Category: Automotive

Problem statement A leading OEM (Original Equipment Manufacturer) faced a persistent challenge of low JPH and high rework ratio in the vehicle production process, spanning the inbound stage to final inspection. JPH (Jobs Per Hour), is a metric commonly used in automotive production, to measure efficiency of a production line. The current JPH (Baseline) was […]

In today’s automotive industry, managing software system requirements is a significant challenge due to the growing complexity and critical nature of these systems. These requirements include functional requirements, such as autonomous driving, infotainment, and user interfaces, and nonfunctional requirements that establish the system’s operational criteria, such as performance, security, and reliability. A recent whitepaper states […]

Introduction This blog post will detail how adopting Virtual Engineering Workbench (VEW) has supported Schaeffler AG, an automotive supplier, within their software development for pre-series development projects. It will also explain the use cases implemented by AWS and Schaeffler, and present one of the many technical examples. This includes how Schaeffler was able to adopt […]

The move to software-defined vehicles (SDV) opens the door to shorten OEM vehicle design cycles by at least 6 months, enabling innovation for new tools and processes for automotive software development. To help stay competitive on a global scale, OEMs are adopting cloud-based development environments and cloud-native software design, supporting software portability across a growing […]

In the realm of autonomous vehicles and advanced driver assistance systems (AV/ADAS), automotive original equipment manufacturers (OEMs), Tier 1 suppliers, and independent software vendors (ISVs) all process vast amounts of data recorded by test vehicles in the field. That recorded data can reach up to 300 TB per vehicle per day. When the recorded data is […]

AWS re:Invent 2024 unveiled game-changing innovations powering the automotive future – autonomous driving breakthroughs, connected vehicle insights, generative AI assistants, sustainable supply chains, and legacy system modernization.

Background Autonomous driving and advanced driver assistance systems (ADASs) require the processing of large and complex workloads in near real time. These workloads typically include tasks such as object detection and classification, lane detection, sensor fusion, path planning, and decision-making. The data from various sensors needs to be processed rapidly to enable the vehicle to […]

Enterprises today are continuing to explore new solutions to increase efficiency, particularly around process automation. That efficiency is pertinent to multiple industries, but it is especially notable in the automotive sector. Automotive research and development (R&D) teams need to address costly, time-consuming, and error-prone processes, for example, in generating request for proposal (RFP) documents. The […]

The need to manage data and software products at scale has become essential with the rise of generative artificial intelligence (see AWS Executive Insights, 2024), the disruptive transformation from hardware- to software-defined vehicles (see Boston Consulting Group, 2021), and the shift to service-based business models (see McKinsey & Company, 2021). This blog post introduces the […]

As the world becomes increasingly more digital and connected, trucks, buses, vans, and specialized vehicles are evolving into sophisticated software-defined machines. This change has shifted priorities to reshape fleet operations, enhance driver experiences, and redefine the nature of commercial mobility. Compared to the passenger car industry, commercial vehicle Original Equipment Manufacturers (OEMs) need to deal […]