Industrial Technology - Update


Harris Williams is pleased to present our industrial technology industry update for Q1 2020. This report provides commentary and analysis on current capital market trends and dynamics within the industrial technology space.

The manufacturing industry is transforming to Industry 4.0, which means that production processes increasingly consist of smart, connected devices and machines that provide companies access to an increasing amount of data. Augmented by advances in artificial intelligence and machine learning, manufacturing processes are becoming more intelligent, solving issues without human intervention and driving an evolution in process optimization. You will find further information in our know-how section.

The year 2019 ended with positive news and less uncertainty across all asset classes and geographies. However, the business cycle is mature, and central banks in the U.S. and Europe restarted their monetary easing programs.

We hope you find this edition helpful, and we encourage you to contact us directly if you would like to discuss our perspective on current industry trends or our relevant industry experience.

Industry Events

Our team will attend the following trade fairs over the next few months. Please let us know if you will be at one of the conferences and would like to connect.

Coming Up: Trade Fairs 2020


picture1_338.pngMarch in Stuttgart, Germany: The LogiMAT is the largest annual trade fair for intralogistics solutions and process management in Europe.


picture1_339.pngFebruary in Orlando, Florida: World's largest HVACR (heating ventilation, air-conditioning and refrigeration) event.


picture1_340.pngMarch in Atlanta, Georgia: Leading trade show for supply chain, manufacturing and distribution industries.


picture1_341.png March in Las Vegas, Nevada: ISC West is the largest converged security industry trade show in the U.S.



picture1_342.pngApril in Hannover, Germany: World's leading industrial trade fair for a wide range of topics: Additive manufacturing, automation, industrial 5G, material handling, predictive maintenance, robotics, etc.


picture1_343.pngJune in Nuremburg, Germany: The Sensor + Test trade fair includes exhibitors from the entire spectrum of measuring and testing systems.


HW Deal Spotlight: teamtechnik


teamtechnik Maschinen und Anlagen GmbH (ttMA) announced the sale of a majority stake in its Polish subsidiary teamtechnik Production Technology Sp. z o.o. (ttPT) to TDJ S.A. (TDJ). ttMA is an international market leader for innovative production technology, assembly and functional test systems across the automotive, medical and energy industries. Its former Polish subsidiary ttPT focuses on next generation automotive assembly systems.

Harris Williams exclusively advised the shareholders of ttPT during the sales process.

Read the full press release here. Please contact any of the HW team members above if you would like to receive additional information on this transaction.

Industrial Technology - Update

Advancing of Mobile Robots

Automated guided vehicles (AGVs) were the original mobile robot technology, but advances in both machine vision and navigation led to autonomous mobile robots (AMRs). Equipped with machine vision technology, these mobile robots can react to environmental changes and are used to solve shortages of employees and flexibility challenges in factories and warehouses. The main challenges for AMRs today are power charging, payload and navigation. AMRs require optimized intelligent charging solutions, advanced navigation technology, and an increasing payload from applications in new industries, such as aerospace. Read more about mobile robots here.

The Biggest Challenges for Smart Factories and How to Tackle Them

picture1_344.pngEven though the industrial internet of things (IIoT) is increasingly becoming more accessible and important, c. 75% of companies fail to move into a large-scale rollout. However, this fail rate does not affect investment plans of many manufacturers. Eighty-three percent of companies plan to invest further in smart factory technologies within a time horizon of two to three years. Nonetheless, companies transforming to Industry 4.0 face challenges and are frequently uncertain about how to move forward. One of the biggest challenges is the lack of technical skills and the understanding of implementing new technology. Other challenges include data/IP privacy concerns, lack of interoperability between systems, security threats, and a growing amount and velocity of data. Read more about the biggest challenges and how to tackle them here.

Will the Smart Factory Benefit from 5G?

The next-generation wireless technology, 5G, is just being introduced, and industry participants are eagerly awaiting the rollout. According to Gartner, the global 5G market will be worth $4.2 billion by the end of 2020 as companies invest in infrastructure upgrades.

The impact on the manufacturing industry is not clear yet. Industry 4.0 requires connectivity with a stable and fast connection, e.g. to view problems in real time. 5G is expected to offer peak data rates of 10 Gbps and very low radio latencies, which support avoiding operational disruptions to enable seamless machine-type communication. Additionally, the new wireless technology could replace wired connections and has the potential to push the smart factory beyond IoT and big data toward the adoption of virtual reality and augmented reality. Read more about 5G and its impact here.

Additive Manufacturing on the Rise

The acceptance of industrial 3D printing, so-called additive manufacturing (AM), is growing across all industries. The number of manufacturing companies using 3D printing for full-scale production rather than just prototyping has increased by nearly 50% over the last year. Forty-seven percent of companies interviewed are already using the technology in production.

Eighty-five percent of manufacturers see the potential of industrial-scale additive manufacturing to increase their revenues. Other key drivers for many manufacturing companies include reduced costs and improved customer response time. However, to realize the full potential of AM and overcome system inflexibility, manufacturers need an open ecosystem. Read more here.

Industrial Technology - Update

Our know-how section presents a trending strategic concept in the industrial technology space.

Know-How: Machine Learning

picture1_345.pngMachine learning refers to an artificial intelligence (AI) application that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.

Machine learning algorithms can be, and are, used everywhere from our day-to-day lives to industrial applications across all industries. It is used to personalize advertisements, detect frauds, diagnose diseases, regulate traffic and navigate self-driving cars.

With the advancing transformation to Industry 4.0, manufacturing companies installed robotics, computers and equipment, which are connected via the internet of things (IoT). Smart devices and components produce and collect copious amounts of data, which can be analyzed by machine learning algorithms. These algorithms allow the automated optimization of specific processes.

The full potential of machine learning can only be realized when companies overcome current challenges, including understanding which processes need automation, lack of quality data, inadequate infrastructure, implementation of new machine learning methodologies in already existing methodologies and the lack of skilled resources.

Market Forecast

According to a report by Grand View Research, the global machine learning market is forecast to grow to c. $97 billion by 2025 – a CAGR of 43.8% over the forecast period from 2018 to 2025. You can find the report here. A similar report from Zion Market Research forecasts a CAGR of 44.1% from 2017 to 2024.

Machine Learning Market


Further Reading

What Is Machine Learning? – MIT Technology Review

What Kind of Problems Can Machine Learning Solve? – CFO

The Ultimate Learning Machines – The Wall Street Journal

5 Common Machine Learning Problems & How to Solve Them – ProV

Valuation Metrics Overview

Peer group trailing average LTM share price; indexed


Geopolitical Risks Faded in Q4 and Created Room for Hope

In Q4 of 2019 the global stock market recovered from geopolitical uncertainties, which had dominated the market for most of the year. According to Fidelity, almost all asset classes logged sizable absolute gains in 2019. Global equities were fueled by further monetary easing by central banks and the de-escalation of the U.S.’ trade stance with China. U.S. large-cap equities outperformed stocks from non-U.S. countries. However, Fidelity states that “the global economy remains sluggish but is showing signs that conditions are no longer deteriorating.”

According to Schroders, equities in the eurozone benefited from the better than expected economic data from Germany as well as the recent trade deal convergence between the U.S. and China. Another positive impact came from the European Central Bank (ECB) and the Federal Reserve as they restarted quantitative easing and Treasury bill purchases. Christine Lagarde took over as president of the ECB in November 2019 and subsequently urged governments to “boost public investment in order to increase domestic demand in Europe.”

Public Markets | Key Trading Statistics

Source: Capital IQ (as of Jan. 21, 2020)


Public Markets Overview

Source: Capital IQ (as of Jan. 21, 2020)


Public Comparables Detail

Source: Capital IQ (as of Jan. 21, 2020); $ in Millions, except per share amounts





Our Sector Practice & Selected Experience


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