Watch the recordings of the Digital Enterprise Virtual Summit
The Digital Enterprise Virtual Summit on July 16, 2020 was a lively, interactive digital event that brought together decision-makers and experts from various industries. You can now watch videos of all presentations, discussion panels, expert talks and deep dives on-demand at your convenience.
#BecauseYourDigitalTransformationMattersWhere do you start? What's the best approach? Siemens can help.
With our extensive digitalization expertise and comprehensive industry knowledge, our experts support you on your journey to become a digital enterprise. Future proof your product and production development – quickly, efficiently and holistically. Benefit from the knowledge of our experts and start your digitalization journey, step by step.
The three stages of consulting, implementation, and optimization are based on our end-to-end approach, in which we are there to support you from the start of your digitalization project through to the stage of continuous improvement. We work with you to develop the best possible approach and coordinate the solution with your company’s specific needs.
Services from Siemens are available to support the digital transformation, from consulting to implementation. We are there to help our customers on their path to digitalization, from strategic consulting for industrial digitalization to consulting on solutions to improve KPIs. Underpinning the consulting process is a thorough analysis of how ready your company is for digitalization, which our digitalization experts perform together with you. We work together to establish the level of digitalization for each company and use the result to develop a digitalization strategy and roadmap specially tailored to your needs.
Get to know the three steps in detail
Consulting is the start of your digital transformation
“We work with you to analyze your company’s existing level of digitalization. On that basis, we then develop a digitalization strategy together, and draw up a roadmap for implementation.”
Consulting on constructing a new production line
The construction of a new SMT production line with especially high performance and top quality provides an example of consulting in action. Customer specifications are used to determine the best possible solution, and this is then coordinated with the customer. Improving protection for the production plant is an additional requirement. First comes a thorough assessment, and then the actions needed to ensure end-to-end monitoring are determined.
We take care of installing the hardware and software
“The digitalization roadmap forms the basis for the digital twins of your machines, plant, production and products. As a result, you benefit from shorter times to market, greater efficiency and flexibility, and higher quality.”
Simulation and testing using the digital twin
The implementation stage starts with creating a digital twin of the new production plant, to enable it to be simulated and tested. It may become clear at this point, for example, that the desired throughput will be impossible using the selected machine modules. Simulation can make bottlenecks visible and identify alternative solutions. The safety measures are implemented at the same time.
Ongoing optimization is the key to success
"Regardless of whether you want to optimize individual processes or the effectiveness of the entire plant, we ensure the necessary connectivity from field to cloud and help you evaluate the results of the analysis. We can also use future-oriented technologies like artificial intelligence to help you identify events before they happen.”
Continuous optimization through data analysis
The open, cloud-based IoT operating system MindSphere is used for optimization. Machine data is recorded, worked up and analyzed using edge computing, so it can be utilized in the detection of anomalies. Artificial intelligence analyzes the data using machine learning to recognize when tools have become so worn that they are at risk of failing, for example.
A further algorithm can be used to make product quality predictions. The algorithm is constantly trained to improve its recognition ability, which will greatly reduce the number of quality tests required.