Important Things Industrial IoT Report 2021
The silver linings are everywhere. Is this the end of the assembly line as we know it? We stayed home, we got bored, we shopped online. The green revolution? It's a marathon, not a sprint.
The silver linings are everywhere. If you look for them. Reflecting on industrial digitization in 2021 is really an exercise in assessing the ongoing impact of Covid-19 on the global economy. The digital mandate is not new. If you have followed our musings in the past, you know it’s what we eat and breathe daily. What fascinates us right now is the role of digital technology in industry’s response to the pandemic and resulting economic rollercoaster. It is safe to say none of the spaces we track are immune to the direct and indirect consequences of the global health crisis. The pandemic is giving all industries and companies (big and small, incumbent and emerging) the unexpected opportunity to rethink critical elements such as supply chain, manufacturing and distribution alongside the adoption of scalable and robust automation and analytics. Yes, we said opportunity. Our glass is always half full! Our deep dive into the world of robotics illustrates this well in the context of manufacturing and warehouse environments that are undergoing rapid transformation, particularly with the events of last year accelerating a boom in eCommerce. You may have noticed 2020 also saw a new wave of bull market activity. Investors were buoyed by fiscal and monetary stimulus and globally shifted their focus towards ‘digitally accelerated’ segments of public and private markets. M&A activity soared and SPACs rose from dormant slumber to quickly outpace IPOs in 2021 and emerged as the ‘weapon of choice’ for technology companies with public listing aspirations.
A number of these SPACs are targeting companies in sustainability (e.g. EV charging, clean energy technology). This space is now the place to be thanks in part to the election of the Biden administration in late 2020. Global renewable electricity installations hit a record level in 2020 and will do it again this year too. There is also a surge in demand for software and AI to increase efficiency and reduce costs across the broader energy space. The record-low demand for traditional fossil fuels in early-to-mid 2020 helped make that happen. We regularly comment on the growth of key IIoT metrics since we created McRock in 2010. Never have we seen a transformation like we did last year. We can no longer adequately measure the Industrial Internet of Things in terms of metrics like sensor deployments. Segments such as remote monitoring for predictive maintenance, digital twins for supply chain visibility and analytics, and robotics for warehousing are now being steered in part by supply disruptions, talent shortages and fears of subsequent waves. Has it been challenging? Of course. But every meaningful conversation about business continuity and operational efficiency for industrial companies now includes discussions around the potential for digital technology and automation. We’d say that’s a pretty significant silver lining.
Is this the end of the assembly line as we know it?
HOW A GLOBAL PANDEMIC ACCELERATED OUR NEED FOR ADAPTABLE INDUSTRIAL AUTOMATION. Are you old enough to remember the early 1980s? When the ill-informed masses thought robots would take over the world? Good thing the automotive manufacturing sector looked past the hysteria and fully embraced the technology we now accept as a necessary component of modern manufacturing. Kuka, Fanuc and Yaskawa were among the first in line to adopt the technology that would catapult them to behemoth status. They saw the potential in the early generation robots to fulfil routine and repetitive tasks.
They were automatically controlled, free functioning on three axes and reprogrammable. It wasn’t all sunshine and daisies, however. The machines had minimal sensory abilities and thus lacked the 'intelligence' required for autonomous activities or to safely collaborate with humans. Thankfully the engineers did what they always do; they continued to toil away at the technology, bringing new generations of robots to market that would meet ever-changing needs.
What are the robots doing today? Since pursuing human domination clearly wasn’t in the cards.
Trends in automation over the past 10 years have largely focused on creating safe (uncaged) and truly responsive work with humans. (See, naysayers? It’s all good!) Those innovations include LiDAR (light detection and ranging) and computer vision assisted-mobility and guidance, with superior technical specifications (ISO 10218 and ISO / TS 15066). The market for industrial robotics has also increased by double digits since 2012 with--guess who?--the global automotive sector leading the way. They are the largest spenders in the space since 2010 with 126,000 robots installed. That’s about 40 percent of industrial robots installed by car makers and their suppliers.
Let’s talk about Covid-19. It’s impossible to talk about the state of automation without it. The global pandemic and economic downturn affected the vast majority of industrial sectors, even the forward-thinking innovators. Most segments of the robotics market faltered in 2020 with growing backlogs by robotics purchasers, including auto makers. People stayed home, stopped buying cars, and the automotive manufacturers suffered. Cause and effect in action. Covid-19 will likely go down as one of the worst things to happen to the human race in 100s of years...but there is a silver lining! Analysts universally agree that the same pandemic and economic slowdown that brought the world to its knees has now created conditions for exponential growth and that is what we are seeing today. Social distancing rules for manufacturing installations, lower reliance on human labor and the shift towards less physical infrastructure are changing the game. And once again, robotic technology is considered the go-to solution.
Orders for robotics in the latter half of 2020 rebounded from the short-term crisis with 11 percent growth in the automated guided vehicle (AGV) segment and 45 percent growth for autonomous mobile robots (AMRs). What’s so special about those particular technologies? AGVs perform material handling tasks automatically without human intervention, but are limited to navigation using physical infrastructure and lag behind the more advanced AMRs. Those systems tend to use a mix of computer vision and LiDAR to sense the physical environment, meaning they can navigate without the need for external markers or infrastructure. What does that have to do with creating safer conditions for humans? Mobile robots and collaborative robots are accelerating the resumption of production lines, in part because they can effectively complete traditional worker tasks–autonomously transporting materials between different stations to avoid physical contact and reducing the density of factory workers. When aligned with remote human technical support and remote human monitoring for predictive maintenance, these technologies will be the key to a safer, more productive and physically distanced manufacturing processes in the post-pandemic world.
'(In the current environment, AMRs) allow the workforce to efficiently and safely focus on the tasks which are uniquely suited to humans, and they’re often higher-value tasks.'
- Matt Rendall, Clearpath Robotics
The proof is in the pudding. There is still a growing demand for both AGV and AMR technology, but growth capital globally has been directed primarily towards AMR development since 2010--approximately US$ 7.1B.
We’re not in Kansas anymore Dorothy. There is no return to 'normal'. It looks like these post-pandemic adjustments to manufacturing and safety protocols are here to stay. It is easy to make the case for more mobile manufacturing to extend beyond the pandemic. Manufacturers are decentralizing the ‘straight’ conveyor-based assembly line as the fundamental area of work in their facilities. This creates savings in fixed infrastructure costs and efficiencies from more flexible production.
AMRs do not require any fixed infrastructure. Sounds too good to be true? Everything about them–from the machines themselves to their charging points–is moveable. They are also getting faster and bigger. Some have payloads approaching 3 tons and may be modular with robotic arm attachments. The key selling feature however, is that AMRs improve efficiency and accuracy. On a per-unit basis AMRs can contribute to a 90 percent reduction in costs when compared to manual handling, and AGVs can realize a 33 percent cut. Together that is a drop of 80 percent in forklift operating costs and 50 percent of conveyor costs. That is nothing to sneeze at. Why would we even want to go back to normal when the new normal is a significant lift in productivity, safety and efficiency?
Should manufacturers be afraid of a sizable capital investment this new tech requires? We don’t think so.
Many companies are developing new paths to market and funding models to address the varied production methods required to build and deploy new technology. Think software as a service (SaaS) or greenfield installations. When manufacturers introduce new products there is also a change in the production processes required to make them. Look at electric cars, for example. No need for a conventional engine, but the battery production has become much more intensive. Industrial engineers have the opportunity to rethink the entire manufacturing operation. Mobile inspections, gluing instead of welding...these changes have the potential to create catalytic adoption of emerging robotics.
Financial Impact of AMR Systems
Source: Clearpath Robotics
Where will tech be testing the waters for long-term growth? The robotics providers that emerged from the pandemic have good reason to celebrate--the future is bright. But you won’t catch them sitting around basking in the glow of victory. The smart companies are already rethinking what their customers will want and need next. Material handling is poised to become the platform where the predicted shift to autonomous transportation initially plays out.
Adoption of Automation Innovations
2022 to 2025 will be critical years for 'autonomous' industrial automation. Source: Deloitte – Automation Innovation Survey Results
Have we future-proofed manufacturing with industrial automation? It’s true, improvements in robotic technology helped industrial manufacturers around the globe emerge from the most recent economic crisis and prepare for future challenges, but that’s not where it started. The pivot to industrial autonomy started decades ago. Covid-19 just helped accelerate the transition at a blinding pace.
Shift in Robotic Operator Concerns
Some may say the robotics industry was one of the lucky ones to emerge from the last two years with so much growth and opportunity ahead, but what is it they say about luck? It’s what happens when preparation meets opportunity! We’re looking forward to seeing what’s next for an industry that’s making manufacturing and materials handling better, faster and safer for the world it serves.
We stayed home, we got bored, we shopped online.
MEGA-RETAILERS LEAD THE WAY IN AUTOMATING DISTRIBUTION LOGISTICS. We can’t blame Covid-19 for everything. We were shopping online well before the global pandemic brought the world to its knees. But the trend that started a couple of decades ago experienced a surge--nay, a tsunami--as nations issued stay-at-home orders and in-person shopping came to a near standstill. That massive spike in eCommerce activity has fueled another trend that was also underway: automation in the global logistics space. Warehouses that support online orders and store replenishment are accelerating their efforts to deploy large quantities of robots to meet the swell in demand. Sales grew more than US$260 billion in the US in 2020 alone. Mega-online retailers such as Chinese internet giant JD.com, Ocado and Amazon are already making huge investments to meet the challenge: storage and retrieval systems, picking systems, sortation systems, conveyors, and palletizing systems to data capture devices, software, and AMRs.
US growth in eCommerce sales; yes, that's a substantial spike. Comparing growth: US ecommerce vs. total retail* sales Year-over-year growth, 2010-2020
*Total retail figures exclude sales of items not normally purchased online such as spending at restaurants, bars, automobile dealers, gas stations and fuel dealers. Source: Digital Commerce 360 analysis of U.S. Department of Commerce data Updated January 2021
eCommerce fulfillment was already a giant, Covid just sped things up. Evolving and complex supply chain rules alongside social distancing requirements for workers have compounded the turmoil for warehouse operators. The push to automate started before the pandemic and was largely driven by constraints in the labor market and the need for more predictability and less variability. Warehouse employment has tripled since 2000 even as distributors invested heavily in robotic deployment. It may seem like a paradox, but robots are an incredibly effective tool for handling repetitive and ergonomically challenging tasks, which in turn, allows employees to focus on more complex, higher-value initiatives. Warehouse automation is not a new idea. Conveyors, sortation systems and AGVs have long been a staple along with other systems.
The past five years have seen a burst in related areas: robotic picking, for example, to support case-level mixed pallet configurations for omni-channel replenishment, as well as AMRs, goodsto-person (G2P) picking technology, highdensity shuttles, and automated storage and retrieval systems (AS/RS). These technologies share an allimportant core of autonomy. The newest generation of robotic systems can adapt to dynamic industrial environments and accommodate unpredictable situations, such as volume surges and packages of variable types, shapes and sizes, while still working with established warehouse management and execution systems (WMS, WES).
Have you ever wondered who packed your order? Hint: it may be a robot.
Piece picking is a critical application of robotic fulfilment. Individual items of an order are picked and then placed in a box before shipping. It is labor-intensive and therefore an especially important feature of automation systems in pandemic times. Think pharmacies and groceries, but also online retail. Order picking comprises as much as 55 percent of a warehouse or distribution center’s total operating expenses, so accuracy and efficiency are essential. Robotic arms used for these functions are typically stationary with limited range (one to two meters) but have a mounted computer vision system. Providers of these systems contend that various iterations of robotic arms have been around for up to 30 years; they are highly reliable with options between collaborative and more basic robots. The focus has recently shifted away from the design of the arm into the AI and computer visioning system in order to handle the unique nature of each pick. For example, there may be 25 items in a bin, all lying at different angles and in slightly different locations, so the robot arm needs to recalibrate for each pick. Given that there may be 100,000 products over the course of a year, the vision and AI of the overall system needs to be extremely robust in the event of occasional failures.
Pandemic woes: forget toilet paper hoarding, what about the overworked, understaffed and running-at-warp-speed warehouse? The critical success factor for warehouse automation ultimately lies in its ability to scale up in the face of accelerated online retail growth. Effectively automating these simple tasks as volumes scale up will reap incredible benefits by eliminating friction and streamlining operations. The latest efforts in automation technology are focused on applying robotics to leaner inventories, smaller and more
eCommerce activity is already ahead by five years in the wake of the pandemic.
local fulfillment centers and opportunities to change the flow of distribution. eCommerce activity is already ahead by five years in the wake of the pandemic, now warehouse operators are being forced to think five years ahead to avoid stress on their operations.
A ROBOT FOR EVERYONE? NOT QUITE.
Are there benefits to automating distribution? Yes. Is it the right solution for all businesses with online orders to fulfill? Not even close.
Operators often think of problem solving in terms of delivering to service level agreements (SLAs) with customers. Robotics are enticing but there are limits to what the technology can do in commercial settings. Challenges around mass adoption include the interoperability of multiple robot platforms from a variety of vendors, complexity with warehouse management and control systems. There are Capex versus Opex
considerations. Finding SIs to integrate smaller robotic systems. And then there is the issue of long-term maintenance. See? Not so easy. We understand the appeal for all businesses, but only organizations with significant--think massive--warehousing and product volumes can make the ROI-based business case to adopt AI-embedded robotic systems.
Still interested? Consider the following: How long does it take to charge the robots? How will the associated downtime--and cost--be handled? How many multiple-point application robotic systems are needed to replace each person to ensure 100 percent uptime? What are the actual costs of maintenance? Remember to calculate on-site service engineers and long-term service contracts. What about Robots-as-a-Service? What is required to reconfigure the robots to address volume volatility and other business changes? Have paths been optimized to minimize travel? This is a common post implementation challenge with robotic systems when addressing changes and re-slotting SKUs. And what about the humans? A partially automated environment still needs people to keep things running. That means measuring and managing labor metrics, and managing and alerting labor to step in on occasion during operations. Without that, the robots will not live up to their potential.
The investment goes beyond the robots themselves. The robotic solutions are often based on sophisticated vision systems, which in turn require (at a minimum) very good lighting and color-coded racks, bin locations, and assembly lines. The advanced algorithms needed for robotic functioning are compute intensive, which may also
require the purchase of expensive edge processing systems, powerful smart batteries, fast charging technology and automatic docking capabilities. Pretty sure those all come at an additional cost.
Top 3 challenges of automating with robotics. 1. Cost of robots 2. Lack of homogeneous programming platforms/interfaces 3. Lack of integrators working across OEMs/geographies/industries
Online shopping and the need for automated distribution isn’t going anywhere, so now what?
It appears that micro-fulfilment centres, automated storage and retrieval systems and dark warehouses will be the way of the future. At least as long as the pandemic continues to impact eCommerce, logistics, and retail operations. And most likely even after we reach the elusive “post-pandemic” phase.
from US$4 billion at the start of 2020 to more than US$22 billion within the next few years. A Deloitte poll of warehousing decision makers in 2020 also reveals 69 percent are looking to implement substantial digital supply chain features. They clearly see potential in robotcentric systems to reduce errors and improve cycle times, and so much more.
Automation will be a table stake for future eCommerce operations with substantial distribution needs. Warehouse and logistics robotics spending is expected to catapult
Hats off to the warehouse robotics systems and the people who run them. It can’t be easy to keep up with on-demand delivery expectations. Same-day free delivery? Yes, please!
The green revolution? It's a marathon, not a sprint.
AUTOMATION AND DIGITAL TECHNOLOGIES WILL ENSURE IT HAS LEGS FOR THE LONG RUN. Did any sectors come out of the pandemic unscathed? It has definitely been a tumultuous time for the global energy industry. Demand for fossil fuels temporarily hit an all-time low, while global renewable electricity installation hit an all-time high. It would be premature to say our reliance on fossil fuels is a thing of the past, but the positive movement in “green” energy is worth celebrating. Look at some of the other indicators: GDP recovery was fueled--pardon the pun--in part by record-shattering stimulus policies that helped drive green energy initiatives and adoption. Close to 90 percent of new electricity generation capacity in 2020 came from
renewable sources with just 10 percent powered by gas and coal. Investors increasingly see the appeal in renewable energy initiatives, despite those who continue to deny climate change (bless their hearts). There is also growing consensus that cutting carbon emissions requires all hands-on deck. The stock market agrees. Shares in renewable energy equipment makers--particularly in the solar space--and project developers have outperformed most major stock market indices, and the value of shares in solar companies has more than doubled since December 2019.
This trend puts green electricity on track to become the largest power source in 2025, dethroning coal after 50 years of domination.
Low-carbon sources extend their lead in the power mix. Global generation shares from coal and low-carbon sources, 1971-2020 40%
Low-carbon Coal Nuclear Solar PV
Wind 20% Other Renewables
For the first time in 50 years, low carbon technologies overtook coal as the leading source of electricity in 2019, and they are moving ahead in 2020. Source: International Energy Agency (iea)
Let’s not put a crown on green energy just yet. In order for it to succeed as a long-term solution to the global climate crisis, it needs to keep pace with surges and fluctuations in demand. That’s not happening. Yet. Market analysts believe that the key to sustained profitability and viability of renewable energy technology lies in those businesses adopting robotics and analytics platforms. Can it be done? It must be done. But it won’t be easy. The energy sector has high barriers to entry. It is a mature, difficult market to penetrate, and also notoriously slow to embrace innovation. But there’s hope!
Building wind turbines is just the start. Maintaining them is a whole other thing.
Wind may be the new darling of the renewable energy sector. All signs are pointing to a surge in the offshore wind industry. (Another pun. Couldn’t resist.) The conditions are perfect for the investment required to make it a major source of electricity in the US: Democrats in the White House, Congress and Senate, and a large percentage of the population living on the coasts. It’s already happening. New York State announced two offshore wind projects in 2021 to be led by Equinor and BP. The $900B COVID relief bill (alongside a $1.4T federal spending package) also included a one-year extension to the wind production tax credit (PTC) as well as a new 30-percent investment tax credit for new offshore wind projects built through 2025. The PTC is
set to expire at the beginning of 2022 but is expected to receive political support for extension or re-creation. What’s the catch? The upfront costs for turbine, foundation and transmission assets can be substantial even when they are expected. The challenge comes from the services and technology providers, particularly in the operations and maintenance segments, that are required to support them. Aging wind fleets are inevitably challenged by increasing and unpredictable O&M costs. It would be one thing if these costs could be calculated and anticipated, but there is nothing standard about them. They typically vary by geography, turbine vintage and OEM makers.
'Even if the number of trained technicians doubles in the next year, (wind farm owners) will struggle to keep up with the maintenance required.' - Danny Ellis. CEO Skyspecs
Wind assets also frequently change hands between financial investors. With each change, there is due diligence to assess existing wind turbine portfolios and investment into new projects based on the overall “health” of the wind farm. Companies like SkySpecs--a global leader in fully automated blade inspections and asset management for wind turbines--play a critical role in this environment. They recognize the need to increase digitization and automation for O&M, predictive maintenance and data-driven decisions in order for the sector to succeed. Wind energy is already listed as one of the fastest growing job creation markets, but without that focus on maintaining operability of the turbines, the sector won’t ever achieve long-term sustainability.
How do they do it? They take a holistic approach to evaluating data across all assets in multiple locations. They collect data points for an entire fleet, rather than in single turbines, in order to apply insights at scale. If a component of a turbine breaks down, for example, maintenance workers can pre-emptively examine similar components across the fleet rather than waiting for another failure to occur. There is an important human component to this equation. Operators help guide the systems that learn from all the data and provide better analysis to identify patterns. The robotics, software and internal solutions support the entire renewable energy operation. Together they work towards a common goal of predictive maintenance: digitized repair planning workflows and analytics dashboards that help operators anticipate damage before it happens, project repair costs and calculate ROI.
Is it fair to say the future is bright for emerging technologies in renewable energy? The industry is adapting to rapid changes in US energy policy: the pause and review of oil and gas drilling on federal land, the elimination of fossil fuel subsidies and the transformation of the government’s fleet of cars and trucks into electric vehicles, to name just a few. There is incredible potential to leverage powerful data-driven solutions to increase productivity, identify cost savings, and generate better, faster decisions. These trends are placing emerging technology companies at the forefront of innovation in the global energy sector.
Is there room for artificial intelligence in this sector, too? Several global renewable energy companies looked to AI data platforms and technology providers in 2020 to help lower operational costs. ThoughtTrace is one such AI-driven contract solutions provider working with subject matter experts across industries to build models that both understand contracts and display critical information in an actionable format. Machine learning is both supervised and unsupervised to identify unique items and outliers in the languages and terms of contracts. Information is extracted from the language, then the contracts are analyzed for metrics and integration with ERP, CRM, and other systems to provide performance analysis. BI analytics and display offer clarity without the use of large legal and functional teams.
'An end user can go in and ask very complex domain-specific questions and get answers in seconds. It takes things that would have taken weeks or months to do and compresses them down into hours, minutes, or less.' - Nick Vandivere, ThoughtTrace
Using innovation to power insights: cut operating costs through digitalization. Identify key provisions in wind & solar agreements without tedious manual review: Curtailment Rights
Operations and Maintenance Requirements
450+ Others (out-of-the-box)
Credit Support Source: ThoughtTrace
The company serves multiple verticals including the broader energy space--a sector that was among the first to adopt the technology. It has found success by applying AI to automatically analyze elements such as purchase options, production guarantees, hidden obligations and risks in agreements. Its pioneering document understanding solution is the only integrated document management & contract analytics solution trained to work in the renewable energy sector. What else can AI do? AI and NLP will play an integral role in expanding the capacity of renewable sources to generate electricity by providing clarity around legal elements at stages such as site evaluation, development planning, and after. This is good news for financial investors looking to quickly build portfolio positions; the time required for due diligence is accelerated in areas such as the analysis of key provisions and the comparison of precedents to support valuation.
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