The Innovation Imperative: Agile Design in the Automotive Industry

The Innovation Imperative: Agile Design in the Automotive Industry

The automotive sector is one the world’s most important industries. It spends over $100 billion annually on R&D, it employs around 12.9 million people in Europe and, at over $2 trillion a year, its value is surpassed by only four economies. Despite its success, the sector faces challenges. Legislation – especially environmental – requires fundamental design change. Consumer behaviour is leading to demands for connected, smart and autonomous vehicles. A modern car is a high-tech machine and automotive companies are busy trying to reinvent our driving experience. In this article, Kirk Gutmann, SVP of Industry Strategy at Siemens PLM Software, looks at these issues in more detail before explaining that now, more than ever before, an innovation culture with more clean-sheet design is vital to the automotive industry’s future. Kirk then moves on to describe five ways auto companies can enhance their design and manufacturing processes to accelerate innovation and stay ahead.

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Innovation era

Of all the challenges facing the automotive sector, environmental legislation is perhaps the most significant. Emissions must be cut in half and fuel economy doubled by 2025. That’s a four-fold improvement in the next decade compared to the previous one. New targets require new approaches. Indeed, there’s a strong case for arguing that the industry’s accepted blueprint of incremental design improvements must be replaced by a new clean-sheet approach to find the major weight reductions necessary to help cut emissions. Clean-Sheet design refers to the idea of reinventing the entire vehicle development processes and finding ways to look for solutions at every aspect of an automobile design. One example of this is how automakers are increasingly using composites, aluminium, and other new materials for bodywork and asking suppliers to find ways to cut weight by 15-25%.

In addition to the quest for ‘light-weighting’, the industry is involved in a big innovation race to make vehicles smarter to enhance the driving experience. For example, advances to location-aware systems and computer analytics are improving navigation and safety. Automotive companies are therefore investing heavily in specialist teams to create engaging in-vehicle interfaces that present a wealth of information in a simple, usable and helpful way without compromising safety. Premium vehicles already have in excess of 100 million lines of code – that’s more than a fighter jet – and software will only continue to grow in importance as we progress to fully autonomous vehicles. Indeed, it’s a key reason why car design is becoming so much more complex than it was before.

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New ways of working needed

As more next generation vehicles hit the roads, it is a reminder that car companies must simplify vehicle development processes and shorten development cycles by prototyping in more agile and efficient ways

 

This agility can be achieved by creating digital clones of new models. These models enable much of the development and testing to take place in the virtual world and thereby accelerating the design, test and approve cycle. To move to a digital design environment we recommend five steps:

 

Creating the digital twin of the car is only the first step. To achieve accelerated and efficient product development we believe that it’s vital to create a robust digital enterprise designed to foster innovation. I see five key steps that car companies can take to drive digitalization of the vehicle development process.

  • More clean-sheet Design: Clean-sheet design is an approach used widely in aerospace. The aerospace companies host projects, teams and suppliers on a modular but integrated set of Project Lifecycle Management (PLM) tools to reinvent every aspect of the plane. While PLM is used extensively in the auto industry, we believe its scope and capabilities need to change. The reason for this is that, with every area of design being scrutinised, it’s essential to coordinate change between different functional areas to ease complexity. The tools must make it easier to unite disparate development packages in a single product design and simulation environment; create and update technical documentation; configure and manage bills of materials; and coordinate people and processes towards shared goals. You also need capabilities to cover all areas of vehicle development including mechanical, electrical and software components. A common PLM backbone makes it easier to manage change, align virtual teams and shorten the development cycle.
  • Integrate Computer Aided Engineering and Computer Aided Design (CAD): We are seeing increasing need to align design and engineering analysis activities along with integrating this with vehicle testing and simulation. By using 1D and 3D digital models in vehicle prototyping time can be significantly reduced because it’s impossible to physically validate all the components, designs and parts when design validation happens in an iterative way. By integrating the virtual and physical world, we can understand component performance prior to signing-off on fabrication to help cut product development costs and timelines.
  • Model the software: Given the importance of software in automotive, it’s imperative to make it much easier to create, document, store and run tests on codes. This requires an integrated Application Lifecycle Management (ALM) and PLM system to ease complexity, optimizes efficiency and helps contain costs in embedded software development processes. An integrated ALM-PLM environment makes it easier to develop and manage embedded software from project inception to end-of-life and make this process integral to the overall vehicle development plan. This enables management of large-scale software deployments while ensuring traceability and error checking
    • Execute change: With the massive amount of change requests that happen in a global program launch, it’s vital to better connect engineering and manufacturing systems. Engineering and manufacturing must work together to determine what type of tooling and operations changes are required to handle different vehicle configurations. For example, take installing mirrors in an assembly line. If you think about it, automotive mirrors come in many different types. There is the electric or nonelectric, heated or manual, one with the blind spot assist, and so on. The build sequence for these different kinds of mirrors is different requiring different electrical and mechanical assembly steps. A digital project management platform makes it easier to combine product engineering, manufacturing engineering and shop floor execution into integrated systems. The visibility and control provided by uniting these capabilities in one interface helps cut complexity to get to market faster and ensure that, when the product is launched, the right processes – and process controls – are in place.
    • Integrated quality systems and analytics: We are encouraging customers to look afresh at quality systems and analytics. A comprehensive set of quality tools and analytics can provide insight into how designs translate into production and if there are any discrepancies between predicted and actual product quality – e.g. the margin for error in bodywork joints. The data will help improve production quality and can feed into the design process to drive continuous improvements in vehicle engineering, component production and assembly.
    • Complexity and control
      There’s no doubt that automotive design and production is becoming much more complex. And while technology – in the form of complicated software interactions – is a root cause of this challenge, it also provides the answer. Just as the sector is busily reinventing the vehicle, we’ve looked afresh at our software portfolio to get complexity under control and accelerate product development. By providing a cohesive suite of tools across design, testing, simulation, production and execution analytics, it’s much easier to manage virtual teams, contain costs, and automate and validate development processes. As the industry enters a period of intense investment and competition – the likes of which we have not seen before – a smart innovation portfolio can help automotive teams design, engineer, manufacture, and most importantly, achieve innovation.
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About Author – (Guest Post)

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Kirk Gutmann –Senior Vice President, Industry Strategy – Siemens PLM Software

Kirk A. Gutmann is senior vice president of  Industry Strategy for Siemens PLM Software, a business unit of the Siemens Digital Factory Division.

Kirk is responsible for overseeing the company’s 8 vertical industries, capturing industry-specific PLM requirements for solution investment and development as well as insuring industry process leadership with product lifecycle management products.  Prior to his current position he was Vice President for Siemens PLM Software’s Automotive & Transportation industry.

Before joining Siemens PLM Software, Gutmann was Chief Strategy and Technology Officer at General Motors, where he was responsible for managing the IT strategy, application, technology, and investment portfolio globally across the various functional areas of the company.  Also while at General Motors, Gutmann spent six years as the information Officer for Manufacturing and quality and six years as Information Officer for product development.  During this time he developed extensive international experience leading a worldwide team responsible to commonize processes and systems across global operations.  He also received the GM Chairman’s Award in 2000, 2002 and 2007.

Kirk also spent 10 years at Navistar International Corp. in a number of manufacturing and truck engineering leadership roles.  As Vice President and Officer – Truck Engineering, Gutmann was in charge of product development, product studios, prototype,  and manufacturing plant support.  Gutmann started his career at Booz, Allen & Hamilton Inc. in Cleveland, Ohio as a management consultant.

Gutmann received an engineering degree in Industrial Engineering from Purdue University in 1980. He later received a M.Sc. (1981) and MBA (1990) from Purdue University.  Kirk has been recognized in the CIO 100 Awards in 2005, Information Week Top 100 in 2008 and 2009 as well as the Information Week Top 20 and Industry Innovator in 2010.

 

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