Last year was great for industrial markets - process, discrete and hybrids. While growth will be strong in pockets, Ram Ramasamy's personal advice for companies would be to prepare for an overall soft 2019. This is primarily driven by factors such as geopolitical uncertainty, market volatility, widening skill gaps, dynamic shifts in demand models. Below is a view on broad market segments:
Process industries: Upstream oil and gas will be stressed, as supply will continue to outpace demand for most of 2019. Midstream, LNG, Refining and Chemicals are poised to fare well as modernisation, value-chain integration, and performance transformation drive growth. Customers, in general, have embraced digital in a piece-meal fashion.
Discrete industries: Two industries standout - Automotive, Electronics and Semiconductors. For Automotive - plant capacity consolidation will be a major trend, as customers look to produce more models within a smaller plant footprint. Electric vehicles growth is also poised to challenge many OEM's, as current infrastructure is grossly under-prepared for scale. Throughput, product quality, traceability, recalls, visibility, workforce productivity are major areas of focus. As customers build Digital Factories of Future - single assembly lines can churn out multiple car models, consistent product quality can be achieved and sustainability is at the heart of all.
Hybrids: The silver lining of the industrial markets - Lifesciences, F&B have for long been steady-growth verticals. There is more promise in them as customers embrace automation and digitalization to increase efficiency while reducing time to market. Apart from these two, my personal prediction is pertaining to the water industry. This is something to watch out for 2019 and beyond. Remember Flint, MI - The Global water infrastructure will see some fresh perspectives and movement. Smart cities investment, urbanization will mandate a change in water infrastructure.
There are tectonic shifts underway across all three aforementioned market segments. Let us look at the convergences first:
Digital transformation: It was the most spoken phrase in my conversations with clients. Everyone understands the benefits of digital, but there is a striking disconnect between awareness and action. For the beginning, we would need to classify industrial customers into three digital states of maturities: Enterprise digitisers (<10% of the market), selective digitisers (35-40%) and non-digitisers (45-50%). Digital also is not a one-size fits all approach but will need to be built around the industry and the specific customer pain points.
Near-adjacency learning: At the outset, I am often observing customers looking at adjacent/other industries to see what can be learnt from them. For example, upstream oil and gas customers were taking a leaf out of automotive production processes. Similarly, there is quite a bit that can be learnt from healthcare/patient analytics and applied to asset performance management.
Moving beyond the four walls: For a long time, manufacturing has been seen as something within the four walls of the plant. Rising complexity, inter-dependency, customer influence, advanced planning, and scheduling needs are steering customers to look at integrating the entire value-chain of manufacturing and not just as aspects of production that happen within the plant. Just imagine the power, if you have visibility over suppliers, customers, distributors, warehouses, tank farms, etc. It allows one to have total control of operations and also facilitates 'what-if' scenario's to be better prepared in times of uncertainty.
Convergence of AI with everything: Basic machine learning has been seen at play in areas such as asset performance management, pattern detection, quality management. I believe, the next phase is applying AI in the context of supply-chain, operational data, design, testing, quality, planning, scheduling, cybersecurity, computing, worker safety, sustainability, etc.
On the disruption side:
Edge: De-centralised, at-source computing will see a significant offtake across the industrial space. Powerful chips will make way into next-gen edge product platforms along with modular capability to swap out intelligent algorithms based on context and situational requirements. This does not mean the end of cloud. Cloud will co-exist with edge computing. A case in point: Today's sensors are used to measure point values and report. With edge capabilities, the sensor will not only sense the point value but also compare it with set point value (SPV) and will take action if the measured value is over or below the SPV. Total improvement in productivity, comprehensive automation of the workflows.
Blockchain: As cited by one of the major automation vendors, we live in a world that is devoid of trust. Blockchain is the answer to that. Obvious application areas include digital traceability (parts, food/farm-to-fork, and luxury goods), custody transfer (hydrocarbons), logistic efficiency, goods handovers, remote services of assets, etc.
True Digital Twins: Until 2017, it was very hard for me to find a true digital twin apart from the turbine world. In 2018 - I was blown away by the number of examples I have seen in this space. From reciprocating compressors, robots, CNC machines, refinery and petrochemical twins. A 'true digital twin' is an approach that will allow customers to interact with the physical world, exchange insights with connected service providers, simulate scenarios and predict occurrences. It is not a fancy 3D model that allows you to take a 360-degree tour of the asset. Once this materialises plant managers would be able to unlock efficiencies that were previously inaccessible. I am excited for Jan 31, as the world will see a radical solution being introduced by a Japanese automation major.
Containers, microservices: As digital products emerge, industries shift from centralized to de-centralized computing infrastructures - containers and microservices will be the meat and potatoes of application deployment + management. As per Docker, "A container is a standard unit of software that packages up a code and all its dependencies so the application runs quickly and reliably from one computing environment to another." I might add infrastructure-agnostic software deployment. Edge, responsiveness, and latency will become top competitive differentiations in the future. To support these scaling applications that consume less space, less power will be the need. This is where microservices come in – It’s a wait and watch game. Like cloud and edge, we could see a co-existence of microservices and SOA.
Immersive experiences: AR, VR, MR will create rich UX, that personnel may not even need training to do a job. Onboarding process may not need group settings and it might be just imparted using a VR headset. Truly a game changer in areas such as field maintenance, product design, iterations of design, and collaboration.
Additive manufacturing (AM): Still to catch up the subtractive manufacturing world, but making progress. I first experienced AM during my Mechanical Engineering days. I printed my first part using a FDM machine back in 1999/2000. The industry has come a long way and will evolve, as promising upstarts innovate with metal-based object printing. AM is not just for the discrete world but has implications to the process industry as well. If it takes off, AM might reduce a customer/manufacturer's burden of holding multi-million/billion USD inventories. AM can help to print a required part just in time, in smaller distributed micro-factories that are closer to the customer as compared to monolithic central plant in some corner of the world.
Lastly, few words about business opportunities:
New Business Models: Product margins are failing as commoditisation hts. Still, complex engineered products enjoy healthy margins but this is not a sustainable strategy. A viable growth platform is artfully combining the worlds of products and product-associated services on the foundation of new business models. We predict the end of asset ownership within industrial markets. Customers will shed asset weights and become lighter on their balance sheets while outsourcing the performance of the asset to an OEM or a capable 3rd party solution provider.
Design Thinking: Currently, I am reading a book, which has inspired me to write about this. An aspect outlined in the book is that business plans are often built on past performance and current market conditions. This restrains the ability to truly be transformative. In today's world of dynamic change, wherein technology refresh cycles are under 4 years, we need a design thinking based approach. For tomorrow's problems – let’s not rely on age-old practices!
Value will shift from hardware to software: We can predict that monolithic, expensive computing platforms within industrial space will slowly erode and give way to modular, affordable and swappable computing platforms that have the software intelligence. This will not happen in the DCS market in 2019 but is already happening in other areas which deploy unit controllers.
Cybersecurity: This is a featured opportunity, by many. More awareness leads to investments and growth. Enough said we need action!
Sustainability and safety: What were earlier cost centres, now will be seen as profit centres. Energy conservation and aligning safety practices will help customers reduce costs and increase availability.
Fun fact: Refining industry, on an average, account for 50% of their O&M costs to energy. Imagine the savings, if we are able to save 5% of it.
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