Validation techniques for Industry 4.0: needs and requirements
|Coordinator||RISE Research Institutes of Sweden AB - RISE - Viktoria, Göteborg|
|Funding from Vinnova||SEK 500 000|
|Project duration||March 2018 - December 2018|
|Venture||Electronics, software and communication - FFI|
|End-of-project report||2017-05508.pdf(pdf, 2163 kB) (In Swedish)|
Purpose and goal
FramTEST as a pre-study has been aimed to identify mechanisms that enable organizations within the automotive industry to embed novel techniques for software validation and verification based on AI, machine learning and increased automatization. Such techniques are viewed as key to enable the automotive industry to develop secure and safe vehicles that builds on the vision of autonomous transport.
Expected results and effects
The state-of-art review review generated a model with three socio-technical categories when building a data-driven validation culture. Through an explorative semi-structured interview phase the research model was partly-grounded in empirical data. This resulted in the addition of additional sub-factors, the identification of a potential core variable, as well as a base to develop propositions about the dependencies between the variables. The pre-study has created the basis for future research how data-driven validation can be embedded in the incumbent automotive industry.
Planned approach and implementation
The pre-study was performed during 2018 and included three phases. In the first phase, state-of-art, a meta-review was done on 23 projects funded by FFI and classified as validation and verification. In addition, a literature review of 73 papers was performed to elicit potential factors that affect the transformation of the validation process within an incumbent organization towards data-driven verification.