Digitalization in engineering is progressing rapidly. This challenges companies to adapt their development processes to new technologies. Cloud-based PLM platforms offer concrete solutions for managing product data more efficiently and making development processes more flexible.

The article The Future of PLM: Cloud Platforms and AI in Engineering examined the fundamental evolution of PLM, focusing on the shift toward cloud platforms and AI technologies. This article will discuss practical applications.

Why is cloud-based PLM gaining importance in practice?

Many companies are currently faced with the task of modernizing their existing PLM systems or adapting them to new requirements. The increasing complexity of modern products and the growing volume of engineering data necessitate flexible and scalable solutions. At the same time, development teams today often work across locations and disciplines. In this context, traditional on-premises systems are increasingly reaching their limits, particularly when it comes to accessing up-to-date data or integrating external partners.

Cloud-based PLM platforms offer new opportunities to organize development processes more efficiently and improve collaboration among the various stakeholders.

Key Benefits of Cloud PLM in Everyday Engineering
The use of cloud PLM offers a range of benefits that can be directly leveraged in day-to-day engineering work.

  • Improved collaboration: Cloud PLM provides centralized access to product data for all teams involved. Changes to designs or bill of materials can be tracked in real time, making coordination processes significantly more efficient.
  • Scalable use of resources: Modern products generate large amounts of data, particularly in the areas of CAD and simulation. Cloud platforms enable flexible scaling of storage and computing resources, allowing even data-intensive applications to be used efficiently.
  • Faster implementation of new functions: Cloud-based systems are continuously being developed. This allows new features, particularly in the areas of data analysis and AI, to be deployed and utilized more quickly without the need for time-consuming system updates.
  • Reduced IT operational overhead: Since the provider handles operation, maintenance, and updates, internal IT overhead is significantly reduced. Companies can thus focus more strongly on their core engineering competencies.

Typical Use Cases for Cloud PLM
The benefits of Cloud PLM become particularly clear when examined in specific engineering use cases:

  • Global product development: Companies with distributed development sites use Cloud PLM to ensure a consistent data set. This allows teams to work on products simultaneously, while changes are managed centrally and documented transparently.
  • Collaboration with external partners: Cloud platforms significantly simplify the integration of suppliers, development partners, or service providers. External partners can access relevant data in a targeted manner without the need for complex local system integrations.
  • Data-driven product development: With large amounts of data available, companies can make their development processes more data-driven. Analytical functions and AI-powered applications help identify patterns and make informed decisions.
  • Reuse of engineering knowledge: Cloud PLM facilitates access to existing designs and components. This allows existing solutions to be efficiently reused and reduces redundant development efforts.
  • Integration into digital system landscapes: Modern cloud-based PLM platforms can be more easily integrated with other systems, such as ERP, MES, or IoT platforms. This enables a seamless flow of information throughout the entire product’s lifecycle.

Challenges associated with the implementation of cloud PLM
In addition to the advantages listed above, companies should also consider the difficulties associated with implementing cloud PLM.

These include, among others:

  • Migration of existing data and systems
  • Adaptation of processes and workflows
  • Organizational changes within the company
  • Integration into existing IT landscapes

Successful implementation requires careful planning and close coordination between IT and business departments.

A future article will delve deeper into aspects such as handling sensitive engineering data and further requirements for the protection of digital systems.

Conclusion
Cloud PLM offers companies a wide range of opportunities to streamline their development processes and optimize the use of product data. Especially in global and data-intensive engineering environments, the use of cloud-based platforms can deliver significant added value.

The implementation, however, requires a structured approach as well as the adaptation of existing processes and organizational structures. Companies that tackle this transformation in a targeted manner can leverage the potential of cloud PLM in the long term and future-proof their engineering processes.