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Assessing the adoption of blockchain in financial services – FinTech Magazine

August 3, 2023 | Author: admin

Blockchain has been somewhat of a quiet revolutionary. Essentially a distributed database containing an ever-growing list of ordered records blocks its introduction as the enabler of crypto asset trading heralded the beginning of decentralised finance.

But, while blockchain and cryptocurrencies may appear synonymous with one another, the truth is blockchains reach is far more extensive and can be used to monitor supply chains, create digital IDs and enable data sharing.

So, while blockchains association with crypto is well-established, the question remains: is it being used to its full potential in the wider financial services sector?

Understanding blockchain

To gauge blockchains potential in finance more broadly, its important to first understand how it works.

A board member at the Casper Association, Ralf Kubli likens blockchain to a series of remote computers working together to create a trustless independently verifiable, decentralised ledger.

He continues: Every computer on the network, or node, can see every transaction that has ever occurred, and all of this information is encoded cryptographically, decentralised so that any participant can simply run the maths themselves, and confirm that all values are correct.

While for cryptocurrency, certain nodes on the network miners are tasked with ordering batches of transactions into blocks (rewarded for their efforts with newly created crypto assets), Kubli notes that blockchain doesnt have to be used this way. It can be a ledger for virtually any type of data.

Blockchains reach across the financial industry

Kubli continues: While financial institutions such as BlackRock, Siemens and even HSBC are touting tokenisation as a paradigm shift for the economy, with vastly improved systems for delivery versus payment (DvP) settlements, current tokenisation platforms are not digitising the underlying liabilities or cash flows tied to the assets themselves.

Most tokens have a simple embedded PDF that defines its terms and conditions, meaning human intervention is still required to calculate cash flows, which, according to Kubli, can introduce errors and discrepancies, and also prevents this digital capital from being truly automated.

As a result, Lab49s Principal Consultant Yuvraj Sidhu admits the mass adoption of blockchain in traditional financial services is still far off, especially in the institutional landscape, [where] regulatory uncertainty and questions regarding unproven tools and infrastructure have created barriers.

Yet, despite these barriers to adoption, Sidhu feels a need for secure, accurate and instantaneous settlement in the financial services industry is driving many banking institutions to explore ways of leveraging the benefits of blockchain.

He adds that blockchain adoption can proliferate across traditional services once four key barriers are overcome: privacy preservation, regulatory clarity, standardisation, and scalability.

For Peter Greiff, Data and Analytics Team Leader EMEA at DataStax, the issue of blockchains slow cross-market extension is simpler; its a matter of trust, or more specifically, too much trust. Using blockchain is ideal when there is less trust between the parties involved.

In finance, the number of use cases where all those transactions take place without trust is actually small. Banks and financial institutions rely on compliance regulations and backing by governments, which is why they are trusted.

So, while Greiff can see blockchain being useful for records over time and providing tracking for transactions, its use for secure monetary transactions isnt strictly necessary at established financial institutions.

Bringing blockchain to finance

Given blockchains use in traditional financial institutions could look markedly different from its function as a fraud safeguard when it comes to crypto, financial services firms are understanding the wider potential of blockchain slowly but surely, according to Sidhu.

However, before this potential can be truly actualised, Kubli feels the implementation of open banking standards, ultimately introducing smart financial contracts as a means to remedy the current barriers to adoption, will enable legacy institutions to begin implementing blockchain-based innovations.

He adds: Ensuring standardisation via smart financial contracts will enable things like an entire mortgage process, including the underlying obligations, to be placed on the blockchain and become machine-readable, executable, and automated.

This will bring about the true financial potential that is currently missing, and even bring new stability to the existing finance world.

The possibilities blockchain can bring to traditional financial services dont stop there. Sidhu believes asset tokenisation will become an effective way to automate the security issuance process and democratise access to previously illiquid asset classes.

Private equity is a good example currently, private firms such as start-ups have limited options when raising capital. Tokenisation provides a pathway to open new markets and liquidity to these types of firms, he adds.

Post-trading clearing and settlement, too, is something Sidhu feels blockchain can help innovate, calling the current process highly inefficient and fragmented.

The industry currently spends over US$130bn annually in this area, so, unsurprisingly, organisations such as the Federal Reserve and Bank of England are experimenting with blockchain technologies to automate these processes.

For Greiff, combining blockchain technology with distributed databases and streaming technologies will allow financial institutions to get real-time updates for on-chain transactions, and the ability to apply analytics to that data in real-time as well.

Scaling blockchain: the drawbacks

While the scope for blockchains use at traditional financial institutions is evident, should barriers to adoption be overcome, it will need to scale significantly from its current models of use.

With this comes problems, though. Crypto data mining has faced criticism for the amount of energy it consumes through the traditional Proof of Work (PoW) model employed by the likes of Bitcoin and other crypto networks.

However, the more energy-efficient Proof of Stake (PoS) mining model could be the way forward for financial institutions. Crypto trading platform Ethereum recently switched from the traditional PoW to a PoS model and reported a 99% drop in the amount of energy needed to secure the network.

Notwithstanding the perks of PoS models, a switch in mining models is just one barrier to scalability. As Greiff notes: Blockchain cant meet some of the transaction throughput or analytics requirements that companies have.

For example, Bitcoin has around 19.3m coins and sees 500,000-650,000 global transactions per day. Ethereum reached a maximum of 1.9m transactions on one day but tends to be around the 1.2m transactions per day level globally.

In comparison, banks, retailers and payment systems providers cover billions of transactions per day, which is an order of magnitude higher.

To reach the next level of scale, blockchain platforms must innovate ways to carry out real-time analysis on a far greater number of transactions, to meet anti-money laundering and anti-fraud requirements.

The future of blockchain

So, while blockchains path to mass use in traditional financial services is still a bit murky, the standardisation of blockchain-powered financial assets, such as CBDCs, is something Kubli feels we are destined to see.

He adds: As regulations tighten, any assets that dont embrace standardisation will be at risk of non-compliance. There could be exceptions, of course, but any projects that want to be adopted by major financial players will likely adopt this approach.

Once implemented, tokenised financial assets can bring in improved liquidity and new forms of financing for the entire economy.

Sidhu agrees, saying the timing of when tokenised financial assets hit the market will depend on the institutional sector. Wall Street firms such as JP Morgan Chase, BlackRock, Fidelity and Goldman Sachs are defining their approach to blockchain technology, while 114 countries including the UK and US are exploring CBDCs.

Tokenisation of real-world assets could one day be a multi-trillion-dollar market. However, if blockchain and crypto are to become the norm in the future, strides in regulatory harmonisation, standardisation and technology are required.

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Komatsu’s Operation Guidance Monitor for smaller mines and quarries – International Mining

August 3, 2023 | Author: admin

Posted by Paul Moore on 3rd August 2023

Away from very large open pit mines Komatsu offers digital solutions for smaller mines and quarries. Operator Guidance Monitor (OGM) it says is a revolutionary tool designed to optimise fleets of rigid dump trucks, and to reduce unit production costs. Its easy-to-use, clear program allows users to set Key Performance Indicator (KPI) targets and adjust operating parameters, to let Komatsu trucks operate in the most efficient way possible.

The OEM states: OGM is a tool thanks to which operators control and optimise their work in real time. It helps raise and refine their skills, resulting in higher fuel savings and productivity, and increased safety on the jobsite. Marek Skrzydel, Quarry Manager at Heidelberg Materials says: This system allows us to analyse data in real time and we can analyse production and discuss the achieved goals by operator on an ongoing basis.

Customers can quickly set parameters such as payload, planned duration and fuel consumption for each work cycle, idle time, and production (tonnes per hour), target by loading and dumping location. The OGM screen also shows real-time warnings for dangerous operating events, such as excessive speed and sudden braking.

Thanks to a unique login ID, operators performance can be analysed individually. Can-bus data from the machines operation are sent automatically, the user has access to them via a webbased dashboard. The data can be filtered by date, machine, shift, operator and loading and dumping locations.

Operator guidance monitor is one of the new digital Komatsu solutions to support our customers with their daily quarry operation, says Wouter Boon, Telematics Specialist at Komatsu Europe. Operator guidance monitor gives a possibility to set visualised KPI for the operators and follow up and adjust if needed in real time.

In the back office, target KPIs and event thresholds such as speed limits are set up for each haul road from any remote location. The status of each target can be followed by date, time, shift, or operator. The automatic data acquisition from the machine allows remote reporting of production and event data via the dashboard.

Each operator has his own OGM account. Before starting work, he or she logs directly into the tools easy-to-operate 8 in monitor installed inside the cabin. After logging in, the system automatically detects and displays the haul road specific KPIs on the monitor, according to which the operator adjusts the pace and dynamics of the haulers work.Thanks to real-time feedback of operation data, each operator can follow up on individual KPI, as optimal values when loading, transporting, and unloading material.

With parameter values updated in real time, the operator learns how to operate the machine at its best. No input from the operator is required and self-learning is encouraged through this visualisation of operation performance. This all results in fuel savings and more efficient production, achieved in the safest way possible. With real time operator alarms for unsafe operation, such as over speeding or sudden braking, job site safety is improved and can be monitored continuously.

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UK and Zambia announce renewables and mining investments – Mining Technology

August 3, 2023 | Author: admin

The British Government has agreed a partnership with Zambia covering clean energy and critical mineral supply worth more than $3.7bn (2.91bn).

Under the clean energy and green investment partnership, the UK will aim to generate $3.1bn of private sector investment for the Zambian mining and renewable energy industries. A further $600m of funding will come in the form of UK Government-backed investments.

Approximately 70% of Zambias export earnings come from mining. In 2022, Zambia was the worlds eighth-largest copper producer, and second in Africa. In the same year, it was also the worlds 13th-largest cobalt producer.

Cobalt and copper are both vital components of lithium-ion batteries vital in the energy transition. Securing a consistent supply of both would aid Britains stated goals of reaching net-zero carbon emissions by 2050, and attracting investment into the country for transition technology producers such as battery makers.

The Zambian renewable energy sector will also receive investment. The country hosts a large share of the Zambezi River basin and hydroelectric power generates 94% of the countrys power mix, totalling 2,257MW. As a result, Zambia produces renewable electricity at a price of around 8 per kilowatt-hour (kWh), approximately half of the average cost in Africa, making the country a cheap yet bountiful site for renewable investments.

Solar energy investment is also an area of promise in Zambia, with the country averaging around 5.5kWh/m of solar irradiation per day, showcasing the high potential for large-scale solar generation. Zambia experiences around 3,000 hours of sunshine annually.

In 2022, the UK Government stated its aim to diversify its critical mineral strategy by collaborating with international partners and enhancing overseas mineral markets. In 2019, Britain agreed the UK-Zambia Green Growth Compact for collaboration with the country, on which the latest investments are based.

Following a visit to Zambia where the deal was agreed, British Foreign Secretary James Cleverly stated: The UK-Zambia Green Growth Compact and our landmark agreement on critical minerals will support investment between UK and Zambian business, creating jobs in both countries, and improving environmental and social standards.

Zambia has previously been referred to as a safe haven for foreign direct investment into the mining and energy sectors.

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New York’s tech scene is back, but not in trophy headquarters – Crain’s New York Business

August 3, 2023 | Author: admin

Tech CEOs travel a lotthats not news. They fly to meet investors on both coasts, and to pitch or coordinate with strategic partners around the world. For Esipov, it was growth that led him to move eastward, since more frequent in-person meetings with East Coast partners like American Express made the jet commute less tolerable.

A leader whos here just a fraction of the time can still drive local job growth, however. On the Tech:NYC job board, there were about 5,300 positions open with tech-industry employers who are members. A search for remote yields about 600 positions, but many more express flexibility. The board includes all jobs that can be done in New York, regardless of the headquarters address or founders location. Hugging Face, a hub for open-source AI tools, maintains an office in Paris and in Downtown Brooklyn, and its founder reportedly dwells in Florida. We support our employees wherever they are, one of its job listings reads.

Even before Esipov made it official, about half of his employees were based in New York City, he said. The company leases 5,000 square feet in the Flatiron District for the group, which includes members of every company teamcore administrative, go-to-market, legal, compliance and product engineering. It has long been in both the enterprise and consumer tech playbooks to post sales or marketing teams in New York City, while keeping core development or product elsewhere. That was the script Esipov followed, keeping NovaCredits go-to-market team here near banks and credit card firms. Then in 2021 and 2022, three Bay Area-based engineers asked if they could make the cross-country move to New York. Its become the headquarters of the company, he said. A San Francisco office with about one-quarter of employees will remain open.

From an economic development perspective, provided they put people on the ground, including the tech team, the physical headquarters of a company is not its most relevant feature, said Maria Gotsch, president and CEO of the Partnership Fund for New York City. In fact, Gotsch sees the question the other way: The growing talent pool attracts companies to come work here, since they know they will be able to hire. Anecdotally, leaders say the San Francisco-to-New York City move was a common journey for the countrys engineers during the great office untethering of 2020 to 2022.

Post-Covid we have more talent than ever, said Jonathan Lehr, partner at Work-Bench, which invests in enterprise tech firms. If we think about it company-wise, its a net positive. With talent, while not every founder or chief marketing officer is here, there is more talent than there was.

Still, the size of the tech pool is not growing as fast as in other places. Both Boston and the San Francisco Bay Area had double the tech talent growth between 2017 and 2022 as New York City, according to the CBRE data, and Dallas-Fort Worth and Seattle had increases of 28% and 29%, respectively. Austin, Salt Lake City and Phoenix are smaller markets that boasted even more growth.

The writer E.B. White said that newcomers give New York City its passion. He did not live to witness the enthusiasm of the tech nomads and recent arrivals.

Events like the packed Arthur panel are becoming more common, participants in the tech scene say. Lehr said he noticed that newcomers eager to get out into the city and build their networks had been driving attendance at events like his firms Enterprise Tech Meet-up over the last year and a half. New Yorks key place on the international circuit guarantees that not everyones here all of the time, but when they are here, they have business and socializing to do.

Morgan Barrett, who works in the tech group at law firm Lowenstein Sandler, said he has recently been running into industry acquaintances from Texas seeking a respite from the above-100F temperatures there on the streets of SoHo.

Because its the summer, and its so hot in Austin, it feels like half of Austin is here, Barrett said.

He discovered the irrepressible nature of the citys tech scene when he and 10 friends in the industry got together for a breakfast catch-up at Balthazar. We had such a good time, he said, we decided to do it again in a few weeks. The next time the group met, 30 tech types came, then 60. Eventually, he and co-host Ariel Purnsrian started hosting Breakfast Clubs at event spaces, and they were still packed.

I always try to host in SoHo, he said, because its like the center of the universe for startups. The density of New York Cityand the even closer geographic ties of the tech neighborhood in Manhattan below 30th Streetmeans most people can stop in easily to the meet-up on their way somewhere else.

Inquiries for events and dinners from tech-sector clients have grown exponentially over the last six to eight months at SoHo French restaurant La Mercerie, said Dana Rizzo, its director of hospitality. There are client dinners, board meetings and press events, she said: With in-person time less frequent, they want to ensure moments of gathering are memorable and elevated.

The restaurant has a 28-seat table in its private dining room that appeals to companies looking to carve out time to be deeply connective and creative, Rizzo said. Clients have included the big players like Google and Meta, as well as out-of-town companies, like Uber, which Rizzo said hosted an event with its San Francisco-based CEO Dara Khosrowshahi in attendance. Like Barrett, she said the SoHo location makes for an ideal central hub in a remote work world.

The party does not extend to the office. Tech companies with distributed workforces need fewer square feet for desks and conference rooms. Several larger tech firms have recently downsized or called off expansions, and Newmark reports that Meta, Verizon and Publicis are rumored to be returning blocks of office space to the market soon.

The connection between remote work and a slower demand for real estate, even for companies that are committed to New York, is clear.

It is true that technology companies, large and small, are cutting back on their space needs, Fred Wilson, partner at Union Square Ventures, wrote on his blog in July. But that is more a reflection of the era of remote and hybrid workforces than anything else. That, he pointed out, does not mean that tech is no longer a growth industry here.

The story of Dayforward is an example. Launched in 2019, Dayforward sells accessible life insurance plans online to young families. At the helm is Aaron Shapiro, one of the founders of the digital advertising agency Huge, a company whose presence in Dumbo helped define the neighborhood as a hub for creative work in the 2000s.

Shapiro lives in Manhattan but the company is fully distributed.

A lot happened accidentally, he told Crains. He intended for Dayforward to sign a lease in 2020, but with the pandemic, we thought wed wait a little, he said. By the time everything opened up, the team was comfortable working remotely, and several key hires were living elsewhere. For example, Dayforward found its head of underwriting outside of Cincinnati. The 25% of the team based in New York still meet several times a week, but instead of leasing their own office, they go to a space at Juxtapose, the NoHo investor, thats reserved for portfolio companies. Shapiro does not rule out signing a lease for Dayforward some day.

To be sure, for every real estate-agnostic start-up, there are tech companies in physical growth mode. VTS, which sells software for commercial and residential building managers, just took 34,325 square feet at 3 Bryant Park, in a sublease from Salesforce, which will double its local headquarters. Celonis, a process-mining firm started in Germany, leased one floor at 1 World Trade Center in early 2020 and leased a second floor in the spring of 2022. Datadog, a cloud security firm that went public in 2021, leases over 150,000 square feet at 620 8th Ave.; its office has become a different kind of anchor than the meet-ups or the AI panels, said John Dickerson, chief scientist of Arthur.

We are only just starting to get the big players in the space, he said, calling Datadog the shining jewel of the New York scene because of its firm presence and deep integration with scores of other tech companies who use its cloud services and may need to meet its representatives in personsimilar to how the citys finance industry attracts fintech firms like NovaCredit to be on the ground in New York.

In addition to smaller and distributed firms, he said, We need that style of company.

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Friendship Day 2023: Privacy threat of online friendship, what does the research say about it? – mid-day.com

August 3, 2023 | Author: admin

Friendship Day 2023: While these digital connections offer unprecedented opportunities to connect and communicate with people across the globe, they also raise concerns about data privacy

Image used for representational purpose. File photo

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Online friendships have become an integral part of modern social interaction, enabled by the widespread adoption of social media platforms and virtual communities. While these digital connections offer unprecedented opportunities to connect and communicate with people across the globe, they also raise concerns about data privacy.

This piece delves into an in-depth analysis of the privacy threats associated with online friendships, drawing from various research studies and expert opinions.

Data Privacy Concerns

One of the most significant concerns surrounding online friendships pertains to data privacy. As individuals interact within virtual networks, they often share personal information, experiences, and emotions with their digital friends. This data may include location details, contact information, and daily routines. Unfortunately, research has shown that users may inadvertently disclose sensitive data, leaving them vulnerable to malicious actors who can exploit this information for identity theft, stalking, or targeted advertising.

Privacy Settings and User Awareness

The effectiveness of privacy settings plays a critical role in safeguarding personal data in online friendships. However, many social media users remain unaware of the available privacy settings or do not use them effectively. This lack of awareness can lead to inadvertent oversharing and expose individuals to privacy threats. Research suggests that education and user awareness campaigns are essential to empower individuals to protect their personal information.

Third-party Access

Social media platforms often collect vast amounts of user data to provide personalized services and targeted advertisements. The data collected can also be accessible to third-party apps and services through application programming interfaces (APIs). This raises concerns about the potential exploitation of user data by third-party entities, posing significant privacy risks.

Social Engineering and Phishing

Online friendships can become a gateway for social engineering and phishing attacks. Cybercriminals may exploit digital connections to impersonate a friend or use shared information to manipulate individuals into revealing sensitive data or falling for scams. Such deceptive practices can lead to severe consequences for the victims and compromise their privacy.

Cyberbullying and Harassment

The digital landscape presents unique challenges related to cyberbullying and harassment. Research highlights that online friendships can be susceptible to negative behaviors, leading to emotional distress and privacy concerns. Cyberbullying can cause psychological harm and erode trust in online relationships.

Data Mining and Surveillance

Social media platforms extensively engage in data mining to gather user information for targeted advertising and algorithmic content curation. The extensive data surveillance raises questions about user privacy and the potential misuse of personal data for commercial purposes.

Informed Consent

An essential aspect of online friendships is obtaining informed consent from users regarding data sharing and usage. Researchers emphasize that users should be aware of the potential privacy risks associated with digital interactions and be empowered to make informed decisions.

Context Collapse

Online friendships can lead to a phenomenon known as "context collapse," where individuals mix different social circles, such as family, friends, and work colleagues, within a single platform. This can create privacy conflicts, as certain information may be intended for specific groups and not for broader visibility.

Online friendships offer a plethora of opportunities for connection and communication, but they also come with privacy risks. The data shared within these virtual networks can be exploited by malicious actors and third-party entities, leading to identity theft, cyberbullying, and social engineering attacks. To mitigate these threats, user awareness, effective privacy settings, and informed consent are essential. As technology continues to evolve, it is crucial for individuals to prioritize their privacy and safeguard their personal information while engaging in online friendships.

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Biopharmaceutical third-party logistics Market Size, Share and … – Digital Journal

August 3, 2023 | Author: admin

PRESS RELEASE

Published August 3, 2023

Biopharmaceutical Third-Party Logistics Market to reach over USD 176.28 billion by the year 2031 Exclusive Report by InsightAce Analytic

InsightAce Analytic Pvt. Ltd. announces the release of a market assessment report on the Global Biopharmaceutical Third-Party Logistics Market Size, Share & Trends Analysis Report By Supply Chain (Cold Chain, Non-cold Chain), By Service Type (Transportation, Warehousing & Storage), Region, Market Outlook And Industry Analysis 2031

The global Biopharmaceutical third-party logistics market is estimated to reach over USD 176.28 billion by 2031, exhibiting a CAGR of 5.2% during the forecast period.

Get Free Sample Copy of Report : https://www.insightaceanalytic.com/request-sample/1935

A service called biopharmaceutical third-party logistics allows pharmaceutical companies to import and export biopharmaceutical ingredients with the help of third-party logistics. Inventory management, warehousing, and fulfilment to a third-party business authority are some services third-party logistics provide. This procedure comprises two corporate activities working together under contract.

By providing green solutions that encourage energy efficiency, lower carbon emissions, and advance sustainable practises across industries, the Global Biopharmaceutical Third Party Logistics Market will take the lead in this movement. This is in line with the rising demand for ethical and responsible solutions, opening up enormous growth potential for market participants.

In the Biopharmaceutical Third Party Logistics Market, the non-cold chain sector, which will account for the biggest revenue share of 81.3% in 2020, is receiving more attention than the cold chain segment. The widespread distribution of drugs and vaccines, high visibility, cost-effective optimization, and higher returns with lower risk, and these elements all contribute to the markets growth. They also aid in the development of a robust logistic network.

List of Prominent Players in the Biopharmaceutical third-party logistics Market:

Market Dynamics:

Drivers-

Technological advancements are a major factor in the expansion of temperature management logistic services. Emerging technologies like warehouse robotics, mobile cloud solutions, data mining, and real-time monitoring have an impact on the logistics sector. A global survey conducted in July 2021 revealed that third-party logistics providers (3PLs) prioritize cold chain services. More than 60% of 3PL service providers think that the future of their business depends on the availability of cold chain services.

Challenges:

The COVID-19 pandemic also significantly impacted global logistics, partly due to decreased air freight capacity and staffing levels at ports, warehouses, and airports. The biopharmaceutical third-party logistics market severely harmed small firms that typically lack a recovery, backup, or intermittent operating plan. Technological improvement is one of the main elements influencing the use of temperature management logistic services. Technologies like real-time monitoring, mobile cloud solutions, data mining, and warehouse robotics have significantly altered the logistics sector.

Regional Trends:

In 2022, North America held an enormous market share, contributing more than 42.0% of worldwide revenue. This is attributable to the regions dominance in the pharmaceutical and biologic medications market and a surge in biopharmaceutical exports and imports. Additionally, the adoption of new technologies is moderately increased in the region due to the high cost of healthcare. Pharmaceutical firms with operations in North America depend increasingly on 3PL service providers to optimize warehousing and transportation, fueling regional growth. Furthermore, the presence of essential firms supports the regions progress.

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Recent Developments:

Segmentation of Biopharmaceutical Third-Party Logistics Market-

Biopharmaceutical Third-Party Logistics Market By Supply Chain-

Biopharmaceutical Third-Party Logistics Market By Service Type-

Biopharmaceutical Third-Party Logistics Market By Region-

North America-

Europe-

Asia-Pacific-

Latin America-

Middle East & Africa-

For More Customization @ https://www.insightaceanalytic.com/report/biopharmaceutical-third-party-logistics-market/1935

About Us:

InsighAce Analytic is a specializing in market research and consulting services that helps in building business strategies. Our mission is to provide high quality insights with using data analytics techniques and visualization tools that drives the disruption and innovation in market research industry. Our expertise is in providing syndicated and custom market intelligence reports with in-depth analysis and key market insights in a timely and cost-effective manner.

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Why Palantir Technologies Stock Soared (Again) on Monday – The Motley Fool

August 3, 2023 | Author: admin

What happened

Shares of Palantir Technologies (PLTR -1.10%) charged sharply higher (again) on Monday, spiking as much as 12.3%. As of 1:50 p.m. ET, the stock was still up 8.6%. This marks the second consecutive day of remarkable gains, as the stock gained more than 10% on Friday.

The artificial intelligence (AI) and data-mining specialist moved higher Friday on an initiation and bullish commentary by a veteran Wall Street analyst. That same analyst was making the rounds to discuss his call, further stoking excitement about the stock.

To recap, on Friday, veteran Wedbush analyst Dan Ives initiated coverage on Palantir, assigning the stock an outperform (buy) rating and a $25 price target, which represents potential gains for investors of 55% compared to Thursday's closing price. The analyst's bullish commentary helped drive the stock higher.

Ives followed up that call by making the rounds on the financial programming circuit, comparing Palantir to soccer great Lionel Messi, who led Argentina to a FIFA Cup win last year. Ives points out that while many companies peddling AI solutions are Johnny-come-latelies, Palantir has a proven track record of success. He further argues that the company's history of top-secret contract work for the U.S. government and its allies gives Palantir a great deal of credibility, particularly in terms of data security.

I've long argued that Palantir's stock is a buy, as investors climbed the wall of worry about its ability to offer competitive solutions to enterprises. The company recently added a new layer of AI functionality onto its existing solutions, and CEO Alex Karp said demand for its Artificial Intelligence Platform (AIP) "is without precedent," which suggests Ives commentary is spot on.

Palantir stock is quite pricey, selling for more than 15 times next year's sales. That said, given the company's long track record and growing market opportunity, I'd argue that the premium is well deserved.

We're still in the early stages of the AI revolution, and Palantir is well positioned to ride these secular tailwinds higher.

Danny Vena has positions in Palantir Technologies. The Motley Fool has positions in and recommends Palantir Technologies. The Motley Fool has a disclosure policy.

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The Role Of Big Data In IoT in 2023 – IoT Business News

August 3, 2023 | Author: admin

By Laurenz Dallinger, Application Engineer at Cedalo.

The number of IoT devices and the data they generate is constantly increasing. Organizations use IoT data to obtain useful information, optimize their work, and increase profits. Therefore, it is necessary to use technologies that can process and analyze IoT data effectively.

The Internet of Things (IoT) refers to a network of devices and sensors capable of collecting and exchanging data over a network. After receiving the data, the device processes it and can perform certain actions such as sending notifications, automatically configuring devices, etc.

Key Components of IoT:

Big data refers to the extensive and complex datasets derived from diverse sources that are challenging to process using traditional methods. Nevertheless, businesses need to analyze big data to identify trends and patterns in user behavior to offer in-demand products and services. The trend is towards on-demand services. You no longer buy multiple devices that you then have to connect and you save money. You buy the result, preferably without having to buy the devices (e.g., a cloud application).

Big data and IoT are closely interconnected and dependent on each other. IoT devices constantly generate a huge volume of various data. This includes structured, semi-structured, and unstructured data obtained from various types of sensors and devices, which increase the variety and volume of big data.

The rapid development of the Internet of Things has contributed to the development of big data technologies, which are widely used to analyze IoT data.

To obtain useful information and identify patterns, companies apply big data analytics methods and tools to IoT data. This allows them to gain valuable information about system performance, customer behavior, predictive maintenance, anomaly detection, etc., and make decisions based on that information.

Big data analytics techniques and tools are used to process and analyze huge amounts of IoT data. Tools like Apache Spark, Apache Storm, and Flink allow companies to process the high-speed streaming data generated by IoT devices. Machine learning, data mining, and predictive modeling are used to make decisions based on IoT data.

Big data technologies enable the integration of IoT data with other data obtained from other sources. For example, customer, sales, and supply chain data. This allows organizations to get a complete picture of their activities, customers, or processes to provide a better understanding of complex systems and processes.

Big data technologies such as distributed file systems and cloud storage platforms are used to store and manage IoT data. They are fault-tolerant, support replication, and allow organizations to reliably and efficiently store large amounts of data.

Using the IoT and Big Data together helps companies effectively analyze data, identify trends, and make decisions. Lets list the main advantages of using big data in IoT for business.

Big data analytics in IoT allows companies to better understand customer behavior and market trends. This allows them to make the right strategic decisions and conduct marketing campaigns to expand the business.

Thanks to IoT devices, businesses can gain detailed information about their operations, processes, and assets. By analyzing this data, they can identify inefficient processes, reduce downtime, and reduce costs. With the help of special sensors, administrators can also detect equipment malfunctions and schedule device maintenance to avoid breakdowns and unplanned downtime.

IoT devices provide valuable information about product usage and customer feedback. This information is used to develop new features, optimize design, and adapt the product to customer needs.

A variety of IoT sensors enable real-time supply chain tracking. E.g., they provide information about the amount of fuel, the location of the car, the delivery route, etc. Using this information, companies can identify bottlenecks, improve inventory management, and optimize overall supply chain efficiency.

Although big data in IoT plays an important role and brings many benefits for business, it is also important to consider some challenges and risks of its use. Lets look at some of the problems that may arise when implementing this technology.

IoT devices are vulnerable to cyber threats, and the data they collect may contain sensitive information. Therefore, it is an important task to protect the data of IoT devices during transmission, processing, and storage. Keep in mind that every security measurement adds to the potential risk of overhead.

Every day, the amount of data generated by the Internet of Things is increasing. Storing and processing this amount of data requires significant investment in scalable data storage, processing, and analytics infrastructure.

Using MQTT is particularly resource-efficient for storing and processing large amounts of data. So, it is important to choose an MQTT broker, which plays a critical role in ensuring efficient communication and data exchange between devices, facilitating the seamless flow of big data in IoT.

IoT devices continuously generate and transmit data in real-time. Real-time streaming data processing and analysis requires the latest technologies to manage high-speed data flow and obtain useful information on time.

Visualization of a huge amount of data of many different formats and types in real-time is a rather difficult task. Therefore, companies have to implement new data visualization capabilities to better understand the data.

Big data in IoT is useful for various business sectors. Lets look at some examples.

Big data analytics in IoT allows banks to identify and resolve problems faced by users. In addition, special algorithms are used for analyzing customer behavior and detecting fraud.

Connected health monitors make it easy to remotely monitor various patient health indicators. Special machine learning algorithms can detect negative trends and inform the doctor on time, saving patients lives and health.

IoT devices and sensors in retail stores can generate vast amounts of data on customer behavior, footfall, and inventory levels. Big data analytics in IoT enables retailers to gain insights into consumer preferences, optimize store layouts (e.g., heatmaps), personalize marketing campaigns, and improve the overall shopping experience.

IoT devices embedded in assets or vehicles provide real-time location data. Combining this data with IoT Big Data analytics enables effective tracking, inventory management, and optimization of logistics operations.

Big Data analytics in IIoT optimizes manufacturing processes, improves supply chain management, and enhances product quality. By analyzing data from sensors, machinery, and production lines, organizations can identify bottlenecks and optimize workflows. Using AI algorithms, IIoT systems can make automatic decisions without human intervention.

Big data plays an important role in the IoT system. The use of big data in IoT enables the efficient storage, processing, and analysis of huge volumes of data generated by IoT devices. It allows companies to easily obtain important information about internal processes, improve marketing activities and supply chain management processes, effectively analyze user needs, and implement new technologies.

However, working with a huge amount of real-time IoT data requires solving some significant problems, such as using a scalable and reliable infrastructure, ensuring data and device security and privacy, and implementing advanced analytics and data management techniques.

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The Global Composite AI Market size is expected to reach $8.5 billion by 2030, rising at a market growth of 36.9% CAGR during the forecast period -…

August 3, 2023 | Author: admin

ReportLinker

The need of Composite AI in Security & surveillance is growing as organizations may increase situational awareness, strengthen threat detection capabilities, automate monitoring procedures, and allow more effective and proactive security actions by using composite AI in security and surveillance.

New York, July 31, 2023 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Global Composite AI Market Size, Share & Industry Trends Analysis Report By Technique, By Vertical, By Application, By Offering, By Regional Outlook and Forecast, 2023 - 2030" - https://www.reportlinker.com/p06481214/?utm_source=GNW Therefore, Security & Surveillance acquired $83.4 million revenue in the market in 2022. Composite artificial intelligence (AI) may significantly advance numerous elements of safety monitoring, danger identification, and response. The market is predicted to expand due to the increased requirement for data protection since many firms have recently experienced severe security breaches and data breaches.

The major strategies followed by the market participants are Partnerships as the key developmental strategy to keep pace with the changing demands of end users. For instance, In June, 2023, Google LLC signed a partnership with Sysdig to integrate its generative artificial intelligence (AI) features with Sysdigs cloud security platform. The partnership would provide the joint customers of the two companies with secure cloud-based automation solutions that would drive better productivity. Additionally, In June, 2023, Salesforce extended its partnership with Google Cloud to develop solutions for AI-powered customer experience solutions. The partnership would allow the two companies to provide their clients with personalized customer experience solutions.

Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation and Google LLC are the forerunners in the Market. In June, 2023, Microsoft Corporation extended its partnership with HCLTech, an Indian IT company, to provide generative AI-powered business transformation solutions to enterprises. The partnership would allow Microsoft to serve its customers in a better way by providing them with solutions for better decision-making through the use of AI-powered operational insights. Companies such as Intel Corporation, NVIDIA Corporation, SAP SE are some of the key innovators in the Market.

Market Growth Factors

Real-time decision-making via integration with edge computing and IoT

Edge computing adoption is being fueled by the ubiquity of Internet of Things (IoT) devices and the need for real-time decision-making. By processing and analyzing data locally, composite AI systems linked with edge devices may lower latency and enable quicker insights and answers. This integration makes the deployment of composite AI solutions in edge computing settings possible. Intelligent applications and 5G/6G Internet of Things (IoT) networks rely heavily on edge computing. The IoT ecosystem creates enormous, heterogeneous, extremely noisy, spatiotemporal-correlated, real-time data streams that need intelligent learning for effective data analysis and insight extraction. These devices include sensors, mobiles, and memory units.

AI applications are becoming more intricate to improve performance and accuracy

The complexity of AI applications is increasing, necessitating the fusion of many AI models and technologies. Organizations are now dealing with the fact that training a large neural network using ML only sometimes scales to address challenges of growing complexity. In conclusion, the increasing complexity of AI applications will support the rise of the market for extraordinary performance and accuracy.

Market Restraining Factors

Issues with data security and privacy

Due to a lack of confidence in AI technology or incomplete awareness of its potential and constraints, some businesses could hesitate to employ composite AI solutions. Implementation challenges may also arise from worries about data security, privacy, and possible biases in AI algorithms. Data leaks and illegal access to private information are the key privacy issues with AI. Thus, over the projection period, worries about data security and privacy may restrain the development of the market.

Offering Outlook

Based on offering, the market is segmented into hardware, software, and services. The software segment held the highest revenue share in the market in 2022. Composite AI software often provides a platform or framework that enables the smooth integration and orchestration of several AI models or algorithms. It allows users to make better judgments by using the many capabilities of these AI components to address complex problems. Organizations may create sophisticated AI applications that process and analyze various data kinds, comprehend complicated patterns, provide insights, anticipate outcomes, and carry out activities that call for a mix of AI approaches using composite AI software.

Software Outlook

Under software, the market is bifurcated into AI Development Platforms & Tools, ML Frameworks, AI Middleware, and other software. In 2022, the AI Development Platforms & Tools segment registered the largest revenue share in the market. Businesses and developers may now design and modify AI solutions more quickly and simply because of the emergence of low-cost and accessible AI tools and platforms like TensorFlow, PyTorch, and IBM Watson. AI systems may speed up software development procedures like code compilation and quality assurance, which can cut down on the time and expense involved in developing software.

Technique Outlook

Based on technique, the market is categorized into proactive mechanisms, data processing, pattern recognition, conditioned monitoring, data mining & machine learning, and others. In 2022, the data mining & machine learning segment projected a prominent revenue share in the market. Techniques for data mining and machine learning are essential for commercializing Composite AI solutions. Composite AI systems that combine data mining and machine learning methods allow the system to analyze enormous volumes of data, find patterns, anticipate the future, and improve decision-making. Using datas power allows composite AI systems to offer intelligent, adaptive, and context-aware capabilities across a range of domains and applications.

Application Outlook

On the basis of application, the market is divided into product design & development, quality control, predictive maintenance, security & surveillance, customer service, and others. In 2022, the predictive maintenance segment registered a significant revenue share in the market. In predictive maintenance, which seeks to anticipate equipment breakdowns or maintenance requirements, composite AI may be beneficial. It provides better asset management methods, data-driven decision-making, and accurate projections.

Vertical Outlook

Based on the vertical, the market is segmented into BFSI, retail & eCommerce, manufacturing, energy & utilities, transportation & logistics, healthcare & life sciences, media & entertainment, government & military, telecom, and others. The BFSI segment registered the maximum revenue share in the market in 2022. In the BFSI industry, composite AI solutions are used for various purposes, including compliance and regulatory reporting, risk assessment and management, customer service, credit scoring, and fraud detection and prevention.

Regional Outlook

Region wise, the market is analysed across North America, Europe, Asia Pacific and LAMEA. The North America region led the market with highest revenue share in 2022. North America is a global leader in implementing and expanding composite AI solutions. The existence of cutting-edge AI technology businesses, strong R&D skills, and a developed market ecosystem all play a role in the regions fast rise of composite AI solutions. Composite AI is being used by major sectors, including healthcare, retail, BFSI, and manufacturing, to promote innovation, improve consumer experiences, and increase operational effectiveness.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include IBM Corporation, SAS Institute, Inc., Microsoft Corporation, Google LLC (Alphabet Inc.), Salesforce, Inc., Amazon Web Services, Inc. (Amazon.com, Inc.), NVIDIA Corporation, Intel Corporation, SAP SE, and Squirro AG

Recent Strategies Deployed in Composite AI Market

Partnerships, Collaborations, and Agreements:

Jun-2023: Microsoft Corporation extended its partnership with HCLTech, an Indian IT company, to provide generative AI-powered business transformation solutions to enterprises. The partnership would allow Microsoft to serve its customers in a better way by providing them with solutions for better decision-making through the use of AI-powered operational insights.

Jun-2023: Google LLC signed a partnership with Sysdig, a cloud-based security solutions provider, to integrate its generative artificial intelligence (AI) features with Sysdigs cloud security platform. The partnership would provide the joint customers of the two companies with secure cloud-based automation solutions that would drive better productivity.

Jun-2023: Google LLC partnered with Twilio Inc., a customer engagement platform, to integrate Twilios customer engagement offerings with Google Clouds generative artificial intelligence (AI). The partnership would allow Google to provide its clients with AI-powered customer engagement tools that would drive their business growth.

Jun-2023: Salesforce extended its partnership with Google Cloud, a cloud platform offered by Google, to develop solutions for AI-powered customer experience solutions. The partnership would allow the two companies to provide their clients with personalized customer experience solutions.

Jun-2023: Amazon Web Services Inc. announced an extended partnership with Lacework Inc., a cloud security services provider, to integrate Amazon GuardDuty with Laceworks portfolio. The partnership would allow Amazon Web Services to provide its customers with anomaly detection solutions that would drive better security outcomes.

May-2023: Microsoft Corporation signed a partnership with NVIDIA, an American technology company, to provide solutions for Ai-powered business transformation. The partnership features a combination of Microsofts Azure Machine Learning with NVIDIA AI Enterprise software that would allow the joint customers of the two companies to gain access to a protected business platform.

May-2023: NVIDIA Corporation partnered with ServiceNow, a software company based in the US, to provide workflow automation capabilities. The partnership would allow NVIDIA to serve its IT customers in a better way by providing them with generative AI solutions.

May-2023: SAP SE signed a partnership with Google Cloud, a cloud platform offered by Google, to integrate Google Clouds Data and Analytics Technology with SAPs portfolio. The partnership enables SAP to serve its customers in a better way by providing them with a portfolio that would simplify the data landscapes, perform advanced analysis and provide quick access to important business-related data.

Feb-2023: IBM Corporation announced a partnership with NASA, an American civil space agency, to develop AI-powered solutions for contextual analysis. The solutions developed by IBM in the course of this partnership would be useful to several other organizations including NASA, thereby, allowing IBM to strengthen its market position.

Feb-2023: Amazon Web Services, Inc. partnered with Baker Hughes, an energy technology solutions provider, to develop solutions for automated field production. The partnership would allow the joint customers of the two companies to increase their productivity by providing them with solutions for proactive management and automated field production.

Dec-2022: SAS Institute, Inc. entered into a partnership with Basserah, a data solutions provider based in Saudi Arabia, to provide solutions for data analytics to Saudi enterprises. The partnership allows SAS to expand its data analytics offerings and would allow the company to enhance its market share in the Saudi region.

Nov-2022: Squirro AG teamed up with Semantic Web Company, a knowledge graph provider, to launch Composite AI solutions. The collaboration would provide the joint customers of the two companies with better decision-making solutions by combining Squirros Insight Engine with Semantic Web Companys knowledge graph technology.

Sep-2022: Salesforce, Inc. entered into a partnership with AWS, an IT services provider based in the United States, to integrate the Salesforce Platform with Amazon SageMaker. The partnership allows the two companies to provide their customers with solutions to build business-specific AI models.

May-2021: SAP extended its partnership with Team Liquid, a leading worldwide professional esports organization. By using the power of SAP HANA, predictive & machine learning functionalities, and the SAP Business Technology Platform, Team Liquid would more rapidly and efficiently evaluate opponents approaches.

Jan-2021: SAP SE extended its partnership with Microsoft, an American multinational technology company. This partnership aimed to combine Microsoft Teams with SAPs intelligent portfolio of solutions and boost the adoption of SAP S/4HANA on Microsoft Azure. In addition, the companies also focus on simplifying and streamlining users journeys to the cloud.

Product Launches and Product Expansions:

May-2023: IBM Corporation announced the launch of the Watsonx Platform, an AI-powered solution that provided end-to-end workflow solutions. The Watsonx Platform features three product sets namely, IBM watsonx.ai, an AI-powered solution that facilitates generative AI and machine learning deployment, IBM Watsonx.data, a data store used for AI workloads and governed data applications and IBM Watsonx.governance, an AI-workflow solution.

Apr-2023: Amazon Web Services announced the launch of Bedrock, a service used for developing generative AI applications. The Bedrock features accessibility to Amazons Titan language models and customizability for data-specific needs. Furthermore, Bedrock can also be used with third-party language models.

Mar-2023: Salesforce, Inc. announced the launch of Einstein GPT, a CRM technology solution that utilizes AI to provide AI-created content at a hyper-scale. The Einstein GPT is compatible with Salesforce Data Cloud and features OpenAIs chatbot technology.

Mar-2023: NVIDIA Corporation introduced the NVIDIA NeMo framework and NVIDIA Picasso service. The NVIDIA NeMo framework is used for deploying large language models (LLMs) and facilitating enterprise hyper-personalization. The NeMo framework features NVIDIA DGX Cloud. The NVIDIA Picasso service is purely cloud-based and is used to create and deploy generative AI-based visuals. The Picasso service features Edify foundation for generating high-definition videos and images.

Mar-2023: SAP SE unveiled SAP Datasphere, a cloud-based data warehouse used for data integration and data cataloguing applications. The Datasphere features the SAP Business Technology Platform (BTP) used for data protection and governance purposes. Furthermore, Datasphere can be used with third-party technologies to overcome errors in data management.

Feb-2023: Google LLC unveiled Bard, a chatbot that leverages the use of AI for better results. Bard features the use of Googles Lambda language model that would facilitate humanlike interaction between the user and the chatbot.

Scope of the Study

Market Segments covered in the Report:

By Technique

Data Processing

Data Mining & Machine Learning

Conditioned Monitoring

Pattern Recognition

Proactive Mechanism & Others

By Vertical

BFSI

Telecommunications

Retail & eCommerce

Healthcare & Lifesciences

Media & Entertainment

Energy & Power

Transportation & Logistics

Government & Defense

Manufacturing

Others

By Application

Product Design & Development

Quality Control

Predictive Maintenance

Security & Surveillance

Customer Service & Others

By Offering

Hardware

o Processors

o Memory Units

o Networks

o Others

Software

o AI Development Platforms & Tools

o ML Framework

o AI Middleware & Others

Services

By Geography

North America

o US

o Canada

o Mexico

o Rest of North America

Europe

o Germany

o UK

o France

o Russia

o Spain

o Italy

o Rest of Europe

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The Global Composite AI Market size is expected to reach $8.5 billion by 2030, rising at a market growth of 36.9% CAGR during the forecast period -...

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Running the Mill – Hoist

August 3, 2023 | Author: admin

A US steel mill has seen its fully automated cranes system improve its operational efficiency.

When a major US steel mill in Arkansas required a new approach to coil handling for its rolled-toorder production strategy, its engineering and materials handling equipment partner, Morgan Automation, devised and implemented a fully automated, nonmanned series of three cranes to work with two coil transfer cars accepting hot coils off the walking beam from the hot mill. In manufacturing this system solution, Morgan turned to its long-time drives and motion control partner, Siemens, which provided a full complement of drive, programmable logic controller (PLC), safety input/output (I/O), power quality meters, PCs, wireless hardware plus communication software and its Totally Integrated Automation (TIA) Portal for commissioning and monitoring on the project.

The excellent reliability and performance of the Siemens solution on this project was invaluable in helping us achieve complete operational efficiency and zero downtime during the first six months of operation, says the president of Morgan Automation, Mark Sharamitaro.

This project involves the handling of approximately 1,000 coils or 30,000 tons of steel a day at the mill. A typical coil in this yard measures approximately 83in (outside diameter) by 82in (width) and weighs 28 tons on average. As the mill operates on a made to order mindset, there is a dual challenge of handling hot coils from the mill and organising their staging for shipment by truck, rail or barge, with an area (a quadrant) for coils heading via the coil transfer cars provided by Morgan to the pickling line tandem cold mill (the PLTCM is a production line that chemically cleans and flattens steel coils, utilising pickling and tandem cold rolling techniques) on the premises.

In the yard, the walking beam delivers the coils from the hot mill, then the crane grab secures the individual coils and places them in the coil transfer car or on a saddle in the appropriate quadrant on the floor. During low production times, the system reorganises the coil assortment into the proper positions to conserve storage space filling empty storage spaces and grouping common destination coils together with full tracking in real time. Each crane has a thermal imaging camera for temperature sensing plus a laser positioning system that reports its exact location on the yard. The thermal imaging cameras ensure coils are not moved until they cool, and the order in which coils are moved is prioritised based on the facilitys workflow. The comprehensive data tracking is displayed in the mill control room with real-time key performance indicator (KPI) calculations.

The goals for the autonomous yard included reduced rust and corrosion by eliminating the need for outdoor coil storage, improved coil handling to meet the shipping protocols, reduced energy costs by eliminating lift truck handling, and reduced physical distancing of coils through dense coil storage indoors, plus faster location of the coils on their saddles for crane handling into shipment staging areas.

Integration of the entire operation is handled by the proprietary Morgan Cephas logistic management system, which performs inventory tracking and routes every coil from the mill to the shipping stage in a time-sensitive and deterministic order of motion, with a rules-based engine for algorithmic decision-making. Cephas uses a custom yard map to optimise the placement of every coil, logging its position for precise inventory tracking. To optimise the efficiency of coil storage, the team at Morgan programmed Cephas to divide the yard into four quadrants, where coils are stored according to their final destination. Before receiving a coil, Cephas gathers and records all primary data associated with the coil. This includes its production specifications, as well as final shipping details.

When its time for a coil to leave the yard, Cephas knows exactly where to find it and will retrieve it automatically. The system is tightly integrated with the mills production and shipping schedule so that coils destined to leave the facility are automatically placed on a saddle where they can be handled by a forklift or placed on the transfer car and automatically moved to the PLTCM.

All the information management is transmitted and handled by mill personnel, using the in-house platform and virtual private network (VPN).

Morgan worked with the Siemens team to utilise the full range of product and software options for construction of the optimum materials handling, motion control and data management system for the yard.

When we automate operations, our team always starts with a thorough analysis of a companys existing processes, says Sharamitaro. Then, we apply our decades of engineering experience to design a custom automation system that addresses the challenges of that unique application.

We were bringing our established Cephas warehouse management system to this challenge and seeking to marry it to a single user interface, driven by the rules established by our customer, so theres essentially a single bucket of data on each coil, says Sharamitaro.

In that bucket are all the physical characteristics and temperature of the coil plus the determined location for placement. The data is transmitted through a series of Siemens Sinamics drive modules, Simatic PLCs and the Sinema network monitoring server, complemented by Simatic WinCC V16 supervisory control for monitoring over long distances. In addition, Siemens offered its Scalance wireless suite of ethernet switches and access points to communicate the ring topology and virtual local area network (VLAN) data to the mill control room personnel.

Siemens Siplus controller components were used outside of the e-house (a prefabricated space that houses electrical equipment and systems) because of the higher ambient temperatures, as these devices are built for more hostile environments. Sharamitaro reports that the Morgan team tested these components beyond their published ratings, so his team knew the components would perform in this application, especially at the moment when the crane would pick up a hot coil and hoist it up near the trolley with the controls onboard.

Sharamitaro also notes the need for an embedded quality system to identify secondary coils on the floor and determine their transfer path. As each coil is grabbed, a full battery of sensors, switches, I/O power supply, drives, PLCs and wireless communication sends information from the crane trolley directly to the control house. The three 190-ton cranes are thus fully synchronised for handling the incoming coils from the hot mill plus the placement of the coils in the transfer cars and staging lines. The information feeds the Cephas system, which makes the algorithmic determinations for each coil, based on predetermined parameters set by the mill.

When the system is in operation, every movement is carefully orchestrated, and every sensor is continuously monitored and logged with its time stamp, says Sharamitaro. This real-time data collection and evaluation allows the team at [the steel company] to continually identify and improve operational performance.

SAFETY

Morgan Automation integrated a number of safety-related features into the project, including a ground-based safety system that help protect workers from passing cranes. Mill personnel cannot access any of the four quadrants in the yard if the lockout devices are engaged. The system asks the crane for permission before allowing personnel to access the area. Nine remote I/O cabinets and 21 safety gates were implemented.

Sidewall sensors prevent the crane from damaging coils, while a selfcentring device ensures they are always positioned perfectly.

One of the individuals leading the project for Siemens was Roland Najbar, business development manager.

Once we had the full requirements from Morgan, we went to work assembling our motion control and material handling product and software suites to accommodate them, says Najbar. The need for fully unattended operation and wireless communication in the mill presented some challenges, but our team responded with a combination of timetested drive, wireless and PLC products as well as some newer offerings such as the Sinema network monitoring system.

He further notes that Morgan took the Siemens offerings to new heights of performance, through the integration with Cephas.

Najbar also cites the intentional redundancy in the drive safety and production isolation that allowed the cranes to keep working independently but in a highly integrated manner to achieve a non-stop production environment at the mill. The open communication protocol on the Siemens Simatic S7-1500TF PLC allows for C++ high-level language applications, such as protocol converters, database connectivity, and complex algorithms such as those on the Morgan Cephas system, plus integration of crane vision systems and laser trackers.

To evidence the energy savings, Siemens also provided its PAC3200 power meters that track and record power consumption and communicate data over a network protocol. Another key component in the Siemens solution here was the Sinamics S120 Smart Line Module for crane applications, which features onboard regenerative drive. This feature takes the excess motor power from a crane hoist, for example, during descent and feeds it to another component in the system or back to the grid for trackable energy savings to the customer.

Since commissioning the Morgan system, the facility is said to have improved operational efficiency, increased machine availability and reliability, reduced fuel costs, more efficiently utilised personnel labour, and reduced cycle times.

Were a technology company that just happens to make steel, says the CEO of the steel company. We embrace automation, big data mining, accurate measurements whether it be weights, consumption, what have you in everything that we do.

Morgan understands where the future of industrial America and industrial operations through the world need to get to to maintain top-level performance.

Morgan Automation is sister company to Morgan Engineering and part of the Morgan Industries group of companies, which has served the steel industry for over 150 years. Morgan Engineering is a designer of overhead electric travelling cranes, and manufacturer of more than 30,000 cranes.

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Running the Mill - Hoist

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