A guide to industrial automation, data infrastructure, and AI implementation for manufacturing excellence

Your competitors are delivering faster. Your margins are tightening. Aging equipment is causing increasing downtime. The transition to the smart factory is no longer a futuristic vision—it is a matter of survival.

However, the most common mistake is attempting to implement artificial intelligence (AI) without first mastering automated data acquisition. This guide covers the following elements:

In collaboration with Baseline / Centris Technologies

• The strategic value of structured data collection
• Understanding the ISA‑95 hierarchy: where does your data infrastructure stand?
• AI in action: concrete, value‑creating use cases
• Use Case 1: Intelligent planning in a merger context
• Use Case 2: Predictive maintenance on a bottling line
• Use Case 3: Performance optimization on a food processing line
• Taking action: start building the foundations of your smart factory today

1. The Strategic Value of Structured Data Collection

Manufacturing data acquisition is not simply about reading sensors. It is the process of transforming machine electrical signals into business intelligence. A robust infrastructure enables you to:

• Measure true OEE (Overall Equipment Effectiveness): No more paper‑based estimates—gain an accurate view of availability, performance, and quality.
• Identify hidden losses: Micro‑stoppages of 30 seconds, often ignored, are frequently the most costly by year‑end.
• Detect bottlenecks: Precisely identify which machine is limiting your plant’s overall throughput.
• Prepare, standardize, and transform data for AI: AI models require structured, time‑stamped historical data to predict failures or optimize scheduling.

2. Understanding the ISA‑95 Hierarchy: The Master Blueprint

To build a smart factory, we rely on the international ISA‑95 standard. It structures industrial information systems into layers to ensure that shop‑floor equipment communicates effectively with business management systems.

Learn how Centris Technologies approaches industrial automation.

The Five Levels of Integration (ISA‑95)

• Level 0: Physical process
  Your machines, motors, conveyors, and robots.
• Level 1: Sensors and actuators
  Devices (e.g., PLCs/controllers) that measure temperature, pressure, or speed and act on equipment.
• Level 2: Control and supervision (SCADA)
  Systems that collect data from PLCs and allow operators to monitor production in real time.
• Level 3: Manufacturing Execution Systems (MES)
  The software layer that manages work orders, product genealogy, and quality management.
• Level 4: Enterprise Resource Planning (ERP)
  Company‑wide management and control (accounting, purchasing, sales).

The ISA‑95 model structures the flow of information between the shop floor and business systems, transforming raw data into AI‑ready information. AI in manufacturing does not depend on the volume of data collected, but on its consistency, contextualization, and traceability across enterprise layers.

At Levels 0 to 2, sensors, controllers, and SCADA systems capture and structure physical reality. Data is normalized, time‑stamped, and historized, but remains primarily technical and equipment‑centric. At this stage, its value for AI is limited because business context is missing.

Level 3, enabled by the MES, is critical. It connects production data to manufacturing orders, batches, recipes, products, operators, and quality events. This contextualization transforms technical signals into structured, comparable, and historized industrial information, directly usable by AI models for predictive maintenance, quality defect prediction, or process optimization.

Finally, Level 4, through the ERP, completes the chain by adding the economic and strategic dimension. Industrial performance can then be correlated with costs, inventory, and customer commitments, enabling AI to support decision‑making at the enterprise level.

Once structured and contextualized within the ISA‑95 framework, data becomes fertile ground for advanced applications, particularly concrete AI use cases in manufacturing.

 

3. AI in Action: Real‑World Examples

Data alone does not create value. What matters is how it is used.

Once your data is accessible, AI can detect patterns, anticipate failures, and optimize parameters in real time to address real‑world challenges. Baseline’s AI expertise, combined with a robust data infrastructure, delivers transformative results. Here are three examples with measurable outcomes.

Use Case 1: Intelligent Planning (Company Merger)

Challenge:
A chemical manufacturer acquired a competing plant. Both sites used disparate Excel‑based planning methods, resulting in delivery delays.

Solution:
AI was used to analyze the real production capacities of both plants and generate an optimized production schedule.

Result:
A 12% increase in production throughput without adding new equipment.

Use Case 2: Predictive Maintenance (Bottling)

Challenge:
A high‑speed bottling line experienced costly motor failures.

Solution:
Installation of vibration and current sensors (Level 1), analyzed by AI‑driven predictive maintenance models.

Result:
Failures were detected before complete shutdowns, allowing repairs to be planned during scheduled maintenance downtime.

Use Case 3: Performance Optimization (Food Processing)

Challenge:
Product weight variability caused raw material waste.

Solution:
Real‑time dynamic adjustment of machine parameters using an AI algorithm based on acquisition data.

Result:
A 15% reduction in raw material waste.

4. Taking Action

Don’t let your data sit idle in your controllers. The journey toward Industry 4.0 begins with a solid foundation.

• Assess your current connectivity (Levels 1 and 2).
• Centralize your data within a structured system.
• Analyze to identify quick wins.
• Optimize with AI to achieve operational excellence.

About the Authors

This article is a collaboration between Centris Technologies, a Québec‑based industrial automation system integrator specializing in SCADA and MES, and Baseline, an artificial intelligence company focused on developing customized AI solutions across multiple industries.

With our expertise in industrial software development, manufacturing equipment connectivity, and industrial data visualization, our team is ready to help you build your path toward the connected factory.

© 2026 Centris Technologies and Baseline | All rights reserved.