Open Access

Deep etched structures in GaAs with high aspect ratio have promising applications in optoelectronics and MEMS devices. The key factors in their fabrication process are the choosing of proper mask material and etching conditions which results in high selectivity and an anisotropic etch profile with smooth sidewalls. In this work, we studied several types of mask materials (Al, Ni, Cr, SiO2) for deep reactive ion etching of GaAs using inductively coupled plasma system. Thus, several sets of experiments were performed with varying gas mixture, pressure and ICP/RF power. As a result, we find optimized conditions and minimal thickness of mask material for achieving deep etched (>140 m) GaAs structures.

The properties of SiC and diamond make them attractive materials for MEMS and sensor devices. We innovated specific laser ablation techniques to fabricate membranes and cantilevers made of SiC or nano-(micro-) crystalline diamond films grown on Si/SiO2 substrates by microwave chemical vapour deposition (MWCVD). We started research to generate surface moulds to grow corrugated diamond films for membranes and cantilevers. A software tool was developed to support the design of micromechanical cantilevers. We can measure deformation and resonant frequency of diamond cantilevers and identify the global mechanical properties. A benchmark against finite element simulations enables an inverse identification of the specific system parameters and simplifies the characterization procedure.

Purpose: Although there is an apparent potential in using data for advanced services in manufacturing environments, SMEs are reluctant to share data with their ecosystem partners, which prevents them from leveraging this potential. Therefore, the purpose of this paper is to analyse the reasons behind these resistances. The argumentation paves the way for elaborating countermeasures that are adequate for the specific situation and the typical capabilities of SMEs. Design/Methodology/Approach: The analysis is based on literature research and in-depth interviews with management representatives of 15 companies in manufacturing service ecosystems. Half of these are manufacturers and the other half technology or service providers for manufacturers. They are SMEs or partly larger companies operating in structures that are typical for SMEs. Findings: Data sharing hurdles are investigated in the five dimensions, 1. quantifying the value of data, 2. willingness to share data and trust, 3. organizational culture and mindset, 4. legal aspects, and 5. security and privacy. The ability to quantify the value of data is a necessary but not sufficient precondition for data sharing, which must be enabled by adequate measures in the other four dimensions. Originality/Value: The findings of this empirical study and the solution approach provide an SME-specific framework to analyze hurdles that must be overcome for sharing data in an ecosystem. Manufacturing SMEs can apply the framework to overcome the hurdles by specific insights and solution approaches. Furthermore, the analysis illustrates the future research direction of the project towards a comprehensive solution approach for data sharing in a manufacturing ecosystem.

Smart services disrupt business models and have the potential to stimulate the circular economy transition of regions, enabling an environmentally friendly atmosphere for sustainable and innovation-driven growth of regions. Although smart services are powerful means for deploying circular economy goals in industrial practices, there is little systematic guidance on how the adoption of smart services could improve resource efficiency and stimulate smart regional innovation-driven growth, enabled through circular design. Implemented in the scope of Vorarlberg’s smart specialization strategy, this paper contributes to the literature on the circular economy and regional innovation-driven growth by assessing critical factors of the value creation and value capture implemented within the scope of the quadruple helix system. By identifying the main challenges and opportunities of collaborative value creation and value capture in setting-up smart circular economy strategies and by assessing the role of innovation actors within the quadruple helix innovation system, the study provides recommendations and set of guidelines for managers and public authorities in managing circular transition. Finally, based on the analysis of the role of actors in creating shared value and scaling-up smart circular economy practices in the quadruple helix innovation systems, the paper investigates the role of banks as enablers of circular economy innovation-driven regional growth and smart value creation.

Recent developments in the area of Natural Language Processing (NLP) increasingly allow for the extension of such techniques to hitherto unidentified areas of application. This paper deals with the application of state-of-the-art NLP techniques to the domain of Product Safety Risk Assessment (PSRA). PSRA is concerned with the quantification of the risks a user is exposed to during product use. The use case arises from an important process of maintaining due diligence towards the customers of the company OMICRON electronics GmbH. The paper proposes an approach to evaluate the consistency of human-made risk assessments that are proposed by potentially changing expert panels. Along the stages of this NLP-based approach, multiple insights into the PSRA process allow for an improved understanding of the related risk distribution within the product portfolio of the company. The findings aim at making the current process more transparent as well as at automating repetitive tasks. The results of this paper can be regarded as a first step to support domain experts in the risk assessment process.