In the context of the Piedmont Competence Center, the know-how of CEMAS Elettra and Siemens represents an important resource made available to consortium companies and all partners to test how services related to 4.0 processes can produce measurable results through digital applications.

The future of industry poses and will pose greater challenges to industrial machinery manufacturers every day. The so-called fourth industrial revolution will lead to an increasingly automated and interconnected production system.

In such an environment, efficient data analysis can be the determining factor in a company’s success or failure, regardless of whether it operates in manufacturing, infrastructure, energy production, or any other sector.

For this reason, CEMAS Elettra chose to invest in innovation and, working in synergy with SIEMENS, is now one of the first companies in the field of plastics welding to offer a specific and targeted “Industry 4.0 service package” for each stage of the production process.

Smart production

Thanks to the so-called “Digital twin” (literally “Digital twin”), it is possible to digitally replicate a physical entity (be it a simple or complex object, asset or process) and simulate its operation and performance. The Digital Twin can then be used to optimize a product and its production system before investing in physical prototypes and assets. This fosters collaboration between humans, machines and systems.

Smart services

By virtue of next-generation management of IT and technical infrastructure, during the manufacturing process, Siemens’ MindSphere (an open, cloud-based operating system for the Internet of Things) can quickly and efficiently collect and analyze the enormous amount of data produced by an asset, plant or infrastructure, thereby contributing to its optimization.

Smart energy

Adopting more high-performance, cost-effective and environmentally friendly infrastructure is a major goal for the industry of the future. In fact, an efficient customs monitoring system is the indispensable starting point for achieving “predictive maintenance.” This concept defines an “intelligent” monitoring system that, using “neural networks” (sets of algorithms), analyzes of production data, identifies patterns and predicts errors or critical issues before they occur.