Toshiba controlled 17.6% of the global market for NAND memory in 2018, but its share for solid state drives was under 10%, as indicated by IHS Markit. The company hopes to catch up with opponents like Samsung Electronics, which enjoys a share of more than 35% in both. The global market for solid state drives totals around $30 billion. Inspite of flagging demand from data center servers, the market is predicted to enhance over the long term with the rise of artificial intelligence and 5G connections.

 

Toshiba Memory was spun off from the Toshiba group in June 2018 and is owned by a coalition that includes Bain Capital. It aspires to carryout a primary public offering by the end of the fiscal year in March. The holding company logged a net loss of 95.2 billion yen ($896 million) for the April-June quarter.

 

'Solid state drives face less volatility in demand than NAND,' which is a commodity product, one analyst said. Stronger solid state drive operations inclined will help Toshiba Memory stabilize its gains. Lite-On's joint solid state drive venture with China's state-run Tsinghua Unigroup will not be part of the acquisition.

 

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By just establishing a framework to measure capacity, the ministry strives to help develop a market for used electric vehicles and encourage battery reuse. The draft guidelines will be revealed as soon as September and may be finalized within the year.

 

Automakers are believed to respond positively and will be asked to introduce the gauge in future models. The gauge will reveal charge capacity relative to when the vehicle was purchased. Nissan Motor's Leaf already offers a battery health indicator, but not all electric vehicles do.

 

The ministry is envisioned to settle on a gauge design for automakers to adopt: either indicating the drop in capacity on a scale as with the Leaf, or showing the current full-charge range relative to the vehicle's initial range. Electric vehicles, which are predicted to come into wide use, require servicing when battery capacity declines.

 

Nissan has revealed an initiative in which a subsidiary collects old Leaf batteries and refurbishes them for reuse in other electric vehicles or elsewhere. Knowing a battery's charge capacity will aid in determining an electric vehicle's value in the used-car market or the battery's value to the recycling industry.

 

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The main attraction of neural networks is their massive interconnections among processors, comparable to the complex interconnections among neurons in the brain. This lets them perform numerous operations all at one time, like the human brain does when looking at faces or listening to speech, making them more efficient for facial and voice recognition than traditional electronic computers that execute one instruction at a time.

 

The latest electronic neural networks have reached eight million neurons, but their future use in artificial intelligence may be limited by their high power usage and limited parallelism in connections. Optical connections through lenses are inherently parallel. The lens in your eye simultaneously focuses light from across your field of view onto the retina in the back of your eye, where a wide range of light-detecting nerve cells detects the light. Each cell then relays the signal it receives to neurons in the brain that process the visual signals to show us an image.

 

Glass lenses process optical signals by focusing light, which performs an elaborate mathematical operation called a Fourier transform that preserves the information in the first scene but rearranges is completely. One use of Fourier transforms is converting time variations in signal intensity into a plot of the frequencies present in the signal. The military used this trick in the 1950s to convert raw radar return signals recorded by an aircraft in flight into a three-dimensional image of the landscape viewed by the plane. Today that conversion is done electronically, but the vacuum-tube computers of the 1950s were not up to the task.

 

Development of neural networks for artificial intelligence started with electronics, but their AI applications have been limited by their slow processing and need for extensive computing resources. Some researchers have built hybrid neural networks, in which optics perform simple linear operations, but electronics perform more complex nonlinear calculations. Now two groups have demonstrated simple all-optical neural networks that do all processing with light.

 

In May, Wolfram Pernice of the Institute of Physics at the University of Münster in Germany and colleagues reported testing an all-optical 'neuron' where signals change target materials between liquid and solid states, an effect that has been used for optical data storage. They demonstrated nonlinear processing, and produced output pulses like those from organic neurons. They then produced an integrated photonic circuit that incorporated four optical neurons operating at different wavelengths, each of which connected to 15 optical synapses. The photonic circuit contained over 140 components and could recognize simple optical patterns. The group wrote that their device is scalable, and that the technology promises 'access to the high speed and high bandwidth inherent to optical systems, thus enabling the direct processing of optical telecommunication and visual data.” 

 

Now a team at the Hong Kong University of Science and Technology reports in Optica that they have made an all-optical neural network based on a different process, electromagnetically induced transparency, in which incident light affects how atoms shift between quantum-mechanical energy levels. The process is nonlinear and can be triggered by very weak light signals, says Shengwang Du, a physics professor and coauthor of the paper.

 

In their demo, they illuminated rubidium-85 atoms cooled by lasers to about 10 microKelvin (10 microdegrees above absolute zero). Despite the fact that the technique may seem unusually complex, Du said the system was the most accessible one in the lab that could produce the desired effects. 'As a pure quantum atomic system [it] is ideal for this proof-of-principle experiment,' he says.

 

Next, they plan to scale-up the demonstration using a hot atomic vapor center, which is low-cost, does not require time-consuming preparation of cold atoms, and can be integrated with photonic chips. Du says the major issues are reducing cost of the nonlinear processing medium and increasing the scale of the all-optical neural network for more complex tasks.

 

'Their demonstration seems valid,' says Volker Sorger, an electrical engineer at George Washington University in Washington who was not involved in either demonstration. He says the all-optical approach is interesting because it offers very high parallelism, but the update rate is limited to about 100 hertz because of the liquid crystals used in their test, and he is not totally convinced their approach can be scaled error-free.

 

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The automation industry has been working for at least two decades to simplify the code-writing process, first by setting standards for programming languages and methods, and then developing specifications for creating basic function block libraries. But implementing these strategies to a certain machine still requires a great deal of engineering expertise and customization.

 

While today’s customers demand ever-greater degrees of customization and flexibility in new equipment, OEMs and end-users alike find themselves hindered by the lean operating principles that have slashed the number of in-house engineers. The problem is how to develop and update the software code that controls electromechanical systems without major investments in software development. To address this challenge, Mitsubishi Electric has introduced a controls software platform, named iQ Monozukuri, after the Japanese word for manufacturing, that aims to simplify the design, commissioning and maintenance of machinery. First introduced for packaging machines, the platform’s latest iteration will be focused on converting equipment.

 

iQ Monozukuri Packaging, which is available for a 60-day trial, combines a comprehensive library of packaging-specific function blocks, written and verified by Mitsubishi engineers, with sample programs and HMI screens for specific applications. The iQ Monozukuri platform is designed to meet the requirements of customers who want to change package sizes, alter product form factors and do it all in minutes rather than hours or days. It’s optimized for small- and medium-sized machines.

 

“With Mitsubishi’s expertise in many different industries, we’ve been able to develop a set of helpful tools that will dramatically reduce the amount of engineering time needed to develop machine controls,” explains Elaine Wang, senior product marketing engineer. “The platform allows packaging OEMs to easily create projects based on cam profile function blocks, software templates and sample graphical operator terminal (GOT) screens. This modular approach,” she says, “minimizes the amount of software that an OEM or end-user needs to code.”

 

Rather than writing or customizing function blocks, OEM engineers just need to enter parameters on a screen. The packaging function block library includes cam auto-generation, mark compensation and alignment conveyor. Creating cam profiles requires minimal cam knowledge and no cam calculations. Cams are auto-generated for rotary cutter, flying shear, box motion, long dwell times and mark detection applications.

 

“Since different types of packaging machines can share a single programming template,” Wang adds, “OEMs can adapt these reusable and scalable sample programs to different types of machines much more quickly than if they were developing their own code from scratch.”

 

The iQ Monozukuri portfolio of tools also addresses the needs of engineers who must incorporate further disciplines, such as motion and visualization, to complete their machines. These disciplines in general require learning yet another semi-complementary programming language. Simple motion modules, for illustration, make it possible to boost production throughput through faster processing. These built-in modules, which are available for both iQ-R and iQ-F motion modules, enable highly synchronized motion control for more accurate and consistent operations.

 

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The technology allows more connections all at one time and access to a broader range of radio frequencies, which enables faster data transmission. Mesh networks, groups of small access points that relay signals and increase coverage, are the key to the improved technology, according to Qualcomm president Cristiano Amon. His company is trying to broaden its customer list at a time when the electronics industry is arguing that there will be an explosion of connected devices on new 5G cellular networks.

 

To underscore its point, the chipmaker notes that the number of connected devices per household has doubled every two years since 2012 and will average 24 by 2020. On top of it, there will be four billion connected devices in the workplace by 2022. Phone service providers need to embrace the transition if Wi-Fi is to continue as the home and office technology that supports cellular by handling traffic indoors.

 

They will also need to shift from providing their customers with only basic modems to investing more in that technology, Mr Amon said. 'We expect to see a change in the carrier view to Wi-Fi first,' he said on Tuesday an event in San Francisco. If service providers do not offer the latest gear to their subscribers, major cloud companies such as Amazon.com Inc will step in, offering products to users and taking advantage of their positions as managers of the connected devices and the flood of data that they create, Mr Amon said. Qualcomm's Atheros division competes with Broadcom Inc to be the major supplier of chips that drive Wi-Fi access points.

 

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A Call for Responsibility

 

With consumers having more and more insight into product development, it is no real shock that there is a growing focus and desire for sustainability. In the coming year, hardware developers will start to see an even greater desire for responsible labor practices, design for product end-of-life, sustainable material use, and transparency throughout their supply chain.

 

Google is already making a shift into sustainability by aiming to have all hardware products include recycled materials by 2022. Between 2017 and 2018, the company also reported that shipping emissions were cut by 40%. Adidas is also focusing significantly on sustainability during production. Their upcoming product, called FutureCraft.Loop, is a 100% recyclable shoe that is designed to be returned to Adidas, melted down, and fully reused to make a new pair of shoes.

 

As 2020 speedily approaches, product developers will likely start to ask questions about product end-of-life and recyclability, particularly around material sourcing.

 

Shifting to Agile, Global Product Development

 

Growing tensions in the global trade war have introduced important new barriers for product developers to overcome in order to procure manufactured parts for prototyping or production. Agility has become an important piece of the puzzle as teams try to figure out ways to mitigate risks involved with international logistics. Data from the 2019 Stage of Hardware report shows that 66% of respondents were forced to change business operations deu to tariffs on global trade.

 

It's probably that hardware developers will start to implement more in-depth “tariff engineering” strategies over the next year and avoid increasing costs. Tariff engineering isn’t new - historically, there have been a number of famous examples.

 

In 1912, Bernard Citroen imported pearls into the United States and, to get around higher tariff costs, unstrung them from the necklace they were to be part of so they wouldn’t be classified as jewelry. Rather than being charged a 60% duty on jewelry, the pearls were ultimately classified as “in their natural state, not strung or set” and were dutiable at 10%.

 

This example is one that contemporary hardware developers will turn to when thinking about ways to legitimately restructure or reclassify goods as they travel globally through customs. Though it will require assistance and research ahead of time, often it’s worth the cost. As one State of Hardware respondent noted, they will need to start to “pay closer attention to what state of completeness products are shipped at,” as it may make more sense to classify at a lower tariff and assemble the final product in the US.

 

Magnifying the ‘Where’ and ‘What’

 

Traceability is also a question that both producers and consumers must start to think about more in the coming months.

 

As supply chains continue to grow globally and become more versatile, that also leaves space for risk. 43% of the 2019 State of Hardware respondents noted that they don’t feel they have the proper resources to manage a supply chain, which ultimately may lead to less oversight of material sourcing.

 

Jeff Wilson, a Senior Business Development Manager at NSF International, says one possible solution for improving traceability in manufacturing is to change the model. “Most brands and retailers know very little about their suppliers outside of their finished goods manufacturers,” Wilson says. Moving away from a traditional “chain”, he says, could help in many ways, including improving quality, increase speed and flexibility during development, and creating more trust with consumers. New approaches for providing transparency and traceability are also being tested. Ledger-based blockchain solutions for manufacturing supply chains will soon become an emerging trend.

 

The future of manufacturing is constantly changing, but the growing focus on agility, sustainability, and traceability certainly won’t slow in the next year. Hardware developers will continue to dig into these topics and make a concerted effort to improve relationships with manufacturers and consumers alike.

 

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The drive to develop a Vietnamese production base demonstrates the twin pressures of higher Chinese labor costs and the spiraling tariffs resulting from the trade war between Washington and Beijing. The U.S. internet giant plans to eventually move production of most of its American-bound hardware outside of China, including Pixel phones and its popular smart speaker, Google Home, according to the sources. The Vietnam production lines will be an important part of Google's drive for growth in the smartphone market. Google intends to ship some 8 million to 10 million smartphones this year, double from a year ago, sources told the Nikkei Asian Review. While Google's Pixel smartphone brand is still a minor player in the industry - not even rating in the global top 10, according to tech research firm Counterpoint - it is growing swiftly.

 

The mid-priced Pixel, released in April, helped Google become the fifth largest mobile brand in the U.S. for the second quarter of 2019, grabbing market share despite a broader industry slump. Google's aggressive hardware campaign is supposed to heap pressure on second-tier mobile makers such as LG Electronics and Sony, which are struggling as the industry confronts its third consecutive year of slump.

 

By diversifying its production into Vietnam, Google hopes to ensure that sustainable production of the Pixel range, a showcase for its Android operating system. Installed in 80% of the world's smartphones, Android is encountering a challenge from Chinese rival Huawei Technologies, the world's second largest handset maker, which in August unveiled its own mobile platform, Harmony OS.

 

In 2018, Google delivered some 4.7 million smartphones, which only accounted for 0.3% of global market share, research company IDC said. However it has already shipped 4.1 million units in the first half, according to IDC, thanks to the Pixel 3A, priced at $399. Approximately 70% of Google's smartphone sales in 2018 were in the U.S., its biggest market, followed by the U.K. and Japan, as reported by IDC. For smart speakers, the U.S. accounted for some 64% of shipments.

 

Under current plans, Google will shift some production of the Pixel 3A phone from China to Vietnam just before the end of this year, the people said. For its smart speakers, some production is very likely to be moved to Thailand, sources said. But the company's new product development and original production for its hardware lineup will still be in China, they said.

 

'Google are likely to keep some activities inside China. The U.S. company knows that if it is going to be serious about making hardware, it could never give up the massive Chinese market,' one of the sources said. 'However, they also understand that, due to rising costs and the macro-environment, they need to have production outside China for the long term in order to support their hardware manufacturing.'

 

Google is the latest to seek safety by diversifying its production as the trade war escalates. HP and Dell have moved their server production away from China to dodge Washington's punitive tariffs, while also shifting some notebook production to Taiwan and other Southeast Asian countries such as Vietnam, Thailand and the Philippines. Apple also has begun to analyse how it might diversify its supply chain, though it remains highly reliant on China with more than 90% of its hardware manufactured in the country.

 

Google initiated dabbling in the smartphone market as early as 2008, when it collaborated with Taiwan's HTC to operate the first-ever Android operating system on a mobile device under the Taiwanese company's brand. By 2017, Google had greatly accelerated its hardware business, hiring 2,000 handset engineers from the financially embattled HTC. It has also been scooping up hardware engineers and supply chain specialists from Apple.

 

But the relatively small scale of the Pixel handset production makes it easier for Google to think about shifting out of China at this stage, said Mia Huang, a smartphone analyst at the Taipei-based TrendForce. 'Any potential capacity shifting for [Google] would be easier than Apple.' Google, like many internet technology companies, sees hardware as a means of locking users into its ecosystem of software products. Amazon of the U.S. and China's Alibaba Group Holding are also using voice-activated smart speakers to drive customers to their e-commerce services. ByteDance, the parent of TikTok, the world's most popular short-video sharing platform by downloads, newly introduced its first smartphone to expand its influence outside software.

 

'For Google's smartphone business, it's still less about selling hardware but is really to demonstrate how powerful its mobile system and software could be,' said Joey Yen, an analyst at IDC. 'The main goal of Google's hardware business is to help the expansion of its core software, data, and advertisement business and to grow its ecosystem.'

 

However, Google's smartphone sales could benefit if Huawei gradually lost access to Android as a result of Washington's crackdown on the Chinese company, Yen said. Outside China, 'it still challenging for Huawei's new Harmony OS to grow into a mature and complete ecosystem soon,' she said. 'A new OS requires so many developers' accumulated efforts for a long time. So some Android phone makers such as Samsung and Google could benefit from that ban in the near term.' Google did not respond to requests for comment for this story.

 

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One area of industry in which the result from 5G is envisioned to be significant is robotics. As noted in a recent PMMI Business Intelligence report, “Robots 2019: Innovation 2 Implementation,” pick-and-place, collaborative, and mobile robots are assumed to be most affected by the advent of 5G.

 

And robots figure prominently in Nokia’s 5G 'factory of the future' in Oulu, Finland. Just recently selected by McKinsey and the World Economic Forum as an Advanced 4th Industrial Revolution (4IR) Lighthouse, this pre-production facility uses Nokia’s private (4.9G/LTE) wireless networks to securely connect all assets within and outside the factory. Other technologies used in this factory of the future include Nokia’s IoT analytics running on Nokia’s Edge cloud. This combination of technologies is also used by Nokia to provide a real-time digital twin of the facility’s operations data.

 

If you aren't aware that Nokia was supplying IoT analytics and edge/cloud technologies for industry, don’t feel out of the loop. According to Stephane Daeuble, head of 5G industry vertical network slicing and private wireless networks solution marketing at Nokia, the Nokia Oulu factory is “an environment in which we can test and prove the value of our private wireless 4.9G & 5G, Edge cloud (in which cloud capabilities are distributed across the network to place computing resources at the edge of the network), analytics, and edge application technologies for smart manufacturing use cases.”

 

Daeuble included that Nokia has an evergrowing number of deployments in the manufacturing and processing industries with companies such as Rio Tinto, the BMW-Brilliance plant in China, Goldfields, Beach Energy, Konecranes, and Cargoteh-Kalmar. “In addition, we are working with an expanding array of partners, such as Bosch, Komatsu, Sandvik, and ARENA2036 [Active Research Environment for the Next Generation of Automobiles—a testing ground for suppliers to the car manufacturing industry in Germany] to drive the ecosystem of industrial devices, machines, sensors, and systems that embed private wireless 4.9G (and future 5G) modems within their products, and to integrate new industrial applications on top of Nokia’s own as part of our Edge cloud solutions,” he said.

 

Nokia’s Oulu facility makes 1,000 Nokia 4G and 5G base stations per day. Following the implementation of Nokia’s private wireless 4.9G & 5G, Edge cloud, and IoT analytics, the company said it has seen a 30% improvement in productivity gains, a 50% savings in time to market, and a yearly cost savings of millions of euros.

 

Evaluating the facility’s improvement from an automation viewpoint, Daeuble noted that three key technologies were used in the evolution of the factory — virtualization of new product introduction, flexible robots to deliver maximum productivity and adaptability to increase new products quickly, and cloud-based digital twins to drive real-time process management and plant optimization.

 

All of these advances required the implementation of a dependable and secure private wireless (4.9G) network, said Daeuble. “In the past, the factory used CAT cabling and industrial fieldbuses, which are the norm in most factories today. Now, many of our machines, testing equipment, robots, and sensors are connected to the private wireless network, which makes it very easy to add new machines or sensors without worrying about cable runs or adding new switches.”

 

One of the significant areas of improvement with the 4.9G network is the operation of the facility’s automated guided vehicles (AGVs). Before this upgrade, the AGVs were using the corporate Wi-Fi network, and“suffering from poor performance or stoppages when they would hand over from one Wi-Fi access point to the next, or as the Wi-Fi signal degraded, said Daeuble. “These AGVs are now connected over the 4.9G network and are delivering very stable performance and operating at faster speeds. Plant safety has also been increased by the robustness and reliability of the connectivity, as has the efficiency and throughput of the production lines.”

 

Indoor positioning is another benefit the Oulu facility gained from the network upgrade. “Key assets in the factory are now geo-positioned—within 30 centimeters—to provide a live operational overview of each element’s position,' said Daeuble. 'This enables plant managers to find things more easily, but also to feed the digital twin models and deliver the statistical data needed to optimize the automated supply chain between the plant’s different production lines and storage facilities.”

 

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As Japan's working population grays and its labor pool evaporates, parcel distribution companies have been making due with aging drivers. But they have also been exploring alternatives, like drones and automated vehicles. Yamato and Texas-based Bell Helicopter have been building their flying alternative since last October.

 

The craft used for the test flights is 2.7 meters long and can carry loads of about 30 kg. Yamato is also developing similar drone capable of carrying heavier loads. It will later decide where to roll out flying deliveries. It expects to commercialize drone deliveries by 2025.

 

Yamato just isn't the only player investing in delivery drones. U.S. e-commerce giant Amazon is developing similar contraptions, intent on introducing a service that can deliver an order within 30 minutes of being placed. And JD.com, a Chinese online shopping site operator, has been producing drones since 2015 and already runs drone delivery services in China.

 

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Mainly, PARC is creating a new science of computational design by inventing new representations and algorithms to design, analyze and plan the manufacture of heavily complex structures that can be fabricated with state-of-the-art technology. This interdisciplinary work unifies principles of computational physics, geometric reasoning, automated spatial planning, and field modeling to help engineers create entirely new kinds of products – the likes of which many have not yet imagined. In parallel, PARC has spearheaded the development of CBM techniques (called MOXI) which allows for online anomaly detection, diagnostics, and prognostics of industrial assets towards actionable predictive maintenance. These techniques have been customized and successfully deployed it in many challenging customer environments, including manufacturing floors of major global organizations.

 

How do you define Condition Based Maintenance (CBM)?

 

As opposed to traditional corrective maintenance or scheduled maintenance, CBM is an approach whereby maintenance is executed proactively on evidence of need identified through direct or indirect monitoring and predictive analytics of the assets of interest. To that end, specific knowledge of the asset’s condition is obtained by analyzing sensor information that allows assessing the asset’s condition at any given time in its operating life. Maintenance action can then be planned with enough lead time to minimize the cost and operational impact of the occurrence of a failure. CBM differs from “on-condition” maintenance in that there is an understanding of how much time is available before the required maintenance must be performed.

 

How should one go about deciding whether CBM is right for my company?

 

The first step is to get a well understanding on the effect of equipment downtime on operations by quantifying the impact and juxtaposing that with the cost of implementing CBM. A cost-benefit analysis will then assist to decide whether this makes sense and for which equipment it might make sense. One would begin by first methodically adding up the value lost due to downtime, the cost of repair, logistics, warranty claims, time/cost for part replacement and inventory, etc. On the cost side, there's some hardware and software development cost, and cost for maintaining the infrastructure. One can dig further down to factor in secondary cost and value elements but it is good to begin at a high level to get a rough idea whether there's a possibility for savings.

 

What are the hurdles of implementing CBM?

 

One may have to experience technical and non-technical hurdles. On the technical side, it is required to have some information into assets’ health via sensor measurements and relevant system information/details. While the IIoT, smart maintenance initiatives, and industry 4.0 have been receiving a lot of buzz, having the right kind of sensors implemented at the right locations of the equipment and collecting and managing the data are still hurdles that need to be overcome for most companies. It would be desirable to do some upfront analysis of fault modes (maybe by conducting a Failure Mode Effect and Criticality Analysis) to understand which sensors ought to be deployed where. It is also immensely important to leverage the right kind of analysis tools that can reliably provide information about anomalies, fault root causes, and remaining life at the desired accuracy levels without triggering undue false alarms or missing key events. 

 

On the non-technical side, it is crucial to have a champion within the organization who has budget authority to make needed investments. Just as important is it to gain trust of stakeholders so they understand that the technology is not a threat, but a benefit to how they conduct business. 

 

What are the benefits?

 

If done right, CBM can help to stretch maintenance budgets by proactively focusing action on assets in need; reduce downtime by eliminating failure, thereby maximizing availability; relieving risk of loss of system, and increasing safety; improving spares/personnel management and better inventory control; providing better diagnosis and fault isolation through root cause analysis, thereby decreasing troubleshooting time; reduction in take-back cost and disposal avoidance; In the long run, it can also enable better asset/system planning, and vital operational feedback for design and stakeholder teams.

 

There is a lot of hype surrounding machine learning and AI in the context of CBM. What expectations should a company have with regards to these technologies?

 

Yes, we see lots of promises being made that all maintenance woes can be solved by basically sprinkling some “deep learning” or other popular machine learning technique over operational data without more insight into the manufacturing environment. As is the case with all machine learning approaches, one needs to have access to many significant data to train the models. For CBM, “relevant data” means many observed trajectories of sensor measurements over experienced faults in the field. These have most of the times actually not yet been experienced. Some types of equipment do not frequently fail with the same fault mode. Even if they do, the data have historically not been collected for all operational modes. Due to this fact, the performance of many of these techniques will likely disappoint. It would be advisable to be clear-sighted about where and how AI techniques can augment CBM and where physics-based models have the upper hand – or combine the two similar to what we have done effectively in MOXI for numerous clients and critical systems. And, of course, a sound understanding of the underlying engineering processes and tight integration with the manufacturing floor are very important.

 

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The deal comes as CRRC is under pressure in the U.S. where it has opened two factories and won contracts to supply train cars for transit systems in a number of major American cities. Both houses of Congress have passed measures that would bar the usage of federal funds to buy Chinese rail cars and buses out of concern they could be utilized for Chinese espionage or sabotage. It's not just yet evident if the final version of the bill to which the ban has been attached will finally include it.

 

Vossloh announced Monday that it would sell a locomotive factory it started last year to CRRC Zhuzhou Locomotive, a subsidiary of Hong Kong-listed CRRC. The German company, which is narrowing its focus to railway infrastructure equipment, said it expected to firstly receive a figure in the 'low single-digit millions of euros', and another 10 million euros ($11 million) in follow-on transactions, under its agreement with CRRC Zhuzhou.

 

'CRRC is the very strong partner needed for our future development and the deal is supported by management and workers, as well as their union,' a Vossloh spokesman said. 'In view of this robust support, we are confident that all regulatory approvals will be gained by the end of the year.' A spokeswoman for CRRC was not able to quickly confirm the agreement. Vossloh, which has an existing joint venture with a unit of China Railway Construction, had originally put its investment in the locomotive factory at 30 million euros.

 

It is not clear how much scrutiny the deal will face in Germany, though industry observers do not expect there will be regulatory action against the deal. 'Vossloh does diesel locomotives for short distances, which is a shrinking market segment, as opposed to electric locomotives, which is a growing segment,' said Maria Leenen, founder of railway consultancy SCI. 'Given that there is no key technology involved, I don't see how the foreign trade law could be used to stop the deal,' she added.

 

Even so, the German government has taken a wary stance toward Chinese buyouts since Chinese appliance maker Midea bought robot manufacturer Kuka for 4.6 billion euros in 2016. The government has since implemented measures giving it more power to block selected buyouts on public interest grounds. The government is also considering a plan to create a state fund that could outbid Chinese state companies trying to buy key assets.

 

CRRC Zhuzhou was outbid by local investors in 2016 when it tried to acquire Czech Republic-based train maker Skoda Transportation. CRRC last year generated profits of 13 billion yuan ($1.8 billion) on revenues of 214.52 billion yuan. At least 90% of revenues came from China, with Europe accounting for just 7.57 billion yuan, mainly from sales of auto parts and deep-sea robots. Among its highest profile sales in Europe has been an order received last year from German rail operator Deutsche Bahn for four small shunting locomotives to be delivered in 2021.

 

The acquisition of Vossloh's business should give CRRC's European growth ambitions a substantial boost as EU regulations effectively favor domestic producers, according to Klaus Holocher, a professor for transportation management at Germany's Jade University of Applied Sciences. 'If a Chinese company acquires a domestic player, they get all the standards and technology required to bring its trains quicker onto European railway tracks,' he said.

 

This in turn would make CRRC a stronger rival to Germany's Siemens and France's Alstom, who earlier sought to combine their train businesses to thwart CRRC from grabbing European orders. The European Commission in January forbade the two companies from merging their train businesses to protect competition.

 

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Over the next decade, 4.6 million manufacturing jobs will be created, according to a 2018 study performed by the Manufacturing Institute and Deloitte. However, as many as 2.4 million of those positions are inclined to remain unfilled as a result of the burgeoning skills gap and lack of qualified talent. The U.S. Bureau of Labor Statistics reported nearly 400,000 jobs in the manufacturing sector lay vacant in March 2018, approximately the same number as the year before. The steady stream of Baby Boomers heading for the retirement door, coupled with continued economic expansion, are exacerbating the vacancies.

 

On the other hand, the growing lack of science, technology, engineering, and math (STEM) skills among the worker pool, a continuous fall in the number of technical education programs offered by public high schools and colleges, and a negative perception of manufacturing-sector careers have done little to remedy the situation.

 

The deficiency, which is only expected to get worse, is weighing intensely on manufacturers as they navigate their digital future. The National Association of Manufacturers (NAM) estimates that over 80 percent of manufacturers are struggling to find qualified talent, making it their most pressing business issue today. Survey respondents say the lack of a modern industrial workforce will impede their ability to meet customer demand, innovate, and develop new products — a scenario that can eventually have a negative impact on growth and profitability.

 

“The biggest risk for companies is falling behind competitively and that can easily happen when a company does not embrace new technology or their workforce doesn’t possess the skills in emerging automation technologies,” says Doug Schuchart, northeastern regional manager and material handling and logistics vertical manager for Beckhoff Automation. “Industry 4.0 concepts for predictive maintenance, machine learning for improved throughput, or leveraging data to reduce product waste and energy consumption can enhance machinery and add competitive value, but these are areas in which engineers may not have any existing experience.”

 

Due to this fact, manufacturers find themselves at a pivotal juncture: Without access to a robust and skilled talent pool, they are restricted from pursuing a competitive automation agenda of smart factories, predictive maintenance, and self-organized logistics accomplished through next-generation technologies like robotics, the Industrial Internet of Things (IIoT), artificial-intelligence (AI), and advanced analytics. In truth, the NAM survey found the root of the current talent shortage lies not just with the lack of able bodies, but rather with increased demand for a shifting skills set that puts an emphasis on information technology (IT), digital tools, programming of robots and automation, and soft skills in areas like critical thinking and problem solving.

 

Skills in demand

 

Much of the present industrial workforce does not have a background in emerging areas such as advanced analytics, robotics, and digital manufacturing. Consider the smart factory that capitalizes on technologies like the cloud, machine learning, and IIoT to collect, filter, and analyze machine vibration, pressure, temperature, and throughput data to proactively manage equipment failures, optimize machine performance, or initiate preventive maintenance.

 

While manufacturers have gotten fairly proficient at connecting IIoT-enabled industrial equipment to the network while collecting and storing data, there's a knowledge gap in how to successfully analyze and leverage that data for the myriad new use cases, according to Robert Van Til, professor and department chair of industrial and systems in the engineering department at Oakland University. Furthermore, basic programming and math skills are now a need for production workers to be able to program computer numerical control (CNC) machines and robots on the plant floor or to interact with new human-machine interface (HMI) software and other engineering and digital manufacturing software.

 

“There is a burgeoning need for a more technically skilled trade level because automation is replacing jobs and moving up the skill level,” Van Til says. The factory worker tasked with attaching a simple bolt in a traditional plant-floor scenario could now serve as an operator that must interface with automation software, and that requires different skills, he explains.

 

Along side basic programming and scripting skills, there is also climbing emphasis on bridging the IT and operational technology (OT) divide so data can effortlessly flow between plant floor systems just like supervisory control and data acquisition (SCADA) systems and manufacturing execution systems (MESs) into core enterprise IT platforms such as enterprise resource planning (ERP), product lifecycle management (PLM), and supply chain management (SCM). “The ability to do coding and work with SQL databases, whether writing queries or creating schemas—there is a real shortfall in terms of engineers having cross-discipline skills,” says Kevin McClusky, co-director of sales engineering at Inductive Automation. “Manufacturers realize that the job is no longer just about programming PLCs [programmable logic controllers]. It has to span both sides of the divide.”

 

Still, it’s not just new industry 4.0 skills that are in short supply — manufacturers also need to boost competencies in legacy skill areas such as PLC programming and control system troubleshooting as an aging workforce retires, taking decades of tribal knowledge with them. “The folks working on legacy systems know how to keep the machines up and running, which is critical to any profitability and productivity measurement,” says Gail Norris, director of the Sitrain Digital Industry Academy at Siemens. “It’s the perfect storm with a combination of new skills needed and the legacy skills that still need to be maintained.”

 

The acquisition of legacy skills can be more of an issue than advanced technology expertise because the incoming workforce isn’t being taught older technologies, and several high schools aren’t doing enough to encourage a career track focused on manufacturing and automation. “The great enemy of manufacturers is not foreign cost competition, it’s the high school guidance counselor,” says Brian Fortney, global product manager for customer training at Rockwell Automation, who contends modern-day manufacturing is as legitimate a high-tech career as working for any of the big software giants. “They don’t do a good job of driving awareness and engagement in manufacturing careers as a step forward for individuals.”

 

Technical skills aren’t the only area in hot demand — soft skills around communications and project management are more important than ever, says Amanda Elmore, dean of the Industrial and Engineering Technology Division at Tri-County Technical College in Pendleton, S.C. “Twenty-first century workplace skills, including the ability to work in teams, are just as important now,” she says. “If your technical skills are average, but you have soft skills in spades, you’re actually more employable and promotable as long as you’re coachable.”

 

There is also a need for automation workers to be more multi-dimensional and not just competent in a specific area like robotics or material handling. For example, in today’s factories, roles are very well defined and have a smaller scope — someone loads materials or takes a part from here to there. Not so in the smaller, more localized factories of the future, where workers will need to be more flexible and understand different workloads.

 

“If you are producing several parts that might be different every day and the machine supports an automated workflow, you might have end-to-end responsibility for getting the materials to the machine to all the way through final quality control and shipment,” explains Virginia Palacios, global head of Multi Jet Fusion product management, 3D printing and digital manufacturing at HP.

 

Training the next-gen workforce

 

Suppliers and educators are trying to shift the dynamics through new curriculum at both the high school and technical community college level and through partnerships with industry and universities. Rockwell and Yaskawa Motoman, to illustrate, have joined up with the Robotics and Advanced Manufacturing Technology Education Collaborative (RAMTEC) on a number of workforce development efforts. Yaskawa Motoman and RAMTEC have formed the Ohio Manufacturing Workforce Partnership charged with creating STEM-aligned curriculum and training in Industry 4.0 technologies, while Rockwell has forged another similar relationship to create curriculum and certifications to ensure students graduate with a degree in addition to credentials in control logic, AC/DC, and other critical automation competencies.

 

Included in its partnerships with universities, Emerson is augmenting traditional curriculum development by investing in physical labs that allow students to learn automation technologies through hands-on training and real-world experiences. The company has instrumented a full-scale distillation site and industrial control lab at San Jacinto College in Houston to help students learn how to install, maintain, and troubleshoot integrated control systems through hands-on learning. “The trend is to have as life-like a facility as possible,” says Jeffrey Hackney, director of global education services at Emerson. “We can simulate everything going on from the distributed control system to process variables, and that gets the incoming workforce up and running more quickly.”

 

Training and reskilling is likewise happening at the corporate level. Vendors, seeing an uptick in demand for corporate reskilling and training, are building out a variety of programs designed to close the gap for in-demand automation technology skills. Quite a few, like Rockwell, are delivering new online e-learning content to give employees the flexibility to choose how and when they get skills training, while Siemens and others have new services in place to create custom training programs depending on the corporate need.

 

An additional way companies are addressing the skills gap is through the gig economy, employing back retired industrial workers to come in and fill the legacy skills gap on an interim basis. “Maybe they need a maintenance person for a planned outage and they come back for a three-week assignment,” Siemens’ Norris says. “These folks can help teach the new hires and pass on all that institutional knowledge.”

 

However the skills gap is being addressed, in the enterprise or at the educational level, the process needs to be a continuous one given the accelerated pace of change in both technology and industrial applications. “We have to be prepared for the rate of change taking place,” Tri-County’s Elmore says. “The truth is, we are preparing students for jobs that don’t exist yet and will change again in five years.”

 

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The Disconnected Reality

 

Lots of manufacturing plants in the U.S. are more than 20 years old. Significantly less than 14 percent of the machines on shop floors are “connected.” This means they do not have sensors or monitoring that can extract data about how they are operating. These older machines are likely to get breaking down, and they account for up to $50 billion (annually) in downtime.

 

Hype over Industrial IoT has many manufacturers believing that they must quickly invest in transformational technologies like machine learning, augmented reality, or artificial intelligence to acquire any benefits around efficiency. But that’s far from the reality. While manufacturers need to initiate building the connected foundation to extract and leverage data, it does not need a big overhaul overnight. By leveraging a cloud-based platform, many manufacturers are starting by focusing on Industrial IoT business drivers and then building on initial successes.

 

The Problem with Data in Manufacturing

 

A significant problem toward becoming more connected is getting at data in older machines on the shop floor. A great number of these machines do not have digital controllers or they necessitate external retrofitting and sensors to pull operational data. This can frequently be difficult and expensive so a clear return must be identified to undertake the effort. For this reason, companies focus on the most critical equipment that may have been problematic in the past or represents a critical control point that affects delivery.

 

The next problem is even when data is available, there is hardship around what to do with it. Raw data is not of much value unless there is a way to interpret it and make sense of it. Most manufacturers don’t have data scientists on hand to help with this endeavor. The hype around big data is that manufacturers who have ability to access data will transform how business is done, but the reality is digitization just lays the foundation for understanding what is going on in any particular asset. There has to be a way to visualize the data to make it workable.

 

What’s the Industrial IoT Reality Today?

 

Rediscovering the chief mission of manufacturing — making high-quality products as cost-effectively as possible — the reality with Industrial IoT is more about leveraging capital they already have than it is about the promise of some far-off future. It is about unveiling ideas and opportunities for improvement.

 

Lots of manufacturers are basically gaining visibility into their existing assets. They are looking at how to improve operational effectiveness by knowing what is happening on the shop floor. They are monitoring historical trendlines to learn, diagnose, and improve uptime and performance. They are pinpointing trends that could disrupt operations or quality performance.

 

Leading manufacturers today know that Industrial IoT is a strategy they can not ignore — because there is a good chance that those manufacturers who do ignore it will be like many consumer companies that missed out on the Internet. They know that it’s important to start putting in the connected foundation that will leverage Industrial IoT now rather than wait.

 

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The benefits by Baidu - mirroring fast adoption by Chinese consumers - shows the parallel competition of tech giants on both continents as they produce AI-controlled devices implied to one day run everything from cars to homes to in-store shopping. Baidu, Google and Amazon did not quickly respond to requests for comment. US and Chinese tech giants have long jockeyed in the race to develop the most sophisticated phones, computers and other devices. Due to the nature of the companies, however, many of the brands have first targeted their domestic populations.

 

That's beginning to change. China has mobilised appreciable resource to enhance its dominance in high-tech fields as part of its 'Made in China 2025' strategy. Telecom giant Huawei, even though going through restrictions in the US, has been working to make inroads in Europe. Meanwhile, Amazon and Google have been pushing their devices - and specifically their smart speakers - more internationally, too.

 

While Amazon and Google work to grow their businesses globally, they will cope with technological troubles from differences as basic as the types of homes in which consumers live, says Michael Levin co-founder and partner at Consumer Intelligence Research Partners. Although many US consumers live in homes, the international tendency towards living in apartments may prove difficult for the company's full home-control marketing strategy.

 

'Adapting this market to the other 80 per cent of the world is not a very straightforward proposition,' said Mr Levin. Baidu overtaking Google, while 'no small feat', is a result of the company's sole and aggressive focus on the fast-growing China market, said Jason Low, a senior analyst at Canalys. Google and Amazon have up to now focused heavily on the US, although their global market share is most likely to continue to multiply.

 

'It's a good gauge to see how the market is growing,' he added, saying the rankings are most likely to continue to be fluid. Baidu may also undertake further challenges as an economic slowdown in China could ding the company's core businesses.

 

It is as yet uncertain how the increasing trade war between the US and China will hurt the global smart speaker market, or the global economy generally. On Friday, President Donald Trump announced he would raise the rate of tariffs on Beijing and commanded that US companies quit doing business with China. Mr Trump said Monday that trade negotiations are set to resume, though details were elusive.

 

Experts say that the trade war is a lot more about technology than trade. In May, the Trump administration penalised Huawei by adding it to the Commerce Department's Bureau of Industry and Security 'entity list', causing it to be difficult or impossible for the company to do business with any US firm. Huawei has since been granted a few 'temporary general licences' that allow it to conduct some business here, including providing software updates.

 

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The first data center has been accomplished and put into use in the city of Yancheng, eastern China's Jiangsu Province, according to the Institute of Computing Technology under the CAS. The center has 1,000 compute and storage nodes and 30,000 processor cores. It can adequately process 10 million video streams per second but consume only 750 kilowatts of power.

 

High-throughput computing lets the use of multiple computing resources over long periods of time to achieve a computational task. With high-throughput computing, what could have taken weeks before on one computer will require only a few hours on the company's cluster.

 

A report estimated a tenfold increase in global data volumes from 2016 to 2025. High-throughput computing, with effective data processing ability, can support hundreds of billions of new terminals and huge information processing, said Sun Ninghui, director of the institute.

 

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In manufacturing and logistics, 37% only receive training a few times per year and that training is only 58% effective. In addition,  34% of manufacturing employees said they are trained on the wrong things that do not help them do their jobs. The main highlights from the research include: 

 

Reskilling and  Upskilling 

 

According to the World Economic Forum, well over half of the world's workforce will need significant reskilling by 2023. While there is much uncertainty around how frontline jobs will flourish and what skills will be required to perform these new jobs, the research vividly demonstrated that employees are anticipating these changes and want training that prepares them for what lies ahead.

 

• More than three-quarters (76%) of employees feel the opportunity to complete additional training designed to develop their skills for the future would make an employer (present or prospective) more appealing to them.

• Future-focused development is especially valued by those starting out their career, with nine out of ten Millennials (89%) saying they are interested in future-focused training compared to 81% of Gen Xers and only 59% of Baby Boomers.

• Despite a healthy appetite for additional training that develops skills for the future, only 41% of employees say their employer offers this kind of development.

• The study found 81% of employees believe training makes them feel more engaged (happy) at work. And 79% of participants feel that more frequent training would make them feel even more engaged.

 

Effective Training Techniques

 

Across industries, here are the additional top attributes the research discovered make training effective: 

 

• The most desirable attribute for the third year in a row is training that is easy to complete and understand (91%).

• The ability to access information from anywhere, at any time is also important to employees (90%).

• Training that is personalized and relevant remains a top-ranked attribute (89%). Over the three-year history of this study, training that’s boring/not engaging consistently ranks as one of the top two reasons for ineffectiveness (91% in 2018).

• The ability to apply training on the job is also an important attribute (87%). It’s interesting to note that this was extremely important across the board—regardless of industry, age and employment status.

 

“Preparing the frontline workforce for the future is a win-win situation,” says Leaman.  “Employees get the future-focused training they want and organizations build the future-proof workforce they need to ensure continued business success. The challenge for Human Resources and Learning and Development leaders will be to deliver training at scale so they can equip the modern frontline employee with the knowledge and skills they need to keep up with the pace of business.”

 

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Fujitsu finds out a necessity for such tools amid a shortage of data specialists available to perform credit analysis in Japan's financial sector. With financial technology startups proliferating, the IT-industry blue chip strives to draw on its existing customer relationships in marketing the AI software.

 

Credit scores will be generated based upon such information as bank and business transactions. Lenders will need prospective borrowers' consent to use such data. Fujitsu has yet to decide on pricing for the tool but envisions offering both flat-rate and performance-based plans. The latter would allow Fujitsu receive compensation if the tool leads to an approved loan.

 

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'This wobbly self-driving bicycle is a symbol of growing Chinese expertise in advanced chip design,' said MIT Technology Review in an article. The Tianjic chip features a hybrid design that seeks to bring together two different architectural approaches to computing: a conventional, von Neumann design and a neurologically inspired one, said the article.

 

'The two architectures are used in cooperation to run artificial neural networks for obstacle detection, motor and balance control, and voice recognition, as well as conventional software,' according to the article. The chip also inspiring ideas at the progress China is making in developing its own chip design capabilities, said the MIT Technology Review piece.

 

The research achievement, conducted by Shi Luping and his associates at the Center for Brain Inspired Computing Research of Tsinghua University, was published as the cover story of Nature magazine on Thursday. 'It's not the first self-driving bike. But equipped with an AI chip, it may be the nearest to thinking for itself,' said an article published on The New York Times, titled 'And Now, a Bicycle Built for None.'

 

As corporate giants like Ford, GM and Waymo struggle to get their self-driving cars on the road, a group of researchers in China are rethinking autonomous transportation using a souped-up bicycle, said the article. 'In handling all these skills with a neuromorphic processor, the project highlighted the wider effort to achieve new levels of artificial intelligence with novel kinds of chips,' said the article.

 

The hope is that such chips will gradually allow machines to navigate the world with an autonomy not possible today, said The New York Times. Eric Topol, a scientist at the renowned Scripps Institute in California, tweeted that 'It's a big AI day with the Tianjic chip, autonomous bicycle and the implications for this hybrid/synergic brain-like and machine capability.'

 

Shi's Tianjic chip can integrate the two approaches into one hybrid platform, which enables it to accommodate both machine-learning algorithms and brain-inspired circuits. The first generation of the Tianjic chip was developed in 2015, and then the second generation in 2017. After repetitive improvement, the current second-generation Tianjic chip features even higher performance with much lower power consumption.

 

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The legion of robots, which range from companion robots, security patrol droids to automated delivery vehicles, have pleased the large number of robot fans attending this year's WRC. As the annual WRC enters its fifth year, China is stepping into a new era of market boom and technological advances. The country's robot market is considered to reach 8.68 billion U.S. dollars this year, accounting for about 30 percent of the global robot market and posting an average annual growth of 20.9 percent in the past five years, according to a recent report by the Chinese Institute of Electronics (CIE).

 

China has also unveiled a development plan for the robotics industry from 2016 to 2020 for boosting research and development of key robotics technologies, nurture major innovations and promote international cooperation in the field. Miao Wei, China's minister of industry and information technology, remarked at the event's opening ceremony that the robotics industry serves as a key engine for the development of China's intelligent manufacturing sector and that China is welcoming the rest of the world to take part the development of its robotics industry and encourage international cooperation to collectively advance healthy and sustainable development of global robotics industry.

 

BOOMING INDUSTRY

 

Industrial robots, key to supercharging productivity in the manufacturing sector, are well represented at this year's WRC. HIT Robot Group, one of China's major industrial robot manufacturers, showcased its latest automated pharmaceutical packaging line. It features 10 robotic arms that can agilely pick up pills and arrange them in order. The pills are later packaged, weighed and labeled automatically on the line.

 

'The packaging line has been used in many large Chinese pharmaceutical factories to improve productivity, reduce contamination and slash human exertion,' said Tu Hongsen, vice general manager of a subsidiary of HIT Robot Group.

 

HIT Robot Group is among several other Chinese robotics companies that have cashed in on China's big demand for industrial robots, as the country endeavors to deploy a big robot army to turbocharge its manufacturing sector amid rising labor costs and an aging population. According to the CIE report, China is the world's largest industrial robot market, with an estimated value of 5.7 billion U.S. dollars in 2019.

 

Besides manufacturing, robots are being used in China in many more areas.

 

A robot barista, developed by Chinese home appliance producer Gree Electric Appliances, has captivated a large number of visitors at this year's WRC. The bright-colored robotic arm can make and serve coffee and even create latte art. Also on display is Gree's distinguished robot band, consisting four robotic arms playing the piano, guitar, keyboard and drums. The band became an instant hit when it appeared on this year's China Central Television (CCTV) Spring Festival Gala, the most-watched annual show on Chinese New Year's eve.

 

Audiences at the WRC marveled at the band's performance as the four 'musicians' moved their fingers easily and effortlessly on the instruments. 'It's magnificent. It's difficult enough to make one robot play the instrument according to the rhythm, let alone coordinating the performances of four robots,' said Wu Hao, a Beijing resident who saw the robot band for the first time. 'I can see the great efforts the engineers have put into the robots.'

 

An Longxiang, a staff member with Gree's marketing department, said the robot band is driven by advanced technologies such as flexible mechanical controls and precise algorithms, which have the potential to be used in medical care and other fields. 'The use of robots has expanded from the manufacturing sector to healthcare, service, consumption and other areas. These areas are the future of robots,' Qu Daokui, founder of major Chinese robot manufacturer Siasun Robot and Automation Co., Ltd.

 

OPEN ERA

 

Themed 'Intelligent Ecosystem for a New Open Era,' this year's WRC is aspired at providing a platform for China and other countries to deepen cooperation in the robotics industry. In the WRC exhibition center, a robotic surgical system co-developed by Chinese and Swiss scientists, 'Ophthorobotics,' showcases the latest achievements of international cooperation. The robot, able to perform injection therapy and help treat chronic eye diseases, can finish the injection in two minutes, compared to at least 15 to 20 minutes by an ophthalmologist.

 

The robot has an iris recognition and eye-tracking system, and can diagnose the lesion part and locate the best spot to inject, said Bradley J. Nelson, chief technology officer of the project and professor with the Swiss university ETH Zurich. 'The robot will be clinically tested in China and Switzerland in February next year,' said Liu Qian, president of Zhongrui Funing Robotics Co., Ltd.

 

Up to this point, Liu's company has worked with robotics R&D institutions in countries including Sweden, Switzerland, the U.K., Japan, Germany and Italy and has filed 52 patent applications, among which 23 were filed overseas. Many foreign robotics enterprises have invested and built factories or set up joint ventures in China, and Chinese companies are also seeking overseas partners and exploring the international market, said Xin Guobin, China's vice minister of industry and information technology, at a forum during the conference.

 

To illustrate, in Beijing's Yizhuang economic development zone, where the WRC exhibition center is positioned, more than 180 robotics companies have set up operations, including strong foreign players such as Festo and Yaskawa Electric Corporation. There were exclusively 35 in 2016. Alois C. Knoll, a professor from the Technical University of Munich, said on the sidelines of the WRC that he hoped to see more R&D collaboration between China and other countries as well as further industrial cooperation between Chinese and foreign robotics companies.

 

'China will continue to make the WRC a bridge, take an active part and push forward cooperation in the robotics industry globally,' Xin said. 'We will encourage Chinese companies to work together with their foreign counterparts to put more research into application.'

 

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For years, medical devices such as heart stents were tested on humans or animals. Today, however, research is being done on virtual hearts that are digital twins to their real life counterparts. In a similar fashion car manufacturers once could only see how their cars would handle the stress of a crash by in fact crashing into physical objects. Today manufacturers can “crash” them earlier in the manufacturing cycle in the virtual world, and for a fraction of the cost. Today, entire factories can be created digitally to plan and optimize manufacturing lines. The bottom line is, virtual worlds help people consider differently; they extend and improve the real world.

 

McDermott, a multinational engineering, procurement, construction and installation company, provides an outstanding example of how virtual worlds can create business opportunity. Using virtual twins, McDermott is able to collaboratively engineer, build and operate fixed and floating offshore production facilities, pipelines and subsea systems. By digitalizing and standardizing its processes as well as deploying a single, secure and collaborative environment, McDermott improved efficiency and performance, thereby accelerating the delivery of construction-ready and operations-ready projects.

 

Nonetheless it's not merely enterprises that can benefit from going virtual. In Singapore, the entire city has a virtual twin that integrates real-time, dynamic data into a topographical view of the city.

 

Constructing virtual twins isn't a super easy process, and as companies look to leverage virtual technologies they should be aware that not all virtual twins are equal. To acquire full efficiency and value from the virtual world, the twin must pull in and incorporate information from across the enterprise – marketing, engineering, design and manufacturing. It also must be able to create very detailed models that leverage 3D design and simulation to reproduce an object as a dynamic 3D model.  It’s not enough to just create a virtual object in a vacuum, you must also accurately simulate the environment in which that object will exist. 

 

By understanding the dissimilarities and the interplay between the value-creation processes of the physical world and those of the virtual one, manufacturers can holistically solve strategic production issues to achieve a lean and agile manufacturing process. Platforms that provide a single user interface and a digital thread across all enterprise functions and applications are the optimal way to create and leverage digital models that offer both precision and fidelity. And for those who want to view their model in an immersive virtual experience, headset and all, being able to pull the model into a VR rendering environment is also key. 

 

The industry of the 21st century is simply not identified simply by the ability to manufacture goods. Today’s leaders will be determined by superior mastery of technical knowledge and know-how. This is the new competitive differentiator and it is happening now caused by a convergence of digital technologies that are turning every aspect of industrial business. To drive a renaissance of business requires a platform approach that enables the real and virtual worlds to inform and reinforce one another. By building the virtual before the real, companies can gain valuable insights, reduce costs, increase sustainability and correct mistakes in real time.

 

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