123Fab #18

1 topic, 2 key figures, 3 startups to draw inspiration from

Green Hydrogen – Water Electrolysis for a greener future

Hydrogen (H2), alongside renewables and natural gas, could play a key role in the energy transition by fostering the decarbonization of industries, with the versatility to provide mobility, power systems, heat and industrial services. Substituting polluting fossil fuels with hydrogen — which emits water only when burned – could significantly reduce greenhouse gas emissions and stave off climate change.

Although hydrogen is a very low-carbon energy, it does not exist naturally on earth and is mainly produced from a range of more or less environmentally friendly chemical sources and processes. There are commonly three types of hydrogen: grey, blue and green.

• Grey hydrogen is produced by chemical reactions – steam methane reforming and coal gasification – and by the use of carbon-intensive fossil fuels (natural gas, oil and coal).
• Blue hydrogen is produced the same way as grey hydrogen, but the main difference is that it has a lower carbon footprint. This is because hydrogen uses carbon capture technologies that prevent the release of CO2 and allow the captured carbon to be stored and reused in industrial processes. Blue hydrogen is more expensive than grey hydrogen.
• Green hydrogen is produced by the electrolysis of water, which uses an electric current to break apart water molecules (H2O) into hydrogen (H2) and oxygen (O2). If the electrolysis is realized using renewable electricity (solar PV or offshore wind turbines), the resulting hydrogen is the cleanest variety, producing zero carbon emissions.

The global hydrogen production is dominated by grey hydrogen: according to the International Energy Agency (IEA), 96% of the hydrogen manufactured in the world is “grey”, while less than 0.1% is produced by water electrolysis. This is mainly due to the lower price of grey hydrogen production compared to blue and green hydrogen. The IEA estimates the price of grey hydrogen at around €1.50 per kilo – the main cause being the price of fossil fuels – and between €3.50 and €5 per kilo for green hydrogen. The three most critical factors for the high cost of green hydrogen are 1) the limited and costly capacity of electrolysis at the moment, 2) the high price of green electricity used in the electrolysis process and 3) the costs for safe and clean transportation.

The widespread adoption of green hydrogen remains extremely slow, but the future of clean H2 could be bright. Major players are taking action to stimulate R&D around green hydrogen production, transportation and industrial applications. The European Commission, for instance, strongly believes in the prospective use of green hydrogen to decarbonize heavy industries and transportation, as demonstrated by the adoption of the European Green Deal in January 2020 to support innovation in clean hydrogen and low-carbon resources. The Covid-19 crisis has introduced a new impetus: France and Germany plan to collaborate and invest €7bn and €9bn respectively in green hydrogen R&D projects. Large corporate companies, including Shell, Airbus and Chevron, are also seizing the opportunity to invest in clean hydrogen technologies and applications.

The market is still extremely young, and there is still room for progress. Startups are positioning themselves either in the improvement of hydrogen storage, transportation and distribution, or in the development of new applications (fuel cells for vehicles, industrial use cases), or in the development of new alternatives for H2 production and electrolysis methods (such as alkaline, Polymer electrolyte membrane (PEM) or solid oxide electrolysis)

Process mining, neo-ERPs… – How can Artificial Intelligence power the next level of enterprise process automation?

IT Enterprise process automation is not something new: it began in the 1960s with the automation of white-collar work made possible by the invention of computers. Since then, the global adoption of digital technologies has transformed business process management through the integration of ERP (Enterprise Resource Planning) and other applications, but has stagnated at the basic level of screen scraping and data collection.

Enterprise automation now refers to any technology by which a manual process or procedure is performed with minimal assistance – the goal being to optimize the level of human interaction by making machines perform the repetitive manual tasks. Automatable tasks and processes exist across all business functions (Sales, Logistics, Accounting, etc.) with different levels of complexity and power of automation. Some repetitive and rule-based tasks require only basic automation while more complex and interactive tasks require AI-powered automation.

In fact, the most advanced Robotic Process Automation (RPA) systems can only automate repetitive tasks, that account for 10% to 20% of business processes. The increasing advances of Artificial Intelligence (machine learning and deep learning systems, Natural Language Processing, image analysis and predictive analytics), Internet of Things and Blockchain could take automation to the next level by creating new possibilities and benefits for enterprise automation: a next generation of neo-ERP players is emerging, challenging traditional players.

Those challengers focus on providing three types of services:

• Detecting automatable processes with digital twins and process mining tools: companies need to understand their underlying processes in order to optimize them and find opportunities to improve efficiency. In particular, process mining tools could identify trends and patterns to analyze process optimization performances.
• Automating business processes with cognitive automation tools: every company collects a large volume of raw data that needs to be structured into actionable information to be relevant. Cognitive automation tools could bring a high level of automation with better KPIs across the different business functions.
• Integrating with workflow automation solutions, which includes all automated processes in the different business functions. Integration solutions (iPaaS or cloud-based integration softwares) are particularly interesting for companies that do not wish to build in-house tools.

Enterprise automation looks promising on paper. Yet, the transition remains bumpy as integrated automation applications are still expensive and difficult to implement  – it could take several years before complex automation tools are fully adopted. In particular, the emerging adoption of full automation in SaaS (at the expense of on-premise softwares) is questionable in terms of financial management (subscription based models) and cybersecurity. It is essential to balance the need for increased process management and the impact of full SaaS on the enterprise’s IT environment.

Nevertheless, the Covid-19 outbreak has urged corporates to adopt digital tools to enable business continuity and remote work. According to Appdynamics, 81% of IT leaders state that Covid-19 has created the greatest technology pressure their organization has ever faced. For this reason, the current situation could first trigger the adoption of detection tools (process mining and digital twins), that could lead to more automation.

2 Key Figures

255 process automation startups

in the world, according to Startup Insights

Market size expected to reach $12.6bn by 2023

According to Markets and Markets, the global digital process automation market size was valued at $6.8bn in 2018 and is expected to reach $12.6bn by 2023.

3 startups to draw inspiration from

This week, we identified three startups that we can draw inspiration from: Logpickr, Hypatos & Celigo.

Logpickr

Logpickr is a French startup that combines Process Mining with Artificial intelligence to provide smart business process analysis and optimization.

Hypatus

Hypatos is a German process automation startup that applies natural language processing and deep learning to speed up document processing for financial functions.

Celigo

Based in the US, Celigo creates an iPaaS integration platform that allows cloud-based applications to work together both for IT and business users.

123Fab #17

1 topic, 2 key figures, 3 startups to draw inspiration from

The slow adoption of robotics in Construction

Back in 1987, Japanese academics, robot manufacturers and contractors were already working on the first documented research about automated construction processes. Since then, construction robotics never stopped improving. ‘Robotics’ refers to the use of machines that have an automated component: construction robots are designed to help and assist humans in their day-to-day work on construction sites. The most common construction robots are stand-alone, fixed machines used for repetitive and precise applications (e.g. articulated arms). Then, there are collaborative robots (or cobots) that directly interact with human workers and perform a specific task – such as lifting heavy loads. A third type of robots are exoskeletons which are connected to the human body to support them in difficult tasks (e.g. for heavy-duty). Finally, the autonomous guided vehicles and autonomous mobile robots can navigate either onboard (e.g. camera or laser based) or in external environments (e.g. drones).

A good example of cobot is SAM (Semi-Automated Mason), the bricklaying robot designed by Construction Robotics. SAM works alongside the mason and assists him/her with the repetitive and arduous lifting and placing of bricks. The mason remains in charge of the setup and responsible for final quality. SAMs can lay 250 to 300 bricks per hour, improving by up to 4 times the number of bricks than a man could lay when working alone. With a retail price of $500,000, the firm that SAMs users can expect an ROI within three years, thanks to a reduction of labor costs by at least 30%, low maintenance costs and an expected lifespan of about 10 years.

Construction Robotics are not the only ones coming with an attractive value proposition for construction firms. Robotics companies and start-ups put forward financial benefits, productivity gain and safety as the main commercial arguments. Indeed, labor costs usually represent between 20% and 50% of a construction project total cost – and 38% of it could be automated according to a McKinsey study, leading to a potential cost saving of 20%.  Although the initial investment is high, robotics firms claim that in the long-term, it is more cost-effective to purchase robots: in the United States, the average robot cost (including maintenance) is 4 times lower than labor wage stated McKinsey. Moreover, robotics is a guarantee of accuracy. Its work is extremely precise and predictable, thus meeting deadlines and avoiding delay expenses is easier. Another advantage of robotics is the minimization of injuries and providing a safer workplace. For instance, autonomous vehicles can operate independently in hazardous areas.

However, robotics in construction is still not widely adopted and there is under-automated when compared to other manufacturing industries. The construction industry has been classified by McKinsey as « in middle range for automation ». There are several reasons for slow adoption rate of robotics in this industry:

• The complexity of construction sites – unique end-product, unpredictable weather –   leads to non-repetitive tasks and involving judgement
• The unpredictable and ever-changing environment: the flexibility required for construction works is for still difficult to automate. As previously said, only 38% of the time spent on unpredictable physical work in construction could be automated with current technologies compared to a 70% for predictable physical work (e.g. in automotive).
• The need for technology to improve: although there are plenty of promising innovations, improvements of the current technology are needed in the adaptability to real-time variability. Moreover, on construction sites there are hundreds of tasks and multiple phases. As there is no multitask-programmed robot, many construction firms remain reluctant to integrate robots to their regular activities.
• The significant investment costs: Investing in robotics involves high initial capital investment, including R&D. Although in the long term it is said to be beneficial, it remains an obstacle for many companies.
• Legal and safety issues: even though robots should reduce the risks on construction sites, the appropriate allocation of risk is a concern for all the construction participants. There is a need specific regulation in the use of robotics on sites. This issue is starting to be addressed (e.g. the compulsory use of Building Information Models in UK since 2019). The cyber risk also needs to be considered.
• Jobs implications: If 40% of current construction jobs would be “at high risk” of automation by the 2030s, according to a 2018 PwC study, the transition will take some time and the major challenge for workers will be to not be replaced by robots but to learn to work side by side with them. A specificity of the construction industry is the importance of craftsmanship, that adds value to projects. Replacing all human workers by robots would mean taking away the quality-assessment aspect that current robots cannot provide. Thus, collaborative robots may be the most appropriate solution as they are designed to work alongside human counterparts instead of entirely replacing them. Cobots will contribute to improve productivity by carrying out tasks that would otherwise be considered busywork or for employees.

The current labor-shortage in construction – A 2019 survey by Associated General Contractors of America and AutoDesk reported that 80% of firms find it difficult to hire labor force – will surely weight into the scale of construction robotics rise. Thanks to 5G and other technology improvements, better connectivity will make it easier for multiple robots to co-operate and better understand the environment they are operating in. Compared to other heavy industries, job automation in construction is rather low but it is poised to increase faster than them in the coming decades. According to a PwC study, in the late 2020s, job automation potential in construction is 16% versus 19% on average for all industry sectors but the automation potential for construction in the mid-2030s is forecast to be 39% versus 30% for all sectors.

2 Key Figures

77 construction robotics startups

in the world, according to a Tracxn query.

Market size expected to reach $460M by 2026

According to Verified Market Research, the global Construction Robotics market size was valued at $212 Million in 2019 and is expected to reach $460 Million by 2026.

3 startups to draw inspiration from

This week, we identified three startups that we can draw inspiration from: Construction Robotics, Kewazo and SuitX.

Construction Robotics

New-York based company, Construction Robotics is dedicated to developing affordable, leading-edge robotics and automation equipment for the construction industry.

Kewazo

Based in Munich, Kewazo develops smart robotic elevators for industrial and construction sites  with focus on scaffolding. Kewazo solutions intend to improve construction logistics via data analysis and robotics.

SuitX

The US-based startup SuitX builds a robotic exoskeleton for medical and industrial markets, designed to reduce the amount of strain on the knees and quadriceps.

123Fab #16

1 topic, 2 key figures, 3 startups to draw inspiration from

NLP and NLU : from understanding to processing natural language

The increase in smart devices usage in all areas and industries, resulting in the rise of artificial intelligence and cloud-based solutions, have driven the progress and adoption in Natural Language Processing (NLP) technologies.

Natural Language Processing is a branch of artificial intelligence that uses machine learning algorithms to interpret and use spoken and written human language. These AI algorithms are able to analyze the utterance syntax and semantics to determine the meaning of human communications, and consequently allow to provide appropriate and comprehensive answers.

Some NLP algorithms only focus on determining what is literally said, which implies converting conversational text into structured data, but others are more sophisticated and powered with Natural Language Understanding (NLU). NLU is a major sub-topic of NLP that allows computing machines to understand the human language in all its complexity: besides semantic and syntax analysis, NLU involves a pragmatic analysis that enables machines to detect intent and sentiments in human utterances and some NLU solutions integrate noise analysis to better understand the context in which the text is captured. The powerful feature of reasoning and adaptive learning developed with NLU makes it possible for machines to determine precisely what the user is trying to achieve through each request, provide a complex answer and follow-up.

For instance, if my request is “I would like to book a flight from San Francisco to Paris on December 1st, 2020.”. The program will understand that my objective is to book a plane ticket from one location to another, with 3 query conditions: place of departure, place of arrival and date. The result should be a list of flights meeting the criteria. I could narrow the search by asking “Do you know if there is any direct flight with AirFrance?” to which the program should answer: “There is one direct flight with AirFrance from San Francisco to Paris departing at 3:15 and the lowest flight fare is €576.” To conclude, NLU algorithms are able to deal with several queries at the same time, but also engage in real and complex conversational back and forth with the users (which is usually very limited with current voice assistants and chatbots).

NLP and NLU technologies are developing rapidly thanks to the increasing awareness about the advantages and benefits of human-to-machine communication and sentiment analysis in several sectors, including healthcare, industry, mobility and customer services. Yet, real-life applications remain very limited: AI algorithms are still facing difficulties in fully capturing and understanding human languages. The technology has not fully reached its expected potential, but the market is already very dense with large companies and emerging startups competing to develop the most viable and effective NLP solution.

2 Key Figures

398 NLP startups

received funding for a total amount of $3.3bn according to a Crunchbase query.

Market size expected to reach $26.4bn by 2024

According to Markets and Markets, the global Natural Language Processing market size was valued at $10.2bn in 2019 and is expected to reach $26.4bn by 2024.

3 startups to draw inspiration from

This week, we identified three startups that we can draw inspiration from: Inbenta, Agamon, Logically.

Inbenta

Inbenta is a US-based startup that provides a comprehensive automated customer service solution powered by AI, machine learning and NLP.

Agamon

Based in the US, Agamon develops an AI-powered healthcare platform that converts clinical text into structured data, by using an advanced approach to NLU.

Logically

Logically is a UK-based startup that raised £2.5M in July 2020 to develop NLP technologies to fight against misinformation from fake news to state propaganda.

123Fab #14

1 topic, 2 key figures, 3 startups to draw inspiration from

Will Covid-19 propel urban air mobility?

The 2020s are expected to be the decade of the Urban Air Mobility (UAM) revolution. Self-flying vehicles and drones hovering over cities have already been tested. A growing number of large transportation and aerospace companies – including Uber, Airbus and Hyundai – as well as venture-backed startups are racing to launch the first electric vertical take-off and landing aircraft (eVTOL). And there seems to be an emerging consensus that the electrification of aviation will be the next fundamental transportation disruption, including in urban areas. But will it actually disrupt urban mobility?

Air transport for passengers and goods will undeniably be part of the urban mobility landscape, especially in large urban areas and megacities where there is a need to reduce congestion, commute times and pollution. The first prototype flights for autonomous electric flying vehicles and drones are already underway, made possible by multiple breakthrough innovations:

• Electric propulsion is a major technology used to fly eVTOL with no aircraft noise and emissions during take-off and landing. Current aircraft prototypes are equipped with electric motors powering multiple rotor blades that generate lift.
• Most Urban Air Vehicles (UAV) are electric and battery-powered and improvements in battery and energy technologies, in particular lithium-ion batteries, have been crucial in the rise of electromobility, including air electromobility.
• Advances in hydrogen storage and fuel cells technologies, which are an alternative to battery technologies, are likely to make UAV more sustainable.
• AI technologies will facilitate traffic management systems, but mostly help make aircrafts autonomous.
• Finally, production techniques are quite similar to those of the electric automotive and aviation industries, with high quality standards and R&D to find the best technologies and materials. The materials used in the production of UAV have to be particularly lightweight and resistant, like carbon-fiber composites and superalloys.

However, these technologies are still under development. For instance, the use of electric batteries brings a new set of challenges, including uncertainty about the weight of the batteries and charging times and the imbalance of electric grids. Aircrafts’ electric rotors need a lot of energy to operate, which means that they have to be equipped with several high-energy batteries that are particularly heavy and need a couple of hours to charge.

A number of technological challenges remain, but also many regulatory and governance concerns regarding the use of flying vehicles in cities:

• Noise and turbulence in cities: rotating blades produce noise and wind nuisance during take-off and landing. Because of the noise generated, cities and populations can be against flying vehicles.
• Airspace management: the adoption of UAV will require airspace regulations to avoid accidents, infractions, drifts as well as visual pollution. Flying vehicles aim to be autonomous in the long term, but some aircrafts need pilots, which means that flying such a vehicle will require training and a flight licence.
• Safety is one of the biggest concerns for UAM. There are many aspects to consider, including the aircraft and weather conditions.
• Public acceptance is another challenge for UAM advocates: will people trust autonomous flying vehicles and are they willing to accept airspace congestion?
• Take-off and landing infrastructures are critical for success: it is not only about the vehicles themselves, but how they fit in a Smart City design.
• The business model for people transportation has to be demonstrated: should this type of mobility remain fully private or subsidized by the city? As the current prototypes can carry less than 10 people, can these small eVTOL shuttles be financially viable?

To conclude, there is still a lot of work to be done before the sky fills up with autonomous electric vehicles, especially in terms of autonomy and security. Most cases are currently focusing on autonomous delivery vehicles as a means of testing in a lower-risk environment, before launching a passenger flight. The market is still extremely young and production and exploitation costs are still very high. This type of transport will thus be intended for a social elite at first. The democratization of UAM is however not fully certain yet, as the other urban mobility means, including micro mobility, increasingly and smoothly integrate into the existing ground transportation networks. The price to be paid for each minute saved with urban mobility (still to be confirmed if there is a cumbersome take-off/landing process and if the infrastructure is insufficient) remains an unanswered question today.

2 Key Figures

110 Urban Air Mobility projects identified worldwide

almost half of which are in Europe

Market size expected to reach $15.2bn by 2030

According to Markets & Markets, the global urban air mobility market was valued at $5.3 billion in 2018 and is expected to reach $15.2 billion by 2030.

3 startups to draw inspiration from

This week, we identified three startups that we can draw inspiration from: Windcopter, NaviFly and H55.

Wingcopter

Wingcopter is a German startup creating eVTOL aircrafts dedicated to commercial and humanitarian applications.

NaviFly

Based in Ireland, NaviFly develops an air traffic control platform that organizes the drone airspace and enables their operations and logistics within urban areas.

H55

H55 is a swiss startup developing certified electric propulsion and battery solutions to make aviation clean, quiet, efficient and ultimately autonomous.

123Fab #13

1 topic, 2 key figures, 3 startups to draw inspiration from

Is Hydrogen the fuel of the future?

Electromobility is a crucial topic these days, resulting from the need to tackle climate change and Battery Electric Vehicles (BEV) are receiving a lot of attention, boosted by the rise of Tesla and Elon Musk’s popularity. But the adoption of BEV is limited by battery technologies: uncertainty about battery life and charging times, the imbalance of electric grids and the shortage of raw materials — such as lithium which is a scarce material – are challenging the rise of BEV.

Another type of Electric Vehicle is catching up, using compressed hydrogen gas to generate electricity and power electric motors, called Fuel Cell Electric Vehicles (FCEV). The key difference with Battery Electric Vehicles is that FCEV are not powered by a battery that needs to be charged from an external power source. Indeed, hydrogen vehicles can produce their own electric power by filling up the fuel cell with hydrogen. Then occurs a chemical process of reverse electrolysis: the reaction of hydrogen with oxygen produces electrical energy, water and heat – which also means that FCEV do not generate any greenhouse gas emissions. Once converted into electricity, the energy can either be used to power the vehicle or be stored and used when needed.

Hydrogen fuel cell technology brings a new perspective in the development of electromobility. While Battery Electric Vehicles take several hours to charge, hydrogen vehicles take only a few minutes, which makes them highly operational and avoids breaking users’ driving habits. However, this technology also brings a new set of challenges:

• Hydrogen is flammable and an uncontrolled hydrogen reaction with air oxygen can cause an explosion
• Hydrogen (H2) is a particularly small molecule that makes metals brittle and is therefore likely to leak from polymer tanks, which means that new composite materials have to be created to make tanks safe
• Hydrogen is a low energy fuel, meaning that a large quantity is needed to power the vehicle. For this reason, the gas has to be compressed and stored in heavy and cumbersome high-pressure tanks

Some large companies and startups are developing new materials and fuel cell technologies to make FCEV safer, but there are also some players positioning themselves on the hydrogen technologies and services market.

Even though the technologies are yet to be improved, hydrogen appears to be a groundbreaking alternative power source for vehicles, with many noticeable benefits such as reduced noise and air pollution during charging. However, the development and adoption of hydrogen vehicles remain very slow due to the lack of existing refueling infrastructure: at the end of 2019, there were only 432 hydrogen refueling stations worldwide, of which 330 were open for public vehicle filing according to Fuel Cell Works. Consequently, the FCEV demand and production remains very low and the production is not yet to be industrialized, which is why the market prices of FCEV are still very high (around $80,000 according to BMW).

Given the positive impact on the environment and the charging-time benefits compared to BEV, the hydrogen vehicle market could grow significantly in the next decades, especially for large transport systems (trucks, buses, trains and air transportation). Major companies in the automotive and transportation space, as well as hydrogen producers, have invested heavily and joined forces to develop hydrogen-related technologies and democratize hydrogen as the next generation of fuel.

2 Key Figures

70 fuel cell startups

are focusing on developing solutions for the Industry and Mobility sectors.

Market size expected to reach $42bn by 2026

According to Allied Market Research, the global hydrogen fuel cell vehicle market was valued at $652 million in 2018 and is expected to reach $42 billion by 2026.

3 startups to draw inspiration from

This week, we identified three startups that we can draw inspiration from: HyPoint, Ergosup and HySiLabs.

HyPoint

HyPoint is a US-based startup developing the next generation of zero-emission and fuel-efficient hydrogen fuel cells for the aerospace industry and urban air transportation market.

Ergosup

Based in France, Ergosup is developing an innovative process for the on-site production of high pressure hydrogen for the refueling of hydrogen-powered vehicles.

HySiLabs

HySiLabs is a French startup delivering a unique solution to facilitate hydrogen transportation, storage and delivery for the industry and mobility sectors.

123Fab #12

1 topic, 2 key figures, 3 startups to draw inspiration from

Smart Maintenance Operations: from preventive maintenance to predictive maintenance

According to a study conducted jointly by KPMG and L’Usine Nouvelle, two-thirds of the companies surveyed consider the increasing availability of equipment in factories to be a top priority over cost reduction and quality improvement. In fact, plant downtime can be very costly — ranging from $10,000 to $50,000 per minute — depending on the industry (e.g. $22,000 for the automotive industry). However, wrench time in factories has remained stable for almost a decade, demonstrating a real gap between the need for productivity and maintenance efficiency.

In the past, maintenance services were mainly corrective and preventive, meaning that equipment was repaired in the event of an immediate failure or default, or that preventive maintenance operations were scheduled based on time and usage parameters. This maintenance management was based solely on the assumption that the equipment would be degraded after a certain period of time.

Over the past two decades, the adoption of digital technologies has paved the way for smart maintenance. In particular, advances in data management have made it possible to shift from preventive to condition-based maintenance. Condition-based maintenance monitors the condition of an asset in real-time to determine when a parameter reaches an unsatisfactory level in order to plan a maintenance intervention.

More recently, the ongoing transformation of manufacturing practices, driven by machine learning, artificial intelligence and automation, has led to the rise of Smart Maintenance in factories. Several startups are now positioning themselves on this market and developing innovative solutions to optimize and facilitate maintenance operations, based on 3 main pillars:

• Asset monitoring and geolocation, which uses data analysis to provide real-time visibility on the location and condition of the materials and assets within the supply chain. As part of asset monitoring, predictive maintenance allows to accurately predict when a component will fail and determine when to repair it, reducing downtime costs. It often involves the creation of a Digital Twin, a digital replica of a physical asset, developed to replicate the original behavior model.
• Reverse engineering and 3D scanning technologies, which uses data to create 3D virtual models for Computer Aided Manufacturing and Computer Aided Design softwares. These models can be used as a complement to virtual and augmented reality to train workers to maintenance operations.
• Blue Collar Empowering technologies, such as voice recognition, instruction digitalization and project management softwares, which improve worker performance. These technologies are efficient assistants because they save maintenance workers from typing their maintenance or reading complex manuals.

In conclusion, Smart Maintenance has become crucial to maximize uptime and reduce production costs, but also to extend equipment lifetime, ensure compliance and enhance security and energy consumption. However, manufacturing companies may be a little reluctant given the significant investment involved in the transition to Smart Maintenance, especially in this time of crisis. Smart maintenance operations also addresses the critical need for energy optimisation. In France, 20% of energy savings in the industrial sector can still be easily achieved through smarter equipment. Aster Fab is committed to the energy transition in the industrial sector through the INVEEST Programme, an initiative that supports financial and industrial professionals in their transformation. Please contact us to learn more.

2 Key Figures

135 Digital Twin startups

are focusing on developing solutions for the Logistics, Supply Chain, and Maintenance sectors

Market size expected to reach $12.3bn by 2025

According to Markets & Markets, the global predictive maintenance market was valued at $4bn in 2019 and is expected to reach $12.3bn by 2025.

3 startups to draw inspiration from

This week, we identified three startups that we can draw inspiration from: Falkonry, Polyga, and Datch Systems.

Falkonry

Falkonry is a US-based startup offering a ready-to-use machine learning system that helps companies improve their industrial operations in terms of performance, throughput, quality and yield.

Polyga

Polyga is a Canadian startup developing 3D scanners and a mesh processing software to facilitate the use of scan data within Computer Aided Design and Computer Aided Manufacturing systems.

Datch Systems

Based in the UK, Datch Systems develops an intelligent voice interface for industry, enabling blue workers to use their voice to document their work.

123Fab #11

1 topic, 2 key figures, 3 startups to draw inspiration from

How can battery innovation power the rise of electromobility?

The need to tackle global warming and improve air quality has led to an exponential increase in the use of Electric Vehicles (EV). Electromobility has been a crucial topic for governments and automotive manufacturers, and regulation incentives have contributed to accelerate the transition to EV. According to Forbes, there were 7.2 million electric cars on the road worldwide in 2019, up from 17,000 in 2010. The growing EV adoption implies an increase in EV production, which translates into an increase in battery production.

However, the growing number of EV and batteries being produced brings with it a new set of challenges: uncertainty about battery range and charging times, electric grid imbalance and a shortage of raw materials, especially lithium, which is the scarce material used in battery production.

Consequently, battery innovation is crucial to disrupt electromobility and battery startups and manufacturers are working to improve the performance, durability, optimisation and recycling of batteries.

• Lithium-ion technology dominates electromobility use cases, and will dominate for at least the next 20 years, but alternatives are being developed such as sodium-ion, lithium-sulfur or lithium-air. These alternatives allow to either replace lithium, generate higher capacity and longer lifetime or create safer batteries. Innovation is also underway in the structure of batteries, from cell structure to modules and packs, allowing to save space, optimize charging time and control the temperature.
• EV Li-ion batteries need to be cooled because excessive temperatures can cause capacity degradation, thermal runaway or fire explosion. Some startups and Original Equipment Manufacturers (OEM) are focusing on developing Thermal Management Systems (TMS) to cool them.
• Startups and corporates are also testing and offering software and analytical solutions that have a signficant impact on the battery lifecycle by improving its development, optimizing its operations and solving reinsurance issues.
• Finally, startups and OEM are exploring three emerging business models:
  • Battery leasing, which is discontinued by OEM as battery prices fall;
  • Battery swapping, which is mainly used by micromobility operators;
  • Battery recycling, which allows old EV batteries to be reused for stationary storage.

In conclusion, battery innovation is evolving very rapidly, both in terms of technologies and business models and is making a major contribution to the rise of electromobility by making EV more efficient and resilient. The market is still young and needs more structure, as a large number of corporates and startups are positioning themselves on the battery value chain. In particular, OEMs have developed Open Innovation strategies through M&A or strategic investments  to acquire upstream battery competences and technologies. It is hoped that the Covid-19 pandemic will accelerate research and investment in this sector to ensure a rapid and effective transition to electric vehicles.

2 Key Figures

Battery storage startups raised $1.7bn in 2019 

According to Business Insider, battery storage startups raised $1.7bn in 2019 of which $1.4bn were raised by Li-ion battery startups.

Market size expected to reach $84bn by 2025

According to PR Newswire, the global Electric Vehicle battery market size was valued at $23bn in 2017 and is expected to reach $84bn by 2025.

3 startups to draw inspiration from

This week, we identified three startups that we can draw inspiration from: Tiamat, Feasible and Relectrify.

Tiamat

Tiamat is a French startup that designs, develops, and manufactures sodium-ion batteries for mobility and stationary storage.

Feasible

Based in the US, Feasible develops the EchoStat Platform, which delivers unique real-time insights on the battery, by using ultrasounds to detect physical properties of batteries.

Relectrify

Relectrify is an Australia-based startup making energy storage affordable by unlocking full performance from battery cells in order to increase battery cycle life.

123Fab #10

1 topic, 2 key figures, 3 startups to draw inspiration from

How to effectively manage large projects in the digital era  

Over the past two decades, companies and industries have had to deal with unprecedented and accelerating dynamics. The rise of digital technologies and the Internet has brought about radical changes for organizations, forcing them to adapt slowly and transform their working methods and tools into a new digital fluid space for communication, creation, information processing and knowledge sharing. The COVID-19 pandemic has emphasized and accelerated this digital transition.

Digital transformation has fundamentally changed the way large companies and industries manage their projects, sustain their knowledge base and deliver value to their customers. Fully embracing the integration of web-based technologies, traditional project management has been replaced by a more digital and agile generation known as project management 2.0 (PM2).

Project management 2.0 implies the adoption and use of IT tools to monitor a large array of aspects of large complex projects to increase team performance, gain a more complete view of the project and ensure its success. In particular, data management processes, integrated with project management softwares, have been a real game changer to maximize project productivity and time management.

Digital technologies have helped redefine a more efficient approach to project management, through the development of strategic software. Key softwares for PM2 are:

• Collaborative communication tools: the use of collaborative work environment software enables a more effective cross-team communication and coordination by allowing all team members to connect, interact and organize their work while tracking the project progress in real-time.
• Document management softwares, allowing team members and co-workers to share documents on the cloud to ensure that all participants have the same level of knowledge, develop collective intelligence and capitalize on their expertise.
• Computer Aided Design and Computer Aided Manufacturing, which enables virtual models to be designed, optimized and tested while sharing information with team members. This type of software improves communication throughout the modelling process, but also to creates a useful database for manufacturing.
• Automated project management softwares, powered by artificial intelligence, use all the data generated during the project to improve planning, predictive scheduling and cost management, because managing time, resources and progress is key to get the best outcomes.
• Safety and Risk Management softwares, which also use artificial intelligence to prevent and manage risks during the project.

These analytical technologies allow project managers to have time to focus on strategy optimization and project delivery rather than on project processes and coordination.

Consequently, project management softwares are becoming crucial and strategic tools for businesses and industries, which explains the increase of innovative players on the market, both in terms of technology and business models. The market is very dense due to the presence of many startups and large corporations, but emerging startups are making their mark by developing innovative technologies and striving to become more engaged with customer while optimizing the project management processes.

2 Key Figures

97 project management startups 

received early-stage in the past two years

Market size expected to reach $6.7bn by 2026

According to GlobeNewswire, Global online project management software market is expected to reach $6.68bn by 2026, due to the increasing adoption of cloud-based solutions.

3 startups to draw inspiration from

This week, we identified three startups that we can draw inspiration from: Wizzcad, Sharktower AI and Sitetracker.

Wizzcad

Wizzcad is a French startup providing a BIM (Building Information Modeling) based SaaS platform for digital transformation of construction projects, from design to operations and maintenance.

Sharktower AI

Sharktower AI is a UK-based startup developing a data and AI software to transform how businesses deliver change by providing portfolio insights visualization, predictive analytics and decision-making without bias.

Sitetracker

Sitetracker is a US startup which raised $10 million to develop a cloud-based project management platform that powers successful deployment of critical infrastructure.