PE and smart manufacturing: Intelligent designs

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The emergence of internet-connected manufacturing has created a new investment area that will impact adjacent sectors and even entire economies for decades to come. PE is among the early movers

 

The first two deals completed by Asia-IO Advisors say much about the scope of the investment potential of the emerging industrial IT sector known as smart manufacturing. The GP partnered with leading contract manufacturer Foxconn Technology and other investors to create Maxnerva Technology Services, a Hong Kong-based systems integration specialist. It followed up with the acquisition of Source Photonics, a hardware supplier for cloud computing companies operating in the US, China and Taiwan.

 

On one level, these investments illustrate the disruptive depth of the smart manufacturing space by touching on growth areas in both physical and systemic support industries. They also offer an example of how global giants and start-ups are proving to be compatible collaborators, moving the industry forward on multiple fronts with different risk profiles.

 

From a higher perspective, the prominent role of long-term smart manufacturing in AsiaIO’s early deal making could help graduate the industry from a science buzzword to a viable business-building investment category – as well as establishing it as a distinct private equity specialization. In earlier cycles of factory technology development, GPs pitched strategies in IT and manufacturing domains separately. Now those worlds have converged, opening a door for those able to identify synergies between the two.

 

“Now that these two areas crisscross each other, it creates a new area for growth,” says Denis Tse, managing principal at Asia-IO Advisors. “Smart manufacturing gives a competitive advantage to managers that understand both the technology and manufacturing side vis-à-vis investors that are just organized around pure technology or industrial verticals.”

 

The next big thing

 

Smart manufacturing, also referred to as “industry 4.0” and the industrial internet-of-things (IIoT), is an umbrella term for digitization of the factory floor. Essential technologies include cloud computing, artificial intelligence (AI) and IoT. It involves enhancing the efficiency of sensors, robots and other relatively recent automation advancements through online equipment management platforms that allow for a greater ability to process big data and troubleshoot operational bottlenecks.

 

In Asia, China remains unsurprisingly the center of gravity, with grand plans to take its factories online through a string of ambitious, multi-generational partnerships with Europe’s global frontrunners. Recent activity reflecting this momentum includes a $1 billion fundraise by AGIC Capital, which focuses on Asia-Europe manufacturing, and the $4.4 billion acquisition of German automation expert Kuka by China-based consumer electronics maker Midea Group.

 

“Rising labor costs and an ageing population not only in China but globally offer vast opportunities for Midea and Kuka to improve factory automation in many countries and strengthen Midea’s future manufacturing capabilities,” says Paul Fang, chairman and CEO of Midea.

 

Meanwhile, manufacturing-dependent Taiwan has prioritized smart factory policies in its various economic plans, while aiming to double the growth rate of its connected machinery uptake to 5% a year by 2023. The effort will be characterized by a focus on integrating downstream, midstream and upstream services so that they can be marketed as a comprehensive business tool.

 

“Taiwan’s role in the development of the smart manufacturing sector in Asia has been shifting from being a pure OEM/ODM [original equipment/design manufacturer] to a system integration-based role with experience and capabilities in the export of integrated services,” says Ray Han, an analyst at Taipei-based Market Intelligence & Consulting Institute.

 

The first industries to experience widespread uptake of smart manufacturing technologies are expected to involve products that demand high quality standards including automobiles as well as less expensive goods that require precision assembly such as high-end mechanical devices. The proliferation will be balanced across heavy industrial giants looking for efficiencies in high-volume operations and smaller companies seeking above-the-line gains in the vein of new services or product streams.

 

The forked nature of this projection implies a range of inroads for private equity investors. For example, in addition to pursuing more implementation support services for its existing manufacturers, Taiwan is pushing hard on the start-up end of the equation with its “Asian Silicon Valley” project. The proposed technology park in the country’s northwest will focus on IoT factory and supply chain applications.

 

Recent PE interest at the venture end of the spectrum, however, has tended to focus on other markets. Tokyo-based Sparx Asset Management is a case in point, having recently launched its first VC vehicle since being founded in 1989. The fund draws inspiration from the emerging manufacturing applications around robotics and AI, as well as Japan’s demographic drivers. Last year, it participated in a $10 million round for 3D Media, a company that allows factory robots to move independently of preconfigured patterns through advanced vision systems.

 

“US tech companies have been leading in most IT industries, but in robotics, we think Japanese companies like 3D Media have huge potential because they’re globally competitive in both software and hardware,” explains Shun Ozasa, a spokesman for Sparx. “This is important in Japan because recruitment in factories is suffering due to the population decreasing, and robots are needed to increase productivity.”

 

Taking it slowly

 

Singapore, like Taiwan, has benefited from substantial government support, particularly in the form of the “smart nation” initiative, which earmarked $13 billion in public funds last year for automation and big data-related technology development. Although similar civic modernization agendas usually become mired in municipal bureaucracies, the city-state’s top-down federal authority system has allowed it to take a leading role.

 

“Industry 4.0 is at a global tipping point, and a meaningful ecosystem has been growing in Singapore,” says Swee Yeok Chu, CEO and president at Singapore’s EDBI, an investment arm of the country’s Economic Development Board. “With Singapore’s leading manufacturing capabilities and base of high-value manufacturing activities, it is in a strong position to anchor and create smart manufacturing production and post-production activities in the region.”

 

EDBI has described the flow of smart manufacturing investment into Singapore during the past two years as reaching a “critical mass.” But its investments suggest a prudent approach, aiming to leverage growth opportunities as they gradually materialize. Chu notes that new adopters implement simple improvements like adding sensors and dashboards to better track operations, and eventually graduate to complex projects like machine learning and predictive maintenance.

 

Much of the prevailing rhetoric in this space likewise balances urgent themes of an industrial revolution with more tempered advice on cautious deployment strategies. The consensus is that smart manufacturing integration plans need to be rolled out in a series of small steps that allow business to incrementally absorb the changes and become more competent with the technology.

 

Accenture estimates that IIoT has the potential to add $14.2 trillion to the global economy by 2030, but notes that capitalizing on the opportunity may be difficult. Among the more subtle pitfalls is the failure to align the new IT with existing operational technology (OT).

 

“Companies that organize operations, planning and engineering separately find it difficult to integrate processes even if they’ve already adopted technologies that make it easier to integrate supporting IT systems,” says Peter Soh, a managing director at Accenture. “Many traditional OT systems are proprietary and closed. The way out is to develop a multispeed IT architecture that fuses the old with the new to deliver value at speeds required by the business.”

 

The core challenge of smart manufacturing, however, is simply the expense of operating a factory on the cutting edge. For GPs, the potential for costs overruns, time delays and resistance from discouraged management puts an onus on diplomacy with portfolio companies and developing a business case that allows for shared risk.

 

What to capture

 

Operationally, the success of connected sensor systems will depend on understanding that the process of data collection is not as clean as it appears. Not all of it will be reliable, and even useable information could be too much of a good thing. Excess data collection has been flagged early as one of smart manufacturing’s recurring issues, resulting in “open loop” workflows where practical outputs are insufficiently monitored.

 

Oversight in this regard will require scrutiny of what information is being collected, who’s using it and whether there is a better way of getting the desired result. Ideally, closing a data collection process loop will entail separate management for data generation, requesting the appropriate response action and confirming whether or not the response was successful.

 

“The biggest problem I see today when we talk about all these new technologies is that everybody wants to do it, but they don’t really think about what they’re really getting out of it,” says Tim Szymcek, head of lean and advanced manufacturing for New Balance in Hong Kong. “A lot of times factories just collect data and give some report to their customer to say that they’ve done it, but they didn’t get much benefit. In fact, it just took their time, so they had a negative effect.”

 

At this stage in smart manufacturing development, the industry’s stated operational expectations reflect a wide range of strategies. According to Boston Consulting Group, only 21% of manufacturers anticipate that the technology will make its biggest mark by reducing costs. This compares to 16% for improving product quality and 13% for driving innovation.

 

The difficulties around defining how these objectives should be monitored and prioritized are perhaps the clearest indicators of smart manufacturing’s immaturity as a business development agenda. “You cannot approach it with the usual ERP [enterprise resource planning] implementation mindset and lay out A-Z what is going to be good for you in industry 4.0,” says Domonkos Gaspar, digital transformation leader for Swiss industrial group Autoneum. “It’s is not a revolution, it’s an expedited evolution because you have to respect the growth curve of the organization and use a trial and error approach.”

 

From this perspective, the management of a rollout must be approached essentially as an R&D program. Trying and failing is part of the game, and not every effort will result in a return on investment. And the hardest lessons for the pioneers could be learned in the realm of data security. Industrial environments moving toward open protocols, wireless sensors and connected operators will be prone to amplified cyber-attack vulnerabilities, especially in tightly competitive markets.

 

“Companies cannot wait for the next software patch to address these issues,” says Accenture’s Soh. “This is because security solutions are no longer limited to the proprietary data of a company. They extend beyond the traditional software and encompass the hardware such as the shop floor machines and other industrial equipment.”

 

The need for such upgrades may represent an opening to private equity given the work appears to fall neatly under the traditional portfolio value-add thesis. However, smart manufacturing differs from other company expansion models in that it often requires an exhaustive overhaul of operations and management.

 

Shaw Kwei & Partners has demonstrated a successful approach to this challenge with Chinese industrial adhesive manufacturer YongLe Tape, which it bought for $66 million five years ago, turned around, and recently sold for $190 million. The GP introduced modernized ERP protocols, upgraded manufacturing equipment and refocused marketing toward more complex products. This transition amounted to a fairly thorough reboot necessitating not only a more highly trained team on the manufacturing line, but also a more sophisticated sales team.

 

“It doesn’t make sense to do smart manufacturing unless you train your employees as well,” says Kyle Shaw, founder and managing partner at ShawKwei. “It’s not just as simple as bringing in some sophisticated new equipment – you’re looking at having to make changes across the organization or the investment will underachieve its potential.”

 

People power

 

The notion upgrading workers as well as the equipment they use hints at the cultural challenges around resolving the operational and implementation aspects of a smart manufacturing rollout. Most management practices in manufacturing pre-date the technological upheavals of recent decades, which means that even the savviest of professionals tend to follow archaic, redundant procedures. As a result, investors must take a delicate approach to reconciling the old ways with the new.

 

“You need people who are set up broadly enough to be able to converse about how this new technological approach is going to fit in with the old bibles of manufacturing management,” adds Autoneum’s Gaspar. “You have to be able to convince people who are from that school that there is big added value in maybe a little less time on the shop floor and more time on the computer. That’s a human gap I’m seeing that is not getting elaborated when people talk about industry 4.0.”

 

Another cultural consideration for long-term investors is that this human gap will also manifest itself outside the factory walls. On a macro level, the transition to smart manufacturing is tipped to utterly reshape national economies and cause major workforce displacements.

 

Professional conferences on the subject have so far maintained an optimistic drumbeat of arguments that smart manufacturing will employ different people but not necessarily less people. Concerns are mounting, however, that the unskilled millions underpinning Asia’s massive manufacturing industry will be left out in the cold, putting economic pressure on the very governments currently lobbying for smarter factories.

 

As one industry professional puts it: “If there’s an operator on the line just putting two things together all day, do you really go to him and say, ‘I’m going to train you to be a robot programmer?”

 

This outlook highlights another risk factor for early adopters in the sense that governments may have to alter incentive schemes and regulations in order to negotiate politically sensitive employment issues. At the same time, the sheer magnitude of the potential social reverberations offers a reminder of the inclusively progressive nature of the opportunity set.

 

“The digital disruptors are attacking the multi-trillion dollar manufacturing industry using software, connected hardware, data and new business models to root out inefficiencies and create new profit pools,” says Steve Taub, senior director of advanced manufacturing investments for GE Ventures. “Not only is this going to generate great returns for the entrepreneurs and the investors who back them, but it will also create value for consumers who will ultimately benefit from the better, lower-cost goods that the advanced manufacturing technologies allows us to produce.”

 

SIDEBAR: Robot revolution?

 

Robots are the highest profile components of a technologically advanced factory and historically represent the manufacturing industry’s most promising – and frustrating – modernization ploy. They are fast and precise, but inherently inflexible, expensive and unable to adapt with the level of agility that most manufacturers need to meet market demands.

 

Industrial robots have been in use since the 1960s, but for most of that time, only the largest companies have had the in-house engineering resources to program and train them effectively. And even in the best of circumstances, the results have been decidedly underwhelming. It is said that industrial robots are capable of achieving only 10% of manufacturing tasks.

 

“Now, with the introduction of smart, software-driven collaborative robots, organizations can affordably begin to address that 90% gap,” says Jim Lawton, chief product and marketing officer at Rethink Robotics. “Companies have quickly realized the value of flexible automation, and the collaborative robotics industry is poised for rapid growth as a result.”

 

The US-based start-up is tackling this issue with backing from investors including Highland Capital Partners and GE Ventures. In December, Switzerland-based private equity firm Adveq led an $18 million Series E round to support ongoing work to empower collaborative robots with cloud computing and internet-of-things technologies.

 

The company’s most recent developments on this front suggest that progress improving robot capabilities will be realized through a new generation of train-by-demonstration software. Such services, for example, are expected to allow manufacturers to deploy and coordinate an entire work cell through the controller of a single robot. The goal is to facilitate first-time smart factory technology integrations by allowing for value creation in the immediate term.

 

Rethink has a substantial footprint in Asia Pacific, with an office in Taiwan as well as operational experience in China, Japan, South Korea and Australia. As such, it offers an enticing outlook on how Western leadership in automation R&D could quickly translate into a seamless smartening up of Asian factories in a more connected world.

 

“We envision a time in the future where a robot can learn from other robots through shared knowledge in the cloud,” Lawton adds. “You could have a robot in the US capturing data and understanding that if it handles a part a certain way, it improves part quality. The robot could then share that knowledge in the cloud so that robots in China could begin handling the part in a more efficient manner, as well.”