Introduction: The Rise of Smart Factories

Manufacturing is undergoing a massive transformation. It’s the age of the smart factory. These cylinder boxes of concrete slabs and industry have gone digital, completely reshaping how goods are made and shipped. The industrial AI reckoning is here. Integrated, data-driven factories are using artificial intelligence, IoT (Internet of Things), automation, and extensive oversight into their entire supply chain view.

Arguably, no single company has made the transition 100%—but plenty have made the leap. It’s a prudent pivot embraced by companies with global supply networks. In an era of persistent market volatility, companies need AI-powered insights to remain competitive and viable on the cusp of this new frontier.

Industries worldwide are investing heavily. The U.S. is going all in, with the Department of Energy announcing nearly $13 million in incentives to accelerate the adoption of smart manufacturing.

Deloitte attributes the heightened interest to rising customer expectations and more fractured, chaotic supply chains that require real-time responsiveness.

In its 2025 Smart Manufacturing Survey, Deloitte researchers found that 83% of manufacturers believe smart factory initiatives are critical to their competitiveness over the next five years.

At Epicor, we’ve seen this compressed evolution firsthand. Companies using Epicor solutions are applying Industry 4.0 principles to streamline operations and cut costs as they transition into the age of AI.

Connected, AI-powered smart factories have progressed beyond proof-of-concept futurist babble and are delivering exceptional business results.

What is a Smart Factory?

A smart factory, or smart manufacturing plant, is a large industrial complex where goods are processed or manufactured using machinery, assembly lines, and connected digital technologies.

The added layer of digital connectivity is what separates a smart factory from an ordinary, old-school manufacturing plant. While a traditional plant relies on manual processes, human oversight, and human review, a smart factory is a highly adaptive, self-optimized environment. A combination of sensors, software, and internet devices collects and processes data in real time for precise inputs, automation, and more responsive decision-making.

It comes down to interoperability: smart factories have it and non-digitalized factories don’t. This interoperability brings speed, efficiency, and accuracy to factory floors that were unimaginable even a decade ago. Systems, sensors, equipment, and software can seamlessly share information across the entire production lifecycle. Manufacturing outputs are automatically, continuously refined in real time, reflecting changes in consumer demand, equipment maintenance needs, and supply chain intelligence (National Institute of Standards and Technology).

Key features of smart factory interoperability often include:

  • Connected Devices Sensors and wireless devices that track machine performance, quality metrics, and production output in real time. All data streams connect to one platform, often an ERP with shared visual dashboards, for a single source of truth.
  • Advanced Analytics and AI: Tools that process large volumes of data to predict issues, optimize production schedules, and enhance quality control.
  • Automation and Robotics: Machines and systems that handle repetitive or high-precision tasks for improved speed and precision.

The Core Technologies Powering Smart Factories

Smart factories rely on a stack of advanced technologies that work together. These interconnected tools create a virtually endless loop of data (and data feedback), from product design to delivery.

Industrial Internet of Things (IIoT)

An IIoT network connects sensors, machines, and devices across the factory floor. These devices gather data on everything from temperature and vibration to equipment usage—insights that let teams identify performance issues before they cause unplanned downtime (McKinsey: Transforming advanced manufacturing through industry 4.0).

Artificial Intelligence (AI) and Machine Learning (ML)

AI models analyze historical and real-time performance data to optimize maintenance scheduling. AI makes predictive recommendations on when machinery will need servicing and then automatically schedules the most optimal time to do so.

According to McKinsey, this proactive, data-driven approach reduces machine downtime by up to 50% and increases machine life by up to 40%.

And it’s not just shopfloor equipment. AI delivers the same inventory sights for inventory optimization, worker scheduling, workfloor layout, and other process improvements.

Robotics and Automation

Automated guided vehicles (AGVs), robotic arms, and autonomous mobile robots (AMRs) can handle repetitive, labor-intensive, or dangerous tasks to increase speed and accuracy while protecting workers from injury or tedium.

Cloud-Based ERP Systems

Cloud-based ERP platforms like Epicor Kinetic connect operational data from across the business. This integration ensures everyone—from line operators to executives—has access to accurate, real-time insights.

Digital Twins

These virtual replicas of physical assets allow manufacturers to test new processes, products, or scenarios—but in controlled virtual environments. With limited resources, digital twins can reveal to companies the end results of what-if simulations—with astonishing accuracy and zero real-world exposure (McKinsey: What is digital-twin technology).

Business Benefits of Smart Manufacturing

While transitioning to smart manufacturing comes with upfront investment, companies are finding that the returns in productivity and ROI justify the investment.

Increased Efficiency

Beyond extending equipment life and shopfloor uptime, companies using smart assets see a roughly 10% improvement in OEE (Overall Equipment Effectiveness) and yield, along with remarkable productivity and revenue gains. (LNS Research).

Streamlining workflows, these connected machines perform better and faster, producing higher-quality goods in shorter timeframes with fewer defects or reworks needed.

Cost Reduction

Predictive maintenance reduces unplanned downtime by identifying and correcting potential roadblocks early, while AI-powered inventory management minimizes excess stock and carrying costs.  

Epicor customers like Detectortesters have cut operational costs by 50% by digitizing their warehouse processes with Epicor Mobile Warehouse.

Quality Improvements

Connected systems continuously monitor production variables and detect defects much sooner. Early AI intervention reduces scrap and rework, helping ensure that products meet quality standards. Over time, these systems build historical data pools to refine quality control even further.

Enhanced Agility

Smart factories are more responsive to disruptions. Armed with real-time data, operators can quickly adjust schedules or modify production runs. Resource reallocation that used to take days or weeks now takes minutes.

Sustainability Gains

Data-driven optimization is a win for the environment. Leaner operations reduce energy consumption and material waste, helping manufacturers comply with environmental regulations and meet sustainability targets.

Even companies not focused on green operations are investing to reap the upside: better public image, reduced waste, and cost savings.

All of these benefits compound over time. Once a factory achieves baseline efficiency gains, the improvement loop drives continuous optimization and innovation.

The Role of ERP in Smart Factory Success

Although individual technologies such as industrial Internet of Things (IIoT) sensors or AI tools  deliver gains on their own, an enterprise resource planning (ERP) system maximizes those wins and brings everything together in one connected hub.

ERPs consolidate data from the shop floor, supply chain, finance, and customer management into a single view.

For example, Epicor Kinetic integrates directly with manufacturing execution systems, inventory control, quality management, and customer order platforms. This enables:

  • Real-Time Decision-Making: Operators and managers see the same live data, allowing them to respond to issues immediately rather than waiting for end-of-shift reports.
  • Improved Supply Chain Visibility: ERP systems monitor raw material availability, supplier performance, and delivery timelines, helping to prevent stockouts and production delays.
  • Automation of Repetitive Tasks: Workflows such as order entry, purchasing, and scheduling can be automated, reducing administrative overhead and the potential for human error.
  • Regulatory Compliance: Centralized documentation and traceability features simplify adherence to industry standards and audit requirements.

Case Study: Detectortesters’ Digital Transformation with Epicor

Detectortesters, a UK-based leader in fire detector testing equipment, was struggling with slow, manual warehouse processes. Relying on paper and spreadsheets, mistakes slowed down production lines and increased errors.

Already an Epicor Kinetic customer, Decortester needed new ways to modernize operations without disrupting production.

Detectortesters added Epicor Mobile Warehouse to its existing tech stack. Instead of paper and clipboards, workers now use handheld devices to scan materials and deliveries directly into their ERP system.

The results are striking:

  • Planning Time Cut by 80%: Production run planning dropped from five days to just one.
  • Picking Time Reduced by 57%: Component picking time went from seven hours to three.
  • Operational Costs Reduced by 50%: Leaner processes and fewer errors led to major cost savings.
  • Lead Times Improved by 50%: Faster operations meant customers received products sooner.

The company delivered a solid ROI in under two years and also improved its JIT (Just In Time) and MRP (Materials Requirement Planning) processes.

Keith Herring, Head of IT at Detectortesters, described Epicor Mobile Warehouse as “one of the easiest software applications Detectortesters has ever implemented.”

Using Epicor Mobile Warehouse has also improved customer service. Herring says, “Having Epicor Mobile Warehouse in place ahead of our eCommerce website brings the ability to expand our reach and deliver a best-in-class service to our customers.”

With ERP as its foundation and smart technologies layered on, Detectortesters is well-positioned for resilience, agility, and growth. In the near future, the company plans to roll out IoT-enabled products and an eCommerce platform for direct customer sales.

Read the full Decortesters success story.

Overcoming Common Implementation Challenges

Despite the well-documented benefits, some manufacturers face an uphill battle. Common challenges include:

  • Data Silos: Legacy systems and departmental divides can make it difficult to consolidate data into a single enterprise resource planning (ERP) platform.
  • Change Resistance: Employees accustomed to manual processes may resist new technology.
  • Integration Complexity: Merging ERP with the Industrial Internet of Things (IIoT), Manufacturing Execution System (MES), and AI tools can be complex if the systems aren’t designed for interoperability.
  • Upfront Costs: Although ROI can be significant, the initial investment in hardware, software, and training can be a barrier.

Epicor addresses these challenges by offering modular, out-of-the-box solutions like Epicor Mobile Warehouse that integrate seamlessly with Epicor Kinetic. This approach minimizes customization requirements and reduces deployment time.

Worker enthusiasm and adoption are critical. A successful smart factory rollout cannot succeed unless employees have bought in. Phased deployment, robust training, and regular feedback loops can help employees feel confident and capable with new tools.

Start where your employees can see early wins. Detectortesters began their implementation by automating their workers’ least favorite manual tasks, such as shopfloor picking. Replacing the old method with the more precise, automated system was a big win for everyone; from there, the staff quickly embraced the new platform.

Future Trends in Smart Manufacturing

The next wave of smart factory innovation will continue to build off centralized enterprise resource planning (ERP) systems. Key trends to watch include:

  • Increased Use of AI and Machine Learning (ML): Predictive analytics will become more precise, enabling proactive maintenance, quality control, and demand forecasting.
  • More IoT-Enabled Products: Manufacturers like Detectortesters are already exploring IoT (Internet of Things) integration to gather usage data for product improvements, predictive servicing, and consumable replenishment.
  • Sustainability Tracking: ERP systems will increasingly monitor energy consumption, waste reduction, and carbon emissions.
  • Hyper-Personalization: Advances in manufacturing flexibility will allow for mass customization at scale, with ERPs dynamically adjusting production to meet individualized customer specifications.

As these trends mature, ERP systems already integrated with the Industrial Internet of Things (IIoT), manufacturing execution systems (MES), and AI tools will be best positioned to capitalize on them.

Conclusion: Building a Resilient, Future-Ready Factory

Smart factories are, arguably, the new operational standard for manufacturers. By combining ERP with AI technologies, manufacturers can confidently and swiftly respond to challenges. Disruption is a constant, but smart factories offer the tools and oversight companies need for immediate course correction. They can react in minutes—not days or weeks—and with greater confidence and team alignment.

An Epicor ecosystem, from Epicor Kinetic to Epicor Mobile Warehouse, provides the crucial tools manufacturers need for a sustainable transformation. Our customers have already proven this, achieving double-digit efficiency gains, cutting lead times in half, and unlocking new revenue channels like direct eCommerce.

Thriving manufacturers will be those that view smart factory adoption as a continuous optimization journey—one where each improvement builds on the last, driving compounding gains for an enduring competitive advantage.

→ Epicor is your partner for smarter, more agile operations. Connect with us today to see how the solutions that helped Detectortesters save over 50% in operational costs can unlock similar results. Book a quick chat. Let’s connect.

Andrew Robling
Epicor Principal Product Marketing Manager

Andrew Robling is a Principal Product Marketing Manager at Epicor, where he leads the development of innovative solutions for the manufacturing industry. Andrew was educated at Princeton University and is based in Georgetown, Ontario.

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