Cloud Computing in Manufacturing: On-Premise, Cloud, or Hybrid?

Cloud computing is no longer a debate topic in manufacturing. The question has shifted from “should we move to the cloud?” to “which components should we move to the cloud?” This article examines different deployment models, their advantages and risks, and how to determine the right strategy for manufacturing companies.

Three Deployment Models

On-Premise

All servers, databases, and application infrastructure are hosted in the company’s own data center.

Advantages: Full control over data, internet-independent operation, regulatory compliance (especially for defense industry suppliers), and low latency within the facility network.

Disadvantages: High upfront investment, IT maintenance burden, scaling challenges, and disaster recovery costs.

Cloud

Applications and data are hosted in the cloud provider’s data centers under a SaaS (Software as a Service) subscription model.

Advantages: Low initial cost (opex model), automatic backups and updates, universal access, and rapid scaling.

Disadvantages: Internet dependency, reduced data location control, potentially higher total cost of ownership at scale, and bandwidth requirements for IoT data volumes.

Hybrid

Critical systems run on-premise while supporting systems operate in the cloud. This is the most common choice for manufacturing.

Typical hybrid scenario: ERP and MES on-premise for production continuity, BI and reporting in the cloud for universal access, backup and disaster recovery in the cloud, and IoT data storage split between edge and cloud.

Manufacturing-Specific Considerations

Production Continuity

A production line stoppage can cost tens of thousands of dollars per hour. Critical systems like ERP and MES must operate independently of internet connectivity.

Data Security

Production data, formulations, cost information, and customer orders form the foundation of competitive advantage. For defense industry suppliers, data location is a legal requirement.

IoT Data Volume

Sending all data from thousands of sensors to the cloud every second is neither practical nor economical. An edge computing layer processes data at the source and transmits only meaningful information to the cloud.

Integration Complexity

Communication between ERP, MES, PLM, CRM, IoT platform, and BI tools may require additional integration layers in mixed deployment models.

How to Choose the Right Model

Step 1: Criticality analysis — classify each system by its impact on production continuity.

Step 2: Cost modeling — calculate both initial and five-year total cost of ownership (TCO) for each model.

Step 3: Regulatory requirements — identify sector-specific data location and security obligations.

Step 4: Growth plan — project user counts, facility numbers, and geographic expansion over five years.

The BilTAY Approach: Flexible Deployment

The BilTAY NexUS ecosystem supports all three deployment models: On-Premise, Cloud, and Hybrid. Same software, same modules, same user experience — only the infrastructure differs.

Our open-source option provides source code access for enterprises that require full control over their data. With deployment experience across 160+ factories, we have seen that every business has different requirements. The right strategy is not committing to a single model but designing the optimal combination for your business needs.

Think Next. Think US.