Navigating On-Premises, Cloud, and Edge Data Infrastructures in Manufacturing

Why this article worth your time:

Gain a nuanced understanding of on-premises, cloud and edge data infrastructures, along with their respective strengths, limitations and real-world applications in manufacturing environments.
Learn practical strategies for aligning your data infrastructure with your organization's scale, flexibility needs, and operational demands to optimize efficiency and security.
Review actionable considerations and case examples to help you build smarter, data-driven operations.

The more data a business has, the harder it is to maintain the increased processing power and real-time connections needed to support smart, seamless operations. Tools like artificial intelligence (AI), machine learning (ML) and manufacturing execution systems (MES) can all help streamline data-driven operations, but they’re only applicable in a well-maintained data infrastructure. As a result, manufacturers must consider which of the modern data infrastructure approaches — on-premises, cloud and edge — is best for their specific use cases.

Regardless of whether they are long-standing or newly developed, each of these data infrastructure options provides potential benefits for manufacturers’ computing environments. But their utility depends on the specific needs, demands and systems already in place within a manufacturing environment. As such, decision-makers must understand each option’s strengths, weaknesses and potential applications before they begin implementation.

On-premises infrastructure

The most established of the options, on-premises (on-prem) data infrastructures are built around hardware and software that are hosted and controlled on-site by their owners. Before storing data in the cloud or at the edge was an option, businesses were required to build and maintain on-prem server ecosystems to facilitate data collection, storage and analysis.

This on-site control is one of the greatest strengths of on-prem infrastructure — businesses have complete oversight over the operation of their data ecosystem without needing to collaborate with third-party providers. This also offers enhanced security capabilities, since data is stored within the facility’s walls.

Potential drawbacks of on-prem infrastructure include complex maintenance requirements, minimal backup and recovery capabilities, and a limited flexibility and capacity to scale. On-prem infrastructure can be well-suited for smaller manufacturing operations that may not be operating on a global scale. It can also be feasible for certain types of more sensitive data, as long as it is still accessible to those who need it.

Cloud infrastructure

As businesses became more data-driven and globally interconnected, cloud infrastructure grew in capacity and popularity. Cloud infrastructure leverages distributed hardware and software to support a wider range of server, storage and computing capabilities. This moves the burden of creating and maintaining systems from internal teams, allowing them to rely on third-party experts instead.

In cloud computing, data is collected from sources at the edge of the network — such as production equipment, tracking systems and worker devices — and transferred to a central server for processing. Edge computing infrastructure processes high-priority data as close to the source as possible, eliminating the need for data transfers.

Other benefits of cloud infrastructure include increased flexibility, cost efficiency, improved backups and scalability. It gives manufacturers access to the benefits of data-led operations without as many barriers to entry. However, the model comes with weaknesses as well —fully cloud-based systems can lead to difficulties with platform interoperability, vendor lock-in, and less hands-on control over security and privacy.

Cloud infrastructure is often a good choice for distributed organizations whose users require timely access to a range of data. For instance, a manufacturer with production facilities in one state and distribution facilities in another could both benefit from cloud-based storage to support streamlined customer order and fulfillment processes.

Edge infrastructure

In cloud computing, data is collected from sources at the edge of the network — such as production equipment, tracking systems and worker devices — and transferred to a central server for processing. Edge computing infrastructure processes high-priority data as close to the source as possible, eliminating the need for data transfers.

While still largely in development, edge computing can help manufacturers maintain a more dynamic, real-time understanding of their processes and improve connectivity.

Reducing the time for data transfer and easing the data load on a central server can make manufacturing operations more efficient and enable greater responsiveness to bottlenecks, equipment failure and other disruptions. Potential drawbacks, however, include a lack of data consistency, security disruptions and technological disparities.

Edge computing is a powerful tool for manufacturers who need to streamline their production processes. For example, a combination of sensors and computer vision devices can be leveraged to detect anomalies and automate the quality control process of a production line. Edge devices can also be used to help automate inventory and tracking logistics and support smart machines on the factory floor.

Which infrastructure is best for you?

Each of the options discussed above present a feasible infrastructure model for different manufacturing use cases. They can be used on their own or in combination with one another, as long as their capabilities are considered in relation to the manufacturer’s needs and specific use cases.

As is often the case in manufacturing, however, there’s no one-size-fits-all solution to any given challenge. Data infrastructure is no exception, and leaders will need to dive into their operations to decide what will work best for them.

Consider the following factors to help make an informed decision that suits your business case:

Scale: How big is your organization and how much data do you produce? Smaller-scale organizations can operate using on-prem infrastructure as long as it can be maintained and accessed effectively. If your organization is larger and more distributed, integrating cloud and edge components will be key to interoperability and consistency.
Flexibility: Do you anticipate the need to keep up with shifting industry trends or is your business in a relatively stable sector? Keeping up with the pace of evolving technology, supply chains and demand requires a real-time, connected understanding of the data across your tools and facilities.
Tracking: Can you keep up with the data you need for optimized operations or is it too siloed in different regions or disconnected platforms? Do you need to bring this data together in a unified, accessible and digestible location?

In many cases, manufacturers leverage a combination of these infrastructures to build an ecosystem that suits their current and future data-driven business needs. The joint capabilities of on-prem hardware, scalable cloud platforms and smart edge devices can support a data ecosystem that is reliable, accessible, secure and up to date for your team’s various business needs.

Regardless of the infrastructure options you choose, it’s crucial to maintain the necessary oversight, accessibility, adaptability and capacity to meet your business’s specific needs. By choosing platforms that can adapt to changing needs and support seamless operations, you can streamline production without getting locked into a rigid and inefficient infrastructure.

Bill Rokos is the chief technology officer at Parsec Automation.