INTRODUCTION
In the rapidly changing world of industrial manufacturing, digital transformation has become an imperative. From small manufacturers to global companies, all are striving to optimize and transform production and maintenance processes using data from machines, production lines, meters, sensors, etc.
Why? Because real-time machine information is extremely useful in understanding how to increase productivity, improve product quality, reduce waste, and reduce operating costs.
But implementing industrial digitization strategically, rather than acquiring, orchestrating and analyzing machine data, means ensuring that the implemented solution supports a wide range of platforms, current and future, and avoiding the creation of data ‘silos’ that then become obstacles to the indispensable evolution of digitization.
In an increasingly connected and dynamic manufacturing environment, breaking down information silos and adopting open architectures makes all the difference.
The 'infographic below summarizes the key benefits, from revenue growth to waste reduction to time savings per employee, that companies achieve by integrating systems, data, and platforms in a seamless, cross-platform way.
From Accenture Research
Interpretation
Accelerating growth: a high level of interoperability unlocks value beyond simple technical integration, multiplying the speed of revenue growth by six.
Increased agility: working on open, interoperable platforms not only reduces integration costs, but frees up valuable time (about two hours per day per employee) → more focus on innovation.
End-to-end efficiency: benefits reverberate throughout the entire value chain (supply chain, operations, customer experience, HR management and sustainability), confirming that cross-platform architectures are the basis for truly “future-proof” digital transformation.
These data demonstrate unequivocally that investing in interoperability is not just an IT best practice, but a strategic driver of growth, efficiency, and resilience.
Below, you will find key considerations for anyone with an interest in the industry, for business decision makers responsible for making technology investment choices, for ICT managers, and for production and operations managers.
We will explore the ‘importance of a versatile and 'future-proof’ architecture, and illustrate how solutions such as Alleantia Core software enable them to accelerate their digital transformation, while still keeping options open to manage future evolutions, and thus current and future integration costs.
Modern production lines can generate gigabytes of data every day, from sensor readings and machine logs to operational metrics, enterprise resource planning (ERP), and manufacturing process management (MES).
| Level | Period | Data volume | Equivalence in GB/day |
|---|---|---|---|
| Production Line | 1 giorno | > 70 TB | > 70 000 GB |
| Smart factory | 1 week | ≈ 5 PB | ≈ 714 000 GB (5 000 000 GB ÷ 7) |
| Single machine | 1 week | ≈ 5 GB | ≈ 0,7 GB |
The next critical step is to convert this data into usable information. However, many organizations fall prey to “vertical siloed” deployments in which data then remains locked into a single platform or application.
A successful 'digital transformation initiative should ensure that machine data remain easily usable for new applications, data analytics platforms, data science and self-learning tools that are already available and others that will emerge in the future.
This is critical because an initial “high priority” project, such as integrating production data into ERP. It will almost certainly be followed by subsequent initiatives on 'data analytics, artificial intelligence-based decision making, or specialized solutions to support the shopfloor in improving its operations.
When you rely on closed, proprietary systems, you risk high integration costs, challenging migrations, and often the need for specialized expertise in the future.
An open architecture that provides standardized machine data models, combined with ready-to-use integration capabilities, can greatly reduce the time-to-market for new use cases.
It also allows experimental projects (PoCs) to be implemented more easily, enabling organizations to test new platforms and solutions with minimal effort and expense.
| Multiplatform | Interoperability |
|---|---|
| Provides APIs, connectors and SDKs** to connect different technologies “out-of-the-box” | Adopt standard data models (e.g., OPC UA, MQTT, REST) to make different parts talk to each other |
| Supports fieldbus, legacy and modern cloud protocols without custom build-ins | Converts data to interoperable formats, reducing integration time and cost |
| Allows a choice of multiple vendors (edge, analytics, AI) depending on use cases | Ensures that new tools and platforms can be integrated without rewriting the architecture |
This includes classic fieldbuses, proprietary machine interfaces, modern protocols such as MQTT, REST APIs for Web applications, and direct integration with popular databases and cloud environments.
Reducing downtime during the initial deployment or implementation of extensions is a critical success factor for the long-term manageability of digital industry project evolutions.
This consistency also enables interoperability between different applications and future data-driven projects.
Make sure your platform can meet current safety requirements and regulations, and they will surely evolve in a restrictive direction, for different regions and sectors.
An industrial vehicle manufacturer integrated machine data from legacy machinery with a modern MES.
PHASE 1 - The initial goal was to obtain a solution to track and measure production performance, gaining an up-to-date view regarding:
They chose Alleantia's IoT software for its broad support of protocols and certified API connectors, seamlessly connecting data from decades-old CNC machines to a modern MES in a matter of weeks.
PHASE 2 - Several months later, the manufacturer decided to extend its data analysis capabilities.
The goal was to delve deeper into monitoring the execution of the machines' actual work schedules to identify causes of performance slowdowns.
This was achieved by using a powerful business intelligence and reporting platform to implement massive data analysis.
The Alleantia solution already had a standard machine data model available in an accessible format. This made it immediate to implement the BI platform connection, without costly redesigns or complex data migrations.
Alleantia has added edge computing capabilities to implement real-time data aggregation and correlation to support highly detailed analysis models.
Within two months, the analysis system was completed providing engineers with additional data and tools to take action on continuous improvement of operational efficiency.
Adopting an open, cross-platform IoT platform today means breaking free from the constraints of a single vendor and gaining maximum operational flexibility.
The company can thus integrate-and replace-analytical tools of different kinds at any time, choosing the most effective solution for new business objectives on a case-by-case basis.
This freedom to experiment accelerates innovation, reduces the risks of obsolescence, and enables the rapid exploitation of emerging technologies, ensuring a truly “future-proof” digital transformation path.
Ultimately, only those who build their ecosystem on open standards can continue to grow, adapt and remain competitive in an ever-changing market.
Choosing an industrial IoT solution that avoids vertical silos and supports cross-platform connectivity is essential for any modern industry.
Take a look at the integration capabilities of the Alleantia platform, and find out if your current application platforms are supported.
Contact us for more information and learn how Alleantia's IoT platform can accelerate your digital transformation journey, reduce integration costs, and open up new possibilities.