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Digital quality infrastructure Exploiting the potential of new technologies for more efficient quality assurance

Even in an increasingly digitised world, the hallmarks of an effective quality infrastructure are safety, reliability and quality of products and services. In a network made up of business, academic and civil society stakeholders, the “Digital quality infrastructure” initiative (QI-Digital) develops solutions for modern and efficient quality assurance.

Accreditation as a key component of our quality infrastructure

The accreditations issued by DAkkS help to improve the quality and safety of products, processes and services and to simplify trade in Europe and around the world. This makes DAkkS in its role as the national accreditation body a key stakeholder in Germany’s quality infrastructure. The quality infrastructure also includes standardisation, conformity assessment, market surveillance and metrology.

This system of quality and safety is evolving continuously as a result of digitisation processes and the advent of artificial intelligence. To meet the challenges this entails and to take advantage of the opportunities offered by this development, DAkkS has joined forces with the other stakeholders in the German quality infrastructure in the “Digital quality infrastructure” initiative (QI-Digital).

Go to the “Quality infrastructure” website

Digitisation in conformity assessment and accreditation

Digital processes are increasingly used in virtually all sectors of the economy. For some of these processes, the tools and methods of evaluation within conformity assessment and accreditation need to be reviewed in terms of their accuracy of fit, and adapted or newly developed where necessary.

Current examples of digital processes can already be found in pathology, whose institutes in Germany are accredited as inspection bodies in accordance with the ISO/IEC 17020 standard. This is an area where methods of image analysis supported by artificial intelligence (AI) are increasingly used. With AI-based diagnostics, some of the work previously the preserve of highly qualified people is being delegated to digital processes. In terms of accreditation, this means that it is necessary to clarify whether and to what extent these AI applications can be trusted.

The increasing functional dependency of products on software also serves as an example of new challenges arising in the area of conformity assessment. For example, is a car after a software update still as safe as had been previously determined by an accredited technical service as part of the type approval process?

In light of these developments, DAkkS with its accreditations must in future continue to ensure that the statements of conformity made by the conformity assessment bodies it monitors are based on reproducible scientific foundations and warrant a reasonable level of confidence in their veracity.

The “Digital quality infrastructure” initiative

In a range of activities undertaken collectively, QI-Digital’s collaborators address the challenges posed to the proven system of quality infrastructure by the advent of new, complex digital products and processes. At the same time, the opportunities offered by the digital transformation as a result of networked and interoperable solutions are identified and exploited to ensure continued trust in products and services in the future. The “QI-Digital” initiative is supported by:

  • The Federal Institute for Materials Research and Testing (BAM)
  • Deutsche Akkreditierungsstelle GmbH (DAkkS)
  • The German Institute for Standardization (DIN)
  • The German Commission for Electrical, Electronic & Information Technologies in DIN and VDE (DKE)
  • The National Metrology Institute of Germany (PTB)

QI-Digital innovation ecosystem

The constitution of a comprehensive QI-Digital innovation ecosystem serves as the basis for the development and establishment of practical solutions in connection with new technologies and innovations. Specific areas of action can be used to define problems systematically, find practical solutions and identify areas where further research is needed. The system is therefore built on three pillars:

  • Realistic test environments: Case studies are used to develop practical solutions to hitherto unsolved problems. Solution development is based on freely accessible cooperation platforms, for example in the form of competence centres or living labs, which form the basis for technical testing and provide the physical infrastructure required to carry it out.
  • Transfer measures: By refining the activities and results in the test environments, a comprehensive application of the developed solutions by the QI landscape and the business community should be possible. The results should also serve to develop the market framework (legislation, standards, testing, measuring, certification procedures). In an effort to achieve this, measures such as network development and maintenance, as well as educational and advisory services, are being promoted.
  • Research and development: From the test environments and networks, there arises a need for further research work and QI-Digital innovations in the market, which little by little supplement the developments in the test environments. The services required for this are supplemented by external projects.

Case studies

Implementation of the QI-Digital innovation ecosystem starts with three defined initial case studies.

1. Artificial intelligence in medical technology (medical data hub)

Artificial intelligence (AI) in medical engineering stands for new medical devices with a high proportion of software that require new approaches to certification, risk assessment and clinical testing. The software is either part of a medical device or is considered a medical device in its own right and must undergo a strictly regulated conformity assessment (EU Medical Devices Regulation). Given that there is already a lack of notified bodies with sufficient expertise, considerable difficulties with approvals (CE certification) of innovative medical devices are to be expected.

To ensure uniform assessment and safe new products, objective assessment methods for the quality of AI algorithms, procedures for the provision of reference data with medical experts, and norms and standards for quantifiable and testable criteria for data quality will need to be developed, while also taking account of quality assurance requirements for the conformity assessment procedures for these products and for the bodies themselves. These developments should be concentrated on a digital quality platform and it should be possible to validate them using AI-based solutions, for example for the detection of breast cancer. This can increase the level of trust in AI methods and speed up the transfer of AI research to the market.

2. Additive manufacturing / 3D printing (competence centre)

Additive manufacturing / 3D printing is an example of a new world of business and production. Products are digital to begin with and are produced in one-off production (batch size 1). This makes tailor-made and individual products possible. It is important to establish quality assurance integrated into the process that starts as early as the digital image.

Equally important are the development of non-destructive test methods, new digital methods for the assessment of process and measurement data, as well as standards and conformity assessment infrastructures for the digital testing, inspection and certification of companies, systems and processes. The steps constitute the prerequisite for the confirmation of the competence of this conformity assessment infrastructure through accreditation. The goal of establishing a competence centre as a testing and research environment for an additive process or production chain with technical systems from the market is to develop practical solutions and test them in real operation. The potential for efficiency gains compared to the previous quality-assured alternative of stocking spare parts is considered very high for German companies and is an enormous advantage in an Industry 4.0 world.

3. Hydrogen filling station (living lab)

The hydrogen filling station represents the overall system of a hydrogen infrastructure, for which there are special requirements in place in terms of safety and quality. Made possible by the use of digital technologies, the latest quality assurance procedures can help with the development and safe control of these stations.

When a hydrogen filling station is operated as a living lab, important roles are played in particular by the integration and networking of sensor technology, the processing of sensor data and the development of a digital twin for the monitoring of safety in use (predictive maintenance). The transformation of the complete QI system from the analogue to the digital world is being tested here. This can increase confidence in the new technologies in the market as a whole and the results can be adapted in all areas, particularly in terms of quality assurance during operation.

Further information

These case studies constitute the starting point for the “QI-Digital” initiative. Information on further case studies and on active participation is compiled on the initiative’s website.

Ihr Kontakt

Susanne Kuch, M.A.

Digitisation Policy in Quality Infrastructure | Staff Unit Accreditation Governance, Research and Innovation

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