Adapting legacy systems such as SCADA, DCS to the service-oriented digital streams is a challenging task for companies, especially those in the manufacturing sector. One of the major concerns while adapting the new-age automation systems is to re-engineer the existing systems and upgrade them to a newer version. This upgrade is referred to as ‘Migration’.

When the migration strategies of the legacy applications make use of cloud computing technology, the whole process is referred to as cloud migration. Simply put, cloud migration is the process that essentially involves cloud integration of legacy applications by formulating process objectives that aim to deliver desired functionalities and improves efficiency in processing the data.

The cloud application development of legacy applications is generally carried out on a large scale, as it includes both infrastructure and applications. The outdated legacy systems lack robust security. The cloud integrations make these applications secure against data breaches and failure.

Not only this, migrating legacy systems to the cloud makes them more agile and scalable to meet the real-time needs of the consumer. However, a single mistake during the cloud integration could interrupt the industrial processes and cost heavily to the organization.

To avoid such a situation, you need to understand what could go wrong while migrating legacy applications to the cloud. In this blog, we will discuss the factors that must be considered and also the crucial mistakes you need to be careful of during the cloud migration process.

What are factors to be considered while migrating applications to the cloud?

Most of the legacy applications are mission-critical industrial systems but lack basic data security, and futuristic vision. These often cannot be replaced by new technology as it would not only increase the operational costs but also hamper the industrial processes.

Therefore, data migration services help these organizations in shifting the legacy system safely to the cloud, to make it more scalable, agile to the emerging needs and cloud technologies.

To attain the goal of cloud migration, product engineering companies are leveraging DevOps services so that they:

• Reduce time to market of the product
• Meet customer demands
• Lower the costs related to:
  • Product Development
  • Product Testing
  • Deployment
  • Operations

With the cloud migration services, businesses can take the best foot forward in modernizing their legacy systems. Some of the major factors that these services consider while shifting legacy applications to the cloud are:

• Understand existing systems using the documents available, plant design, and system interfaces.
• Analyze business needs and prioritize the legacy applications accordingly. The main motive of moving applications to the cloud is to increase productivity. So, the ones that matter the most in this context, must be given the highest priority.
• Analyze risks associated with migrating legacy applications to the cloud. It helps in monitoring the possible sources of cloud integration failure and take proactive actions accordingly.
• Performance monitoring is a must. Your cloud integration strategy must include a blueprint of how you are going to track the performance of the legacy systems during and after their transition.
• Proper closure helps in evaluating the cloud migration project in terms of performance, KPI, and other relevant metrics. These give you an insight into how cloud migration services have helped your business grow and at what scale.

Cloud and data integrations with your legacy application decide how well your manufacturing plant is ready for the fourth industrial revolution. However, there are few common pitfalls you must look out for while carrying out the same.

5 mistakes to avoid while migrating a legacy application to Cloud

Here’s what you need to be careful of while modernizing your legacy applications.

1. Limited understanding of technical and business requirements
2. Overlooking the importance of risk assessment
3. Lack of visibility
4. Overlooking the security aspects
5. Lack of technical support

Training the staff to use the new technologies will help bridge the intellectual gap and truly make the migration process a success for your company.

Conclusion

The cloud computing effect is now omnipresent in almost every industrial realm. As technology advances at lightning speed, the fourth industrial revolution will soon be replaced by its fifth version. To make your plants ready for the present and future, you need to look out for legacy applications that are essential yet disrupting for your business to adapt to the much-required changes.

Utthunga’s digital transformation consulting includes cloud migration services and data migration services. Leverage our years of technical expertise in helping companies attain their digital transformation goal in the range of domains Cloud, Mobility, IIoT, Analytics, and much more.

Get in touch with us to know more.

The database technology landscape in industries has changed considerably in the last decade. Database technology has morphed into several different forms that assist in defining how data is stored, accessed and utilized inside an organization.

Data management in industrial systems

The 4.0 industry is a term associated with significant technological progress in sectors. The factories are now automated, integrated, and controlled by sensors, controllers and other field devices. All of this is now a reality, thanks to the Internet of Things (IoT) and other technologies and systems.

These new capacities of everyday products open up a world of possibilities in industrial sectors. Proper database management solutions improve organizational data accessibility, allowing end-users to exchange data more rapidly, securely, and efficiently across the company.

Help brand managers track and sell products

A robust and sophisticated database management solution allows brand managers to add new data, update the existing data and delete the information no longer needed. Furthermore, this enables companies to track and sell their offerings in an efficient manner.

Consistent data that complies with regulations

Data inconsistency occurs when multiple versions of the same data exist in different areas within an organization. You can ensure that an all-encompassing picture of your data is provided throughout your company by utilizing a good management system and data quality management tools.

Furthermore, data management systems give a stronger foundation for enforcing data privacy and security regulations. Better management implies more openness and a lower chance of regulatory violations.

End-User Productivity Increase

Deploying a database management system, assuming good end-user adoption, will always result in enhanced user productivity. They make it possible for end-users of data to make fast and informed decisions to improve the long-term performance or failure of their organization.

Database technology for the creation of industrial applications

Although there are multitude of options for organizations to incorporate a robust database system, the most prominent ones are listed below.

• Oracle
• It provides instant consistency as a single server
• Advanced Multi-Model databases that handle Structured Data (SQL), Semi-Structured Data (JSON, XML), Spatial Data, and RDF Store
• Blockchain Tables
• Supports both OLTP and OLAP workloads
• Microsoft SQL Server
• Provides ACID transactional assurance
• Supports server-side scripting with T-SQL,.NET languages, R, Python, and Java
• Supports Structured Data (SQL), JSON, and Spatial Data
• Tooling support for both on-premise and cloud deployments
• MongoDB
• It provides horizontal scalability and includes built-in replication and is consistent and partition tolerant (CP)
• Distributed multi-document ACID transactions
• Rich and robust query language also supports Map-Reduce queries, text search, graph search, and geo-search.
• Provides a full-text search engine (Atlas Search) and a data lake (Atlas Data Lake) based on MongoDB
• Elasticsearch
• Horizontal scaling via automated sharding and a scalable search engine
• Provide a REST API and handle both structured and schema less data, well suited to analyzing logging or monitoring data
• Support for automated replication and cross-cluster replication (CCR)
• Widely used in observability landscape
• Cassandra
• It is used as an OLAP database (e.g., Data Warehouse) to manage massive amounts of data
• It is also utilized as a time-series database.
• It provides linear horizontal scaling and is one of the most scalable databases with automated sharding; it is AP (Available and Partition Tolerant).
• A decentralized database with automated replication is fault-tolerant with no single point of failure.
• It has a user-friendly Query Language and SQL-like query language (CQL).

The substantial rise in edge analytics applications is due to the widespread use of the internet of things (IoT), widely acknowledged by industries as the most important tech trend due to the broad range of IoT services and domain capabilities.

How does edge analytics work?

When used as a data-driven approach to extracting tangible and measurable metrics from the IoT, edge analytics enables businesses to obtain data faster by deploying advanced analytics and machine learning at the point of data collection via connected devices and real-time intelligence.

In terms of the industrial IoT industry, it is expected that industries using edge computing will grow further owing to the edge analytics advantages of dispersed aggregation and offering shop-floor data gathering across all industrial sectors.

The idea of edge analytics allows for developing an optimum model for managing data transmission from the edge and ‘smart’ data storage in data centers. Advanced analytics techniques, independent of their application area, operate behind the scenes to anticipate system component failure, keep devices operational, and ensure a continuous workflow.

Overall, edge analytics skills are actively used to develop smart machines that perform self-responsive activities and anticipate consequences.

Edge AI video-based analytics have found widespread use in a variety of areas, most notably education. Indeed, it can revolutionize the teaching-learning process by providing innovative methods for delivering instructional films in novel ways. Sony, for example, demonstrated its AI edge analytics-based solution for producing video content: its primary unit, in conjunction with different licensed appliances, demonstrates how video streaming may be elevated to a new level.

Why do edge analytics matter in 2021?

Industry 4.0 is now facing significant obstacles that are impeding its development. Computing at the edge is the answer to many of these problems. Here are some of the most significant benefits that the edge offers to Industry 4.0.

Increased interoperability

IoT systems may be a hurdle to smart manufacturing’s growth. However, an IoT network is just as good as its interoperability.Concerns about interoperability are among the most significant obstacles to its adoption since there is no standard protocol. By relocating computer operations to the edge, part of the requirement for a universal standard is eliminated. When devices can transform signals on their own, they will operate with a wider range of systems.

The edge also acts as a link between information and operational technologies.

Reduced latency

When sending data to a distant cloud data center for analysis, the latency is lengthy and unpredictable. For time-sensitive use-cases, the chance to act on the data may be lost.

Edge computing provides predictable and ultra-low latency, making it suitable for time-critical scenarios such as any use-case where the process is mission-critical or in motion. Delays in moving cars, equipment, components, people, or fluids may result in lost opportunities, excessive expenses, or security concerns.

Analytics-enabled technologies

Companies decide to include edge computing technology in their network architecture due to the number of benefits it offers. There is something for everyone, from real-time AI data analysis and improved application performance to significantly reduced operational expenses and planned downtime.

Technologies enabling Edge Analytics:

Edge Computing with Multiple Access

Multi-access Edge Computing or MEC is an architecture that allows for computing and storage resources inside a radio access network (RAN). The MEC contributes to increased network efficiency and content delivery to end-users. This device can adjust the load on the radio connection to enhance network efficiency and reduce the need for long-distance backhauling.

Internet of Things

The idea of the Cloud of Things (CoT) is still in its early stages, but it has many potentials. All computing power in a Cloud of Things is obtained from the extreme edge at the end-user.

We all have powerful gadgets in our hands, such as industrial tablets, smartphones and Internet of Things (IoT) devices in our plants. These gadgets are often underused. Although IoT devices currently have limited computing capacity, many modern devices are very powerful.

Using mobile or IoT enabled devices, cloud services may be provided directly at the edge. These devices may be coordinated to provide edge cloud services. For example, a vehicle traveling through traffic may transmit traffic warning alerts to others and re-arrange alternative routes without user involvement.

The idea of the Cloud of Things is akin to that of fog computing. All IoT devices in a CoT form a virtualized cloud infrastructure. All computing in the CoT is done by the IoT devices themselves, which are shared resources.

Fog Computing

Fog computing, fog networking, or simply “fogging” refers to dispersed computer architecture. It brings cloud computing (data centers) to the network’s edge while also locating data, storage, and applications in a logical and efficient location. This location occurs between the cloud and the data source and is often referred to as being “out in the fog.”

Future of edge analytics

Edge computing has gained traction because it provides an efficient answer to growing network issues connected to transferring massive amounts of data that today’s businesses generate and consume. It’s not simply a matter of quantity. It’s also an issue of time; applications rely on processing and responses that are becoming more time-critical.

According to projections, there will be 21.5 billion linked IoT devices globally by 2025. Consider if half of them could do computational work for other devices and services. This massive, linked computer network would be especially useful for smart manufacturing.

Conclusion

Edge analytics is a burgeoning area, with companies in the Industrial Internet of Things (IIOT) industry increasing their investments every year. Leading OEM and suppliers are actively spending in this rapidly growing industry. Edge analytics offers real business benefits by decreasing decision latency, scaling out analytics resources, addressing bandwidth problems, and cutting expenditures in industries such as retail, manufacturing, energy, and logistics.

Utthunga’s expertise in edge analytics and edge computing along with IIoT technologies enables organizations to scale their processing and analytics capabilities exponentially. Contact us for your edge analytics requirements to leverage the real-time business insights from the edge.

What is Industrial Automation?

Automation helps save a lot of time and effort and at the same time, it helps get a job done more accurately. Industrial automation involves the use of control systems, computers and robots to handle and perform certain operations. A survey by Fortune Business Insights reported that the global industrial automation market will reach 296.70 billion dollars by 2026. In this blog, let’s explore the top 10 advantages of industrial automation. In this blog, by Industrial Automation, we are referring more to the advancements of this century, i.e. after the time computers and electronics started to play a key role in the industrial sector.

Industrial Automation in Manufacturing

Automation is greatly transforming the manufacturing industry. This revolution is bringing cyber-physical systems into existence. Many manufacturing units are already employing robots and using digital technology to automate processes. A few examples of automation in manufacturing are:

• Automation of food and beverage packing to reduce chances of human contamination
• Numerical control in the machine tool industry
• Use of thermal sensors to monitor high activity areas on the floor
• Automatic sorting in the production line
• 3D printing

Top 10 Advantages of Industrial Automation

1. Reduces Cost

One of the top advantages of automation is reduction in manufacturing costs. Instead of having a floor full of workers, you can now have a few supervisors and have robots do the job. The initial investment will be a little high, but then the operation costs will reduce, which will be beneficial in the long run. Your expenses will only include maintenance, repairs, and energy. AI and data analytics have also helped reduce production costs by providing insights and information to make the right production decisions. Automation helps improve productivity, quality and system performance, which in turn reduces your operating expenses (OpEx). At the same time, automated preventive maintenance can improve the life and performance of the machines. It enhances the value of your assets and in turn decreases your capital expenses (CapEx).

2. Increases Productivity

Automated productivity lines consist of workstations connected by transfer lines. Each work station takes care of one part of the product process. Robotic process automation can be used to mimic many human actions. The system can be configured to login to applications and take care of the administrative work related to the business process. Robots can also be used on the production floor to handle raw materials, clean equipment, operate high-pressure systems, and do lots more. For example, in an automobile manufacturing unit, auto components are cut and shaped in different press working stations. All the parts are then brought together to one place where a robot puts them together to build the vehicle. Process automation greatly speeds up the production process.

3. Enhances Quality

Industrial automation also helps increase and maintain consistent quality of the output. In manual processes, the error rate can vary considerably. On the other hand, automated machines in the manufacturing industry have an error rate that is as low as 0.00001%. Adaptive control and monitoring help check every level of the manufacturing process to reduce the margin of errors.

4. Industrial Safety

A huge benefit of automation is improved safety at the workplace. Using robots for loading and unloading materials or transferring huge machine parts reduce risks of accidents. Safety curtains keep workers from going too close to the assembly lines or fast moving components, thereby improving safety. Thermal sensors continually check the temperatures in the production area. In case, they identify any spike in temperature, the sensors will send an alert. Immediately, precautions can be taken to ensure the safety of everyone on the production floor.

5. Accurate Results

Data automation is based on accurate data integration and connectivity. When accurate information is used in the production process, you can be assured of precise results. AI and ML solutions help you get detailed data that can be analyzed using data analytics tools to get accurate information.

Deep learning algorithms are used to build self-healing digital grids that use data analytics and intelligent energy forecasts to manage energy generation. Machine Learning apps have been used to build a self-learning quality control system for assembly line. ML and AI solutions are scalable and self-learning. Both these features ensure that the automated systems deliver accurate results every time, without fail.

6. Better Working Conditions and Value-Addition

One of the prime benefits of industrial automation is that it ensures consistent production and results. Computers, robots, and automated machines work at a steady pace. It allows you to have a better grip on the production rate. Automation not only delivers consistent production, but also consistent quality. In a flexible manufacturing system, the tools, processing machines, and material-handling robots are connected and controlled by a central computer system. Once the entire process is computed, the production goes on continuously without any drop in the pace or the results.

Flexible automation process lets you design or reconfigure a machine to suit a different product measurement or new product. In traditional production processes, it may take days or weeks to train employees. Another problem is that it can be difficult for workers to get used to the new process, which could cause production delays or quality issues. On the other hand, reprogramming a machine or a robot is easier and takes up less time. Plus, after a few trials, you will be ready to go into full production.

Automation frees up employees from working on tedious and repetitive tasks. This means that they can focus on other areas where they can do a value add. They can help with research and process development. Also, workers can effectively use robotic tools and machines to deliver faster and quicker results. Employees also experience the feel-good factor of doing positive and progressive work.

Industrial automation also helps improve working conditions. As the automated machines are able to step up the production, workers need not work long shifts or overtimes. Work hours are reduced, leading to an improved quality of life. In the United States, industries that adopted automation solutions were able to set a standard work time of 40 hours per week.

7. Industrial Communication

Without industrial communication, industrial automation can be near impossible. The communication system helps monitor and operate entire production lines, manage power distribution, and control machines. Some of the popular protocols for industrial communication are Foundation Fieldbus, PROFIBUS, EtherCAT, EtherNET/IP, and CANopen. Industrial communication allows for faster data analysis and real-time decision making.

8. Monitoring & Predictive Maintenance

A huge benefit of industrial automation is that it helps in monitoring and predictive maintenance. Production lines and production floor can be continuously monitored using sensors. These sensors track temperature, acoustics, time, frequency, oil pressure and other parameters related to the production process. If the sensors detect any change in these parameters, they will immediately send an alert. When the alert is received, the technicians can immediately identify the cause for the change. If it is noted that the changes in parameters may cause equipment problems or issues in the production process, then immediate service or repairs can be done. Automation can therefore help identify possible issues before they blow up into huge problems that can result in production downtime.

9. Equipment Monitoring

An automated equipment monitoring system helps observe the working condition of all the equipment in the manufacturing unit. Sensors, cameras, and network can be used to observe the equipment from afar. The monitoring system also helps diagnose any issues in the equipment and do the necessary repairs and services. This automated solution can be effectively used in petrochemical plants, manufacturing units, and other industries where large and complex machines are used. The automated system enhances safety, reduces the number of operators on the floor, and improves machine performance and lifespan.

10. Production Traceability

Automating the entire production process can greatly help in production tracing. Traceability is not only important in the food and beverage industry, but also in other industries. Tracing helps increase the quality and value of your product and facilitates mapping. Also, traceability makes root cause analysis more effective and aids continuous development. Automation helps trace the entire lifecycle of a product from the raw material to the location where the final product is shipped. You will also have a clear record of when and who did the product inspections, the assembly status, the condition of the machine when the product was processed.

How can Utthunga help in Industrial Automation?

With more than 13 years of industry experience, Utthunga is a leader in industrial automation. Our team includes experts in the latest digital technologies and industry professionals to provide digital transformation solutions customized to your business process and business goals. A few of our industrial automation solutions include:

• Deploying sensors, PLCs, controllers, etc. for automation
• Using embedded engineering to create smart devices (non-digital to digital)
• Offering data integration solutions that integrate plant floor assets to each other and other systems
• Building applications (desktop, mobile) for commissioning, calibration, local diagnostics and configuration
• Building bespoke application to enable integration of OT data to SCADA, MES, Enterprise systems
• Creating analytics solutions

Contact us to know more about our industrial automation solutions.