The opinions and views within this video, are from a well known industry expert Walker Reynolds

Why Manufacturers Build vs Buy MES: Technical Reasons & How Fuuz AI Solves the Challenge

Introduction

Manufacturing Execution Systems (MES) represent the most critical piece of software in any manufacturing operation. While manufacturers often start by seeking off-the-shelf solutions from vendors like Rockwell, Wonderware, Siemens, or PTC, they quickly discover that cookie-cutter software doesn't fit their unique business requirements. This article explores the technical reasons why manufacturers ultimately choose to build their MES systems and how Fuuz AI Industrial Intelligence Platform provides the optimal solution.

Source Video: Why Companies Choose to Build Manufacturing Execution Systems

Understanding MES in the Manufacturing Workflow

The Manufacturing Software Stack

Manufacturing execution sits at the heart of the industrial software ecosystem:

• CRM: Where products are sold
• ERP: Where manufacturing is planned (master data model)
• MES: Where manufacturing actually happens
• SCADA/PLC/HMI: Plant floor control systems
• WMS: Warehouse management
• Shipping systems

Why MES is the Largest Component

Manufacturing execution systems are typically the largest software component in most organizations. Even when execution is paper-based (travelers, work orders, barcodes), the execution layer represents the bulk of operational activity. ERP may be huge, but it's the tip of a pyramid, with multiple MES instances across different sites forming the foundation.

The Core Four MES Capabilities

Every manufacturing execution system requires these fundamental capabilities:

1. Work Order Management
2. Scheduling
3. Overall Equipment Effectiveness (OEE)
4. Downtime Tracking

Additional Capabilities Based on Business Needs

• Recipe and formulation management
• Quality management
• Batch tracking
• Statistical process control
• Bill of materials (BOM) kitting
• Lot traceability

The Technical Challenges with Off-the-Shelf MES

Problem 1: Data Standardization Issues

The fundamental challenge lies not in defining what a cell, line, or area is, but in standardizing how data flows from diverse equipment:

Equipment Variation Examples:

• Cell A: Uses state registers (31 = stopped for reason X, 44 = stopped for reason Y)
• Cell B: Generates alarm lists (500 possible alarms, 31 currently active)
• Cell C: Simple binary status (1 = running, 0 = stopped)

Off-the-shelf solutions require machines to fit the software's data model, not the other way around.

Problem 2: Rigid Edge Device Limitations

Many vendors provide edge devices to normalize data, but these create new problems:

• What happens when machinery is moved or updated?
• How do you handle new equipment installations?
• Edge devices often break when production layouts change

Problem 3: Limited Capability Lists

Off-the-shelf MES solutions come with predetermined capability lists. If your manufacturing process requires capabilities not included in the package, you're simply out of luck.

How Fuuz AI Solves the Build vs. Buy Dilemma

The Fuuz AI Advantage: Industrial IoT Platform Architecture

Fuuz AI Industrial Intelligence Platform eliminates the traditional build vs. buy dilemma by providing:

Flexible Connectivity Layer

• Connects to any industrial hardware and software
• Universal connectors for diverse equipment types
• No rigid edge device requirements

Adaptive Data Operations

• Converts individual equipment events into standardized information
• Flexible information modeling that adapts to your equipment
• Real-time data processing and normalization

Customizable Visualization Engine

• Build dashboards tailored to your specific needs
• Support for operator, supervisor, and analyst views
• Extensible interface components

Core Visualization Requirements Met by Fuuz AI

Operator Level Dashboard

• Real-time work order visibility
• OEE metrics (availability, performance, quality)
• Individual cell performance within production lines
• Downtime tracking and reporting

Supervisor Level Analytics

• Multi-line production oversight
• Schedule visibility across areas
• Top 10 downtime analysis by production line and cell
• Shift performance comparison (actual vs. target production)
• Pareto charts for downtime reasons
• Defect tracking by individual cells

Advanced Analytics Capabilities

• Predictive analytics using linear regression
• Real-time production trending
• Future performance predictions mid-shift/month/quarter
• Statistical process analysis

The Fuuz AI Unified Analytics Framework

Data Abstraction Layer

Fuuz AI processes raw asset data through a structured approach:

1. Data Ingestion: OPC, flat files, MQTT, manual operator events
2. Line and Cell Data Abstraction: Standardized event formatting
3. Core Event Types: In-feed, out-feed, waste, status
4. Custom Parameters: Flexible attribute addition
5. Manufacturing Data Model: Purpose-built for MES functions

Information Modeling and Analysis

• Calculate OEE, availability, performance, and quality metrics
• Generate insights through advanced analytics
• Create visualizations for different user roles
• Integrate with existing ERP and scheduling systems

Why Traditional Approaches Fail

Off-the-Shelf Limitations

• Systems Integrators: Often master only one off-the-shelf solution
• Customer Steering: Force customers toward software capabilities rather than business needs
• Known Limitations: Work within predetermined constraints

Custom Build Challenges

• Edge Device Dependency: Still rely on rigid hardware interfaces
• Shape-Based Integration: Try to force equipment data into predetermined formats
• Limited Flexibility: Can't adapt to changing manufacturing requirements

End User Dissatisfaction

As manufacturers become more sophisticated in their digital journey, they become increasingly dissatisfied with both approaches. Most successful MES implementations evolve from off-the-shelf to built solutions.

Fuuz AI: The Optimal Path Forward

Platform-Based Approach

Fuuz AI provides the industrial IoT platform foundation that enables:

• Flexible Equipment Integration: Connect any machine without rigid data formatting
• Scalable Architecture: Add new capabilities as business needs evolve
• Future-Proof Design: Adapt to changing manufacturing requirements

Integration Capabilities

• ERP Integration: Seamless work order and scheduling integration
• Third-Party Modules: Support for specialized manufacturing modules
• SDK Availability: Extensible platform for custom development

Real-World Implementation Benefits

• Faster Deployment: Platform approach reduces implementation time
• Lower Total Cost: Eliminate rigid edge devices and custom hardware
• Better ROI: Adapt system as business grows and changes
• Reduced Risk: Proven platform with industrial-grade reliability

Conclusion

The technical reasons manufacturers choose to build rather than buy MES systems stem from the fundamental limitations of off-the-shelf solutions: rigid data models, limited capabilities, and inability to adapt to unique manufacturing requirements.

Fuuz AI Industrial Intelligence Platform bridges this gap by providing a flexible, industrial-grade platform that combines the benefits of both approaches:

• Platform Flexibility: Like building custom solutions
• Proven Components: Like buying off-the-shelf software
• Future Adaptability: Evolves with your business needs

For manufacturers serious about digital transformation, Fuuz AI represents the optimal path forward—providing the power to build exactly what you need on a foundation designed specifically for industrial applications.

Ready to transform your manufacturing execution? Contact Fuuz AI to learn how our Industrial Intelligence Platform can eliminate the build vs. buy dilemma for your organization.