![\"\"](\"https:\/\/blogs.sw.siemens.com\/wp-content\/uploads\/sites\/24\/2020\/02\/Fig-2-Harness-Variants.jpg\")
Next, cost is a paramount concern in the intensely\ncompetitive automotive industry. Increasing demand for electric and electronic\nfeatures means that companies must keep larger inventories on hand, parts\nbecome obsolete driving re-design efforts, and miss-builds become more likely\nas automakers handle massive numbers of design variants. Design, marketing,\nmanufacturing, logistics and engineering groups must work in concert to meet\nmarket demands for features and performance while managing production cost.\nLeveraging data from all of these domains is critical to constraining these\ncosts.<\/p>\n\n\n\n
Vehicle recalls, however, may prove to be the most costly. A\nproblem discovered after the car is on the market is up to fifty-times more\nexpensive to fix than one that is identified in development. Large-scale\nrecalls are even more expensive because they cause damage to the manufacturer\u2019s\nbrand and reputation in addition to the financial cost of recalling cars.<\/p>\n\n\n\n
Finally, during E\/E systems development, engineers must\nconsider the impact of design changes in multiple domains. Changes in the\nrequirements for the vehicle platform and systems are the most obvious as they\ncan require all new connectivity schemes. Each change affects the rest of the\nsystem, and the unforeseen effects can be very difficult to predict. Migrating\nan ECU to a new location or network in the architecture may affect performance\nelsewhere in the system. This change in behavior may cascade, causing any\nnumber of sub-systems or functions to fail. Such a change can even completely\ninvalidate the technical implementation of the architecture, driving the\nre-design of multiple systems. <\/p>\n\n\n\n
Navigating\nthe Storm<\/strong><\/p>\n\n\n\n If a design process could address all three of these issues,\nwhat kind of capabilities would it need? This design flow would need to help\nengineers manage increasingly complicated electrical and electronic systems,\ncosts that result from this complexity, and more numerous design changes that\nhave wide-ranging effects. Generative design fulfills each of these\nrequirements. <\/p>\n\n\n\n Generative design uses automation to generate architectural proposals for the logic, software, hardware, and networks of the electrical and electronic systems of a vehicle (figure 2). This enables engineers to iterate on these proposals, optimizing for performance, reliability, and weight. Through generative design, teams can address the rising challenges of complexity, cost, and change management.<\/p>\n\n\n\n Employing automation throughout the design process will help\ndesign teams manage complexity without increasing time-to-market. Automation empowers\nengineers to focus on the most critical aspects of E\/E systems design and\nverification, and reduces the need for design changes by quickly generating\nproposals that engineers can evaluate and iterate on to reach optimal designs. <\/p>\n\n\n\n Teams must also be able to re-use validated data across\nvehicle platforms to improve quality and reduce development costs. Design\nre-use accelerates development cycles and reduces change orders by leveraging\nknown-good design data in a new vehicle platform. This prevents the design\nteams from spending time and resources manually re-designing vehicle systems\nthat may already exist. Generative design enables engineers to apply existing\ndata to new platforms effortlessly to maximize the benefits of re-use.<\/p>\n\n\n\n Generative design can enable automotive design teams to overcome the pressures of complexity, cost, and change management. Implementing such a flow, however, requires a tool set that supports advanced design automation, a holistic view of the project in a platform context, and seamless integration between design domains and upstream and downstream tools. Part two will explore how generative design can be achieved in electrical and electronic design, delivering engineers tooling to deal with complexity, cost, and change management.<\/p>\n\n\n\n![\"\"](\"https:\/\/blogs.sw.siemens.com\/wp-content\/uploads\/sites\/24\/2020\/02\/Fig-4-Generative-design-workflow-1024x576.png\")