Uptime Engineering GmbH
Schönaugasse 7/2
8010 Graz, Austria
Tel: +43 (0)316 711 921




  • Dealing with complex systems and products in an highly competitive market environment demands state of the art product validation.
  • The quality of the durability development programme is one of the key factors for a successful product. System reliability and customer satisfaction are directly linked to the ability of the test programme to detect failure modes.
  • Uptime Engineering has a strong background in the field of automotive engineering. Our engineers have successfully carried out reliability related projects for a variety of technologies in the field of transportation, including
    • Rail applications
    • Passenger cars
    • Heavy duty
    • Agricultural applications


  • Complex systems: system complexity driven by customer and legal requirements is increasing with each evolution step. Conventional test programmes are replaced by statistically optimized programmes that can cover the wide range of potential failure modes.
  • Shortened development times: as well as the design and prototyping phase the time for product validation is decreasing drastically. Amongst other actions a focus on component testing typically allows a high system maturity level to be achieved in an early stage of development.
  • Optimisation of validation activities: complex test programmes must be optimised in terms of timing, duration and cost. A strong but complex relationship exists between expenditure in validation activities and field reliability. The definition of the required level of investment, the required activities and the division of responsibility between OEM and suppliers are all examples of difficult decisions that must be met.
  • Parts commonality: an important element is the assessment of co-validation, i.e. the transfer of validation results from a tested configuration to another variant. Transfer of test results is justified only for parts that are equal with respect to the failure modes under consideration. Therefore the careful tracking of parts-equivalence is required for this approach.
  • Field failures: the success and profitability of new products depends strongly on achieving high levels of availability and reliability in the field. Series failures in the hands of customers can be extremely expensive to correct and quickly lead to reduced customer confidence. Given the complexity of the technical system and the large number of failure modes that may occur, spotting problems and reacting as early as possible can only be managed with state of the art statistical methods.


  • Systematic approach: Uptime Engineering applies a clearly defined approach to optimised product validation and field monitoring. The core of the approach is an intelligent workflow and state of the art statistical and physics-based algorithms.
  • Usage space analysis: different applications, customers, environmental influences are investigated with respect to load parameters. This leads to a clear picture of the load on the system and its components.
  • Test design: two main types of tests are common. Highly accelerated tests are focused on one or a small number of failure modes. On the other hand tests covering a high number of failure modes are hardly accelerating and represent typical customer usage. Damage physics-based analysis is the basis for test design and the quantitative evaluation of test efficiency.
  • Test programme optimisation: if multiple tests are merged to a test programme the contributions of each test to the component reliability have to be accumulated. The software module Uptime LOCATE will additionally optimise the test programme with respect to time boundaries, test cost and test facility availability.
  • Failure Investigation, Root Cause Analysis RCA: Uptime Engineering offers systematic failure investigation and RCA as a service. We have a detailed understanding of failure mechanisms and material science and have partners for detailed laboratory analysis. The resulting knowledge is fed back to design and manufacturing or may be used to validate diagnosis and prediction systems.