Siemens Is Offering Enhanced Software Integration for Rapid Development

Interaction Siemens Enhanced Software Integration Rapid Development
Siemens Is Offering Enhanced Software Integration for Rapid Development

The need for automotive OEMs to manage product complexity in a global industry mandates a systems-driven product development process, which combines systems engineering methodology across all development domains with an integrated definition of the product. Auto Tech Review met Dave Lauzun, Vice President of Automotive and Transportation Strategy, Siemens PLM, to understand the critical software requirements during various vehicle development stages.

Siemens PLM Software’s collaborative decision support platform enables systems-driven automotive product development by bringing together all cross-domain knowledge into a single, logical location that is accessible to authorised users no matter where they are in the organisation or located in the world.

SYSTEMS-DRIVEN DEVELOPMENT

By applying a consistent process framework based on systems engineering, a vehicle manufacturer can capture, manage and organise information and knowledge, beginning with the voice of the customer, and continuing through to service, support and product end-of-life. By modelling requirements and allocating them through functional and logical decompositions to physical implementation, a carmaker can achieve a significant level of traceability throughout the vehicle.

Cross-attribute simulation and testing safeguard the balance between different critical design attributes. The automotive industry is facing significant challenges in engine downsizing engines and improving powertrain technology, and the need to offer hybrid and EV solutions, while still keeping the emphasis on minimising weight by achieving a higher level of overall performance and efficiency. The PLM Software from Siemens offers a wide range of 1D and 3D simulation and testing tools to optimise this balance in every step of the design, including the interior, chassis, powertrain, body, electronics and vehicle integration.

It is critical to the success of an automotive OEM to unite the different product bills of material (BOMs) and bills of process (BOPs), and to align the semantics of these different views, such as usage versus product structure. Once those alignments have been built, this information backbone makes it possible to drive integrated processes, such as configuration and change management across the spectrum. To launch a new car program successfully, automakers have to achieve their first-time quality goals and avoid unexpected issues during production. It is necessary to validate product and manufacturing processes digitally to ensure production rates are achievable and are meeting all quality and dimensional metrics.

A vehicle manufacturer has to verify that the supply chain is aligned adequately for global program launch and production ramp-up. Significant cost overruns can occur if labour scheduling, equipment usage and assembly processes need to be changed at the late stages. Therefore, there is a need to closely monitor cost overrun situations in order to achieve program profitability targets.

Integrated manufacturing solutions from Siemens support the sophisticated machining requirements of engine blocks, transmissions and drive components. Close adherence to quality and tolerance targets are critical at this stage. Software solutions from Siemens provide PMI-driven machining along with feature-based recognition to ensure that the correct tools and machining processes are selected, said Lauzun.

MANAGING PRODUCTION VARIATION

A critical need in the automotive final assembly operations is the ability to support manufacturing processes that can manage growing product variations. An efficient assembly line that can support several different car models and their variants with minimum disruptions can significantly influence profitability. The integrated manufacturing solution from Siemens allows re-use of best practices and ensures consistencies between plant processes. Line balancing capabilities ensure that plant equipment is utilised efficiently to support multi-product and multi-variant production. In addition, human simulation and ergonomic analysis tools can be used to make sure assembly processes are safe and efficient.

Embedded software is driving remarkable new business opportunities in the automotive industry and fuelling innovation in connectivity, electrification, and autonomous vehicle development. However, managing automotive software development complexity is a big challenge. The complexity is driven by the difference between mechanical and software system product development approaches.

Most automotive programs are managed in a three- to five-year cycle. They follow a gate-based development paradigm with strict checkpoints and certifications. Software development, on the other hand, is incredibly fast paced, as it follows agile processes where collaboration and rapid innovation is key. Typically, development of mechanical and electrical systems is managed within product lifecycle management (PLM) tools, whereas software development is managed with application lifecycle management (ALM) tools.

The challenge is to combine these two product development methodologies. Software and hardware engineers working on their respective ALM and PLM applications must be able to access information across all the lifecycle related processes. Engineering departments today must develop smart products that integrate mechanical functions with electronics and controls, utilise new materials and manufacturing methods and deliver new designs within ever shorter design cycles. This requires current engineering practices for product performance verification to evolve into a more predictive role for systems driven product development.

There is a need for modern day software solutions to combine system simulation, 3D CAE and test to help predict performance across all critical attributes earlier, and throughout, the entire product lifecycle. By combining physics-based simulations with insights gained from data analytics, dynamic process integration helps optimise design and deliver innovations faster and with greater confidence.

TEXT: Anwesh Koley