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Motivation - Ambiguous product targets, a global market, innovation pressure, changing process requirements and limited resources describe the situation for engineering management in the most R&D organizations. Achieving complex objective with limited resources is a question of performance. Performance in engineering departments is highly correlated to the existing capability of the engineering staff. When the reduction of engineering effort in development projects becomes additional goal for the management, an increase of engineering productivity is required. International engineering sites are established globally to push the capacity limits and to increase the productivity by the accessing big employment markets of engineering talents. By solving the conflict of limited resources and complex engineering goals, a need organizational challenge occurs - global co-engineering.

Achieving functional safety in mechatronic systems with growing product functionality is a major challenge in systems engineering. Following the current discussion, this challenge is mostly allocated to electronics and software development. For most of the scenarios this focus is feasible. Product design - the construction of the product - defines the properties and the appearance of the product by shape, material and assembly. So, the product design is often not under control of the safety management system. A hazardous deviation of part shape can be easily identified after the parts product or at least at its mounting. A wrong assembly is controlled by assembly documentation or data (e.g. screw torques) and identified at end of assembly line checks. The identification of a hazardous material choice depends on the product material class. Product materials can be separated into two classes: passive or active materials.

Computer vision (CV) represents the idea of giving machines the capacity to make meaning out of images frames, and for decades it consisted mostly of laborious and complex techniques that provided poor performance. With the advent of Deep Convolutional Neural Networks (DCNN), CV systems reached levels of accuracy to become industry-relevant. A major challenge, however, resides in deploying real-time CV systems in environments (such as driverless cars) that impose a series of constraints in terms of energy supply, weight and space. This technical paper describes how a real-time embedded image recognition system was developed and how the design guidelines were specified in terms of functionality and performance. A minimum rate of 30 frames per second (fps) was identified as a real-time boundary. Alongside the decision for a DCNN topology, system architecture and software technology, the Nvidia’s Jetson TX2 embedded computer was chosen as the evaluation board.

Functional Safety engineering aligned to an international standard is already a long-lasting discussion. Nevertheless, the requirements of process conformance to assure functional safety have been detailed in description and interpretation. The ISO 26262 is seen as state-of-the-art Functional Safety engineering basement in Europe, the closer interpretation of the IEC 61508 is claimed by assessors in America and Asia. This work shows how stagnation in engineering process improvement is solved by re-engineering projects. The benefits of re-engineering are described in this context. A four month, proven-in-practice project plan is explained. The expected results of such a project are given as generic goals for similar projects. A practice report shows the realistic outcome of such a project for the Chinese automotive industry. The report shows how the motivation of the involved engineers was gained and how existing engineering documentation was used in an efficient way.

There have been many publications about requirements management, and still organizations are struggling to show 100% coverage and traceability in a lean way. It does not start with CMMI nor SPICE. It does not end with tools like DOORs, Polarion, Codebeamer or JAMA. It does depend on the right setup and how it feels in the everyday life of an engineer. This paper defines and explains what it takes to establish leading edge requirements engineering for the automotive industry. It describes how work day integration of requirements engineering and management can be achieved. The different roles in engineering are addressed with their unique needs to support them. One 120% RQM data model is shown and explained. The necessary rollout project is designed with activities to adapt a tool to existing processes and individual tools, explain, improve, transfer as well as train/coach the engineers.