Development of a Methodology for the Digital Representation of Manufacturing Technology Capabilities

The demand for efficient and digital systems for supporting the decision making during the design of a product is a key issue in manufacturing companies. Decisions made during the development and design of a product have a strong impact on the costs and delivery times of a product. Hence, a digital system which supports the engineer during and after the development process with information about the manufacturability of the product can reduce the production costs and times. In order to be able to evaluate the manufacturing capabilities at manufacturing process and machine level, there is a need to represent them in a digital way.Digital knowledge bases like taxonomies and ontologies provide the possibility for a representation of manufacturing resources. The state of the art shows different approaches for the use of ontologies in the domain of subtractive manufacturing processes as well as additive manufacturing (AM) processes. The goalof this work is the semantical representation of manufacturing technology capabilities with focus on AM-machines and processes. In this paper we introduce taxonomies of Manufacturing Features and Manufacturing Restrictions which were developed in accordance with current standards. To enrich the taxonomies with information, it was enhanced by relations between different manufacturing related entitiesin a knowledge graph. If manufacturing processes and machines can be digitally mapped, described and linked to the geometric information of a product together with information on the current performance of the company/network, bottlenecks and delivery delays during the manufacturing of parts can be avoided

Development of a Methodology for the Digital Representation of Manufacturing Technology Capabilities

The demand for efficient and digital systems for supporting the decision making during the design of a product is a key issue in manufacturing companies. Decisions made during the development and design of a product have a strong impact on the costs and delivery times of a product. Hence, a digital system which supports the engineer during and after the development process with information about the manufacturability of the product can reduce the production costs and times. In order to be able to evaluate the manufacturing capabilities at manufacturing process and machine level, there is a need to represent them in a digital way. Digital knowledge bases like taxonomies and ontologies provide the possibility for a representation of manufacturing resources. The state of the art shows different approaches for the use of ontologies in the domain of subtractive manufacturing processes as well as additive manufacturing (AM) processes. The goal of this work is the semantical representation of manufacturing technology capabilities with focus on AMmachines and processes. In this paper we introduce taxonomies of Manufacturing Features and Manufacturing Restrictions which were developed in accordance with current standards. To enrich the taxonomies with information, it was enhanced by relations between different manufacturing related entities in a knowledge graph. If manufacturing processes and machines can be digitally mapped, described and linked to the geometric information of a product together with information on the current performance of the company/network, bottlenecks and delivery delays during the manufacturing of parts can be avoided

Ice-nucleating particle concentrations of the past: insights from a 600-year-old Greenland ice core

Ice-nucleating particles (INPs) affect the microphysics in cloud and precipitation processes. Hence, they modulate the radiative properties of clouds. However, atmospheric INP concentrations of the past are basically unknown. Here, we present INP measurements from an ice core in Greenland, which dates back to the year 1370. In total 135 samples were analyzed with the FRIDGE droplet freezing assay in the temperature range from −14 to −35 ∘C. The sampling frequency was set to 1 in 10 years from 1370 to 1960. From 1960 to 1990 the frequency was increased to one sample per year. Additionally, a few special events were probed, including volcanic episodes. The typical time coverage of a sample was on the order of a few months. Historical atmospheric INP concentrations were estimated with a conversion factor, which depends on the snow accumulation rate of the ice core, particle dry deposition velocity, and wet scavenging ratio. Typical atmospheric INP concentrations were on the order of 0.1 L−1 at −25 ∘C. The INP variability was found to be about 1–2 orders of magnitude. Yet, the short-term variability from samples over a seasonal cycle was considerably lower. INP concentrations were significantly correlated to some chemical tracers derived from continuous-flow analysis (CFA) and ion chromatography (IC) over a broad range of nucleation temperatures. The highest correlation coefficients were found for the particle concentration (spherical diameter dp > 1.2 µm). The correlation is higher for a time period of seasonal samples, where INP concentrations follow a clear annual pattern, highlighting the importance of the annual dust input in Greenland from East Asian deserts during spring. Scanning electron microscopy (SEM) analysis of selected samples found mineral dust to be the dominant particle fraction, verifying their significance as INPs. Overall, the concentrations compare reasonably well to present-day INP concentrations, albeit they are on the lower side. However, we found that the INP concentration at medium supercooled temperatures differed before and after 1960. Average INP concentrations at −23, −24, −25, −26, and −28 ∘C were significantly higher (and more variable) in the modern-day period, which could indicate a potential anthropogenic impact, e.g., from land-use change

Ice nucleating particle concentrations by droplet freezing assay measurements from the B17 ice core, Greenland, dating from 1370 to 1990

The data set reports on measurements of ice nucleating particles (INPs) from an ice core in Greenland (B17, 72.25, -37.25, 2820 m AMSL) that dates back to about 1370. INP measurements were performed using the FRIDGE INP counter as a droplet freezing assay for N = 135 meltwater samples from the core. From each sample 3 x 65 droplets of melt water (2.5 µL) were pipetted onto a sample substrate. The experimental nucleation temperature T was decreased at 1 °C/min until every droplet was frozen. The frozen fraction (FF) as a function of T is used to calculate the INP abundance per mL of melt water. A conversion factor is used to estimate atmospheric INP concentrations. The typical time coverage of a sampe is in the order of a couple of months. Samples were selected in regular time intervals of 10 years, plus a number of additional samples. This data supplement is related to a scientific publication (doi:10.5194/acp-2020-556)