Article
Refine
Year of publication
- 2024 (39)
- 2023 (77)
- 2022 (91)
- 2021 (109)
- 2020 (132)
- 2019 (120)
- 2018 (125)
- 2017 (108)
- 2016 (116)
- 2015 (126)
- 2014 (142)
- 2013 (139)
- 2012 (130)
- 2011 (182)
- 2010 (178)
- 2009 (199)
- 2008 (180)
- 2007 (176)
- 2006 (180)
- 2005 (188)
- 2004 (214)
- 2003 (154)
- 2002 (167)
- 2001 (157)
- 2000 (173)
- 1999 (153)
- 1998 (165)
- 1997 (154)
- 1996 (140)
- 1995 (147)
- 1994 (135)
- 1993 (107)
- 1992 (102)
- 1991 (74)
- 1990 (82)
- 1989 (79)
- 1988 (80)
- 1987 (77)
- 1986 (65)
- 1985 (59)
- 1984 (56)
- 1983 (47)
- 1982 (38)
- 1981 (39)
- 1980 (50)
- 1979 (43)
- 1978 (41)
- 1977 (22)
- 1976 (25)
- 1975 (18)
- 1974 (13)
- 1973 (6)
- 1972 (15)
- 1971 (7)
- 1970 (2)
- 1968 (2)
- 1967 (1)
Institute
- Fachbereich Medizintechnik und Technomathematik (1593)
- Fachbereich Wirtschaftswissenschaften (705)
- Fachbereich Elektrotechnik und Informationstechnik (638)
- Fachbereich Energietechnik (609)
- Fachbereich Chemie und Biotechnologie (602)
- INB - Institut für Nano- und Biotechnologien (542)
- Fachbereich Maschinenbau und Mechatronik (484)
- IfB - Institut für Bioengineering (451)
- Fachbereich Luft- und Raumfahrttechnik (380)
- Fachbereich Bauingenieurwesen (333)
Language
Document Type
- Article (5646) (remove)
Keywords
- Einspielen <Werkstoff> (7)
- Multimediamarkt (6)
- Rapid prototyping (5)
- avalanche (5)
- Earthquake (4)
- FEM (4)
- Finite-Elemente-Methode (4)
- LAPS (4)
- Rapid Prototyping (4)
- biosensors (4)
The fourth industrial revolution introduces disruptive technologies to production environments. One of these technologies are multi-agent systems (MASs), where agents virtualize machines. However, the agent's actual performances in production environments can hardly be estimated as most research has been focusing on isolated projects and specific scenarios. We address this gap by implementing a highly connected and configurable reference model with quantifiable key performance indicators (KPIs) for production scheduling and routing in single-piece workflows. Furthermore, we propose an algorithm to optimize the search of extrema in highly connected distributed systems. The benefits, limits, and drawbacks of MASs and their performances are evaluated extensively by event-based simulations against the introduced model, which acts as a benchmark. Even though the performance of the proposed MAS is, on average, slightly lower than the reference system, the increased flexibility allows it to find new solutions and deliver improved factory-planning outcomes. Our MAS shows an emerging behavior by using flexible production techniques to correct errors and compensate for bottlenecks. This increased flexibility offers substantial improvement potential. The general model in this paper allows the transfer of the results to estimate real systems or other models.
The treatment method to deactivate viable microorganisms from objects or products is termed sterilization. There are multiple forms of sterilization, each intended to be applied for a specific target, which depends on—but not limited to—the thermal, physical, and chemical stability of that target. Herein, an overview on the currently used sterilization processes in the global market is provided. Different sterilization techniques are grouped under a category that describes the method of treatment: radiation (gamma, electron beam, X-ray, and ultraviolet), thermal (dry and moist heat), and chemical (ethylene oxide, ozone, chlorine dioxide, and hydrogen peroxide). For each sterilization process, the typical process parameters as defined by regulations and the mode of antimicrobial activity are summarized. Finally, the recommended microorganisms that are used as biological indicators to validate sterilization processes in accordance with the rules that are established by various regulatory agencies are summarized.