Direct Lithium Extraction (DLE) is gaining momentum as lithium producers look for faster and more efficient ways to recover lithium from brines. But deploying DLE technology does not automatically mean a facility is achieving its full recovery potential. 

Recovery can be affected by brine variability, pretreatment, process conditions, equipment performance, and operational controls. 

Here are five warning signs that your DLE facility may be leaving recovery—and production value—on the table. 

If recovery changes significantly with feed conditions, the process may not be optimized for the actual brine entering the plant. 

Watch for: 

• Variable lithium concentration 
• Changing impurity levels
• Unstable flow or temperature 
• Recovery fluctuations without a clear cause 

Understanding the relationship between brine characteristics and recovery is the first step toward improving performance.

DLE performance starts before the extraction stage. 

Solids, scaling compounds, organic matter, and other impurities can affect extraction media, membranes, solvents, and downstream equipment. 

Signs of a pretreatment problem include: 

• Increasing fouling 
• Frequent cleaning 
• Pressure fluctuations 
• Rising chemical consumption 
• Declining extraction performance 

A stable pretreatment process creates the conditions for more consistent DLE recovery. 

The extraction stage can only perform as well as the feed preparation allows. 

DLE systems typically involve multiple cycles, including extraction, regeneration, washing, and lithium recovery. 

Small inefficiencies can accumulate into significant production losses. 

Long cycle times can reduce throughput, while incomplete regeneration can reduce extraction capacity in subsequent cycles. 

Operators should continuously monitor: 

Cycle time | Extraction efficiency | Regeneration performance | Lithium concentration | Chemical consumption 

The objective should be to optimize the complete operating cycle, not just one process parameter. 

DLE facilities can generate large volumes of process and equipment data. But more data does not automatically mean better recovery. 

If operators cannot connect changes in flow, pressure, chemistry, temperature, equipment condition, and recovery, important optimization opportunities can remain hidden. 

Industrial connectivity and analytics can help identify: 

• Recovery deviations 
• Process instability 
• Equipment degradation 
• Abnormal operating conditions 
• Emerging bottlenecks 

Digital twins can also help evaluate process changes before they are introduced into the operating plant. 

The goal is not more data. It is better recovery decisions. 

A recovery percentage tells you what happened. It does not necessarily tell you where the loss occurred. 

A stronger approach is to track lithium across the complete process: 

Brine Feed → Pretreatment → DLE → Regeneration → Concentration → Product Recovery 

This can reveal where lithium is being lost and which process stage offers the greatest opportunity for improvement. 

Instead of optimizing individual equipment, producers can then focus on end-to-end recovery performance. 

Utthunga helps DLE technology providers and lithium producers connect process engineering, automation, industrial connectivity, and digital intelligence to improve plant performance. 

Its capabilities include: 

• Process & Plant Engineering – identify constraints and recovery losses. 
• Automation & Controls – improve process stability and control. 
• Industrial Connectivity – connect equipment, control systems, and operational data. 
• Digital Twin & Simulation – evaluate optimization scenarios. 
• AI & Analytics – identify process deviations and performance patterns. 
• Commissioning & Optimization – support the transition from pilot to stable operations. 

For DLE facilities, improving recovery is not about optimizing one number in isolation. It requires understanding how brine quality, pretreatment, extraction, regeneration, downstream processing, equipment, and controls work together. 

DLE’s commercial value depends on consistent performance under real operating conditions. 

If recovery fluctuates, pretreatment becomes unstable, cycles take longer than expected, operational data remains disconnected, or lithium losses cannot be traced, valuable production may be left on the table. 

The question is: 

Are you measuring recovery—or actively engineering it? 

By connecting engineering, automation, data, and continuous optimization, DLE operators can move toward higher recovery, more predictable production, and stronger commercial performance. 

Want to identify where your DLE facility may be losing recovery? Talk to Utthunga’s lithium engineering experts → 

Snippet:

In many industrial enterprises, PPx (Plant & Process Engineering) represents a significant share of operating spend, often without clear visibility into its impact on performance. Leading companies are addressing this through value engineering—reducing complexity, standardizing processes, and improving output and reliability. The focus shifts from spend to discipline, ensuring engineering investments consistently deliver measurable returns.

In many industrial enterprises, PPx (Plant & Process Engineering) quietly consumes 25–40% of operating expense and a substantial share of capital deployment — often exceeding SG&A in asset-intensive environments. Yet enterprises rarely have full transparency into how much of that spend directly improves throughput, yield, reliability, or unit cost. The issue is seldom over-investment in growth; it is structural complexity: duplicated engineering standards across sites, unmanaged process variation, bespoke equipment configurations, and legacy systems layered over time that dilute returns.

Leading operators show that disciplined value engineering can reduce PPx costs by 25–35% while sustaining — and often improving — output, safety, and reliability performance. The shift is strategic rather than tactical: from project-driven expansion to margin-accretive process design and asset optimization. For enterprises, PPx optimization is not cost cutting; it is capital allocation discipline — protecting EBITDA, strengthening asset productivity, and ensuring engineering investment delivers measurable economic return.

In asset-intensive organizations, PPx cost inflation rarely appears as a single large line item. It accumulates gradually — embedded in design choices, capital approvals, site-level autonomy, and legacy decisions that compound over time. What begins as operational flexibility often hardens into structural inefficiency. For boards, the risk is not visible overspend, but embedded complexity that suppresses asset productivity and erodes return on invested capital.

• Overlapping Product Lines and Process Configurations

Multiple production variants or parallel process lines designed to serve marginal demand differences drive duplicated tooling, maintenance regimes, and engineering oversight. Incremental revenue rarely offsets the fixed-cost burden embedded in the asset base.

• Excess Customization by Region or Site

Local engineering autonomy can result in bespoke equipment specifications, control systems, and safety protocols. While intended to optimize for local conditions, the outcome is fragmented standards, higher spare parts inventories, and limited economies of scale in procurement.

• Legacy Architecture and Technical Debt

Layered control systems, outdated automation platforms, and incremental retrofits create operational fragility. Maintenance costs rise, downtime increases, and capital is repeatedly deployed to patch rather than redesign.

• Overbuilt Capabilities with Low Utilization

Facilities are frequently engineered for peak demand scenarios that seldom materialize. Idle capacity, oversized utilities, and redundant redundancy inflate depreciation and energy costs without proportional revenue contribution.

• Inefficient Vendor Ecosystems

Fragmented supplier bases and project-by-project contracting reduce negotiating leverage and standardization. Engineering teams spend time managing interfaces instead of optimizing process performance.

• Under-Leveraged Shared Engineering Services

When design, procurement, and maintenance engineering are replicated across sites, organizations forfeit scale advantages. Centralized standards, modular design libraries, and shared technical centers are often underutilized.

Real Cost Impact of Product & Process Complexity:

Research across manufacturing firms shows that as product variety increases, roughly 75% of total revenue comes from only about 13% of the product portfolio, highlighting how a small share of products often drives most profits — while complexity costs from the remaining portfolio drag on margins.

Sorce : ScienceDirect

Even without digging into line-by-line engineering budgets, boards can detect warning signs that PPx (Plant & Process Engineering) spend is becoming inefficient. These symptoms often precede margin erosion and reduced return on capital, and they are critical signals for executive oversight. The diagram below represents the symptoms:

Complexity Is Costing U.S. Manufacturers Billions — and Few Are Acting

According to a 2025 survey of 150 U.S. manufacturing executives, while 84% of companies say reducing product capabilities or features is very important to cost takeout, only 31% are engaging in value engineering or product redesign — meaning most are focusing on short‑term cuts rather than structural cost discipline that could sustainably improve margins.

Sorce : efeso

At the enterprise level, value engineering is far more strategic than simply cutting features or trimming budgets. It is a disciplined approach that ensures every engineering investment — whether in plant design, process improvement, or capital projects — delivers measurable economic return. High-performing organizations treat value engineering as a lens for capital allocation, not just cost control.

Many engineering investments are made to satisfy internal preferences or minor customization that customers do not value. Standardization of non-differentiating elements ensures resources are deployed where they create competitive advantage.

When investment aligns with delivered value, organizations can optimize pricing, throughput incentives, and product availability. This ensures that engineering spend translates directly into economic benefit, rather than incremental complexity or unused capacity.

Achieving a meaningful reduction in PPx spend requires strategic levers, not ad hoc cost cutting. Leading enterprises systematically address complexity, inefficiency, and misaligned investment to free up capital while sustaining growth.

Boards should ensure the organization focuses on what truly drives value. This means eliminating redundant features, sunsetting low-margin or low-adoption product variants and concentrating resources on capabilities that differentiate the business and support monetization. The goal is a leaner, higher-return portfolio.

Overbuilt, bespoke systems create hidden costs. Rationalization emphasizes modular, reusable components, reduction of technical debt, and platform standardization. By simplifying architectures, organizations reduce marginal costs, improve maintainability, and accelerate innovation.

Inefficient supply chains and fragmented vendors inflate costs. Consolidating suppliers, renegotiating enterprise-level contracts, and strategically deciding what to build versus buy ensures the organization captures scale advantages and reduces redundancy.

Decisions must be grounded in hard metrics. Investments should prioritize features or process improvements with measurable contribution margin, retiring underperforming initiatives, and aligning roadmaps to monetizable outcomes. This ensures capital drives economic value, not activity.

Disciplined oversight is essential. Implementing stage-gate investment processes, enforcing ROI thresholds, and establishing an executive-level PPx review board ensures every engineering dollar is evaluated, approved, and monitored for impact. Governance converts strategic intent into measurable financial results.

In today’s competitive industrial landscape, structured value engineering is no longer optional — it’s a strategic imperative that drives profitable growth. Achieving up to 30% PPx cost reduction is best realized through close partnerships with expert engineering firms. An experienced partner aligns investments with business outcomes, standardizes processes, and embeds data-driven decision frameworks.

Utthunga is one such partner, helping organizations optimize plant and process performance through advanced automation, digital twin simulations, and standardized engineering practices. By rationalizing systems, consolidating vendor ecosystems, and embedding data-driven decision frameworks, Utthunga delivers measurable reductions in operational costs, improved asset reliability, and faster project execution.

Contact us to learn more about our services.

Snippet:

In today’s fast-evolving manufacturing landscape, relying on siloed systems and legacy networks is increasingly risky. Industrial connectivity enables real-time data flow, prevents costly disruptions, and drives smarter, more resilient operations. Read this blog to discover how industrial connectivity delivers tangible business value. Learn how to create a clear implementation roadmap and practical steps toward resilient, smart manufacturing. Expert partners can help accelerate the process.

In today’s rapidly evolving manufacturing landscape, plant managers, engineers, and executives face a recurring challenge: ensuring operational continuity while driving innovation. Many still rely on siloed production systems, manual data collection, and legacy networks, assuming that traditional methods are sufficient for day-to-day operations. But in an era of global supply chain disruptions, rising cybersecurity threats, and ever-increasing customer expectations, this assumption is increasingly risky.

Consider a mid-sized automotive components manufacturer that experienced a week-long production halt because a single networked machine failed to communicate with the central control system. While the machines themselves were operational, the lack of seamless connectivity prevented data exchange, halted automated scheduling, and delayed deliveries. Such scenarios are no longer rare; they are warning signs that traditional approaches to industrial communication and control are inadequate.

The solution lies in industrial connectivity—a robust, integrated network infrastructure that links machines, sensors, systems, and stakeholders across the enterprise. By enabling real-time data flow, predictive insights, and secure remote access, connectivity forms the backbone of smart manufacturing, fostering resilience, agility, and growth.

Unlike conventional IT networks, industrial connectivity is specifically designed to meet the unique demands of production environments—from high uptime and precise timing to ruggedized equipment interfaces and strict safety compliance. By integrating these capabilities, manufacturers can achieve real-time operational visibility, smarter decision-making, and resilient production workflows.

Key components that make industrial connectivity effective include:

• Machine-to-Machine (M2M) Communication: Ensures that equipment shares operational data automatically for optimized production.

• Edge Computing and Data Aggregation: Processes critical data locally, reducing latency and enhancing reliability.

• Secure Remote Access: Enables engineers and operators to monitor and control processes from anywhere, without compromising security.

• Standardized Protocols and Interoperability: Ensures devices from different vendors can communicate effectively.

• Cybersecurity Measures: Protects data and operations from external threats while maintaining compliance with industry regulations.

In today’s digital-first manufacturing landscape, industrial connectivity is no longer a “nice-to-have”—it has become critical for compliance, operational resilience, and competitive advantage. Manufacturers face a convergence of pressures that demand robust, secure, and interoperable networks. From meeting stringent safety and cybersecurity regulations to satisfying customer expectations for transparency and agility, connectivity is at the heart of maintaining trust, reducing risk, and staying ahead in a fast-paced market.

Key factors driving the urgency for industrial connectivity include:

• Compliance and Safety Standards: Regulations such as ISO 27001 (information security), IEC 62443 (industrial automation cybersecurity), and regional mandates require secure, auditable networks.

• Market Expectations: Customers increasingly demand transparency, traceability, and rapid response to changing production needs. Without robust connectivity, organizations risk missing delivery timelines or quality standards.

• Operational Risks: Siloed systems and intermittent data flow increase downtime risks, reduce productivity, and limit scalability.

• Emerging Threats: Cyber-attacks targeting industrial networks have grown in sophistication, highlighting the need for secure, resilient connectivity infrastructures.

By building a connected and secure ecosystem, manufacturers not only ensure regulatory compliance but also strengthen trust with partners, regulators, and customers—turning connectivity into a strategic differentiator in today’s competitive industrial landscape.

In modern manufacturing, connectivity isn’t just about linking machines—it’s a powerful business enabler. By creating a seamless flow of data across production systems, industrial connectivity transforms operations from reactive to predictive, from siloed to agile, and from standard to strategic. Organizations that embrace connected systems don’t just meet compliance requirements—they gain measurable efficiency, reduce risk, improve product quality, and unlock competitive advantages that directly impact the bottom line.

1. Enhanced Operational Efficiency

• Real-time monitoring reduces unplanned downtime.
• Automated alerts and machine-to-machine coordination streamline workflows.
• Predictive maintenance lowers repair costs and prevents production halts.

2. Agility and Scalability

• Rapidly integrate new machines or production lines without extensive reconfiguration.
• Easily adapt to changing production schedules or market demands.
• Leverage cloud-based platforms to scale analytics and control across multiple facilities.

3. Improved Product Quality

• Continuous data collection allows for in-process quality checks.
• Early detection of deviations ensures fewer defects reach end customers.
• Supports continuous improvement initiatives by providing actionable insights.

4. Risk Mitigation

• Enhanced visibility into operations reduces the risk of failures or safety incidents.
• Secure network frameworks protect against cyber threats and unauthorized access.
• Supports compliance reporting with automated documentation.

5. Competitive Advantage

• Faster time-to-market due to synchronized production planning.
• Greater transparency enhances customer trust and brand reputation.
• Data-driven decision-making enables strategic growth initiatives.

For manufacturers aiming to unlock the full potential of industrial connectivity, a structured, strategic approach is key. The following steps serve as a practical roadmap to strengthen operations, improve agility, and safeguard systems:

1. Conduct a Connectivity Assessment

• Map all devices, control systems, and networks to understand current infrastructure.
• Identify communication gaps, legacy bottlenecks, and potential cybersecurity vulnerabilities.
• Define connectivity KPIs aligned with operational and business objectives.

2. Standardize Protocols and Interfaces

• Transition to widely supported protocols (e.g., OPC UA, MQTT) to enable seamless communication.
• Ensure interoperability across different vendors and platforms for smoother integration.
• Reduce reliance on proprietary systems that can limit scalability and flexibility.

3. Implement Edge and Cloud Integration

• Utilize edge computing for time-critical processes to minimize latency and enhance reliability.
• Integrate cloud platforms for predictive analytics, centralized monitoring, and secure remote access.
• Balance data privacy, latency, and operational requirements to optimize performance.

4. Strengthen Cybersecurity Measures

• Apply multi-layered security frameworks including network segmentation, firewalls, and encryption.
• Conduct regular penetration tests and vulnerability assessments to stay ahead of threats.
• Ensure compliance with industrial security standards such as IEC 62443 and NIST guidelines.

5. Document and Monitor Continuously

• Maintain clear, up-to-date documentation for devices, networks, and data flows.
• Use dashboards and visualization tools to track real-time performance metrics.
• Periodically review and refine the connectivity strategy to keep pace with evolving technology.

Implementing industrial connectivity can be complex—especially in legacy environments or across multi-site operations. Partnering with specialized engineering and technology service providers like Utthunga delivers significant strategic and operational advantages:

• Faster Deployment: With deep domain expertise, Utthunga assesses existing infrastructure, identifies gaps, and designs scalable, future-ready connectivity architectures—accelerating time-to-value.

• Reduced Risk: Proven methodologies ensure compliance with industry standards while embedding robust cybersecurity practices to safeguard critical industrial assets.

• Optimized Performance: Utthunga enables efficient data flow, seamless integration with analytics platforms, and edge computing optimization—unlocking actionable insights and operational efficiency.

• Ongoing Support: From proactive monitoring and troubleshooting to continuous upgrades, Utthunga ensures industrial connectivity remains resilient, secure, and aligned with evolving business needs.

By collaborating with experienced partners like Utthunga, organizations can transform connectivity from a technical necessity into a strategic enabler of growth, innovation, and long-term resilience. Contact us now to know more about our industrial connectivity services.

Snippet

Most startup delays don’t happen during commissioning—they’re locked in during design and procurement. Strategic commissioning integrates testability, validation, and startup sequencing into early project phases, removing risk from the critical path. Plants designed with commissioning in mind transition faster from construction to stable operations, accelerating revenue realization and protecting financial assumptions. When commissioning thinking starts at the first design decision rather than the final testing phase, projects gain weeks in startup timelines and millions in faster payback.

A plant does not start generating value when construction ends. It starts when the first unit of production moves through the system.

That gap between mechanical completion and stable operations is where projects either protect their financial assumptions or quietly erode them. Every extra day in startup holds back revenue, keeps teams on-site longer, and extends the period where capital is tied up without return.

What makes this challenging is that most startup delays are not caused during commissioning itself. They are the result of decisions made much earlier, during design, procurement, and construction. By the time commissioning begins, teams are often working around constraints that are already locked in.

Where Startup Delays Actually Come From

Most delays follow a familiar pattern:

• Control systems being tested for the first time on-site
• Gaps or inconsistencies in vendor documentation
• Piping and layout decisions that complicate flushing and testing
• Sequential commissioning plans where parallel execution was possible
• Late discovery of integration mismatches across disciplines

None of these issues originate during commissioning. They simply surface there, when time is limited and the cost of delay is at its highest.

In capital projects, not all inefficiencies are equal. A small loss in operational efficiency, sustained over years, often outweighs a one-time increase in capital cost. That puts pressure on getting the design right, not just from a technical standpoint, but from an operational one.

Commissioning plays a critical role here. When it is introduced early, during pre-FEED and FEED, it brings a different lens to design decisions. Instead of asking only whether a system will work, teams begin asking how easily it can be tested, validated, and brought online.

Piping layouts are evaluated not just for flow efficiency, but for how easily they can be flushed and leak-tested. Control systems are designed with loop checks and integration in mind. Equipment layouts are planned to allow parallel commissioning instead of forcing sequential dependencies.

Each of these decisions can save days, sometimes weeks, during startup.

• Design reviews include testability and startup sequence, not just functionality
• Procurement packages define factory testing and documentation requirements upfront
• Control systems are validated before they reach site
• Construction sequencing supports progressive commissioning
• Startup becomes a planned transition, not a compressed final phase

The shift is subtle in execution, but significant in outcome.

Traditional execution pushes risks toward the end of the project. Integration issues, controlling logic gaps, and equipment inconsistencies often surface during on-site commissioning, when there is little room to maneuver.

Fixing problems at that stage is expensive, not just because of rework, but because every delay directly impacts revenue realization. Strategic commissioning changes by shifting validation earlier.

Control systems are tested before deployment. Equipment performance is verified before installation. Interfaces between systems are validated in controlled environments. Documentation and test procedures are defined in advance.

What this does is remove uncertainty from the final phase, where it is hardest to manage.

• Pre-FEED and FEED: Defines testability, integration logic, and startup sequencing
• Design Development: Aligns system design with commissioning requirements
• Procurement: Embeds testing, validation, and documentation expectations into vendor contracts
• Construction: Enables progressive system validation instead of last-minute congestion
• Startup: Executes a structured, low-risk transition into operations

The earlier it is applied, the more impact it has.

A plant designed to generate $500K per day loses $3.5M for every week startup extends beyond plan.

And that is only part of the impact. Delayed startup often leads to slower ramp-up, operational instability, and additional time to reach full production capacity. This is why startup performance is not just a project metric, but a business outcome.

Because commissioning shapes both how capital is spent and how systems perform, its financial impact starts early and compounds over time. Projects that bring commissioning into pre-FEED and design stages consistently see faster payback, fewer late-stage changes, and tighter control over execution. Rework is reduced, validation cycles are shorter, and teams spend less time resolving avoidable issues on-site. More importantly, plants reach stable operations sooner, allowing revenue to start earlier and build without the usual setbacks during ramp-up.

Commissioning is often treated as the final hurdle before operations, but it quietly influences every stage that comes before it. When approached as a strategic function, it connects design intent with operational reality, ensuring that what is built can be tested, validated, and brought online without friction. Design decisions become easier to execute, procurement becomes more precise, and construction aligns better with startup requirements.

When this alignment is missing, commissioning becomes a phase where teams are forced to resolve accumulated gaps under time pressure. What should have been a structured transition turns into a reactive process.

Commissioning does not begin at startup. It begins with the first design decision, when there is still room to shape outcomes rather than fix them. The difference is not in the effort required, but in when that effort is applied and how much it costs to get it wrong.

If you’re planning a project where startup performance matters, it’s worth considering how commissioning fits into your early planning stages. Contact us now to learn more about our approach to plant commissioning.