Most professional advice will point towards a cloud-based service if your company explores hosting options for its official platform. Similarly, when you dive deep into the intricacies of cloud computing, you’ll find yourself bumping into Microsoft Azure and Amazon AWS as the two most viable options.
Since choosing between these two most popular options can be a little perplexing, we decided to clear the air for you. So, here’s a detailed comparison of Microsoft Azure and Amazon AWS.
Let’s get started.
A Closer Look at Microsoft Azure
Microsoft Azure is a leading cloud computing platform that renders services like Infrastructure as a Service (IaaS), Software as a Service (SaaS), and Platform as a Service (PaaS). It is known for its cloud-based innovations in the IT and business landscape.
Microsoft Azure supports analytics, networking, virtual computing, storage, and more. In addition, its ability to replace on-premises servers makes it a feasible option for many upcoming businesses.
Microsoft Azure is an open service that supports all operating systems, frameworks, tools, and languages. The guarantee of 24/7 technical support and 99.9% availability SLA makes it one of the most reliable cloud computing platforms.
The data accessibility of data Microsoft Azure is excellent. Its geosynchronous data centers supporting greater reach and accessibility make it a truly global organization.
It is economical to avail of cloud-based services, as users pay only for what they use. Azure Data Lake Storage Gen2, Data Factory, Databricks, and Azure Synapse Analytics are the services offered through this cloud-based platform. Microsoft Azure is especially popular among data analysts as they can use it for advanced and real-time analytics. It also generates timely insights by utilizing Power BI visualizations.
Azure provides seamless capabilities to developers for cloud application development and deployment. In addition, the cloud platform offers immense scalability because of its open access to different languages, frameworks, etc.
Since Microsoft’s legacy systems and applications have shaped business journeys over the years, its compatibility with all legacy applications is a plus point. Since converting on-premises licenses to a fully cloud-based network is easy, the cloud integration process becomes effortless.
In many cases, cloud integration can be completed through a single click. With incentives like cheaper operating on Windows and Microsoft SQL Servers via the cloud, Microsoft Azure attracts a large segment of IT companies and professionals.
Amazon AWS is the leading cloud computing platform with efficient computing power and excellent functionality. Developers use the Amazon AWS platform extensively to build applications due to its broad scope of scalability and adaptation to various features and functionalities.
It is currently the most comprehensively used cloud platform in the world. More than 200 cloud-based services are currently available on this platform.
Amazon Web Services include IaaS, PaaS, and SaaS, respectively. In addition, the platform is highly flexible to add or update any software or service that your application exclusively requires.
It is an Open Access platform where machine learning capabilities are also within reach of the developers – all thanks to SageMaker.
This platform has excellent penetration and presence across the globe, with 80 availability zones in 25 major geographical regions worldwide. But, just like Microsoft Azure, the Amazon AWS model is highly economical.
Businesses only need to pay for the services they use, including computing power and cloud storage, among other necessities.
The Compute Cloud offering allows you to use dynamic storage based on the current demands of your operations. You can use any operating system and programming language of your choice to develop on Amazon AWS.
Besides, all cloud integration services on the Amazon AWS platform are broad-spectrum and practical. The comprehensive tech support available 24/7 is a silver lining too.
The Amazon AWS platform enjoys excellent popularity with several high-profile customers. The transfer stability in the Amazon AWS offerings is quite good, implying that you won’t lose any functionality during migrations.
The instances of latency problems and lack of DevOps support are minimal with this platform.
Comparing Azure and AWS
By Computing Power
Azure and AWS have excellent computing power but different features and offerings. For example, AWS EC2 supports the configuration of virtual machines and utilizing pre-configured machine images. Further, images can be customized with the Amazon AWS platform.
Unlike the machine instance in Amazon AWS used to create virtual machines, Azure users get to use Virtual Hard Disks (VHD). Virtual Hard Disks can be pre-configured by the users or by Microsoft. Pre-configuration can be achieved with third-party automation testing services based on the user’s requirement.
By Cloud Storage
Storage in Amazon AWS is allocated based on the initiation of an ‘Instance.’ This is temporary storage because it gets destroyed once the instance is terminated. Therefore, Amazon AWS’s cloud storage caters to the dynamic storage needs of the developers.
Microsoft Azure also offers temporary storage through D drives, Page Blobs, Block Blobs, and Files. Microsoft Azure also has relational databases and supports information retrieval with import-export facilities.
By Network
The Virtual Private Cloud on Amazon AWS allows users to create isolated networks within the same Cloud platform. Users also get to create private IP address ranges, subnets, network gateways, and route tables. You can avail of test automation services to check the networking success.
The networking options on Microsoft Azure are like that of Amazon AWS. Microsoft Azure offers Virtual Network (VNET) where isolated networks and subnets can be created. Test automation services can help in assessing existing networks.
By Pricing
Amazon AWS’s pricing is based on the services you use. Its simple pay-as-you-use model allows you to pay only for the services you use – without getting into the hassle of term-based contracts or licensing.
Microsoft Azure, too, has a pay-as-you-go model, just that their calculations are by the minute. Also, Azure offers short-term packages where pre-paid and monthly charges are applicable.
The Bottom Line
We hope you’ve got enough to decide which cloud computing platform is most suitable for your needs. For more advice on Cloud Application Development, reach out to our team at [email protected]
Utthunga is a leading Cloud service provider catering solutions like cloud integration services, automation testing services, and digital transformation consulting. To know more about what we do, contact our representatives today.
Industrial connectivity has come a long way since the first time a PLC was controlled by a computer. Well! it was a ‘Hurrah’ moment for industries as it created a whole new horizon for innovative technologies. However, amid the gradual shift towards digitalization, the lack of efficient exchange of data among systems and applications was hindering the communication. When ISA-95 reference model came into light, it compartmentalized the automation architecture into different vertical layers based on the nature of data generated. While this model allowed various industrial manufacturers to innovate technologies keeping the architecture layers in mind, it also helped them understand the communication interdependencies among the systems across the layers. Fast forwarding to today, the coining of the term ‘Industry 4.0’ has emphasized on interlinking various systems (machines, devices, applications, etc.) from plant floor to the enterprise applications of ISA-95 to become a smart factory. This interlinking is possible through efficient connectivity solutions enabling smooth data exchange across the layers. These connectivity solutions are designed keeping the communication needs in mind. While a proximity sensor has a single function, i.e., to detect an object within a certain range, a controller is expected to send sophisticated instructions in different scenarios. Historically, these different communication needs have given rise to the application of various industrial communication protocols.
Factors Influencing the Evolution of Industrial Communication Protocols
As mentioned earlier, the evolution of industry protocols goes back to various scenarios that led various industrial associations and independent OEMs to develop various protocols. Some of the factors that influenced the emergence of various modern protocols are:
Interoperability: With generations of electronics and technologies evolving over the decades, the industries started facing difficulties in establishing compatibility among the heterogeneous devices at various layers, especially at the OT level. The devices developed by different manufacturers supported either vendor-specific proprietary protocols or Commercial-Off-the-Shelf (COTS) protocols. Due to this, the need for establishing interoperability among the devices became one of the primary concerns for smooth connectivity from plant floor to the enterprise layers and beyond. This generated the need for common platforms like OPC UA that allows all the devices to communicate in a common language unlocking the potential of IIoT.
Real-time/Determinism: When it comes to communication, industries need connectivity solutions that enable fast responsiveness, ensure real-time delivery of time-sensitive messages, and reduce jitter. The OEMs and various protocol consortiums are constantly working to innovate solutions for aforementioned criteria and more. In fact, communication standards and protocols like TSN (Time Sensitive Network) and Profinet IRT are already making significant progress.
Operating Environment: One of the most discussed aspects in industries is the safe operating conditions on the plant floor. While some nodes may exhibit a certain amount of heat, vibration, or noise, others may operate in a hazardous environment. Therefore, having stable connectivity channels for such scenarios has always been a challenge. For example, PROFIBUS DP is suitable for manufacturing, whereas PROFIBUS PA has dominated the process industries. In fact, the recent developments in Added Physical Layer on Ethernet (Ethernet-APL) promise to deliver better communication speed along with intrinsic safety benefits to process industries.
Mobility: As the plant operations get more complex, newer inventions replace the legacy systems. For example, the use of Automated Guided Vehicles has minimized the number of workers needed to transport materials within the plant. However, the use of wired connectivity does not fulfil the communication need here as the plant asset is mobile. The evolution of wireless protocols has helped overcome this issue. 5G technology will not only allow plant devices to communicate faster than a human possibly can, but will also ensure the delivery of time-sensitive message by slicing the bandwidth.
Scalability: As and when industries scale-up, new nodes/devices/machines are added in the network. However, expanding the network always puts a challenge in terms of additional configurations, implementation overheads, implications on existing network architecture, etc. This is the reason why self-healing wireless networks like ZigBee are designed.
Power Consumption: With multiple machines deployed on a plant floor, connecting them using specific protocols consumes a lot of power. As a matter of fact, the devices that are battery-powered or electric-powered, a single fault in the power source can seriously damage the entire connectivity. This can be especially a crucial aspect when an end-node is installed at a remote location. Therefore, the invention of low-power wireless networks like Bluetooth low energy, Wi-Fi, etc.
While the conventional purpose of the communication protocols was to provide seamless connectivity among the devices, digital disruption in industries is demanding more than that. The panorama of modern industries needs smooth convergence of OT and IT, which were two different worlds altogether. Along with intelligent devices, industrial protocols are bridging this gap.
Industrial automation pyramid with all 5 layers is a way to look at the communication happening within the system. However, it is not necessary to have all these layers as part of all the industrial network architectures. Since the advent of edge computing, industries are actively deploying it to bypass all the middle layers between control layer and the cloud. This means that the automation pyramid is reduced in size, or in other words, it is flattening, i.e., from 5 layers to just 2 or 3 layers. However, if you look closely, the role of seamless communication is quite important at the moment. While field devices release data at a higher frequency in smaller sizes, client applications on cloud require larger messages in low frequency. Therefore, the connectivity solutions must fulfill the necessary demands of the end industries. In the light of convergence, the role of communication protocols can be discussed at two levels:
Field to Edge
Field devices like sensors and actuators need communication protocols that allow them to communicate in robust way. Some of the communication protocols that are widely used on the field level to connect various machines and devices are IO-Link and the fieldbus protocols like Modbus, HART, Profibus, FF, and Control Area Network (CAN). In fact, Industrial Ethernet protocols like Profinet, EtherCAT, Ethernet/IP, etc., offer great potential to the complex and field devices network. The data transferred to the control layer gets processed and sent to the above layers or specific instructions are sent to the field devices. Therefore, the communication protocols should enable scalability. Some of the communication protocols that provide a scalable connectivity from the PLCs all the way down to I/O and Sensors are EtherCAT, Profinet RT, Powerlink, IO-Link, Modbus, Ethernet/IP, S7, MELSEC, etc.
Edge to Cloud
Conventionally, the data coming from the field and control layers get converted into enterprise-compatible format. However, communication protocols like SigFox, OPC UA, TSN, MQTT, AMQP, etc., are enabling communication right from the sensor to the cloud. The field level specifications of OPC UA, called OPC FLC is under development that will redefine the communication across all the layers of automation pyramid.
While connectivity is making a major progress in the industrial front, the OEMs are constantly on their toes to cater to the communication needs of the end industries. With varied demands of diverse industries, there is surely not one communication protocol that can fulfill them all. However, with continuous research and global consortiums coming forward, we can surely expect an influx of innovative technologies paving the way for seamless and improved communication. Utthunga is one of renowned names in industrial protocols that enables the various industry OEMs to engineer cutting-edge connectivity solutions. We are experts in providing device-level and software-level connectivity services along with verifying, verifying, and certifying the solutions at each step. Therefore, let us collaborate to help you fulfil your connectivity needs. Check out our Industrial Connectivity Services to know more.
Inspired to build a simple version of data aggregation and visualization for systems and applications, we have developed a dashboard builder tool for one of our clients. A global leader in industrial automation products and services, the client provides solution-based software and technology-driven industrial engineering solution. While there are many such tools in the market, what we have built is efficient and easy to use.
Widgets: This is the basic component of the dashboard tool. It has configurable elements like Title, Type of Chart, and other options. These widgets can be resized to fit a specific layout and moved around the dashboard to customize the display.
Dashboards: It is a combination of one or more widgets that provide statistics of configured motors, sensors, or other components in the plant. The dashboard can be customized to suit specific requirements in terms of features, functionalities, or visualization layout.
Templates: These are the industry-standard formats used for aggregation and display of data for individual field devices or the entire plant. The Administrator of the dashboard builder can create such templates based on preferences and requirements at various levels such as an operator, plant supervisor, or the plant head.
The primary javascript plugins used for this dashboard builder tool are:
React Grid Layout (RGL)
The RGL system is used for rendering multiple widgets in the dashboard. This helps layout mapping based on breakpoints. It provides intuitive and easy-to-use layout features for dragging and resizing the widgets that enhance the efficiency and responsiveness of the entire application.
Uplot
We experimented with different types of data visualization charting tools such as Chartjs, Victoryjs, and Uplot for rendering a large number of data points. Finally, based on the best time-series data rendering performance, we selected Uplot. With more than 1 Million points to be rendered, Uplot performed intended functions very efficiently.
Plotly
Other than time-series data, we also used 3D mesh plots and indicators for building effective data statistics features in the tool. Among multiple open source libraries, we used the Plotly library. This provided an excellent set of plots that render simple, yet insightful information for detecting anomalies.
React Table
For certain widgets, we wanted more than just regular table features like sorting (client/server-side), footers, and pagination. Among various options, we chose React Table plugin for its versatile features. We have used the standard list as well as the embedded table in the widget that gives the complete solution.
React Calendar / Date Range
The Date-range option is a very common, and also an important feature for any dashboard. For our client, we introduce predefined options for the shortcuts like last-1 Hr, last-5 Hrs, last-12 Hrs, last-1 Day, last-7 Days, and so on for capturing real-time data. Also, the custom date-range option feature for viewing historical data is a crucial dashboard feature. We found the React Date Range plugin an excellent fit for the use cases.
React Filters / Select
Searchable filters are the obvious choice for long data tables or reports. In our case, however, we needed a dynamic searchable component with intuitive selecting features. The React- select plugin provided us with the exact functionality that suited our requirements. On focus, it displays default drop-down options. Also, powerful features like search functionality with async data, and the color options matched nicely with the default bootstrap theme.
The Dashboard Builder Tool was developed within a short span of 2 months. The application is live in the client’s production environment, delivering delightful performance.
Utthunga cherishes innovating value-added solutions for its customers in various fields of industrial automation. For your queries and requirements write to us at [email protected].
Motion without control has no meaning, and almost certainly; is unproductive. Engineering and industrial motion control play a significant role in factory automation, with countless machines and components moving independently, and in tandem. Apart from the time factor, other elements such as force, speed, accuracy, and position play a crucial role in controlling and engineering the motion to deliver the specific outcome.
The earlier days of motion control technology were largely based on time-consuming and expensive solutions such as gears, cams, belt drives, etc. The next stage witnessed the era of electromechanical, hydraulic, and pneumatic offerings such as cylinders, solenoids, grippers, and so on. Now is the age of electronics and computer-based technologies that are compact, intelligent, and scalable. Programmable motion control, as they are called, employs codes and algorithms driven by various performance parameters that can be embedded in the software programs and memory of intelligent devices.
The primary objectives of innumerable motion control algorithms are to regulate speed, torque, and position. While every algorithm has select benefits based on the need, the below-listed ones are perhaps the most popular in the automation industry.
This algorithm works on the principles of output to input ratio (called gains) and feedback received in terms of Proportional, Integral, and Differential modes under motion control. It works only concerning position feedback of the target profile but can control both the position and velocity of the moving components.
The Position PID Algorithm underlines the target profile to define the axis of the motion for any given moment. The required motion control output is derived from information of target Vs. actual position of the motion axis, together with the required feed. Since this type of algorithm works on the principles of feedback from closed-loop motion control to compute process variables, a high degree of accuracy can be achieved.
Due to PID Algorithm’s efficient and accurate motion control capabilities, it is widely used in specialized automation like robotics as well as a day-to-day application such as cruise control in automotive.
Advantages
One of the most powerful algorithms that uses past, present, and future elements to respond to the logic of differential errors.
Excellent response and tracking capabilities to motion control based on high precision logic.
Widely used, accepted, and understood in industrial automation.
Disadvantages
Being a feedback algorithm, control is not possible unless errors are produced or identified.
Recovery from response lag results in poor performance on the motion control outcome.
Not ideal for advanced applications like defense and precision robotics.
The Trapezoidal algorithm is a motion control mechanism applied to Brushless DC Motors (BLDC). It operates on the commutation principle of the stator-rotor unit and employs switching on and off of electric current through the stator, in a specific manner. This results in the rotor spinning depending upon its polarity response to the magnetic field produced by the commutated rotor.
The spinning rotor causes back- EMF (electromagnetic force) as a result of opposing the current that induced its motion. This back-EMF results in the perpetual trapezoidal waveform, and hence the name Trapezoidal algorithm. This continuous commutation of electrical power can be affected with or without Hall sensors that detect the motor’s position.
This commutation technique also called as six-step algorithm, produces smooth rotation in six distinct directions relative to the stator.
Advantages
Simple, low cost, and reliable in terms of design and performance.
Low processing power is required for the motion control mechanism.
Efficient for high-speed and high-torque applications like power tools and drones.
Disadvantages
Inefficient for low-speed motion control.
Torque-ripple issues due to continuous commutation.
Also known as vector control, FOC is a high computational algorithm for motion control with an underlying objective of achieving maximum torque at a given speed. With rapid advancements of Integrated Circuits (ICs), FOC’s practical application has increased manifold in the recent past. So much so, that it has commoditized its benefits in day-to-day machines like drilling machines, cutters, and grinders (power tools) where battery and performance matter at all times.
Interestingly, FOC is the first technology that is offered to control the two most vital variables of a motor – torque, and flux. This practical advantage makes FOC the most suitable algorithm for high-performance motor applications. Moreover, the ability to deliver smooth operations across a wide range of speeds, produce maximum torque even at zero speed, generating quick acceleration or deceleration makes FOC a preferred choice for a wide range of industrial applications.
Technically in FOC, the current is bifurcated into two perpendicular components. The part that causes the perpendicular pull is the one that generates the torque. The other part responsible for the undesirable outward pull is the flux. FOC aligns these two components in such a way that maximum torque is achieved.
Advantages
Maximum torque response for a wide range of current
Fast dynamic response and steady performance
Greater control over torque and speed
Disadvantages
Sensor needed to determine rotor’s precise position
Reduced control and efficiencies in low-load conditions
Designing sensorless FOC requires expertise, and attracts a huge cost
While several motion control algorithms keep evolving, their network inclusivity and connectivity with devices is one of the most difficult tasks. Recent advancements in application control protocols using EtherNet/IP and EtherCAT technologies knit such intelligent algorithms with field devices and equipment. This helps delivering precision communication for variable frequency drives that make use of smart sensors and gateways.
Cloud-based remote motion control for industrial automation is the next big thing to happen. Currently, some of the motion control algorithms are already implemented in cloud applications. However, it would be interesting to watch how effectively these algorithms perform across distributed networks and systems. Soon, complex algorithms will be equipped to remotely control and monitor the position of the rotary motor and self-tune to overcome harmonic distortions caused by surrounding disturbances.
Due to the increasing demand for speed, accuracy, remote possibilities, and affordability, the future and scope of motion control algorithms is on the rise. However, this niche technology calls for greater thrust from leading enterprises and research scholars. Moreover, since the 5G technology is already influencing many industrial applications, motion control algorithms experts need due encouragement and support to make the best use of knocking opportunities. Timely and focused efforts in this direction can transform how man, machines and technology operate in the future.
We at Utthunga, provide technology based customized solutions to deliver world-class products and services. Please visit the motion control webpage for more information. For your requirements and queries regarding industrial motion control, write to us on [email protected] and our team of experts will connect with you offering world-class solution and services.
Wired sensors connected to control systems via industrial communication protocols like HARTor even a simple 4–20 mA loop take up the required energy supplied over the cabling. It is estimated that wiring takes up majority of the total sensor installation cost.
On the other hand, wireless sensors used for industrial control and automation offer the possibility to reduce overall installation cost as well as reduce the effort required to install the sensor. However, sustainability is an inherent problem when it comes to use of wireless sensors. This is because of the need of a battery on each wireless sensor node and battery replacement can be a costly and time-consuming affair. Many industrial OEMs and end users are willing to explore the benefits of wireless sensors but are concerned with the battery-related cost and maintenance they have to incur when there are thousands of the sensors deployed across their plants.
To counter this problem, energy harvested from ambient energy sources such as air, RF, mechanical, heat and vibration, has been proposed as a sustainable solution for supplying energy to wireless sensor devices.
Sensors used in the plants have to record crucial measurements and perform other key functions, but energy is not always in full supply. While the active power consumption of the sensors is comparatively less, sending a message about something as simple as on-chip temperature measurement requires a lot of energy. For large scale activities even a battery with an industrial grade LiSOCl2 primary cell will not be optimal. Mesh networking, another key factor that increases the transmissions between the devices, increases the active power consumption of a device proportionally to any additional transmission.
This is where ambient energy like light, vibration, heat, encompassing mechanic or kinetic energy can be converted for generating power. This conversion of energy that is usually not in the conventional form to power a sensor is referred to as energy harvesting or energy scavenging. Energy harvesting can help to effectively deliver power to a sensor network without relying on power cables. There are many energy harvesting sensor technologies in industrial automation.
Feasibility of Energy Harvesting in Industrial Automation
“Harvesting” energy from sunlight via solar cells or photovoltaic systems has long been part of industrial offerings. Examples include totalizers used by oil and gas field and flow meters used by water industry. Vibration energy on the other hand is harvested when electrical motors interact with the process, which in turn leads to energy harvesting. For example, if the speed of the motor of a pump is fixed, then vibration harvesters can be adjusted and fitted accordingly to harvest the vibration energy. This stored energy enables the motors run at the configured constant speed.
Harvesting energy from the temperature difference of process and the ambient air using thermo-electric generators (TEGs) is another popular technique. The TEGs convert the temperature difference between a cold side and a hot side to electrical energy. Micro TEGs and regular TEGs that are readily available in the market can easily power small sensor boards. Adaption of TEGs for industrial requirements still remains a major challenge as they will not be generating energy at certain points such as when the systems cool down.
How to Use Energy Harvesting in Industrial Automation?
Wireless sensor networks require low power compared to their wired equivalents, but while transmitting data or for any other peak hour activities, power via energy harvesting can be of additional help. Energy-harvesting technologies remove the hurdles associated with battery-backed sensor nodes. Each sensor node on the wireless network has an energy-harvesting unit, energy storage unit, and sensors. The energy-harvesting systems also store the energy which is generated, and this can be later be used when the energy source is passive. This way industries can save more on cost when the sensors are powered through energy harnessing/harvesting from machinery and other systems. There has been a wide set deployment of energy harvester devices in factories and plant networks for the following reasons:
Readily available energy sources such as thermal, solar, flow, vibration, and even radio frequency (RF)
Capture and store ambient energy
Replace/augment battery power
Advanced piezoelectric-based devices moving from microwatts to double-digit milliwatts
Energy harvesting is offering promising solutions for industrial automation use cases. To reduce power needs, Utthunga’s wireless systems designers are working toward lowering the power requirements of wireless systems. This will make energy harvesting even more sustainable. With Utthunga’s services you can implement a self-sufficient wireless sensor network.
The rise of Industry 4.0, the new digital industrial technology
Today the manufacturing scene in India mainly comprises of small and mid-end capital good industries, textile, pharmaceuticals, leather, and auto manufacturing. Over the past few decades, these industries have moved toward industry 3.0 to improve the efficiency of their manufacturing process with the help of automation and robotics.
Following suit with American and European companies, Indian manufacturers are now leapfrogging into Industry 4.0 with the aim to automate decision making across enterprises through efficient data analytics that can help improve quality and reduce human errors.
The major building blocks of Industry 4.0 that help to eliminate the drawbacks of Industry 2.0’s low-cost labour and ineffective management include: cloud computing, cybersecurity, Augmented Reality, Big Data analytics, Industrial Internet of Things, Additive Manufacturing and more.
Let’s take a brief look at the nine Industry 4.0 digitalization trends and technologies that can tremendously improve the profitability margin of your organization by bringing together isolated cells into an integrated, optimized and automated workflow.
1. Autonomous Robots: Flexible and co-operative, these are the key qualities used to describe autonomous robots. Taking advantage of advanced robots has proven to be highly effective in improving the quality and cost-effectiveness of the manufacturing process. Successors to assembly lines and mechanical arms, today’s autonomous robots are being leveraged by industries around the world for their ability to work together with humans and machines through learning and interaction.
2. Simulation: Simulation technology helps to create virtual clones of real-world machines, products, and humans. The main advantage of simulators in the product development, material development and production processes is that it allows you to first test and optimize the machine settings for a product in the virtual world before deployment. This way simulation can help to reduce failures in any of the production processes, ensure quality and also dial down the setup times for the actual machining process. 3D Simulation is majorly used in plant operations where it is highly important to make the best use of real-time data to create the next best product. With continuous and rapid testing of the 3D model, high-quality physical products can be created and deployed in the market on time.
3. Horizontal and Vertical System Integration: With horizontal and vertical system integration, a company can enable cohesiveness and cross-functionality among its various departments and functions.
Horizontal integration: Enables networking and exchange of product and production data between multiple stakeholders, individual machines, or production units.
Vertical integration: Provides control over the supply chain system through integration.
4. Industrial Internet of Things: IIoT deals with connectivity for machines, smart factories, and for streamlining operations. IIoT connects critical machines and precise sensors including location-aware technologies in high-take industries and generates a massive volume of data. The communication-based eco-system for the industrial sector (manufacturing, supply chain monitoring, and management systems) brings users, analytics and smart machines together to simplify the collection, analysis, exchange, and monitoring of actionable data.
5. Cybersecurity: As Industry 4.0 technologies require increased connectivity, it is highly crucial to protect critical industrial systems and manufacturing lines from cyber-attacks. Businesses make use of cybersecurity to protect their networks, systems, and data from cybersecurity threats.
6. Cloud: With Industry 3.0 propelling production, there will be an increase in data sharing across different verticals and sites within the company. With Cloud, you can store and access data and programs over the internet. By deploying machine data and functionality through cloud technologies that are part of Industry 4.0, you can now make on-time data-driven decisions by coordinating with internal as well as external stakeholders.
7. Additive Manufacturing: Popularly known as 3-D printing, additive manufacturing is used by companies to create prototypes of individual product components. This technology is being widely used by industries to create customized products that offer various production and cost advantages.
8. Augmented Reality: With augmented-reality glasses, eye-pieces, mobile-devices and other products you can provide users with real-time data that can facilitate decision making and improve their work output. AR technology enables access to the right information at the right time and empowers each user to work and make decisions individually.
9. Big Data Analytics: This is perhaps one of the most important building blocks of Industry 4.0. Big Data Analytics enables the collection and also the comprehensive evaluation of data from different sources. With data analysis, you can quickly and easily identify patterns, correlations, and trends that can significantly reduce product failures and also optimize the creation of better quality products. With Big Data Analytics, you can discover and examine large and varied sets of data procured from production equipment and systems and also enterprise- and customer-management systems to support real-time and informed decision-making that will be critical for your business.
How can Utthunga transform your business with Industry 4.0?
Are you looking to fast-track and improve the efficiency of your manufacturing process with Industry 4.0 technologies? At Utthunga, we help you transition into a smart-factory by streamlining and unifying several and disparate manufacturing processes. With our automation portfolio, we can help you to:
Digitalize industry hardware to make field devices smart.
Connect field devices and other industrial assets with our IIoT platform called Javelin that can generate rich visualization and analytics.
Set protocols for getting data for different assets (OPC, FDP).
Follow the industry standards to build business applications.
These services can help to:
Reduce the time taken to collect and analyze data derived from business systems.
Reduce errors that happen due to manual handling of data.
Receive accurate and timely-data on machine performance.
Diagnose problems quickly and rectify issues during planned the down-time for maintenance.
Provides greater visibility of plant and floor equipment.
Make informed decisions regarding asset utilization.
Conduct environment-based and condition-based monitoring to measure performance.
Our Industry 4.0 solutions also simplify interactions between suppliers, producers, and customers as well as human and machines. To know more about how we can help your business benefit from Industry 4.0 technologies, visit https://utthunga.com. Just drop a mail at [email protected] or call us at +91 80-68151900 to know more in detail about the services we offer.
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