Metrology in Micromanufacturing

The manufacturing industry progresses assiduously to fulfill societal challenges, promoting innovation and economic growth with sustainable solutions, more efficient use of energy, and advanced materials. Micromanufacturing can undoubtedly be considered in the larger category of advanced manufacturing, characterized by continuous development of knowledge, methods, and technologies, which require aligned support of metrology with novel implementations, traceability, and product quality assessments [1].

Advanced manufacturing has been identified by the European Commission (EC) as one of the six critical enabling technologies for innovation. Hence, metrology for advanced manufacturing is a research area of rising concern. This has recently been investigated in the context of a new European Metrology Network by analyzing research articles published in 2019–2020 concerning the metrology demands in advanced manufacturing. Among the overall needs identified by the analysis, new solutions for uncertainty assessment and quality assurance were a significant fraction [1].

Comparing with past trends [2], the focus in advanced manufacturing is currently on the assimilation in the industry of digital technologies (including artificial intelligence—intelligent manufacturing), the increase in energy efficiency, and the decrease in material waste while reducing
emissions (sustainable manufacturing). Thus, sustainable and intelligent manufacturing, in the policy of the EC, is expected to promote a “human-centric and resilient European industry,” integrating the existing Industry 4.0 for a transition into Industry 5.0 [3]. Based on such assumptions, competitive and cost-effective manufactured products require accurate measurements of a large extent of quantities in different production environments, which sometimes are even hostile environments. Thus, choosing appropriate measurement methods and techniques is also central to gathering the proper knowledge from the measurement process. This is a challenge for the existing measurement technologies. Considering the advances in freeform structuring of manufactured components’ surfaces and volumes [4–7], novel developments are already coming not only from enhanced product and material processing but also, and above all, from the possibilities offered by several additive manufacturing (AM) techniques with unlimited solutions for useable products and components at costs within reach
[8,9]. The quality assurance for AM processes is still limited to process control and material inspection, with parameters equivalent to manufacturing resolution (e.g., layer thickness, orientation, raster angle, raster width, air gap, etc.) and material properties. Therefore, the existing micro-manufacturing metrology approaches are expected to be reformed soon. For instance, X-ray computed tomography (XCT) has a vast potential to play a dominant role in micrometrology, allowing access to internal and external features. XCT subjects still require improvements; among those, there is traceability and the need for faster acquisitions. The need for enhancements is crucial; however, considering XCT developments in the last decades, it is improbable that such a trend will stop [10]. Another promising technology is the digital twin (DT) [11,12]. The concept refers to a virtual representation of a physical system constantly updated by the physical counterpart. Metrology can also rise to prominence in the DT implementation using characterized measured data and, in turn, use a DT to react to a physical system to change its state (e.g., in process control) [11].

From the viewpoint of this dynamic scenario, this chapter focuses on measurement methods rather than technologies to provide the reader with an essential perspective on crucial requirements in micro-/ nanometrology for manufacturing. Moreover, some methods and notions presented are not always entirely “micro/nano.” Nevertheless, there are postulates in manufacturing metrology that cannot be disregarded and may have limitations at lower scales, highlighted with examples whenever possible.