How Manufacturers are Accelerating Production Cycles with Low-Code and AI

Manufacturers are speeding up production cycles by combining low-code platforms and AI tools. Here's how:

• Faster Development: Low-code platforms enable app creation 75% faster, often within 3 weeks to 3 months.

• AI Benefits: AI improves efficiency with predictive maintenance, real-time quality control, and smarter resource planning.

• Cost Savings: Companies report up to 30% reductions in maintenance costs and 25% fewer defects.

• Real-World Results: Examples include Siemens saving six figures annually and Marshalls optimizing 4,000 daily inventory decisions.

This guide covers how these technologies work together, their impact on manufacturing, and practical steps for implementation.

Low-Code Basics for Manufacturing

Low-Code Platform Basics

Low-code platforms are changing how manufacturing software is developed by speeding up app creation without requiring advanced coding skills. Unlike traditional methods that rely heavily on coding expertise, these platforms use visual tools like drag-and-drop interfaces. This makes app development more accessible to domain experts and even front-line workers.

These platforms connect operational technology (OT) with information technology (IT), creating a unified system for digitizing and automating manufacturing processes. With Gartner predicting a 23% growth in the low-code market in 2023, manufacturers are increasingly turning to these tools to remain competitive. This shift is driving efficiency and productivity gains across the industry.

Benefits for Manufacturers

DAB Pumps revamped its Opcenter user interface using low-code in less than a month, improving both user engagement and functionality.

Here’s how manufacturers benefit from low-code platforms:

Key Manufacturing Features

Modern low-code platforms come equipped with features tailored for manufacturing. For instance, Siemens Opcenter Execution integrates low-code tools through Mendix, offering industry-specific templates for both high- and low-variance manufacturing processes.

Some standout features include:

• Digital Workflow Creation: Replace paper-based processes with digital workflows for smoother data collection.

• Operator Interface Optimization: Simplify operator screens to display only essential, auto-updating production data.

• Material Management Integration: Tools like the Material Kanban app automate and track material requests in real-time.

"Now, with Mendix, there are no more boundaries or constraints in terms of what kind of personalization customers can put in place." – Ben Bozano, Product Manager for Opcenter Execution

These platforms also support different display formats, from large screens to mobile devices, ensuring critical production details are always accessible.

How Low-Code and AI Are Transforming Manufacturing ...

AI Tools in Manufacturing

AI technology is making manufacturing more efficient, building on the flexibility offered by low-code platforms.

Main AI Uses in Manufacturing

AI improves manufacturing by using advanced algorithms and data analysis. These tools help increase production efficiency and reduce costs. For instance, one automotive manufacturer reported a 15% boost in production efficiency and a 10% drop in downtime after integrating AI into their assembly processes.

Merging Low-Code with AI

Manufacturers are now pairing low-code platforms with AI to quickly develop and deploy AI-powered applications with minimal coding.

"We believe AI tools and low-code development are a natural fit to build better software faster. Enterprises using low-code will be able to extract more value from AI in an efficient way using the new features of the Mendix 10 platform." - Hans de Visser, Mendix's chief product officer

This combination is particularly effective for tasks such as:

• Automated Decision Making: AI analyzes production data to make real-time adjustments.

• Visual Quality Inspection: Machine learning models identify defects using camera feeds.

• Predictive Maintenance: AI predicts equipment failures before they occur.

• Resource Optimization: Smarter allocation of materials and workforce.

These integrations are delivering tangible improvements in production processes.

AI Examples in Production

Several companies are already seeing results from AI in manufacturing:

Marshalls (UK) revamped their inventory management with AI, enabling 4,000 daily decisions on order and product allocation. This system optimizes production levels and stock requirements across multiple locations, significantly improving their ability to meet customer demand.

Looking ahead, Gartner predicts that by 2026, 80% of low-code platform users will come from outside traditional IT departments. This shift is making AI tools more accessible, allowing manufacturers to quickly prototype and implement AI-driven solutions across their operations.

Manufacturing Success Stories

Supply Chain Improvements

Manufacturers are seeing impressive gains by using low-code platforms and AI in their supply chains. Take Siemens Motion Control, for example. They developed the Material Supply Manager, a low-code application that uses real-time IoT sensors and visual planning to manage material flow across the factory. The result? Six-figure annual savings.

Another standout is DAB Pumps. By creating a custom operator front-end, they boosted engagement and efficiency in just one month. This showcases how low-code tools can deliver fast, impactful results.

Low-code and AI are also making waves in quality control processes.

Better Quality Checks

AESSEAL revamped its quality control by blending low-code with AI tools. Their solution integrates production orders from SAP, manages job sequencing, and notifies operators about maintenance needs.

"Once a job starts, operators identify the machine and send the CAM program directly from Live Lists."

This approach allowed AESSEAL to develop applications three to four times faster than traditional methods.

Equipment Maintenance Results

Siemens Financial Services took a leap forward with their Lending App, built on a low-code platform. Here's how it works:

Siemens Mobility also showcased the potential of low-code by modernizing its EOS (Experience with Standards Online Service) database. The project, completed in just six months and 15 sprints, now supports over 6,200 active users with essential maintenance and regulatory information.

"The beauty of my job is whenever I see a new product being launched or a new environment being created or a process being digitized – instances that make work faster, less costly, and less complex – seeing this delivered by a great team, which is working jointly between business and IT, these are the greatest moments of being a CIO." - Hanna Hennig, CIO of Siemens

These examples show how fast, integrated solutions can enhance efficiency and streamline production.

Implementation Steps and Tips

Getting Started Guide

To begin integrating low-code and AI into your organization, start by assessing your current setup. Take stock of your technology infrastructure and evaluate your team's capabilities.

Identify a process where improvements can be achieved quickly. For instance, 81% of manufacturing organizations manage to implement AI use cases into production within six months.

Once your pilot is running, focus on overcoming common obstacles to ensure a smooth rollout.

Solving Common Problems

Two major hurdles for manufacturing organizations are data quality and skills gaps.

AI models require reliable, well-structured data. Establishing strong data governance practices ensures your data is accessible, properly formatted, and secure.

By 2026, Gartner predicts 80% of low-code users will come from outside traditional IT departments. To prepare, invest in targeted training programs. For example, one multinational manufacturer introduced an in-house rapid application development platform, enabling 90% of new apps to be built within three weeks to three months.

After addressing these challenges, focus on measuring the results to confirm your progress.

Measuring Success

Once your pilot is complete and issues are resolved, track key metrics to evaluate success:

• 60% of manufacturing executives report positive ROI from AI investments

• 86% see revenue growth of 6% or more

• 80% report improved productivity among technical teams

"We have always believed that low-code had the potential to be much more than a tool to automate manual processes. This survey shows that the market agrees. Used wisely, low-code is about rethinking entire business processes from the ground up. Low-code also opens new avenues for fusion [IT/OT] teams to think bigger when it comes to using tech to transform their organization for the future, as long as they are prioritizing upskilling users to maximize the potential of low-code for their unique use cases."
– Ray Kok, CEO at Mendix

Keep an eye on metrics like development speed, automation rates, and overall efficiency. Aim for the industry standard of three weeks to three months for most projects.

Conclusion

Key Takeaways

The combination of low-code platforms and AI is driving measurable advancements in manufacturing. According to recent surveys, 99% of manufacturing organizations now use low-code in their development processes, with 75% identifying it as essential for scaling innovation.

Some of the most notable operational improvements include:

• 80% boost in technical team productivity

• 76% more efficient development processes

• 43% reduction in operational costs

These technologies are primarily applied to areas like digital transformation (52%), updating legacy processes (48%), and cutting costs (43%). Additionally, 86% of organizations reported revenue increases of 6% or more after integrating AI into production environments.

The Future of Manufacturing

The manufacturing industry is poised for further growth and transformation. A significant 77% of respondents believe that executives see low-code as the future's dominant coding approach.

Emerging trends to watch include:

• Expanding access to machine learning through low-code platforms

• Combining composable operations with low-code development

• Reducing waste to improve sustainability

With 81% of manufacturers deploying AI use cases within six months, the speed of adoption highlights how these technologies are reshaping modern production environments. As these trends continue, the integration of AI and low-code will only deepen, paving the way for even greater advancements in the industry.

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• Mendix and Siemens: Scaling Manufacturing with Low-Code

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• AI-Driven Low-Code Platforms: The Future of Financial Services