ISO 27001 Certification: security as a standard for our cloud products

Digitalization is shaping our lives and workplaces like never before. With this evolution comes an increased responsibility to protect data effectively and ensure stable service delivery. Information security is no longer a “should” but an absolute “must.”

As a provider of industrial software solutions from the cloud, quality, security, and reliability are our top priorities. We are delighted to announce our successful ISO 27001 certification by Datenschutz Cert. This confirms our commitment to providing products that meet the highest security standards and effectively protect data.

More security, efficiency, and sustainability with automation

Our goal was clear from the beginning: to meet security and stability requirements with innovative technologies. We rely heavily on automation and Infrastructure as Code (IaC) to achieve this. These measures enable us to implement security mechanisms effectively and integrate them seamlessly into our development and operating processes.

One crucial aspect of our preparations was to take climate risks into account. Events like extreme weather pose potential threats to IT infrastructures. In response, we developed solutions that minimize risks while enhancing efficiency – such as monitoring tools and automated scaling. These technologies reduce our carbon footprint and help to ensure a high level of security and sustainability.

Security culture as a success factor

Information security is more than just meeting standards—it is an integral part of our corporate culture. Principles such as high availability, automation, and the use of a single source of truth define how we work and foster a structured approach to tackling complex challenges. A standout aspect is the contribution of our team. Regular training and a high level of security awareness ensure that information security is not just seen as a task for IT, but is practiced throughout the entire company. This holistic mindset was a cornerstone of our journey to achieving ISO 27001 certification.

Our automation strategies further illustrate how we combine efficiency with security. By standardizing processes, we reduce human error while laying the foundation for continuous improvement.

Added value for customers and partners

For our customers, certification means one thing above all: trust. ISO 27001 certification is an internationally recognized seal of quality and confirms that we adhere to the highest security standards. This not only enhances the reliability of our cloud products but also assures our customers that their data is in safe hands.

Our partners also benefit significantly from this certification. Standardized processes and clearly defined security requirements make collaboration more seamless, boost efficiency, and establish a foundation of trust for future projects. It is a crucial competitive advantage, especially in a dynamic environment like the cloud industry.

Our vision for the future

ISO 27001 certification is not an endpoint for us but a milestone in our ongoing journey to continuously enhance our security measures. For instance, we plan to make our monitoring systems even more robust, enabling us to detect potential risks more quickly and address them more effectively. The digital landscape is constantly changing – we are ready to face these challenges and ensure the security of our customers, partners, and their data.

Document management in Cloud PLM systems

Optimized processes, security, and global collaboration in the product lifecycle

How can companies efficiently manage their data and documents? How can they provide information across departments, locations, and organizations?

Even in individual projects, the number of documents quickly grows into the hundreds or thousands. Managing this data on network drives or email systems leads to bottlenecks in the face of the complexity of product development. Companies need a document logistics system that creates clarity and fosters teamwork.

Software for Product Lifecycle Management (PLM) is ideal for this task. Cloud-based systems, in particular, make document management more efficient by integrating all workflows and information throughout the entire product lifecycle. In this blog post, we explore how Cloud PLM systems simplify document management.

What are the benefits of cloud-based document storage?

Managing documents via the cloud offers two significant advantages:

Firstly, it promotes global real-time collaboration. Teams around the world can access legally binding documents and work on them together, significantly reducing development times.

Secondly, companies are not solely responsible for the security of their systems. Cloud providers must undergo rigorous certifications and audits, meeting the highest security standards. Sensitive information is optimally protected through data encryption, access controls, and regular security updates. This also simplifies compliance with regulations such as ISO and GDPR for customers.

What are the advantages of document management in PLM systems?

1. Centralized data storage:
The document management feature allows for company-wide organization of documents, promoting teamwork and knowledge sharing. Product-relevant documents, such as CAD files, are managed in a central location, avoiding data redundancies and ensuring all departments have access to up-to-date information.

2. Version control and change tracking:
PLM systems enable document versioning, ensuring teams always work with the latest data, as every change is logged.

3. Workflow and approval processes:
Integrated workflows automate approval and release processes, speeding up decision-making and ensuring structured processes without manual intervention.

4. Access controls:
Access rights can be clearly defined and managed within a PLM system, ensuring only authorized individuals can access sensitive documents.

5. Compliance adherence:
PLM systems provide audit-proof storage to meet regulatory requirements and industry standards (e.g., ISO).

6. Integrated data and processes:
Document management is often closely linked to areas such as project management, quality control, or product development. PLM systems integrate all product-related processes for comprehensive management.

7. Cost savings and increased efficiency:
With document management functions, employees use their working time more effectively, reducing search times and avoiding errors caused by outdated information. Improved collaboration across teams lowers costs in the long term, while automated processes enable faster turnaround times.

What makes document management with CIM Database Cloud stand out?

The intelligent document logistics of CIM Database Cloud enables organizations to maintain clarity and enhance collaboration even in complex processes. A powerful full-text search speeds up document retrieval and simplifies access to vital information.

With seamless integration with Microsoft Office for the web™, employees can use familiar applications to create, edit, and share documents without separate storage. Files are managed in the Cloud PLM document storage, allowing multiple people to work on the same document simultaneously—without requiring local MS Office installations.

Conclusion

Cloud PLM systems offer a powerful, secure solution for document management. Features like version control, workflow automation, and robust security measures help manage documents efficiently. Companies minimize risks and ensure compliance while the cloud-based structure offers maximum flexibility—teams can collaborate anytime, anywhere.

Learn more about how CONTACT CIM Database Cloud can optimize your document management.

Design decisions in minutes – how AI supports product development

Artificial intelligence (AI) is a hot topic and increasingly important in product development. But how can this technology be effectively integrated into development projects? Together with our client Audi, we put it to the test and examined the potential and challenges of a machine learning (ML) application – a subset of AI – in a real project. For this purpose, we chose a crash management system (CMS). It is both simple enough to achieve a meaningful result and complicated enough to adequately test the general applicability of the ML method.

Expertise as the Key

ML can only be effectively utilized to the extent the underlying data foundation allows. Therefore, the expertise of the professionals involved plays a critical role. For example, design engineers enter their knowledge of manufacturing and spatial constraints, usable materials, and dependencies into the CAD model. Calculating engineers share their expertise on the simulation process, while data scientists assist with sampling and evaluation.

The creation of thousands of design and corresponding simulation models, as required for the use of Machine Learning (ML), presents a tremendous challenge without automation. The FCM CAT.CAE-Bridge, a specially developed plug-in for CATIA, enables seamless automation across all process steps. Additionally, it embeds all simulation-relevant information (material, properties, solver, and more) directly into the CAD model. The fully automatic translation into a simulation file is done via tools such as ANSA or Hypermesh.

Automated process: Sampling, DoE, model creation, simulation, evaluation with subsequent training of the ML models. (© CONTACT Software]

Precise Linking of Parameters and Results

Our approach ensures that the relationship between the CAD model and the simulation model is fully preserved. The automated calculation and evaluation of the models based on specific results create an excellent data foundation for the ML process. The vectors of input parameters with corresponding result values form the basis for the ML approach—clear and comprehensive.

Input parameters (blue) identified based on constrained result vectors (red) that meet the requirements. (© CONTACT Software)

With the trained models and their known accuracy, parameter variations can be quickly tested, and the impact on behavior can be derived—literally within minutes. Once the optimal parameters are identified, they are automatically transferred to the CAD model and the design process can continue.

Conclusion

Our project demonstrated that ML is a valid method for design engineering. The combination of parametric CAD models, simulation, and machine learning provides an efficient approach to making design decisions quickly and accurately. The prerequisite for this is a robust database and the collaboration of the relevant experts on the model. The successful results from the Audi project demonstrate the potential of our data-based approach for product development.