No abstract

Automation systems with applied robotics have already been established in industrial applications for many years. In the field of life sciences, a comparable high level of automation can be found in the areas of bioscreening and high-throughput screening. Strong deficits still exist in the development of flexible and universal fully automated systems in the field of analytical measurement. Reasons are the heterogeneous processes with complex structures, which include sample preparation and transport, analytical measurements using complex sensor systems, and suitable data analysis and evaluation. Furthermore, the use of nonstandard sample vessels with various shapes and volumes results in an increased complexity. The direct use of existing automation solutions from bioscreening applications is not possible. A flexible automation system for sample preparation, analysis, and data evaluation is presented in this article. It is applied for the determination of cholesterol in biliary endoprosthesis using gas chromatography-mass spectrometry (GC-MS). A dual-arm robot performs both transport and active manipulation tasks to ensure human-like operation. This general robotic concept also enables the use of manual laboratory devices and equipment and is thus suitable in areas with a high standardization grade.

The measurement of air quality parameters for indoor environments is of increasing importance to provide sufficient safety conditions for workers, especially in places including dangerous chemicals and materials such as laboratories, factories, and industrial locations. Indoor air quality index (IAQ-index) and total volatile organic Compounds (TVOC) are two important parameters to measure air impurities or air pollution. Both parameters are widely used in gases sensing applications. In this paper, the IAQ-index and TVOCs have been investigated to identify the best and most flexible solution for air quality threshold selection of hazardous/toxic gases detection and alarming systems. The TVOCs from the SGP30 gas sensor and the IAQ-index from the SGP40 gas sensor were tested with 12 different organic solvents. The two gas sensors are combined with an IoT-based microcontroller for data acquisition and data transfer to an IoT-cloud for further processing, storing, and monitoring purposes. Extensive tests of both sensors were carried out to determine the minimum detectable volume depending on the distance between the sensor node and the leakage source. The test scenarios included static tests in a classical chemical hood, as well as tests with a mobile robot in an automated sample preparation laboratory with different positions.