Manufacturing relies not just on data, but on documentation as well. Equipment manuals, maintenance procedures, quality protocols, work instructions, training materials, change orders. This documentation is essential, but its sheer volume creates a practical problem: the information you need is there, but finding it quickly enough to matter is the challenge.

With Critical Manufacturing MES v11.2, we’re introducing two AI-powered capabilities designed specifically to address this reality: Ask AI and View Summary. These capabilities exist because there is a real problem to solve. Manufacturing teams need rapid access to information within dense technical documentation. AI happens to be the right tool for this job.

Documentation in Manufacturing

Equipment maintenance manuals can span hundreds of pages with detailed technical specifications, troubleshooting matrices, calibration procedures, and parts diagrams. Quality procedures reference other procedures. Work instructions evolve through revisions and changes. Training documentation accumulates as processes mature.

The knowledge is documented. The challenge is retrieval.

Traditional search mechanisms have tried to ameliorate the proliferation and scattering of information. Nevertheless, they are fundamentally bound to the user knowing the exact term they are looking for, but manufacturing problems don’t always present themselves with searchable keywords. An equipment error might require understanding the relationship between several subsystems. A quality issue might need context from multiple procedures. These situations require understanding context and meaning, not just keyword matching. They also, like a doctor making a diagnosis, have a decision tree of most likely issues and solutions, that require a context and an iteration process.

Two Capabilities, One Goal: Faster Access to Better Answers

Ask AI: Your Documentation Intelligence Layer

Ask AI allows users to interact directly with a large language model that has access to documents and attachments within Critical Manufacturing MES. Rather than searching for keywords, users ask questions and interact with documentation in natural language. The same way they would ask a colleague who knew the documentation thoroughly.

How it works in practice:

A maintenance technician encounters a recurring quality issue with a reflow oven. Instead of manually searching through the equipment manual, they open Ask AI and type: “What causes PCB discoloration?”

The AI analyzes the relevant maintenance documentation and provides a focused answer drawn from the manual, including the likely causes, the step-by-step troubleshooting procedure, and any safety precautions specific to that error condition.

The technician can follow up: “What are the recommended steps to correct the issue?”

The expertise and decision making remains with the technician. What changes is how quickly they can access the documented procedures that inform their decisions.

View Summary: Rapid Document Comprehension

View Summary generates concise summaries of selected documents or attachments, with the ability to ask follow-up questions about specific aspects of the content.

Typical use case:

A quality engineer receives a 45-page deviation report that requires review and response. Rather than reading the entire document linearly to understand its scope, they generate a summary that provides:

• The core issue being addressed
• Key findings and root causes identified
• Recommended corrective actions
• Affected products or processes

With this context established in minutes rather than hours, the engineer can then ask targeted questions: “What validation testing was performed?” or “Which suppliers are mentioned in this report?”

The summary provides situational awareness. The follow-up questions allow focused deep-dives into areas that matter for the engineer’s specific responsibility.

Why These Capabilities, Why Now

We evaluate every potential AI integration against clear criteria:

Does it solve a real, recurring problem? Documentation access and comprehension are consistent pain points across manufacturing operations. Time spent searching is time not spent solving problems.

Does it integrate naturally into existing workflows? These capabilities live within the MES interface, accessible where users already work with documents and attachments. There’s no separate system to learn, no context switching required.

Does it enhance rather than replace human expertise? The AI provides information and context. The maintenance technician still diagnoses the equipment. The quality engineer still makes the compliance judgment. The production supervisor still decides on the corrective action. We’re accelerating access to documented knowledge, not attempting to automate technical decision-making.

Is it built on a foundation we can extend? These capabilities use AWS Bedrock, providing enterprise-grade security and a platform we can build on as AI technology matures and as we identify additional high-value applications in manufacturing operations.

This release represents one deliberate step in a longer strategic direction: progressively augmenting Critical Manufacturing MES with intelligence capabilities that align with how manufacturing actually works.

Technical Foundation: Built for Manufacturing Environments

The implementation uses AWS Bedrock, which means:

• Enterprise-grade security and compliance standards apply
• Flexibility in model selection as AI capabilities evolve

The AI works with documents and attachments already managed within Critical Manufacturing MES: maintenance manuals, work instructions, SOPs, quality procedures, change orders, training materials. If it’s documented in your MES, Ask AI can help users find relevant information within it.

Using AI Responsibly in Manufacturing

We are clear-eyed about what AI does well and what it does not. Large language models excel at understanding natural language, identifying relevant information across large documents, and synthesizing that information into coherent answers. They’re powerful tools for information retrieval and comprehension.

They are not infallible. AI-generated responses should be verified against source documentation for critical decisions, just as you would verify information from any source. The AI cites its sources, allowing users to validate responses against the original documentation. This is crucial, the user is able to traverse, validate and deepen his understanding by leveraging all the original references the AI provides.

This is AI as an assistant, knowledgeable, fast, helpful, but not as a replacement for human judgment in manufacturing operations.

Getting Started

These capabilities are available now in Critical Manufacturing MES v11.2. There’s no complex setup required. If you are managing documents and attachments in the MES, you can start using Ask AI and View Summary immediately.

This is an evolving capability, and your real-world experience will help shape how we extend it.

Looking Ahead

We don’t add technology because it’s trending. We add capabilities that deliver measurable operational value, fewer errors, faster decisions, better outcomes on the shop floor. All of this leveraging a robust shop floor control system, that has years of context and experience, providing a standard and guarded way for AIs to operate.

Document intelligence solves a specific, recurring problem: rapid access to critical information buried in complex technical documentation. It’s a natural fit for AI, and it delivers tangible results. But it’s one capability among many we’re developing.

Our broader vision is clear: we are transforming Critical Manufacturing MES from a transaction system into an intelligent partner. Not by bolting on chat bots or AI assistants, but by using AI to build the actual features and solutions manufacturing operations need.

This means:

Frontline empowerment - AI that augments operators, technicians, and supervisors with the right information and insights when they need them, helping people work smarter.

Operational intelligence - AI that provides clarity and foresight across processes, equipment, and materials, identifying issues before they become problems.

Accelerated value - AI that shortens implementation timelines and reduces complexity, getting you to measurable business results faster.

The document capabilities in v11.2 are another keystone in our foundation. We are building deliberately, learning from real-world usage, and advancing where it genuinely matters.

The MES should progressively understand more about your operations and provide increasingly sophisticated support to the people running them. Not to replace their expertise, but to amplify it.

That’s the direction we’re committed to. V11.2 is the first step.

Author

Hi! My name is Ricardo Magalhães. 🤘

You can check me on LinkedIn

Introduction

A reusable spare part is a component or part of a machine that, after being removed due to deterioration, failure, or maintenance activity, can be restored or repaired and then used again in the same or another machine.

As an example, let’s take an Asset BOM (also called Equipment BOM) for Wafer Inspection Equipment typically used in the Semiconductor industry.

This equipment has 4 different reusable spare parts that can be replaced at any moment or during a maintenance activity:

• Wafer Stage
• Camera System
• Two Control Centers
• Marking Device

Apart from the reusable spare parts, the equipment also consumes a set of consumables that are used exclusively during maintenance activities. Examples include:

• Air Filter
• Vacuum Pads
• Polyalphaolefin based lubricants

Then

And Now

DEMO

Final thoughts

Author

Skills: MES Consultant | System Testing | System Modeling | User Training | Content Creating

When we set out to migrate our Operational Data Store (ODS) from SQL Server to ClickHouse, we knew the ripple effects would extend far beyond the database layer. Our entire reporting infrastructure needed a rethink. What started as a database migration evolved into a comprehensive modernization of how we deliver information to manufacturing operations.

Why We Had to Move

Two driving forces converged to make migration inevitable:

The ClickHouse shift. As we detailed in our previous post on the ClickHouse migration, moving to ClickHouse brought performance improvements for analytical workloads. But Microsoft Report Builder and SQL Server Reporting Services (SSRS) were built for the SQL Server ecosystem. While technically possible to connect SSRS to other data sources, it’s not where the platform shines.

The Kubernetes reality. Our infrastructure is largely containerized and orchestrated by Kubernetes, though we still run our SQL Server databases in VMs. SSRS, however, comes from a different time, one of Windows Servers and IIS. Forcing SSRS into our cloud-native architecture would have been fighting against the current. We needed a reporting solution that embraced modern deployment patterns: containers, horizontal scaling, and cloud-agnostic infrastructure.

The Evaluation Process

We didn’t rush into selecting a replacement. Manufacturing systems demand reliability, and our reports are mission-critical for operations, quality control, and compliance. Our evaluation criteria included:

• Data source flexibility: Native or robust support for ClickHouse, plus the ability to consume OData feeds. Our data access strategy centers on OData exposed through our DataManager component and DataSet system entity type, so seamless OData integration was essential

• Kubernetes-friendly deployment: Docker containers, stateless architecture, and straightforward orchestration

• Report design capability: A designer that wouldn’t feel like a significant step backward from Report Builder

• Export formats: PDF, Excel, and other formats commonly needed in manufacturing

• Migration path: How difficult would it be to convert existing reports?

• Licensing and cost structure: Predictable costs that scale with our needs

After evaluating several options (including open-source alternatives and commercial platforms), Stimulsoft emerged as the best fit. It checked all our technical boxes: native ClickHouse support, robust OData connectivity, runs in containers, and offers a report designer that our team could adopt without a steep learning curve. The JS-based architecture also aligned well with our existing technology stack. An additional advantage was our existing familiarity with Stimulsoft. Our PrintableDocuments module had already been implemented using the same tool, which meant we had proven experience with its capabilities and understood its strengths and limitations in a production environment.

The reality of the market. Let’s be honest: printable reports aren’t sexy. The developer community has moved on to dashboards, real-time visualizations, and interactive analytics. Open a tech conference schedule or browse GitHub trending projects, and you’ll find dozens of dashboard frameworks but very few modern reporting tools. The market for traditional report designers has shrunk considerably. Most innovation and investment flows toward tools like Grafana, Tableau, and Power BI, not toward PDF generation engines. This made our evaluation more challenging than expected. The options were limited, and many tools felt dated or were poorly maintained. Finding a modern, actively developed reporting solution that fit our cloud-native architecture required looking harder than we anticipated.

Why Printed Reports Still Matter in Manufacturing

With real-time dashboards and interactive analytics becoming standard, you might wonder: why invest in traditional reports at all? Why not just build everything as a Grafana dashboard?

The reality of manufacturing operations tells a different story. Here’s why printable reports remain essential:

Compliance and audit trails. Regulated industries require signed, dated documentation. A PDF report with formal approval signatures is often legally required. You cannot simply attach a compliance officer’s signature to a dashboard.

Material documentation. When a material or production batch is complete, you need a comprehensive, frozen-in-time record of what happened. That batch report needs to travel with the material, be archived for years, and be reproducible exactly as it was generated. Dashboards are dynamic; reports are immutable.

Offline accessibility. Shop floor environments don’t always have reliable network access. A printed report or a PDF on a tablet works anywhere, anytime. When a quality inspector is in a warehouse or on a production line, they need information at their fingertips, not behind a login screen.

Formal communication. Some information needs to be packaged formally: reports sent to customers, presented to management, or submitted to regulatory bodies. A well-formatted PDF report conveys professionalism and authority in ways a dashboard screenshot simply cannot.

Complex, detailed layouts. Some manufacturing reports contain dense tables, detailed specifications, and precisely formatted information that spans multiple pages. These are better suited to the document paradigm than dashboard tiles.

The key is: dashboards and reports serve different purposes. They’re complementary, not competing approaches to data visualization.

Implementation: Migrating the Report Portfolio

With Stimulsoft selected, the real work began: migrating existing reports from Report Builder’s RDL format to Stimulsoft’s MRT format.

No magic conversion button. The hard truth is that there’s no automated way to convert RDL files to MRT. Each report required manual recreation. However, this wasn’t entirely bad news; it forced us to examine each report and consider whether it still served its intended purpose. For example, our Material Yield Information report, which was paginated in SSRS, evolved into a Yield Loss Information dashboard in Grafana, better suited to real-time monitoring than static reports.

Leveraging familiar concepts. Stimulsoft’s designer feels familiar to anyone who’s used Report Builder. Concepts like datasets, parameters, groups, and expressions translate cleanly. Our team could open an existing RDL report in Report Builder, have Stimulsoft designer open alongside, and reconstruct the report with reasonable efficiency.

Data source adaptation. Every query needed review. Moving from SQL Server to ClickHouse meant adapting SQL dialects, rethinking some join strategies, and occasionally restructuring queries to leverage ClickHouse’s columnar strengths. In some cases, we discovered opportunities to dramatically improve performance by rewriting queries with ClickHouse’s capabilities in mind.

Template standardization. The migration presented an opportunity to create standardized templates (headers, footers, color schemes, and typography) that could be reused across reports. Consistency in our previous Report Builder environment was not our biggest strength, with each report often having its own visual style and branding approach.

Design Improvement

If you’re going to recreate reports, you might as well make them look better.

Our old reports had accumulated over years, created by different people with varying skill levels and design sensibilities. Let’s just say that some reports looked like they were designed by someone who thought Times New Roman was a perfectly reasonable font choice, while others appeared to have been assembled by developers who believed that if gray text on a gray background was good, then slightly different gray text on a slightly different gray background was even better. And don’t get us started on the creative interpretations of our corporate blue. Some of our reports featured what can only be described as “fifty shades of blue,” ranging from navy to cyan, with each developer using their own personal definition of what “blue” meant.

Some looked professional; others were purely functional. The migration gave us a chance to apply consistent design principles:

Visual hierarchy and white space. Many legacy reports crammed information into every available pixel. We introduced breathing room, clearer section breaks, and better use of typography to guide the reader’s eye.

Consistent branding. Color schemes, logos, and font choices now align with our corporate identity across all reports. This sounds superficial, but it matters when reports are customer-facing or presented to executives.

Data visualization improvements. Where we previously relied on tables alone, we introduced charts and sparklines to make trends more obvious at a glance. Not every report needs to be a wall of numbers.

Better parameter interfaces. The UI for selecting report parameters (date ranges, facilities, product lines) received attention. Clearer labels, better defaults, and logical grouping make reports easier to run for operations staff.

Before and After: A Visual Comparison

The transformation is best seen rather than described. Below is a side-by-side comparison of one of our production reports:

The old version is functional but dense, with inconsistent spacing, color saturation, and weak visual hierarchy. The new version breathes, guides the eye naturally through the information, and presents the same data in more readable and organized layout.

Credit where credit is due: our design team worked wonders throughout this migration. They took reports that had been cobbled together over years by different developers and transformed them into polished, consistent documents. In some cases, the underlying data structure or business logic made a design challenging. Sometimes the team had to put lipstick on a pig, and they did it well. Not every report can be a masterpiece when the data itself is complex and unglamorous, but they managed to make even the most utilitarian reports look readable, functional, and visually attractive.

Dashboard vs. Report: Making the Cut

The migration forced an important strategic question: which of our existing reports should actually remain as reports? We conducted a systematic review of our entire report portfolio, asking:

• Is this information needed in real-time? If yes, it probably belongs in Grafana.

• Does this need to be printed, signed, or archived? If yes, it stays as a report.

• Is this primarily for exploration and investigation? Dashboards excel here.

• Is this a formal, structured document? Reports are the right choice.

• How often is this actually used? Some reports existed simply because they always had.

The result was a rationalization of our information delivery strategy:

To Grafana: Real-time production monitoring, live equipment status, ongoing quality metrics, and anything operators need to watch continuously. These became interactive dashboards where users can drill down, filter, and explore.

To Stimulsoft: Batch documentation, compliance reports, shift summaries, monthly production reports, and anything requiring formal structure or offline access. These remained as traditional reports.

To retirement: Quite a few reports that nobody had run in years. Migration is a great time to kill zombie reports that exist only out of inertia.

This clarity (knowing what belongs where) has made both our dashboards and our reports more focused and effective.

Lessons Learned

Looking back on the migration, a few key insights stand out:

Forced migrations create opportunities. Yes, we had to migrate because of technical necessity. But framing it as an opportunity to improve, not just replicate, made the effort worthwhile.

Don’t underestimate design time. Recreating reports takes longer than you think, especially if you’re improving them along the way. Budget accordingly.

Involve end users early. We previewed redesigned reports with the people who actually use them. Their feedback was invaluable and sometimes surprising.

Containerization pays dividends. Deploying Stimulsoft server in Kubernetes has been smooth. Scaling, updating, and managing the infrastructure is straightforward in ways SSRS never was.

SQL dialect matters. If you’re changing databases as part of your migration, don’t underestimate the query rewriting effort. ClickHouse and SQL Server speak similar but not identical languages.

The best report is the one that gets used. If nobody runs it, it doesn’t matter how well-designed it is. Be ruthless about eliminating unused reports.

Moving Forward

The migration continues, and our manufacturing operations are transitioning to a modern reporting infrastructure: ClickHouse for data storage, Stimulsoft for formatted reports, and Grafana for real-time dashboards. Each tool plays to its strengths. We are currently running both old and new reports in parallel as we methodically work through the portfolio, ensuring each migrated report meets our quality standards before we retire its predecessor.

The transition from Report Builder to Stimulsoft is giving us the opportunity to rethink how we deliver information in a manufacturing context. The reports we’ve completed so far demonstrate the benefits: faster performance, clearer visual design, and an infrastructure that fits our cloud-native architecture. The work continues, but the direction is clear and the results are promising.

For teams facing similar migrations, our advice is simple: embrace the opportunity and don’t just recreate what you had. Build what you need for the future. And be realistic about the timeline; this kind of transformation takes time, but it’s time well spent.

Rework: A short introduction

Can Rework be done indefinitely and without any control?

How MES manages rework limits

In medical industry some products cannot perform rework at all, while others may be reworked but with limits.

Product properties:

Context resolution table configuration:

Here is a demo to show the configurations:

Rework features available in Critical Manufacturing MES

In addition to rework limits, these are the other available related features

Final thoughts

Author

Skills: MES Consultant | System Testing | System Modeling | User Training | Content Creating

The manufacturing industry is undergoing a digital transformation, with Manufacturing Execution Systems (MES) becoming the backbone of modern smart factories. However, as we advance toward Industry 4.0, a new threat looms on the horizon: quantum computing. The cryptographic algorithms that currently protect our most sensitive manufacturing data may soon become obsolete. This isn’t a distant concern - it’s a present reality that requires immediate attention.

Why MES Systems Are Critical Targets

Manufacturing Execution Systems sit at the heart of every modern production facility, making them treasure troves of invaluable industrial property and operational intelligence. The data contained within these systems represents the crown jewels of manufacturing organizations.

MES systems document and store comprehensive production processes that reflect decades of research, development, and optimization. These systems contain detailed product recipes that define the exact specifications, ingredients, formulations, and processing parameters required to manufacture products. For pharmaceutical companies, these might include drug formulations; for semiconductor manufacturers, they contain precise etching and deposition processes; for food and beverage companies, they hold proprietary recipes and processing conditions.

The intellectual property stored in MES systems extends beyond simple recipes. These systems maintain complete process workflows that detail every step of production, from raw material handling to final packaging. This includes optimal processing temperatures, timing sequences, equipment settings, and quality control checkpoints that have been refined over years of production experience.

Real-Time Operational Data

Beyond static information, MES systems continuously collect and store real-time operational data that provides unprecedented visibility into manufacturing operations. This includes:

• Equipment performance data: Machine utilization rates, cycle times, throughput measurements, and overall equipment effectiveness (OEE) metrics
• Quality measurements: In-process quality checks, statistical process control data, defect rates, and product specifications
• Material traceability: Complete genealogy of materials and components, including supplier information, batch numbers, and processing history
• Resource allocation: Labor assignments, skill requirements, and productivity metrics

Production Intelligence and Optimization Data

Modern MES systems leverage advanced analytics and machine learning to optimize production processes. They store predictive maintenance algorithms, demand forecasting models, and process optimization parameters that give manufacturers competitive advantages. This operational intelligence enables manufacturers to reduce waste, improve yield rates, minimize downtime, and respond quickly to market demands.

These systems also maintains detailed audit trails and compliance data essential for regulated industries. For medical device manufacturers, aerospace companies, and pharmaceutical producers, this includes validation records, batch records, and documentation required for regulatory submissions.

Network and System Integration Data

As the central hub connecting shop floor equipment with enterprise systems, MES platforms contain integration configurations and network topologies. This includes access to external system credentials, communication protocols, system interfaces, network architectures, and security configurations that could be exploited if compromised.

The value of this collective data cannot be overstated. A compromised MES system could expose proprietary manufacturing processes to competitors, disrupt production operations, compromise product quality, and violate regulatory compliance requirements. This makes MES systems prime targets for industrial espionage and cyber attacks.

The Quantum Computing Threat Timeline

Quantum computing represents a fundamental shift in computational capability that threatens the cryptographic foundations of our digital infrastructure. Unlike classical computers that process information in binary bits, quantum computers leverage quantum mechanical properties like superposition and entanglement to achieve exponential speedups for specific types of problems.

Current State and Projections

The quantum threat to encryption is not a theoretical concern - it’s an approaching reality with increasingly precise timelines. Recent research and expert assessments paint a concerning picture:

• Conservative Estimates: The Chinese Academy of Sciences projects that quantum computers capable of breaking RSA-2048 encryption may emerge between 2045-2050. The MITRE analysis suggests RSA-2048 could remain secure until 2055-2060 under current technological constraints.

• Moderate Projections: Most cybersecurity experts predict quantum computers will break RSA-2048 within 15 years, with some estimates pointing to 2030 as a critical milestone. Gartner predicts RSA and ECC will become unsafe by 2029 and potentially broken by 2034.

• Aggressive Timelines: Some researchers warn of breakthrough capabilities emerging as early as 2028. A recent global survey found that 61% of security professionals believe quantum attacks will neutralize current encryption within 2-5 years.

The uncertainty in these timelines reflects the complexity of quantum computing development, but the overall trend is clear: the quantum threat is accelerating.

Algorithmic Breakthroughs

Recent developments have dramatically reduced the quantum computing resources required to break encryption. A 2025 study from Google Quantum AI researcher Craig Gidney suggests that breaking RSA-2048 encryption could be achieved in less than a week using fewer than one million noisy qubits - an order-of-magnitude reduction from previous estimates of 20 million qubits.

This reduction comes from algorithmic improvements and more efficient system designs, including approximate arithmetic and compressed error-correction layouts. Such breakthroughs demonstrate that progress in quantum computing can come not just from hardware advances, but also from software and algorithmic innovations.

The “Harvest Now, Decrypt Later” Attack

One of the most insidious aspects of the quantum threat is the “harvest now, decrypt later” attack strategy. Adversaries are currently collecting encrypted data with the intention of storing it until quantum computers become available to decrypt it.

Current Data Collection

Cybercriminals and nation-state actors are actively harvesting encrypted communications, stored databases, and backup systems containing sensitive manufacturing data. This includes:

• Encrypted MES database backups
• Secure communications between manufacturing sites
• Proprietary technical documentation
• Financial and competitive intelligence
• Customer and supplier information

Future Decryption Capabilities

Once cryptographically relevant quantum computers (CRQCs) become available, this stored data will become vulnerable to retrospective decryption. For manufacturing companies, this means that trade secrets, product formulations, and competitive intelligence collected today could be exposed in the future.

The timeline for this threat is particularly concerning for data with long-term value. Manufacturing processes, product recipes, and technological innovations often remain valuable for decades. A pharmaceutical company’s drug formulation collected today could still be commercially sensitive 20-30 years from now, well within the projected timeline for quantum computing threats.

This “store now, decrypt later” strategy creates an immediate urgency for implementing post-quantum cryptography, even before quantum computers become practically available. Organizations cannot wait until quantum computers are deployed to begin protecting their data - they must act now to prevent future exposure.

Interactive Quantum Timeline Simulation

To better understand when current encryption methods might become vulnerable, several organizations have developed online simulators and calculators that visualize the quantum threat timeline.

• IBM Quantum Experience provides access to both quantum simulators and real quantum processors, allowing users to experiment with quantum algorithms and understand their implications for cryptography. The platform includes educational resources about Shor’s algorithm and its impact on RSA encryption.

• Quantum Computing Timeline Calculators are available from various cybersecurity organizations that allow users to input different scenarios (qubit counts, error rates, algorithmic improvements) to estimate when specific encryption methods might become vulnerable.

• NIST Post-Quantum Cryptography Resources provide detailed timelines and migration guidance for transitioning to quantum-resistant algorithms. These resources include risk assessment tools and implementation roadmaps.

While there is no single definitive simulation website, these resources collectively offer interactive ways to explore the quantum timeline and understand the urgency of transitioning to post-quantum cryptography. Organizations should regularly consult these resources to stay updated on quantum computing progress and adjust their security strategies accordingly.

Critical Manufacturing’s Quantum-Safe Leadership

As the quantum threat becomes more tangible, manufacturing software providers must take proactive steps to protect their customers’ valuable data. That’s why Critical Manufacturing is at the forefront of this effort in the upcoming 11.2 release.

Version 11.2 is the first release to support Post-Quantum Cryptography, allowing customers to use X25519MLKEM768, a hybrid key exchange algorithm used in TLS 1.3 that combines the established X25519 elliptic curve with the NIST-standardized ML-KEM-768 post-quantum algorithm.

Support for TLS 1.3 with X25519MLKEM768 highlights Critical Manufacturing’s commitment to spearhead manufacturing excellence and MES innovation. Critical Manufacturing’s continuous dedication to security and secure architecture patterns, allows Critical Manufacturing MES to be one of the first MES solutions to provide Post-Quantum safe communication options.

The Imperative for Action

The convergence of quantum computing advancement and the critical nature of MES data creates an urgent imperative for the manufacturing industry. Organizations cannot afford to wait until quantum computers become mainstream to begin their post-quantum transition.

Immediate Steps

Assessment and Inventory: Manufacturers must immediately assess their current cryptographic implementations, identify vulnerable systems, and prioritize critical assets for protection.

Vendor Engagement: Work with MES providers, equipment manufacturers, and system integrators to understand their post-quantum roadmaps and timelines.

Pilot Projects: Begin testing post-quantum cryptographic implementations in non-production environments to understand performance implications and integration challenges.

Staff Training: Educate IT and OT teams about quantum threats and post-quantum cryptography to build internal expertise.

Long-term Strategy

The transition to post-quantum cryptography will be complex and lengthy, requiring careful planning and execution. Organizations should develop comprehensive strategies that address not just MES systems but entire manufacturing technology stacks including PLCs, SCADA systems, and enterprise applications. When well designed, a hybrid deployment approach with the right MES can significantly mitigate the risks of maintaining some legacy systems running on the shop-floor.

The quantum threat to manufacturing is real, imminent, and potentially devastating. However, with proper preparation and proactive adoption of post-quantum cryptographic solutions like those offered in Critical Manufacturing MES 11.2, the industry can maintain the security and integrity of its most valuable digital assets.

The question is not whether quantum computers will break current encryption - it’s whether your organization will be ready when they do.

This blog post is based on current research and industry developments as of September 2025. Quantum computing and post-quantum cryptography are rapidly evolving fields, and organizations should regularly update their threat assessments and security strategies.

Author

Hi! My name is José Pedro Silva. ✌️

I’m the R&D Director at Critical Manufacturing. Passionate about cybersecurity and everything Software Engineering.

You can find me on LinkedIn.