The Value of Systems-driven Product Development: Case Studies from the Automotive & Aerospace Industries

Transcription

1 The Value of Systems-driven Product Development: Case Studies from the Automotive & Aerospace Industries Technology Management Systems thinking and complexity 23 March 2015 William Theron M.Eng Enterprise Sales Engineer, ESTEQ Guy Hendry BCompSc PLM Applications Engineer, ESTEQ Abstract Traditional product development is no longer the most efficient means of producing products. A methodology that manages the increasing complexity associated with technological advances, customer demand and the ability to scale to the demands of a global supply chain should be adopted. A possible solution to manage product lifecycle complexity would be to adopt a systems engineering approach to facilitate an integrated product development cycle. Systems-driven Product Development / Systems Engineering in a Product Lifecycle Management (PLM) framework could be an effective means of managing the complexity associated with product and technology evolution (Bahill & Dean, 2009; Stark, 2007). This paper will identify the value created by Systems-driven Product Development using the automotive and aerospace industries as benchmarks. Introduction As enterprises evolve and face new challenges they continue to push the boundaries of product development. The nature of competition and technology enhancement naturally pushes organisations to develop increasingly sophisticated and complex versions of their products (Hobday, 1998). Consider the automotive industry; over the last 100 years, vehicles have evolved from purely mechanical devices to a combination of mechanical, electrical and electronic devices, intricately linked with control systems and on-board computers. The continued demand of customers for improved safety and better driving experience, combined with a competitive landscape and advances in technology, has lead the industry to develop multi-domain innovative products. What was once a single domain device (mechanical) is now an integration of multiple engineering disciplines. A vehicle in today s terms is truly crossdomain dependent (Siemens PLM Editors, 2011). Now consider the implications of increasing the links between the multiple domains associated with a modern vehicle. Engineers from multiple specialist fields are required to communicate and understand the influence of their decisions on all other domains associated with their components (Hobday, 1998). Consider the implications this has on the automotive supply chain, where there is a negative moderating effect on the supply chain flexibility when product complexity increases (Blome, Schoenherr, & Eckstein, 2014). It quickly becomes apparent that as vehicles adopt this multi-domain approach, the complexity associated with product development increases exponentially.

2 There are multiple ways around managing the complexity associated with multi-domain engineering. Companies could take more time to get it right, which, however, will have a resource cost associated with it as well as a significant increase on time-to-market and extended cycle times. In contrast, rushing the process could decrease product quality (Siemens PLM Editors, 2011). Therefore, when considering the automotive industry, the traditional product development process of viewing and managing life cycle areas separately, is no longer the most efficient means of producing products. To be efficient, in terms of value engineering, means to be able to decrease the cost of manufacturing and increasing the cost of sales. To manage this complexity and ensure that vehicles are produced in competitive timeframes, a methodology that manages the increasing complexity associated with technological advances, customer demand and the ability to scale to the demands of a global supply chain should be adopted (Bahill & Dean, 2009). Approach The paper will follow an inductive, qualitative approach to research. As described by Thomas (2006), inductive research aims to establish clear links between the evaluation or research objectives by developing a framework of the underlying structure of experiences. The study will, therefore, rely on; existing literature, data collection, and interviews to identify the value of systems driven product development in the automotive and aerospace industries. To achieve this, cases discussing applications of Systems-driven Product Development in the automotive and aerospace will be discussed. Background & Context Product Lifecycle Management Product Lifecycle Management (PLM) was first adopted by manufacturing companies in the early twenty-first Century as a new paradigm for managing products across their entire lifecycle. PLM is seen as one of the most important activities in any company that develops and supports products; it enables a company to be in control of its products from the ideation stage to the end of the product s life (Siemens PLM Editors, 2011). PLM allows companies to control their product lifecycle and avoid the serious consequences that arise, such as product deadlines not being met, poor quality products, and products not achieving their goals. Products are the heart of a manufacturing company and PLM ensures the risk surrounding the product lifecycle is minimised. PLM improves the activity of product development by enabling improved innovation, reduced time-to-market for new products, product cost reduction, and support and new services for existing products. Therefore, the objective of PLM is to increase product revenues, reduce product-related costs, maximise the value of the product portfolio, and maximise the value of current and future products for both customers and shareholders (Stark, 2007). According to Stark (2007), PLM addresses areas previously considered separate, and managed separately. They include products, product data, business processes, applications, people and organisational structures. And PLM addresses them across the product s entire lifecycle, from cradle to grave. Most companies have, in their product portfolios, many products at different lifecycle stages. Managing product lifecycles in a global economy is a daunting proposition. PLM provides a framework in which all of a company s products can be managed together across their lifecycles. Therefore, PLM is a cross-functional framework where responsibility for the product may change at different phases of the lifecycle. At different times it may be with marketing, engineering, product management, manufacturing, finance, sales, and service groups in different companies (Stark, 2007).

3 The link between Innovation, Complexity and Risk To maintain a competitive advantage, companies are required to have a continued emphasis on product innovation. However, according to Friar (1995), Product innovation alone is not sufficient to provide market differentiation, companies must shift their competitive thrust to other dimensions. In other words; to stay ahead, manufacturers need to innovate beyond the product, which involves overcoming complexity and managing risk (Siemens PLM Editors, 2015b). What has changed is not the goal of innovation itself, but rather the environment in which it needs to take place to carve out differentiation: this environment is far more complex. For some companies, this has increased their exposure to risk while reducing their potential for innovation (Siemens PLM Editors, 2015b). One of the reasons PLM emerged in the early twenty-first Century, was because the environment in which products were managed was getting more and more complex (Stark, 2007). Complexity is often associated with risk. To compete in a complex environment companies need to deliver differentiable innovation. Complex systems by their very nature are more inherently risky (Fischi & Nichiani, 2015). When considering a products lifecycle there are risks that with the increasing complexity, product deadlines will not be met. Quality will be of poor standard and overall the product will not achieve its goals. Therefore, managing the ever increasing complexity associated with the lifecycle of a product it is important to manage the associated increasing risk. When considering the product lifecycle, there are three core elements to manage; people, processes and products. As each of these core areas expand, so does the complexity of their interactions. Consider people; the integration of disciplines leads to more people from different backgrounds working in collaboration to develop products. Processes continue to evolve; consider the complexities surrounding a global supply chain. Similarly, innovation in products continues to expand. Therefore, as people, processes and products evolve, the number of intersections between them expand exponentially, leading to greater product lifecycle complexity. There is a well-established approach to define and manage intersections, it s known by various names: systems engineering, model-based design, model-based systems engineering, modelbased enterprise, systems driven product development and many others ( Systems and software engineering - System life cycle processes, 2015). Systems engineering traces its roots back to Bell Labs in the 1940s. Although the approach has been with us for more than 80 years, it s still largely confined to specialist departments, separate from the main stream design and manufacturing groups (Baxter & Sommerville, 2011). So the challenge is not to invent an approach to define and manage intersections. Quite simply, as the source of differentiating innovation moves to the system, more people need to do their work and make their decisions in context of that system. This requires that everyone throughout the product lifecycle be able to leverage the knowledge, understand the dependencies, evaluate the impact of change across the entire system activities systems engineers have done for years but now everyone needs to do. It requires a systems-driven approach to innovation (Siemens PLM Editors, 2015b).

4 Systems Engineering / Systems Driven Product Development: According to the International Council on Systems Engineering (INCOSE); Systems Engineering is an engineering discipline whose responsibility is creating and executing an interdisciplinary process to ensure that the customer and stakeholder's needs are satisfied in a high quality, trustworthy, cost efficient and schedule compliant manner throughout a system's entire life cycle. (INCOSE Editors, 2015). INCOSE goes further to identify that the process of systems engineering is comprised of seven tasks: State the problem, Investigate alternatives, Model the system, Integrate, Launch the system, Assess performance, and Re-evaluate (INCOSE Editors, 2015). They also highlight that the Systems Engineering Process is not sequential. The functions are performed in a parallel and iterative manner. The world is becoming more complex, firstly due to an unparalled level of integration and being immersed in a web of interacting technologies and processes, and secondly due to rapid change becoming the norm and organizations being confronted continuously with the complex integration. Calvano & John (2004) identify the 21 st Century as The Systems Century which spans from the cultural and social aspects to a technical aspect. Systems Engineering as a discipline forms a significant part of this spectrum, which uses traditional and emerging technologies to achieve a complex engineered system (CES). A robust systems driven approach to product development requires several key elements to ensure the sustainability of the approach, these include (Siemens PLM Editors, 2015a): A consistent process framework based on systems engineering Cross-attribute simulation and test-based validation Configuration management Issue, change and schedule management Traceability throughout the entire lifecycle In addition to this, collaboration between disciplines is vital to the success of the framework. Systems driven Product Development in context Companies that can successfully establish Systems-driven Product Development as a core capability of their organization will be maximizing their innovation potential by allowing everyone to do their work and make their decisions in the context of the system. The following steps are suggested to successfully master complexity to maximize innovation and minimize risk through a Systems-driven Product Development approach (Siemens PLM Editors, 2015b). 1. Set Targets, Build Models, Predict Performance Most companies have some process in place to collect requirements and set targets, usually a combination of inputs from the market and regulatory agencies. Systems-driven Product Development starts with that requirement gathering and target setting step. These targets can be performance attributes of the product, maintenance targets (e.g. average time to replace critical components), or timing targets for assembly. Once they are set, models are built to predict performance against each target. To predict a particular aspect of performance, a model has to capture the full reality of how the product and process will behave. To predict total product and process performance, a set of models must be built for each domain and discipline where a target exists. The accuracy of the predictions these models create will depend on an ability to calibrate the models by reusing components, data, knowledge, and process from previous projects as well as collaborators.

5 2. Aggregate, Filter and Transform Information Once a set of models and simulations that will accurately predict product and process performance have been created, they should be connected in order to take account of the interactions amongst them. Each model in the set is going to produce a lot of information and when assembled together, all of the data in its raw form would quickly become overwhelming. When this happens, there s too much data and it s not in a form that people can immediately understand and take act upon, especially when it is coming from another domain. Systemsdriven product development requires that large amounts of data can be quickly and intelligently filtered so that only the information that a particular model or user needs is presented to them, when and where they need it. In addition to this aggregation and filtering, the information must be transformed when it crosses domains so that the recipient can immediately see how it relates to what they are working on. For systems-driven product development to be successfully achieved; aggregation, filtering and transformation has to scale across marketing, engineering, quality, manufacturing, purchasing, and service, as well as to roles outside the traditional product development organization. When that happens, companies rapidly construct a system of systems model that accurately predicts total product and process performance. 3. Understanding the Impact of Change Up to this point, the defined requirements for systems-driven product development have allowed the building of a set of models and then intelligently connected them into a system of systems. This system-of-systems model provides a view as to how the product and process will perform before it s built. When reviewing this performance data, the opportunities to improve performance will become apparent, as well as any hidden risks. Once these opportunities and risks are visible, changes will need to be made changes to capture the opportunities and avoid the risks. The question is, which changes represent real improvement and which might actually make things worse? Systems-driven product development relies on the ability to predict not only the baseline performance of a product and process, but variations that incorporate the effects of proposed changes. Comparisons can then be drawn between the predictions from these secondary models and simulations to the overall targets to see which combination brings the goal closer. To summarise, systems-driven product development allows organisations to: Master complexity to maximize innovation and minimize risk Understand the impact of change early to avoid later lifecycle costs Respond immediately and directly to market demand Develop and produce with maximum flexibility

6 Case Studies 1 Several case studies on the value of a Systems-driven Product Development approach will be discussed next. Aerospace Space Exploration Technologies (SpaceX): SpaceX designs, manufactures and launches advanced rockets and spacecraft. The company was founded in 2002 to revolutionize space technology, with the ultimate goal of enabling people to live on other planets (S. Editors, 2015). SpaceX adopts a PLM framework for product development with an emphasis on system-driven product development, by implementing a systematic methodology and creating a core repository that stores all documentation (product CAD models, specifications and so on) related to the design and manufacture of the Falcon. SpaceX s managed development environment has enhanced collaboration at the company. Designing a rocket takes the coordinated effort of three different engineering teams: propulsion, structures and avionics. At SpaceX these teams are located in different buildings and because everything related to the rocket design is managed by using a systems-driven product development approach, the teams can each work on different parts of the rocket without worrying about interfering with each other. If a structures designer is doing work on a part, an engineer in another building can look at that part and make sure it doesn t interfere with what he s doing. Or they can discuss any potential problems early on. says Chris Thompson, Vice President of Development Operations. Between the significantly better process control made possible by the systems-driven product development methodology and the higher productivity resulting from integration, SpaceX has experienced a 50 percent productivity improvement. By having a fully digital managed development environment built on a systems-driven product development approach, SpaceX s Falcon 1 rocket has moved from development into production and launch, while its Falcon 9 rocket and Dragon capsule are in development, with qualification testing well under way ( Siemens case study: SpaceX, 2013). To quote Chris Thompson, Vice President of Development Operations: Automotive Infiniti Red Bull Racing We now have total team collaboration and it s a huge advantage. Infiniti Red Bull Racing is an Austrian Formula One racing team that is based out of England. The team was formed in 2004 when Dietrich Mateschitz bought the Jaguar Racing Formula One team from Ford, and renamed it to Red Bull Racing (I. R. B. R. Editors, 2015). The team was launched in 2005 and since then the number of designers and design changes has significantly increased each year. It is essential to ensure that up-to-date information flows from design through to simulation, manufacturing, inspection test, and finally onto the car, which is possible by ensuring there is good management of the engineering process. Throughout the process the full car is viewable to everyone on the team, from the factory right through to the track. At the track, the visualization capabilities of the database enables updates to be readily seen and understood which can be used to aid assembly and problem solving. This system allows workers to suggest enhancements back to the factory. In addition to this, by applying a systems-driven product development approach, it ensures that all data is tracked, 1 Note: All case studies are derived from cases and research data provided by Siemens PLM Software Inc.

7 which is used to share the information with the corporate enterprise resource planning (ERP) system which ensures that the right materials and tools are available for the latest parts. By using this shared information and streamlining the processes it has removed non value-added activities, reduced errors, and optimized quality ( Siemens case study: Infiniti red bull racing, 2014). To quote Alan Peasland, Head of Technical Partnerships: To develop the complex product that is a Formula One Racing Car in approximately a five-month period requires intense activity and an extremely robust and efficient PLM infrastructure, coupled with world-class talent and highly developed business processes. Volkswagen Group (South Africa) Volkswagen Group South Africa was established in 1946, and are a wholly owned subsidiary of Volkswagen Aktiengessellschaft (VWAG) in Germany. VW SA is the largest German investment in South Africa and is a major contributor to foreign direct investment, skills development, and technology transfer. VW SA is based about 35km outside of Port Elizabeth (V. G. (South A. Editors, 2015). The systems-driven product development approach comes into play when changes need to be made to a car, by allowing the development process to happen rapidly and ensuring that everyone involved knows what to do and when, and that they have all necessary information. A managed data repository environment is used by the rally team when designing, to manage all information that is related to the vehicle, including CAD data, drawings, analysis results, bill of materials, and so on. The team s system design engineer, Heinrich Erasmus, explains that at any given time they are running 5 to 8 projects simultaneously, making up thousands of drawings. He goes on further to say that a PLM platform makes the process of searching for drawings a lot simpler, and it simplifies the jobs of the designers by giving them more time to spend on new designs, rather than spending time managing which parts are where and having to manage a bill of materials. VW Group South Africa Motor Division uses a systems-driven product development approach and a PLM platform too allow them control of access to vehicle information so that multiple people can work simultaneously on the same change. Johan Smit, Lead Design Engineer, explains that the PLM platform is particularly helpful for a situation where they have two designers working on the same vehicle assembly structure as it allows them to make changes without corrupting any files. In addition to design engineers, manufacturing engineers also benefit from using a PLM platform as it enables them to be confident that they are working with up-to-date CAD data. According to Johan Smit, manufacturing engineers can open up a repository system, go into the latest revision for manufacturing, and have confidence that he can actually manufacture it. The PLM framework and systems-driven product development approach used by the team also allows its suppliers and sponsors to be included in the process. Johan Smit notes that the PLM platform is extremely important in keeping everyone in the loop. The race team believes that the systems-driven product development approach provides them something that is more important to winning, and even more important than money, it gives them time. Mike Rowe, the Motorsport Manager at VW Group South Africa Motorsport division, explains that the most important aspect of motor racing is that all the money in the world cannot buy you time. By using a PLM platform and systems-driven product development approach, the team gains efficiency, giving them extra time to make sure that any changes are correct the first time, which is a big factor contributing to their outstanding success ( Siemens case study: Volkswagen group south africa, 2013).

8 Conclusion Are the traditional methods of managing the ever-increasing complexity associated with product lifecycle management efficient, or is there a better way of doing it? The simple answer is no, traditional methods of managing a products life cycle is no longer efficient, however, there is a solution: systems-driven product development / systems engineering. Systems engineering is necessary for complex, modern products, by using traditional and emerging technologies to achieve a complex engineered system (CES). With this in mind, PLM can greatly benefit from systems engineering as a standard practice. By looking at the case studies it is evident how beneficial it is using the systems-driven product development approach, as it assists with collaboration, removing non value-added activities, reducing errors, optimizing quality, and so on.

9 References Bahill, a T., & Dean, F. F. (2009). What Is Systems Engineering? A Consensus of Senior Systems Engineers Facilitated by. Systems Engineering, Baxter, G., & Sommerville, I. (2011). Socio-technical systems: From design methods to systems engineering. Interacting with Computers, 23(1), Blome, C., Schoenherr, T., & Eckstein, D. (2014). The impact of knowledge transfer and complexity on supply chain flexibility: A knowledge-based view. International Journal of Production Economics, 147(PART B), Calvano, C. N., & John, P. (2004). Systems engineering in an age of complexity. Systems Engineering, 7(1), Editors, I. R. B. R. (2015). Infiniti Red Bull Racing Website. Retrieved from Editors, S. (2015). SpaceX Website. Retrieved from Editors, V. G. (South A. (2015). Volkswagen Group (South Africa). Retrieved from Fischi, J., & Nichiani, R. (2015). Complexity Based Risk Evaluation in Engineered Systems. Procedia Computer Science, 44, Friar, J. (1995). Competitive advantage through product performance innovation in a competitive market. Journal of Product Innovation Management, 12(1), Hobday, M. (1998). Product complexity innovation and industrial organisation. INCOSE Editors. (2015). INCOSE. Siemens case study: Infiniti red bull racing. (2014). Siemens PLM Software Inc. Siemens case study: SpaceX. (2013). Siemens PLM Software Inc. Siemens case study: Volkswagen group south africa. (2013). Siemens PLM Software Inc. Siemens PLM Editors. (2011). Systems-driven product development. Siemens PLM Software Inc. Siemens PLM Editors. (2015a). Siemens PLM Website. Siemens PLM Editors. (2015b). Systems-driven product development: Mastering complexity for greater innovation and less risk. Siemens PLM Software Inc. Stark, J. (2007). Product lifecycle management. Decision Engineering. Systems and software engineering - System life cycle processes. (2015). International Organization for Standardization, International Electrotechnical Commission, Institute of Electrical and Electronics Engineers.

10 Thomas, D. R. (2006). A general inductive approach for analyzing qualitative evaluation data. American Journal of Evaluation, 27(2),