IoT systems based on collaborative sensor networks are becoming increasingly common in various industries owing to the increased availability of low-cost sensors. The quality of the data provided by these sensors may be unknown. For these reasons, advanced data processing and sensor network self-calibration methods have become popular research topics. In terms of metrology, the self-calibration methods lack the traceability to the established measurement standards of National Metrology Institutes (NMIs) through an unbroken chain-link of calibration. This problem can be solved by the ongoing digitalization of the metrology infrastructure. We propose a conceptual solution based on Digital Calibration Certificates (DCCs), Digital SI (D-SI), and cryptographic digital identifiers, for validation of data quality and trustworthiness. The data that enable validation and traceability can be used to improve analytics, decision-making, and security in industrial applications. We discuss the applicability and benefits of our solutions in a selection of industrial use cases, where collaborative sensing has already been introduced. We present the remaining challenges in the digitization and standardization processes regarding digital metrology and the future work required to address them.

Internet of Things (IoT) device data enables diverse applications. However, the quality of data are non-standardized and difficult to quantify. While poor quality data may be usable, establishing error bounds supports IoT's use in critical applications. National Metrology Institutes (NMIs) have long tradition in making measurement data trustworthy, and they are now working to digitalize these practices. This paper forwards that agenda by presenting a Distributed Ledger Technology (DLT) based concept to leverage digital metrology for IoT data and devices. Digital Calibration Certificates (DCCs) offer a solution for describing, certifying, authenticating, and securing IoT data quality. With DCCs, measurement device (sensor) calibration information may be included as metadata alongside samples captured by a device. Metadata may include device identification, which serves as proof-of-origin for measurements and samples, and timing data, to ensure its “freshness.” DCCs enhance communicating the quality of captured information among devices, services, and applications, thereby supporting IoT's use in domains with strict error constraints. Our proposed concept securely validates DCC-based (meta)data traceability chain from NMIs and devices to data end-users with cryptographic measures, rendering IoT data trustworthy for critical applications.

The global quality infrastructure (QI) has been established and is maintained to ensure the safety of products and services for their users. One of the cornerstones of the QI is metrology, i.e., the science of measurement, as the quality management systems commonly rely on measurements for evaluating quality. For this reason, the calibration procedures and the management of the data related to them are of the utmost importance for the quality management in the process industry and given a high priority by the regulatory authorities. To overcome the relatively low level of digitalization in metrology, machine-interpretable data formats such as digital calibration certificates (DCC) are being developed. In this paper, we analyze the current calibration processes in the pharmaceutical industry, and the requirements defined for them in the relevant standards and regulations. For digitalizing the calibration-related data exchange, a multitenant cloud platform-based method is presented. To test and validate the approach, a proof of concept (POC) implementation of the platform is developed with a focus on ease and cost-efficiency of deployment and use while ensuring the preservation of traceability and data integrity. The POC is based on two industrial use cases involving organizations with different roles in the metrology infrastructure. In the testing, the presented approach proves to be an efficient method for organizing the calibration data exchange in industrial use.

Digitalization and the rapid development of IoT systems has posed challenges for metrology because it has been comparatively slow in adapting to the new demands. That is why the digital transformation of metrology has become a key research and development topic all over the world including the development of machine-readable formats for digital SI (D-SI) and digital calibration certificates (DCCs). In this paper, we present a method for using these digital formats for metrological data to enhance the trustworthiness of data and propose how to use digital signatures and distributed ledger technology (DLT) alongside DCCs and D-SI to ensure integrity, authenticity, and non-repudiation of measurement data and DCCs. The implementation of these technologies in industrial applications is demonstrated with a use case of data exchange in a smart overhead crane. The presented system was tested and validated in providing security against data tampering attacks.

Metrology has been a slowly digitalizing field in which a significant part of the handling of data has been dependent on paper-based processes. Due to the need for the improved efficiency and reliability of these processes, digitalization has become a major topic of interest in the metrology community. Data formats such as the digital calibration certificate (DCC) have an essential role as an enabler of further digitalization, acting as the harmonized data format for calibration data. Naturally, introducing these data formats into industrial usage sets new requirements with respect to the calibration management and associated systems. Diversity of metrology also means that the systems need to be flexible and scalable to fulfill the needs of actors in the global calibration infrastructure with very different requirements. This paper presents a conceptual approach for enhancing the communications between the existing systems in a calibration ecosystem and enabling DCC-based data exchange with third-party systems using the Beamex calibration ecosystem as an example. Thus, the presented system architecture concept that introduces data and DCC exchange services would provide a solution to enable the use of DCCs on Beamex systems.

Roll bent or pressed longitudinally welded tube rolls are commonly used as cable drums of large lifting systems. In the present study, a run-out measurement based system was developed for optimizing the roll alignment for turning and for calculating an estimation of the unbalance of the rolls after turning. The intended benefits of the system are the reduction of the manufacturing costs and the overall improvements in end product quality. In addition, the data gathered can be analysed to improve the preceding manufacturing processes. The accuracy of the alignment was analysed by measuring run-out profiles before turning and the wall thickness variation of the test specimens after turning. The accuracy of the estimated static balancing was verified with a balancing machine.