of AVEVA business, which has been around for more than 50 years, focusing mainly on EPCs and oil operators, and the legacy of Schneider Electric software business, which focused on the operational aspects of different industries, including the oil and gas industry, into one entity. Currently, the combined enterprise is worth $1bn in revenues and operates in 80 countries around the world. Craig Hayman joined AVEVA in February 2018 as chief executive officer.
We have almost 5,000 employees and almost 100 of these employees are PhDs. We spend $100mn in a year in research and development on committing ourselves to the digitalisation of the industrial world.“We have almost 5,000 employees and almost 100 of these employees are PhDs. We spend $100mn in a year in research and development on committing ourselves to the digitalisation of the industrial world. We have about 16,000 customers around the world. We are learning from them every day, how to further optimise midstream and downstream sectors, using Industry 4.0 in very compelling ways. What we are learning is fantastic,” Hayman reveals.
“Forty-five percent of our business is from the oil and gas industry, and much of that is from the midstream and downstream sectors. Our business has two aspects — OPEX and CAPEX. OPEX is the operational cost of running the downstream facilities, which are there for, may be, 20 to 50 years. And, CAPEX is the new investments in the greenfield, or brownfield environment. We are focused on optimising both these aspects — delivering better insights to the customers like reduced downtime, increased safety, optimised RoI, reduced project handover time, etc.,” observes Hayman.
In the last three years, the downstream industry’s focus is driving innovation and not just building up new facilities. Innovation in downstream industry means operating facilities at higher operational efficiency, less downtime and better safety. Digital technologies are used in this transformation of downstream production facilities.
The digital tools
Downstream plant operators have a very difficult job — they have to drive increased performance in their facilities and also try to reduce cost, at the same time. To do that, they are looking for the best practices that can be applied within their current budgets.
Most downstream operators want to drive digitalisation. They already have various projects to drive the digital transformation. The only questionthey have is how can they move more quickly enough in their digital aspirations? How can they do it with low risk? How can they do it with a small incremental investment?
“AVEVA helps our customers scale quickly in their digital journey, by running a 90-days pilot, for example, for these plant operators. We start collecting data of the operational facility. It could be from a couple of thousand data points. It could be about a compressor, or a pump, or about vibration, viscosity, pressure, temperature, etc. We collect all of that data. Then, we start visualising it in a reliable, and appealing way. This visualisation gives transformational insight into their business,” Hayman explains.
“Then, we start applying machine learning. We look at the operational data of today versus every other day up till now, to detect anomalies. For example, we may detect a pump is vibrating little bit differently today than it did every other day. We compare that pump with every other pump from that manufacturer. By this process, we can predict when it will fail, before it will fail. The result is, when the plant operator is doing planned maintenance in the facility, the pump could be taken offline and the maintenance on it could be done so that there is no unplanned downtime. As a result, the savings are just incredible for the customers.”
“Machine learning is the fastest growing part of our business. It accounts for 10% of our revenues. Another area is around virtual reality and augmented reality. This is around operator training — being able to take a worker through an operational facility virtually and being able to simulate the maintenance procedure — for example, in which direction a valve should be rotated, in which sequence a valve should be rotated, how that should be kept in concept with the original design of the facility, etc. — this is an amazing boon to increasing operator safety,” adds Hayman.
“A third area, which has been around for a while but really starting to happen now, is the idea of point clouds. Most of the operators do not have their operational facilities digitally modelled. We go through the facility and collect a point cloud of that facility.”
“For example, if you are used to drive a Tesla down the street, it builds a 3D point cloud of the street. We do the same in an operational downstream facility and capture everything in 3D. This allows us to overlay the operational data coming out of that facility and visualise it in a way that is useful for the operator. For example, if pump 335 is about to fail, the operator can know this from an operational dashboard and can look at it in a 3D layout and see that pump in 3D simulation. This is a remarkable innovation,” Hayman asserts.
The convergence of the operational technology with the information technology in the downstream industry facilities is something which is moving very rapidly. These facilities are meting out large amounts of data every day. But this data is not reaching the hands of the very people who need that data in a usable context to operate that facility in an efficient and safe manner.
“What we provide is the way to capture that data and visualise it in a way to make it available in context for the real operator — who is working in manufacturing, or feedstock quality, or maintenance, or in shift handover. We can apply the best practices and algorithms to deliver some insight for the people who are operating the facility,” points out Hayman.
Delivering capital projects on time and at cost
The total CAPEX spend across the world in the downstream industry — lot of that in the Middle East — was averaging around $450bn a year five to ten years back. This is not the case today. The total CAPEX is around $250bn a year now.
There was a big shift in the industry from the belief that building out capacity in downstream facilities would be how it can scale in the market. When the CAPEX spend plummeted from $450bn to $250bn, the operators wanted to make money at any price. This drove innovation in the downstream industry.
Getting capital projects delivered on time and at cost with low risk and low contingencies is a key element in the organisational success in the downstream industry. The design tools pulling in supply chain data connected to procurement of standard materials for capital projects are used by everyone in cloud. This is an area where AVEVA is investing in very heavily.
“Let us make a step there from the design of the facility into the handover. How can we reduce handover time from nine months to about nine weeks? How we achieve this is by delivering not just the facility but the structured data behind the facility into the hands of the operator. Perhaps, it might also specify into the facility some sensors — ability to flow data out of that facility — as it is being made operational. The operator can look at that data and understand how it is performing back to the design,” Hayman clarifies.
“The next step is enforcing a simulation at the same time when you are doing front-end engineering and design. Every other industry does simulation as part of design. In the oil and gas industry, we bring process simulation into the design sequence. So, as we are designing various piping layouts, etc. in the plant, we can see exactly how that facility is going to operate at different levels of efficiency, different levels of production, and different levels of energy. I am convinced, that in the next five years, these approaches are going to be the de-facto method of how we work in capital projects. Of course, today that is not how we work.”
The Middle East connection
“In the downstream industry in the Middle East, we have many customers. We are working on different aspects of their facilities. For example, materials management in the construction of a downstream facility, ensuring the procurement of the standard materials into a facility is optimised,” comments Hayman.
“In the earlier world, where the flow of goods were relatively easy with very few trade barriers, procurement of materials for CAPEX projects were relatively easy. But now, as we get the trade barriers going up between different economies of the world, there is much more focus on ensuring access to consistent flow of standard materials for the construction of a downstream facility. We are involved in several projects around this aspect in the Middle East.”
“Another aspect we are actively involved in the Middle East is big data. In many projects, we are collecting large amounts of data from the facilities and presenting it to the operating companies in a way that they have visibility to their production footprint. Economics makes total sense here. If you can drive a dollar a barrel in efficiency out of these facilities — purely through technology and not through more downstream capacity — you can drive enormous profit savings into your business and the economies which you support. This is what we see extensively happening in the Middle East,” Hayman explains.
Machine learning will be the key tool
“Between now and 2025, there will be phenomenal change in the digital downstream landscape. AVEVA will be right in the middle of this change with our customers. We connect our customers together. When an organisation works with AVEVA, they are not just working with us; they are working with all our customers all over the world, with all the best practices we have in the digital transformation journey,” opines Hayman.
We are so excited about the road ahead for the oil and gas industry, specifically around downstream, because we see so much innovation and digital transformation coming into the industry. It will be an astounding time for the industry.“What will happen between now and 2025 is that these best practices, or patents will be codified into software as standard digital packages and tools. We are so excited about the road ahead for the oil and gas industry, specifically around downstream, because we see so much innovation and digital transformation coming into the industry. It will be an astounding time for the industry.”
The digital downstream facilities in 2025 will look much the same as those do today. But how those operate will be in highly efficient manner, how those deliver will be optimal, and how those turn over RoI will be exponential. The level of risk will be minimal and the level of safety will be significantly higher than it is today.
The way that is going to happen is by data in the design — simulation of those facilities before those are constructed, or data in the sourcing materials on how they are constructed, or simulation on how those operate at start-up, how those operate at low efficiency, high efficiency, or how those absorb unplanned downtime, or how those use large amounts of data in machine learning to predict unplanned downtime. With modern digital tools, within few seconds, an operator will be able to understand deeply how a facility is operating.
“Our customers want to design and operate not just an average facility, they want to operate the very best, the most efficient, the safest, and the cleanest facility that they can, which is going to operate between 20 and 50 years. And, to make this possible, machine learning is going to dramatically change how those facilities operate by 2025,” Hayman concludes.