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.

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.

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.

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

The Oil & Gas industry is going to be a major generator of field data. As the industry embraces the technological disruptions caused by I4.0, it is expected to facilitate a gigantic build-up of data—especially from industrial assets like sensors in oil fields and other interconnected devices.

With such a surge in data accumulation, oil and gas industries need to level up their IT resources and adopt various cloud services. In this context, data migration services are playing an important role—the topic of this blog.

In this scenario, when most oil and gas companies are either on their way or already using digital resources, data migration becomes an imperative step.

The exploration and production (E&P) data that has been accumulated over the years has long been stored in warehouses or on-premises systems. However, as the industry progresses towards digitization, data migration has become the need of the hour.

Below are some key business benefits of data migration services for the oil and gas sector:

Maintaining data quality is a key challenge during data management and migration. Oil and gas companies must pay serious attention to managing the following attributes of data:

• Truthfulness – Data must reflect real-world conditions and market realities.
• Completeness – No data should be missing or ambiguous.
• Consistency – Nomenclature and values should be uniform across datasets.
• Timeliness – Data must remain current and accurate over time.

These technologies help extract high-quality data and map them accurately to target systems. With Industry 4.0 in full swing, these services play a pivotal role in enabling oil and gas companies to modernize their operations.

When a factory floor is full of connected devices, every node becomes a potential entry point. A single compromised sensor, USB stick, or unsecured protocol can bring down a production line or, worse, endanger human life. That’s why cybersecurity is central to how modern industrial systems are designed and maintained.

So what’s the actual risk, and how do you stay ahead of it?

This complexity, combined with remote access and cloud connectivity, creates gaps that can be exploited:

• A worm introduced through a small edge sensor can quickly move laterally across a network.
• A compromised PLC might be instructed to push parameters beyond safe operating ranges.
• Inadvertently plugging in an infected USB device can bring malware past internal firewalls.

Once inside, attackers can modify behavior, extract sensitive data, shut down systems, or trigger unsafe conditions. The impact is rarely isolated. One breach can set off a chain reaction across connected devices.

Securing these endpoints isn’t just about protection, it’s about preserving the reliability and safety of entire operations.

Creating a strong root of trust at the hardware level forms the basis for secure operations. Without it, even well-designed systems can be compromised.

At Utthunga, we work with OEMs and manufacturers to embed security into their products and systems from day one. From securing endpoint devices to building out secure communication protocols, our team helps you stay ahead of threats while focusing on what matters most—quality, uptime, and control.

Want to talk to an expert about securing your IIoT systems? Contact us or explore our Cybersecurity Services to see how we can support your next project.

Various research and studies underline the importance of implementing this philosophy and making it a part of the product life cycle by software product engineering services companies, irrespective of their size. Product engineering companies around the globe have seen an increase in their productivity and overall growth with successful implementation of DevOps tools and practices.

Implementing the right DevOps practices can help you enhance your customer experience and earn your stakeholders’ confidence over time.

Here are six ways you can implement DevOps to improve the product life cycle and reduce the time to market with an efficient product delivery management strategy in place.

As you input the codebase, the automated system checks it thoroughly and auto-generates test results with all the bugs specified. This way, you can include the operations team along with the development team to analyze the test and come up with an effective solution faster.

As every change is constantly monitored, it becomes easy to pinpoint the deviation that caused the defect in the product. Overall, continuous integration practices maintain the quality of the product whilst reducing the time to deliver the same.

With CD in place, you need not worry about breakpoints if you want to shift codes to any other platform. It checks for bugs, highlights the location, and helps you deal with them at the right time to ensure flexibility to the whole software product development process.

Application graphs, patterns, Venn diagrams, well-maintained project statistics, etc., are some of the ways teams can collaborate to understand the status of the project and bring out ideas for the betterment of the process if required. It helps development and operation teams to come up with a cohesive and refined approach towards delivering impeccable products on time.

Agile and DevOps help in improving the digital customer experience to a great extent by considering the key elements of digital transformation like transparency, a paradigm shift in work culture, and overall accountability of the organization.

DevOps consulting services from Utthunga serve as an efficient tool when it comes to helping software product engineering services companies in creating a faster product delivery pipeline. Contact our team to know how our DevOps experts can take your business to greater heights.

• Reusable Components: Prebuilt modules reduce redundancy and coding effort.

• Drag-and-Drop Interfaces: Intuitive design environments for building UIs and workflows.

• Visual Modeling: Logical flows and data structures can be mapped visually, reducing complexity.

• Built-in Integrations: Seamless connectivity with ERP, MES, IoT platforms, and cloud services.

Organizations using low-code platforms report up to 70% faster development cycles compared to traditional methods.

— Forrester Research

• Speed: LCNC enables the rapid development and deployment of custom applications—ideal for real-time decision-making, quick fixes on the shop floor, or launching pilot projects without months of lead time.

• Agility: Industrial operations frequently face shifting compliance requirements, production demands, or supply chain disruptions. LCNC platforms allow businesses to pivot fast by modifying workflows or interfaces without overhauling entire systems.

• Cost-Efficiency: By reducing the need for large development teams and minimizing time spent on custom coding, LCNC significantly lowers development overhead and helps clear IT backlogs.

• Shortage of Skilled Developers: With a growing gap in available software engineers, LCNC platforms empower OT engineers, process experts, and citizen developers to create their own tools—bridging the talent gap and decentralizing innovation.

• Integration: Modern LCNC platforms offer built-in connectors for seamless integration with existing MES, ERP, SCADA, and IIoT systems—ensuring that new applications enhance, rather than disrupt, the digital ecosystem.

By 2026, 80% of low-code users will be non-IT professionals — Gartner

• Rapid Prototyping for New Machines or Production LinesLCNC tools allow quick app creation to test and validate new production workflows or machine interfaces. These apps can also integrate with digital twins to simulate and refine processes before full implementation.

• Streamlining Maintenance and Service WorkflowsIndustrial teams can build tailored mobile apps for field technicians to manage maintenance logs, access remote diagnostics, and report issues in real-time—vital for smart factory efficiency.

• Compliance and Quality Tracking DashboardsOrganizations can create intuitive dashboards to track compliance with ISO, GMP, and OSHA standards. Role-based access ensures that only the right personnel manage or view critical quality data.

• Legacy System ExtensionInstead of replacing outdated systems, LCNC platforms enable modern UI layers and API-driven integrations that enhance functionality—without the cost and risk of full system rebuilds.

75% of large enterprises will be using at least four low-code tools by 2026.
— Gartner

Together, these benefits make LCNC a game-changer for scalable, agile industrial innovation.

• AI/ML Integration: LCNC platforms will increasingly leverage artificial intelligence and machine learning to auto-generate smarter, context-aware applications.

• Stronger Industrial Connectors: Support for protocols like OPC UA, MQTT, and Modbus will improve, enabling seamless integration with shop floor systems and IIoT devices.

• Hybrid Development Models: Expect a rise in environments that blend LCNC with traditional coding—offering flexibility for both citizen developers and professional engineers.

• Unified IT-OT Platforms: LCNC will play a key role in IT-OT convergence, allowing cross-functional teams to build, deploy, and manage solutions from a single platform.

• Mainstream Citizen Developer Programs: Enterprises are formalizing LCNC adoption with structured training and governance, making citizen development a core part of digital transformation.

This evolution positions LCNC as a long-term strategic enabler.

By combining software engineering rigor with domain‑specific knowledge and cutting‑edge integration services, we position industrial firms to succeed with low‑code transformation.

Looking to simplify software delivery across your industrial operations? Explore our software engineering services.

In this insightful discussion, Mr. Majunath Rao, Director, Utthunga, and Dr. Shankar, Co-founder & Director, GyanData Pvt. Ltd. sat down to unpack how engineering can create scalable, sustainable impact across industries. Here’s a seamless Q&A-style recap that dives deep into challenges, practical solutions, and industry use cases.

The common perception that “energy” refers only to electrical energy is inaccurate. In reality, electrical energy accounts for just 8% of the total energy usage. It’s important to distinguish between the different contributors that make up electrical energy.

Beyond electricity, there are various forms of energy such as thermal energy, hydraulic (water) energy, and internal energy. Each of these plays a significant role in the broader energy system, especially in industries like oil and gas, petrochemicals, and chemicals.

The oil and gas sector is highly mature in terms of energy management. These industries not only generate energy but are also accountable for how it is consumed. They are experienced in collecting data and optimizing energy use efficiently.

In contrast, the petrochemical sector represents a medium level of investment in energy conservation and management practices. The chemical industry, however, faces greater challenges. It is highly fragmented, consisting of many small sectors, which makes implementing uniform energy practices more difficult.

To address this, Utthunga is developing a simplified and accessible energy management approach tailored for the chemical sector, helping them manage energy more effectively with minimal complexity.

It’s important to note that we do not physically shift energy from one place to another. Utthunga’s primary goal is to decarbonize energy systems, which means replacing fossil fuel-based energy with renewable and alternative energy sources. This is essential because, regardless of the form energy takes, the carbon footprint remains unless the source changes.

Energy management should be approached systematically. While many claim to manage energy, in practice, their efforts often stop at basic measures like installing LED bulbs. Our approach goes much deeper — we focus on comprehensive energy conservation across all energy types.

Utthunga’s core strategy begins with an energy audit, which we divide into four distinct phases to ensure thorough and actionable insights.

1. Data Collection: Gathering relevant data about energy use in the plant or facility.

2. Baselining and Benchmarking: Analyzing equipment efficiency, often comparing older assets like 30–40-year-old compressors with current industry standards.

3. Finding Opportunities: Using simulations and scientific methods, we identify where energy can be saved—whether by tweaking processes or optimizing utilities.

4. Implementation Roadmap and ROI Analysis: Building a clear plan showing investments needed, expected savings, and return on investment (ROI), which is crucial for decision-making.

During a visit to a petrochemical plant, Utthunga discovered that the plant was incurring a monthly energy loss of ₹1.78 crore. This revelation served as a major eye-opener for the management.

They promptly reached out to us for support, and we carried out a comprehensive energy audit. One of our key findings was that their largest thermic heater was operating at just 18% of its actual capacity. While the company believed the heater’s efficiency to be 88%, our assessment revealed it was only 55%.

In addition, we noticed that chillers and water monitoring systems were poorly managed, contributing to further inefficiencies.

Over a two-week audit period, Utthunga developed and delivered a solution with a return on investment (ROI) within 12 months. Our intervention included process optimization, such as reducing batch reaction times by 10% to 15%, resulting in significant performance gains.

Utthunga also benchmarked their equipment against industry standards. Some of their machines were decades old, creating a substantial performance gap when compared to modern industry best practices.

Everything Begins with Plant Design

The foundation of sustainability in any industrial setup lies in its plant design. This is where the seeds of long-term efficiency and sustainability are sown. It’s not about building a large facility and then operating it at a reduced scale — rather, designing a plant that is fit-for-purpose is what truly matters.

Design Stage: The Ideal Moment for Sustainability Planning

Maximum sustainability value can be achieved during the design phase. Unfortunately, many companies wait until after construction to conduct an energy or sustainability audit — by then, significant investments have already been made, and the opportunity to embed sustainable practices from the start is lost.

This critical planning falls under basic engineering, which then transitions into detailed engineering and construction. This stage demands maximum attention, as any oversight here can lead to long-term inefficiencies and missed sustainability goals across the plant’s lifecycle.

Operations: The Heart of Sustainability

Once the plant is operational, the operations phase plays a massive role — contributing nearly 60% to 70% of a facility’s overall sustainability. This includes factors such as:

• Energy use
• Waste recovery
• Environmental impact

Operational inefficiencies such as poorly configured control valves, ineffective process logic, unnecessary shutdowns, and frequent startups all add up, negatively affecting both performance and sustainability.

Maintenance: A Key Driver for Sustainable Plant Life

Maintenance practices are equally vital. Today, with the rise of predictive and prescriptive maintenance, we can anticipate equipment failures and arrange necessary logistics in

advance, significantly reducing unplanned downtime and increasing operational efficiency.

The Digital Edge in Sustainable Engineering

With the advent of digitization, the scope and effectiveness of sustainable engineering have grown exponentially. Digital tools and data analytics now enable better decision-making, smarter maintenance strategies, and optimized resource use throughout a plant’s lifecycle.

Dr. Shankar, Co-founder & Director, GyanData Pvt. Ltd.

Process Design Changes Offer the Highest Gains

One of the most impactful ways to improve energy efficiency is through changes in process design. This may involve rerouting pipelines, adding a few heat exchangers, or making other system-level adjustments. While these modifications do require some investment, the payback period is typically between 6 months and 1 year. The energy savings, especially in thermal energy consumption, can be significant — ranging from 10% to 30%.

Shifting Focus: Thermal and Electrical Energy Utilization

Over the past 5 to 10 years, the industry’s focus has expanded beyond just thermal energy to include a more integrated view of both thermal and electrical energy usage. The challenge now is: how can we optimize combined energy consumption within a process?

In chemical processes, approximately 80% of energy consumption is thermal, while the remaining 20% is electrical. This presents an opportunity: if a portion of thermal energy usage can be shifted to electrical energy — in a cost-effective way — we can replicate the energy transition seen in the automotive industry, where internal combustion engines are being replaced by battery-powered electric vehicles.

Partial Shift Toward Electrification

While it’s not feasible to fully shift a chemical process from thermal to electrical energy, a partial transition is possible. If the electrical energy is sourced from renewables, this shift becomes not only technically viable but also sustainable and economical.

Evolving Tools: Modified Pinch Technology

To support this integrated approach, Pinch Technology — traditionally used for optimizing thermal energy — is now being adapted to also consider electrical energy. This evolution allows for more comprehensive energy integration strategies, enabling industries to maximize efficiency across both thermal and electrical domains.

Example:

A power plant boiler where hot flue gas exits containing leftover heat. Instead of wasting it, we transfer this heat to two places: the air used for combustion and the water fed into the steam tubes. You have two choices:

• Heat the air first, then the water, or
• Heat the water first, then the air.

It’s due to thermodynamics—heat transfer depends on temperature differences between streams, not just flow. So, if you heat the water first when the flue gas is hottest, you get more heat recovery. This subtle change in configuration can significantly reduce thermal energy consumption.

This approach is broadly applicable to any plant where heat recovery matters. By reviewing existing heat exchanger setups, plants can often identify simple configuration changes that yield significant energy savings. Tools like pinch technology help formalize this analysis, identifying where savings are possible, estimating costs, and calculating payback times.

Distillation columns separate components with small boiling point differences (e.g., 10–30°C). They require lots of thermal energy supplied at the bottom (reboiler) and cooling at the top. Because of the narrow temperature difference, these columns use a lot of energy.

Example:

In vapor recompression technology, the vapor leaving the top is compressed to raise its temperature, then used to supply heat at the bottom. This heat integration reduces the external heat needed.

Yes, but this is a trade-off—sacrificing some electrical energy to save a larger amount of thermal energy. Given the increasing availability of renewable electricity, this approach improves both cost-effectiveness and sustainability.

Vapor recompression technology is used in over 20 distillation processes involving close boiling mixtures, such as:

• Splitting C2 (ethylene/ethane) and C3 (propylene/propane) streams in refining and petrochemicals
• Methanol-water separation
• Benzene-toluene separation

Using pinch analysis and simulation tools, engineers estimate energy savings, electrical power needs, investment costs (like compressors), and calculate payback periods, often around 6 months, ensuring decisions are financially sound.

These include processes involving low temperatures and high pressures, such as:

• Energy liquefaction
• Air separation
• Liquid air energy storage

These processes can realize significant cost and carbon savings today by integrating electrical technologies.

The industry shouldn’t wait for 100% renewable electricity. It can start by:

• Optimizing thermal systems through pinch analysis
• Selectively shifting from thermal to electrical energy use
• Implementing technologies like vapor recompression

These steps reduce costs, cut emissions, and position companies well for a renewable-powered future.

For a deeper dive, watch the full webinar here

Feel free to share your questions or connect with us on LinkedIn!

Cyberattacks targeting OT environments have surged sharply. Recent data shows that 73% of organizations reported intrusions affecting OT systems in 2024, up from 49% just a year before. What’s more concerning is the rise of AI-enhanced attacks—threats that leverage automation and machine learning to carry out operations faster and on a larger scale. These AI-powered attacks now cut the time needed to deploy sophisticated ransomware from hours down to mere minutes.

Traditional cybersecurity strategies are struggling to keep up, especially given the unique challenges OT environments face—outdated equipment, limited patching options, and the need to avoid operational downtime at all costs. Against this backdrop, AI-driven threat detection has become a crucial pillar of modern OT security.

• Reduced Alert Fatigue: AI filters out false alarms and focuses attention on genuine threats. For example, Siemens Energy reported a 40% drop in false alerts after deploying AI-based detection.

• Faster Threat Detection: In mature environments, AI has cut average breach detection times from over 200 days to under 40, giving teams a crucial time advantage.

• Augmented Human Expertise: Automating routine investigations and triage lets security staff focus on strategic tasks. Some manufacturing clients have seen a 25% reduction in incident management time after introducing AI tools.

Across industries like manufacturing, energy, utilities, and logistics, organizations are quietly but steadily adopting AI-driven OT security solutions. Drawing from both our client work and wider industry observations, here’s how AI is being used effectively to secure OT environments in critical sectors:

• At a major European logistics hub, an AI system correlates data from OT equipment—such as crane controllers and fuel systems—with IT security signals. This enables the security team to significantly reduce investigation times and proactively block credential misuse attempts before they escalate into operational disruptions.

• A large utility provider in the Middle East uses passive network monitoring powered by AI to safeguard legacy SCADA systems that cannot be patched. We’ve supported a similar client in deploying this approach, achieving near real-time threat detection across hundreds of substations while keeping systems online.

• In North America, one manufacturer’s AI-driven analytics flagged an unusual pattern in robotic arm movements—not as a mechanical error, but a possible cyber manipulation. Several of our manufacturing clients have since adopted similar AI capabilities to deepen their visibility and response.

• Organizations operating under European NIS2 and GCC’s NCA and NDMO frameworks are increasingly turning to AI not only to enhance security but also to meet regulatory expectations and lower cyber insurance costs.

But putting AI to work in OT isn’t just about adopting new technology. It’s about knowing where it fits, how it behaves around legacy systems, and what risks actually matter on the plant floor or control room.

That’s where Utthunga’s cybersecurity solutions make a real difference. Working with leading industrial clients, we deliver AI-powered threat detection capabilities built specifically for complex OT environments. From passive monitoring of legacy systems to intelligent threat correlation across IT and OT, our cybersecurity solutions are helping organizations stay a step ahead of threats while keeping operations secure and resilient.