Accelerating the Industrial Internet of Things
Log In
Use Cases Asset Lifecycle Management (ALM)

Asset Lifecycle Management (ALM)

The objective of Asset Lifecycle Management (ALM) is to optimize the profit generated by assets over the course of their lifecycle. ALM integrates processes and technologies in order to manage asset portfolios, execute projects, and facilitate efficient asset management practices. Whereas Asset Health Management (AHM) deals with monitoring and optimizing the health the asset in real time, ALM extends across the lifecycle of the asset from design, to procurement, commissioning, operations, maintenance, and decommissioning. IoT technologies enable superior visibility, forecasting, and feedback loops across the ALM process. 

Read More
Filament | Woking Toward Industrial Blockchain
Filament | Woking Toward Industrial Blockchain
These are serious concerns, especially if blockchains are to usher in the kind of post-industrial revolution that its advocates are predicting. Most of us can’t even protect our passwords, much less our private keys; the idea of integrating a corporation with thousands of employees with a high-tech blockchain seems about as realistic as training a cow to trade derivatives.
The Mathematical Functions of IOTA
The Mathematical Functions of IOTA
The rise and success of Bitcoin during the last six years proved that blockchain technology has real-world value. However, this technology also has a number of drawbacks that prevent it from being used as a generic platform for cryptocurrencies across the globe. One notable drawback is the concept of a transaction fee for transactions of any value. The importance of micropayments will increase in the rapidly developing IoT industry, and paying a fee that is larger than the amount of value being transferred is not logical. Furthermore, it is not easy to get rid of fees in the blockchain infrastructure since they serve as an incentive for the creators of blocks.
Artificial Intelligence, Machine Learning, and Deep Learning | Dell EMC
Artificial Intelligence, Machine Learning, and Deep Learning | Dell EMC
Are you facing any of these challenges?“We haven’t been able to take full advantage of our data.”Data is growing at an astronomical rate and it’s impossible to take full advantage of it manually to get insights to win. Automation can help provide faster, better and deeper data insights. Dell EMC Ready Solutions for AI, Machine and Deep Learning can provide the processing power required for the vast number of calculations that need to be made very quickly — for facial recognition, for example. With the speed of automated image and pattern detection, these solutions can help provide better data insights. And with historical data sets, you can get deeper insights into, for example, buying behavior.“We can’t afford to run machine and deep learning in the cloud.”Some public cloud providers charge to get data out, and that can get expensive quickly with the large datasets required for deeper insights such as image recognition and fraud detection . Dell EMC Ready Solutions for AI, Machine and Deep Learning can reduce costs associated with moving significant amounts of data in and out of the cloud while minimizing risks .“We don’t have the in-house expertise.”AI and related computing paradigms are emerging quickly and not many organizations have had the time or resources to develop the skills required to design, deploy and manage advanced machine and deep learning solutions . The Dell EMC HPC Innovation Lab team stays on the cutting edge of AI, testing new technologies, and tuning algorithms and applications to help you keep pace with the constantly evolving landscape . This team of industry and technology experts can help you achieve faster time to results by shortening both design cycle and configuration time . These experts can work with you to create a solution with the right features, at the right price . You can even take a test drive with the HPC Innovation Lab with a proof of concept, in one of the Customer Solution Centers, or in one of Dell EMC’s worldwide HPC Innovation Centers .

The Application Lifecycle Management (ALM) market is expected to grow from USD 2.58 Billion in 2017 to USD 3.63 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 7.0% during the forecast period. 

Source: PRNewswire

Download PDF Version

p: +86 21 6010 5085 (ext 188)  m: +86 156 0183 9705
a: 338 Nanjing West Road, Shanghai 200003 China
e:  w:
twitter@IoTONEHQ  linkedin: IoT ONE

test test