Top 4 IIoT advantages for Oil and Gas industry

Top 4 IIoT advantages for Oil and Gas industry

Industrial Internet of Things (IIoT) is the next big thing that’s happening across the industrial sector. An offset of the IoT, this technology revolves around the use of sensors, devices and software for industrial automation. A survey by McKinsey Digital states that IIoT is set to make an economic impact of up to $11.1 trillion by 2025. Companies that invest in IIoT are estimated to capture a major share of the profit margins. The oil and gas industry is one of the industries where IIoT is expected to play a huge role, both in terms of optimizing processes and enhancing safety.

Below are the four IIoT advantages for oil and gas industry to leverage and add value to their integrated business strategies.

 

1. Asset tracking, monitoring & maintenance:

A typical oil and gas company has multiple refineries that need to be regularly inspected for maintenance and repair. Though it is very important, in many cases, the staff may not be able to do a thorough physical inspection due to various reasons. Setting up an equipment and connecting it to an IoT network can help reduce the need for manual inspections a great deal.

IIoT can be effectively used in monitoring the working condition of field devices, sensors, actuators, valves and other assets of the refineries. Sensors can be fitted on the pumps, pipes, filters, valves and other components. These sensors collect data regarding the asset operation, temperature, speed, pressure or other parameters based on pre-determined conditions. They transmit the data in real time to an external storage, that could very well be on cloud. An experienced technician can analyse the data collected by the sensors to identify if there is any malfunction or impending malfunction in the asset.

At the same time, the sensors also enable technicians to keep track of all the mechanical components of the machineries used in the refineries. It also enables managers to keep track of the replacement parts and spare parts. Based on the tracking details, they will have information regarding the exact location of the new spare/replacement part. Therefore, IIoT enables real-time asset tracking and monitoring, which is not possible during manual inspections.

Moreover, the data collected by the IIoT network allows proactive identification of possible issues. So, technicians can immediately go to the exact point where the anomaly was observed based on the data and do the needful.

2. Data management:

The second major advantage of using an IIoT network is efficient and effective data management. Technologies such as cloud computing, standards based connectivity solutions, etc. help in better data management, which in turn reduces expenses and improves the profit margin. Integrated sensors collect data using industrial protocols from various assets present in the supervisory networks, plant networks, fieldbus networks and ICS networks. Cloud is used to aggregate, integrate and store data from different sources in different formats. Methods such as edge-analytics and edge-processing are used to analyse data and gain insights and information.

Two factors affect the informed decision-making process. First, is the need for reliable and accurate data, and second is the loss of experienced personnel due to organizational restructure or retirements. Through data analysis and remote monitoring, effective asset management and set up of maintenance programs will ensure that the decision makers streamline and optimise the rig operations.

Real-time data obtained from the IoT network can be used to improve the extraction process and drilling strategies. A study by Bain and Company shows that effective use of data management can help oil and gas companies improve their production by 6 to 8%. Also, with monitoring and maintenance, a lot of the unnecessary expenses can be cut down. Plus, the staff don’t need to spend a lot of time and effort on the field trying to identify possible causes of problems. The automated network brings all the data to their fingertips on their systems.

3. Supply chain, logistics & transportation

The supply chain and logistics is one place where IIoT can be very beneficial. Based on the data collected from various touchpoints of the network, managers can plan and schedule their procurements, supplies, and identify the best practises. Connectivity is a huge problem when pipelines and ships are transporting oil and gas. At such time, the stakeholders need to rely on satellite communication to transmit data. It is also difficult to regularly check the working condition and obtain regular updates on the oil pipelines or the ships. Low-power wide-area networks (LPWAN) can be installed in areas of pipelines that are difficult to access. Additionally, wired and wireless networks can be setup along the transportation lines to collect relevant data and transmit it to a cloud source via the satellite connectivity. The office staff will have reliable and accurate information that will help them organise the oil deliveries better.

4. Health & Safety:

One of the major areas where IIoT can play a huge role is health and safety of the employees as well as maintaining the carbon footprint of the refinery. Oil and gas drills and refineries are usually located in dangerous and far-flung areas away from the crowded cities. While the remote location makes it convenient to drill oil, the same distance can make it difficult when there are health and safety issues. A network of connected sensors can help get real-time data on what’s happening on the ground. Also, remote equipment monitoring and predictive maintenance can greatly reduce machine repairs and breakdowns. Data such as pressure, air conditions and other parameters captured by the sensors and real-time images captured by surveillance systems can help ensure that the highest safety standards is maintained at the job site. The workers at the drill site are asked to wear wearables with trackers to ensure their locations can be immediately identified and notified in case of emergencies. All this data can be used to reduce accidents and fatalities.

The IIoT data helps reduce spills, pipe leaks and accidents, which could cause environmental damages. It can also be used, to analyse and identify areas where the carbon footprint can be reduced.

IIoT is definitely the future of the oil and gas industries. This technology helps enhance operational efficiency, reduce costs and aid business growth by delivering real-time and accurate data. Utthunga is a tech-based company with expertise in industrial automation. We can set up an integrated IIoT system for all your oil drilling sites and refineries based on your specific requirements. Contact us to know more.

Top 10 Tips for Industrial PCB Design

Top 10 Tips for Industrial PCB Design

It does not matter if you are an experienced design engineer or a complete novice when it comes to an industrial PCB design. What matters is that for every piece of electronic appliance or industrial mechanical device, there is an printed circuit board (PCB) that plays an important role. These green boards provide the physical platform for the design of a complete electronics system with circuits and components together.

It is said correctly that the success or failure of any product’s function largely depends on the PCB layout product design and development. While PCB manufacturing (PCBM) and the PCB assembly (PCBA) are two different processes with their own unique requirements, they both have PCB design as a common factor.

The astounding level of technical advancements in embedded and semiconductor integration is resulting in shrinking the PCB designs. PCB layout and design services must consider the complexity and expectations of these designs that is reaching new heights.

In this blog, we outline the top ten tips or guidelines for industrial PCB product design and development.

1.Identifying the project need

The customer’s requirements dictates every embedded hardware design. This essentially involves thorough analysis of your project, budget, and requirements. Translating these requirements into an electronic form uses the technical skills and experience of an electronic design engineer. What is the type of your product, what is its operating environment; what are the powering options, communication mechanisms or the specifications/regulations does it comply? These are some questions that come to the PCB design engineers. Having these answers will help in identifying the best possible layout, initial schematic of the PCB, as well as the BOM and other details of your final PCB design.

2.Schematics:

The schematic diagram is the blueprint for PCB manufacturers and assemblers during the production processes. It is a diagrammatic representation of the electronic component symbols and the interconnections between them. Once all the design choices for the various components is finalised, this acts as baseline for developing the schematic design. Preliminary review and analysis is then performed to check for potential problems and then the corrected version is fed to the PCB design software, which can run simulations to ensure the correct functionality of the PCB. Some of the popular software are Eagle, KiCAD, Altium Designer and OrCAD.

3.Bill of Materials:

A bill of materials (BOM) is generated simultaneously along with the schematic’s creation. This is very handy as it lists out each components quantity, numerical values (like ohms, farads, voltage etc.), component part number, the reference designators and PCB footprint for each component. It defines how each component in the circuits is identified and located; the circuit element numbers used for purchasing and substitution, its size with respect to the PCB size etc. An updated BOM will save many complications in the later PCB design stage process.

4.Component placement:

Placing each component in its designated spot on a circuit board is the most critical part of designing. A wrong placement can cause various thermal, electrical noise and power variations in the circuits leading to malfunction of the PCB board and product failure. The design schematic generated earlier is used to determining the correct spot. The most common order of component placement followed by the designers are:

• Connectors

• Power circuits

• Sensitive and precision circuits

• Critical circuit components

• All other elements

The designer then verifies and reviews the initial component placement step and adjusts to facilitate routing and optimize performance. It is adjusted based on the cost and size factor also. Due considerations are given to

• PCB component placement with ground separation, power and isolation between high frequency components

• Place components with the same orientation for assembly easiness

• Print the layout to see if components’ sizes match to avoid any assembly and mechanical issue

At this point based on the size and cost, the placement and package sizes are often reconsidered and changes are made.

5.Thermal Management:

One of the most frequent design issue is thermal management of the PCBs. When heat dissipation is not considered, it leads to poor circuit performance or even a damaged board. Following are some tips to achieve high performance keeping the heating issues in mind:

• Place heat sensitive components (like thermocouples or electrolytic capacitors) away from heat generating components (like diodes, inductors, and resistors)

• Use PCB as heatsinks by using more layers of solid ground or power planes connected directly to heat sources with multiple vias

• Thermal vias dissipate heat from one side of the PCB to another. Having larger and multiple thermal vias lowers the operating temperature of components and contribute to higher reliability.

6.Wiring Considerations:

PCB wiring design is often a complicated process involving the power cord design, ground wire design and other wiring considerations. It is grouped into single wiring, double-sided wiring and multilayer wiring. It is good practice to follow some of the tips:

• Exchange wiring directions between layers. For multiple layers, alternate between directions

• Keep wiring and the distance between the wires uniform and equal

• Allow small loops in loop back wiring

• Ensure smooth soldering of the wiring

• Printed wiring corners should be rounded corners when used for circuit wire for dense or high frequency circuits

7.Mechanical Constraints:

Consider the mechanical constraints in advance before starting the placement and review during the embedded hardware design. There board materials used to create the PCB, the number of layers each PCB will have, the copper traces used to complete the connections, component selection based on availability, numbers, package type, cost and other determining factors. The PCB shape, size and board area are constrained by the PCB hosting cabinet used by the appliance or equipment.

8.Power Constraints:

Any huge current spikes or large voltage changes can interfere with the low voltage and current control circuits. A good power design guideline includes adequate separation, placement and coupling into its schematics.

In the PCB design, it’s recommended to use common rails for each supply, avoid longer power loop while routing and have solid and wide traces. Having separate power and ground planes internal to your PCB while also being symmetrical and centred will help to prevent your board from bending. You can place a small impedance path to reduce the risk of any power circuit interference and to help protect your control signals. The can be followed to keep your digital and analog ground separate.

9.Routing details:

A differential signaling is the process of using not just one, but two traces to transmit a signal on your board. They are (ideally) equal in magnitude and opposite in polarity, thus in the ideal case there is no net return current flow through ground.

There are many reasons for using a differential signaling like reducing the EMI, having precise timing to determine the current logic state a differential pair and separating the power systems.

To achieve the above benefits, it is recommended that you always route the differential signal traces in parallel, keep them as shortly and directly as possible between components. Also, maintain equal length and width of the traces while keeping the spacing constant between the trace pairs.

10.Perform Quality Checks:

One of the good practice of PCB layout and design services is to conduct a DFM and DFT checklist review before signing off your PCB designs for generating the Gerber files. The Gerber format is an open 2D binary vector image file format, which is used universally by the PCB design software. It describes the PCB images and are necessary to manufacture and assembly the final PCB boards. Some of the checklist involves verification of the component placements, routing paths, pre-scan for the thermal integrity and signal integrity among others.

Find an Assembly Service for Your PCB Design

Industrial PCB design can be a formidable task but by following the above basic techniques and best practices, it can lay the foundation for your success. Our expert product design engineering services can guide you with your next PCB design project with cost-effective services and assured quality standards.Contact us today to learn more about the industrial product design engineering services, the PCB design rules and assembly processes.

Top 10 Considerations While Implementing OPC UA

Top 10 Considerations While Implementing OPC UA

Industrial Internet of Things (IIoT) is the most promising trend in the Industrial Revolution. Industries are now leveraging the power of the internet to interconnect their systems to improve their overall communication process. This interconnection will produce the best results if there is a semantic flow of data and a well-defined architecture. This is where the challenge is for the industries.

OPC Unified Architecture (OPC UA) is an international standard for industrial communication between the various layers of the industrial pyramid. It is an IEC standard protocol and is a successor to the OPC Classic specification. What makes OPC UA different from OPC Classic is that it is platform-independent, unlike the latter, which could be used only on for Microsoft (OLE) systems.

OPC UA gained popularity in 2007, around the time of the introduction of Service Oriented Architecture (SOA) in industrial automation systems. Being IEC compliant, it can be easily implemented in areas where communication between devices is required.

OPC UA, a potent solution to overcome interoperability challenges in Industry 4.0

One of the major challenges that I4.0 poses for industries is interoperability. OPC UA proves to be a solution through its semantic communication standard. This is important because the information transfer is mostly between devices and machines, which can hardly understand ambiguous instructions. The more precise instructions, the better result they will produce.

The main crux behind implementing the best OPC UA for your automation system is the choice of tools. Since the devices on IIoT or in any industrial automation environment are controlled by a software application, a well-functioning software development kit (SDK) is necessary. It ensures a quality user experience for end-users and software engineers.

Choose the right software development kit for OPC UA

The key to implementing an effective OPC UA depends on the right selection of software development kit. We have listed out ten points that an automation manufacturer, OEM, discrete and process manufacturer must take note of while choosing an SDK.

Right SDK vendor

Most of the companies lack enough resources, both technical and human. The best they can do is outsource their requirements. Therefore, the chosen SDK must be such that it meets their application requirements and improves the product’s time to market. While choosing the SDK it should be profitable both in terms of money and performance. Most of the SDK vendors offer the basic functions that enable the fundamental OPC UA benefits, like security and API, for better abstraction languages.

Scalability

A scalable SDK enables the implementation of OPC UA in all new and existing systems. Therefore, the manufacturers must consider a scalable SDK, which must accommodate any type of hardware, be platform-agnostic, OS, and vendor independent. This enables the platform-independent OPC UA toolkits to work efficiently in any environment be it a small embedded or a large enterprise-based application.

Ease of Use

This is one of the obvious yet overlooked factors. An SDK should be easy to use and understand, so the OEMs or small-scale manufacturers can save time and energy in understanding the in-depth knowledge of the OPC UA specification. It must deploy a simple application and provide integration using APIs.

CPU Utility

An OPC UA SDK if written based on the architectural principles for embedded systems, utilizes much less CPU. It means the application can perform significant work in a single thread as well. It comes in handy where the multi-threads aren’t available. This in turn reduces the overall cost, as a low-cost CPU can do most of the work, in such cases.

Good Memory

Software, of course, runs on memory. A good OP UA implementation should not have a huge footprint, and should be easy on RAM. Further, memory leaks can accumulate over time and bring the entire system down. It is imperative that there be no memory leaks (under all use case scenarios) in the OP UA SDK.

Compatibility and Security

OPC UA SDK toolkit must be compatible with a wide range of applications and security requirement. The O UA standard supports various security modes, an ideal SDK should support all of them.

Language Support

Even though C++ is the most commonly used language to write SDK codes, other languages such as Java, C, .NET, etc. are also used depending on the requirements. Developing an OPC UA SDK in different languages pose challenges to make incremental improvements to their products depending on the already available specifications like AMQP, Pub/Sub and UDP.

Third-Party Libraries

Third-Party libraries play a crucial role in the software application process. Most companies have their preferred library, therefore most SDK vendors offer wrappers like standard crypto libraries, use-case examples, manuals, and API reference to use wrappers like NanoSSL, mBed TLS, TinyXML2, and Lib2XML.

Accommodate Future Enhancements

While implementing any protocol, the manufacturers must ensure the SDK vendors are well equipped with knowledge and skills to maintain agility in performance owing to the ongoing developments around SDKs, and the OPC Foundation based technologies like AMQP Pub/Sub, UDP, and TSN.

Vendor Support

SDK vendors must be willing to support the manufacturers in every step of their OPC UA implementation with their expertise. A relationship based on trust, mutual benefits and understanding is key to an effective OPC UA implementation.

OEMs, discrete, and process manufacturers must ensure to work with a team that understands OPC UA specifications and implements them in their best interest.Utthunga offers the best OPC UA services focused to make our clients I4.0 ready. Our expert team consists of professionals recognized by the OPC Foundation, and are armed with the right expertise and knowledge for the implementation of OPC UA on any platform. Contact us to know more!

What is the Significance of Regression Testing in Agile?

What is the Significance of Regression Testing in Agile?

What is Regression Testing?

Industrial revolution 4.0 has already started to show signs of significant change in various industrial operations. From manufacturing, to automotive, finance and production, every business process is being explored to unveil the potential of automating them.

Industries are thriving hard to stay in tune with the latest technological advancements and be relevant in the digital era. The popularity of software-based automation for industrial units therefore has seen a sharp rise. According to a survey, the industrial control and factory automation market are expected to reach USD 229.3 billion by 2025 from USD 151.8 billion in 2020, at a CAGR of 8.6%.

The I4.0 brings in a lot of improvements in the manufacturing industry. OEMs, in particular, are embracing the rapidly changing technology, and are implementing software that needs timely up-gradation with the inclusion of new features.

Even though the changes work for the betterment of the system, it may also bring unwanted alteration to the existing features. Hence, proper regression testing is required to check if the changes does not alter the intended purpose of the system.

Regression testing uses the requirement specifications as basis for creating test cases and looks for any bugs or fault in the software system. As more and more OEMs and factory process are drifting towards remote functions and software implementation, this testing helps them to improve the overall quality of the software.

  • Improve efficiency: An OEM with an error-free software ensures precision in its operation. Regression testing constantly checks for deviations in the software each time a modification is made.
  • Better monitoring and decision-making process: In some cases, especially when dealing with a complex software, OEM tends to lose track of the code modification. Regression testing makes it easier, as it keeps a record of all the changes made. This in turn aids in proper monitoring of the changes and decision-making process related to the deployment of the final software.
  • Reduces unnecessary manufacturing costs: Regression testing identifies the errors and notifies the OEMs to fix them in the early stages itself. A bug fix in the production/manufacturing stage of the product life cycle will result in huge manufacturing costs. Regression testing ensures the final product will be error-free.
  • Continuous operation: A crucial aspect in the successful deployment of I4.0 is the assuring the interconnectivity and automation of the devices. Regression testing ensures the bugs are fixed and all the interconnected devices work together seamlessly.

Types of Regression Testing

There are different ways regression testing can be carried out. Based on your requirements and the complexity of the software, a proper regression mechanism is chosen.

In industrial automation, devices need to be connected together. Here, with every additional device, the software may need changes in its code or features. The testing here ensures that the introduction of the new device or an upgrade does not alter the functions of an existing setup.

In an OEM unit, regression tests are mostly executed at the design stage to find the immediate bugs and at the production stage to decide whether the quality of the product matched the specification of the customer.

If there needs to be a functional change in any of the devices, corresponding codes need to be changed, Here the regression testing helps in producing the desired outcome.

Regression Testing in Agile

To keep up with an evolving market, the manufacturing industries and industrial automation in particular are working in an agile environment. The DevOps culture is being widely accepted by the industrial automation companies for on-time and efficient deployment of new software technologies.

The constant upgrades and features introduced by OEMs can change the way the whole system works. This brings in an agile environment where continuous change comes with a high amount of risk.

Risks involve fatal bugs, repeated errors, duplicate entries, etc. These all culminate to either non-delivery of the product or a delay in deployment. Both these cases can be avoided by continuously keeping a check on the code source and its impact, through regression testing.

Benefits of Regression Testing In Agile Environments

OEMs and factory processes are focusing to blend in an agile environment to build a better technology-enabled workspace. This along with the current DevOps culture has helped industrial automation to create a digital identity of its own even in the times of cutthroat competition.

Regression testing helps OEMs to manufacture more reliable products and provide better services. Apart from this obvious benefit, some of the crucial ones are listed below:

  • Since the software testing and development team can easily identify the bugs, they are motivated to deliver high-end bug-free device
  • Each case is handled and verified differently, therefore, it ensures a seamless functional process
  • It ensures the bugs are fixed and the products are ready to be launched in the market.
  • A bug free software ensures better communication between the interconnected devices in an automation system

Conclusion

The future of industrial automation belongs to agile environment and DevOps. These not only offer a better coping mechanism to the changing scenarios but also are crucial in delivering services with utmost precision. With big data and artificial intelligence seeing new heights, industries are sure to leverage them in software testing to bring the best out of the agile and DevOps culture.Catch up with the most effective testing solutions offered by Utthunga. Contact us to know more.

How Embedded OPC UA can Enhance Potential for Interoperability

How Embedded OPC UA can Enhance Potential for Interoperability

Introduction

We have long realized that digitalization is the key to unlocking hidden business opportunities in the industrial sector. Digitization and digitalization becomes more successful when it is integrated across products, services, systems, and solutions. It is therefore essential to establish a seamless interoperability between the components of the enterprise and that of the automation systems. Over the years, industries have faced many challenges in building a unified structure that connects all the components, from factory floor devices to the host applications. We are now closer to the goal of building a unified system that delivers reliable interoperability, thanks to the development of OPC Unified Architecture and its easy implementation in the embedded layer. OPC UA allows you to connect field devices all the way up to the enterprise systems. Embedded OPC UA enables industries to utilize heterogenous data collected from various devices, exchange information with different components, and orchestrate processes across different layers. It also secures data storage and accessibility.

How Embedded OPC UA can Enhance Potential for Interoperability

Embedded OPC UA helps create a singular system (comprised of heterogeneous sub systems) that can work seamlessly with other systems. It presents multiple opportunities for control automation vendors and device vendors to make their products stand out with native open data connectivity that is more secure, easier to integrate in multi-vendor environments, and opens door to new markets due to the widespread use of OPC.

This strong demand for improved access to shop-floor data is driving machine and device vendors to use embedded OPC UA to build products that are interoperable with products (hardware and software) from other manufacturers. OPC UA makes it relatively easy for a multitude of applications to connect with each other. The built-in security enables vendors to provide their applications with the three pillars of secure connectivity: authentication, authorization, and encryption.

Embedded OPC UA SDKs can be ported to many embedded operating systems, including proprietary real-time operating systems, which consume the least memory and CPU resources. It finds application across the horizontal and vertical communication in an enterprise or plant.

Vertical Applications: This includes vertical integration from plant floor devices including the sensors/actuators and controllers in the field to IT systems or the cloud and vice versa.

Horizontal Applications: This includes horizontal integration for controller-to-controller (machine-to-machine M2M) communications.

Both these applications together facilitates the standardized secure communication and is also an enabler for:

  • Making field devices smart for easy connectivity
  • Conditioning monitoring (localized to devices)
  • Asset health monitoring
  • Device diagnostics
  • Production monitoring
  • Process and quality control
  • Security management

Advantages of embedded OPC UA solutions

  • OPC UA has been a popular standard for industrial communications since 2015 (its predecessor, OPC Classic, since the early part of this century)
  • It is compatible with a wide range of OT and IT communication protocols
  • It is scalable from sensor to cloud
  • It allows for effective data management as it enables aggregation, access, secure transfer across the industrial network
  • Industries can use embedded OPC UA with PubSub, cloud technologies and open source software for building effective interoperability solutions
  • Embedded OPC UA also supports publish/subscribe communication model that can be used to establish one-to-many or bidirectional communication systems
  • OPC UA communication is encrypted (though optional) hence ensuring data security
  • Data obtained from embedded OPC UA devices can be routed via central or external gateways, which allows for multiple device configuration and management
  • Once OPC UA is embedded in the devices, the engineer just needs to browse the tags to get the relevant information about the device
  • Its small footprint lets you effectively integrate into a product with minimal changes to the power consumption, cost, complexity, and form factor
  • Embedded OPC UA has an efficient internal architecture, which minimizes CPU utilization

Limitations and challenges of industrial interoperability

The biggest challenges of implementing industrial interoperability are:

  • Standardization

IIoT researchers state global standardization as one of the top challenge for industrial interoperability. Industries use devices from various manufacturers and follow unique processes. So, it can be difficult to come up with a one-size-fits-all solution.

  • Compatibility and connectivity issues

There is a gap in the communication between the existing resources and production process. In most cases, industries have islands of data that are maintained and accessed by different teams. Creating a cohesive network that can build a bridge between these islands of data can be a huge challenge for the developers.

  • Security

Data security is one of the critical factors that needs to be considered while implementing industrial interoperability. With all the data accessible from one point, the chances of cyber threats and hacks also rises. Therefore, security needs to be strongly considered while building an interoperable system.

  • Usage access

It is important to clearly define who will be given access and what they can access. Monitoring accessibility, especially on the production floor can be a huge challenge for all the stakeholders.

  • Cost

In the initial stages, when you are doing a complete overhaul of the existing system, the cost can be a huge limiting factor. Many companies worry about the returns on investment and hesitate to invest in OPC UA solutions. Therefore, it is important to work with experts who come with domain expertise and in-depth experience in OPC UA, so you get full value for your time spent and investment made.

Utthunga has over 12 years of experience in OPC UA server and client development. Our range of OPC UA services includes integration of OP UA in field devices and controllers, OPC UA in Edge devices, OPC UA to database integration, and several other use cases. We also offer OPC UA security consultation services. Contact Utthunga for more details on how you can implement interoperability in your company.

Artificial Intelligence in Industrial Automation: A Primer

Artificial Intelligence in Industrial Automation: A Primer

Role of Artificial Intelligence in Industrial Automation

For many people, Artificial Intelligence(AI) means robots performing complex human tasks in sci-fi movies. Actually it is partially true. Whatever AI offers to the world is allowing the industrial machines to carry out super intelligent tasks. As the global industries and decision makers are facing new challenges, there is an urgent requirement to propel manufacturing by using the most advanced technologies. Industries need to restructure and revamp their control systems and other industrial assets (software or hardware) in order to keep pace with the unprecedented speed of change. Artificial Intelligence or AI could potentially help meet these goals. AI applications are already becoming pervasive in industries like banking, gaming, retail, entertainment and more. The fourth industrial revolution is driven by new ways of automating the industrial tasks with smarter sensors, controllers, IO modules, PLCs, gateways, enterprise systems, etc. and restructuring the ways humans and machines interact to create a stronger digital ecosystem.

Machine Learning- The Driving Force of Industrial Automation

With the growing changes in the customer behavior in regard to product quality and customization, it is difficult for the businesses to make changes in their system. That is where Machine Learning (ML) benefits the industries. ML is a subset of AI and empowers the computers to learn automatically from the data inputs and applies that information without any human intervention. ML aids in optimizing the production and supply chain efficiency, fraud detection, risk analysis and risk mitigation, portfolio management, GPS based predictions, targeted marketing campaigns, to name a few.

Machine Learning algorithms are categorized as:

Supervised Machine Learning

This model needs to have a dataset with some observations and labels of the observations that can be used to predict the future events.

Unsupervised Machine Learning

This model needs to have a dataset with some observations without the need of labels of the observations. It does not predict the right output but explores the data and draws inferences from the data sets.

Semi-supervised Machine Learning

This model is positioned between the supervised and unsupervised Machine Learning families. It uses both labeled as well as unlabeled data.

How AI impacts the Industrial Automation?

  • Get Valuable Insights from Data

Industries generate tons of valuable data in a single day. With the right industrial AI models, all the raw data can be turned in to useful insights that can lead the designers or engineers in to discovering new ways to improve and update according to the latest technologies.

  • Improve Product and Service Quality through computer vision

Computer vision tends to replicate the functionalities of human vision and extract important information from the images and videos. Computer vision operates on three main elements that include visual data, high-processing computers and smart algorithms. From the industrial automation perspective, this contributes to the overall increase in production, efficiency, plant safety and security.

  • Enhance Manufacturing techniques and handle conceptual data with Data-driven Deep Learning and Cognitive Computing

Deep Learning uses ML techniques based on artificial neural networks and is capable of extracting high-level insights from the raw data inputs. Cognitive computing is attentive on comprehending and reasoning at an advanced level, and is capable of handling even symbolic or conceptual data.

  • Boost Productivity and Safety with Collaboration Robots (Cobots) and Digital Twins

Cobots play a significant role in industries or laboratories. These autonomous systems intend to work alongside humans to pick, place, inject, analyze and pack items. They can also keep track of motion and avoid accidents or errors. Digital Twins can decrease the downtime and cost to set up such robotic systems.

  • Aid in Decision making with Reinforcement learning and Big Data Analytics

Reinforcement learning is a cutting-edge ML technique that attempts to train the ML models for advanced decision making. The ML model uses trial and error to find the appropriate solution to any complex problem. This technique is widely used in games but it can also shape other industries. Big Data Analytics enables to discover valuable patterns, trends, correlations and preferences for industries to take better decisions.

    li>Making Machine Learning accessible to the end-user with AI-enabled chips

The cloud servers hold most of the computational, storage and networking capabilities. Cloud-based services are great for those who have access to reliable connection and high-speed internet but they are unattainable for those in remote areas. AI-enabled chips can provide access to intelligence without cloud-based services and benefit the industries, especially the ones operating in the remote areas.

  • Analyze and Predict Future Trends by Deep Learning Platforms

Deep Learning models use unstructured data sets to predict the future trends. Deep learning is crucial for image and speech recognition and depends on three different factors including intelligent algorithms, tons of data and Graphics Processing Unit (GPU) to accelerate learning.

When AI Goes Wrong?

Now AI is playing an increasingly bigger role in our lives. It appears in everything from manufacturing, retail, education and scientific research to banking, criminal justice, hiring and entertainment, to name a few. However, the more we trust this new technology to take important decisions, the higher is the chance for large-scale errors. To prevent such errors, we must understand how and why AI reaches certain conclusions. The two terms which come up in the mind while thinking about improving AI are:

Explainable AI– It comprises of techniques that allow systems to explain their decision making and also offer insight in to the weak and strong parts of their thinking. It will enable us to know how much we can rely on AI results and how to make improvements.

Auditable AI– It takes the help of third parties to test the thinking of the AI system by giving varied queries and measuring the results to find flawed thinking or errors.

Future Trends of Industrial Automation

Further Expansion of IIoT with Predictive Analytics

Predictive maintenance programs are used to track equipment real-time to enhance responsiveness and decrease unplanned outages, resulting in safer operations, lower expenses and higher customer satisfaction.

Increased Implementation of VR and AR Tools

Augmented Reality (AR) and Virtual Reality (VR) tools offer interactive experiences that are specifically used for personnel training. Historically, the personnel training programs have been one-size-fits-all but with AR and VR tools, the training will be more customized based on the skills of the trainee. These technologies will also enable the personnel to train in non-disruptive and safe environment, especially when the training is on rare operations that may be difficult to understand and experience in real-world.

Growth of Edge Computing

The significant rise in data from devices which operate 24/7 often cause bandwidth issues as well as slow processing times. Edge computing technology shifts the information storage and processing from cloud services or data centers towards the specific location where it is required, which is often the device itself. Edge computing can enable the connected devices to make use of more real-time data for business decisions and process controls. Since more and more IoT devices are being used, edge computing is expected to increase.

Expansion of Smart Robot Usage

With advent of 5G network technology, availability of faster and more reliable internet connectivity along with improved satellite coverage to remote areas, the use of smart robotic applications in industries will expand rapidly.

Some Statistical Information on AI

After being a distant aspiration for the industries for many years, we are now more close to adoption and meaningful ROI of AI systems in the industrial landscape. As we see above, the potential advantages of AI adoption into the industrial ecosystem are huge. However, the articulation of the problem statements and the mapping of the right AI tools/technologies to these problem statements is fraught with several challenges. Internal champions (in the plant floor and above) and external technology providers have to collaborate deeply. The promise is there, the execution is the key. Surely, some of these technologies will get even more mature and “easy” to use with time, but choosing to wait and delay implementation will lead to a competitive handicap. Industries should act now, start small, but start now.

Utthunga is a leading engineering and industrial solutions company that can transform your business to leap in to a new world with intelligent, fast, secured and scalable end-to-end intelligent solutions.  We understand the industrial domain very well, and are well positioned to leverage the new technologies to deliver the best in class solutions to our customers.For more information on how to build an automated system with Artificial Intelligence and offer the best-fit solution for your industry requirements, contact Utthunga.