Opportunities for organoids as new models of aging.

The biology of aging is challenging to study, particularly in humans. As a result, model organisms are used to approximate the physiological context of aging in humans. However, the best model organisms remain expensive and time-consuming to use. More importantly, they may not reflect directly on the process of aging in people. Human cell culture provides an alternative, but many functional signs of aging occur at the level of tissues rather than cells and are therefore not readily apparent in traditional cell culture models. Organoids have the potential to effectively balance between the strengths and weaknesses of traditional models of aging. They have sufficient complexity to capture relevant signs of aging at the molecular, cellular, and tissue levels, while presenting an experimentally tractable alternative to animal studies. Organoid systems have been developed to model many human tissues and diseases. Here we provide a perspective on the potential for organoids to serve as models for aging and describe how current organoid techniques could be applied to aging research

Intelligent production systems in the era of Industrie 4.0 – changing mindsets and business models

Industrie 4.0 has been becoming one of the most challenging topic areas in industrial production engineering within the last decade. The increasing and comprehensive digitization of industrial production processes allows the introduction of innovative data-driven business models using cyber-physical systems (CPS) and Internet of Things (IoT). Efficient and flexible manufacturing of goods assumes that all involved production systems are capable of fulfilling all necessary machining operations in the desired quality. To ensure this, production systems must be able to communicate and interact with machines and humans in a distributed environment, to monitor the wear condition of functionally relevant components, and to self-adapt their behaviour to a given situation. This article gives an overview about the historical development of intelligent production systems in the context of value-adding business models. The focus is on condition monitoring and predictive maintenance in an availability oriented business model. Technical as well as organizational prerequisites for an implementation in the production industry are critically analysed and discussed on the basis of best practice examples. The paper concludes with a summary and an outlook on future research topics that should be addressed

Intelligent production systems in the era of industrie 4.0 - changing mindsets and business models

Industrie 4.0 has been becoming one of the most challenging topic areas in industrial production engineering within the last decade. The increasing and comprehensive digitization of industrial production processes allows the introduction of innovative data-driven business models using cyber-physical systems (CPS) and Internet of Things (IoT). Efficient and flexible manufacturing of goods assumes that all involved production systems are capable of fulfilling all necessary machining operations in the desired quality. To ensure this, production systems must be able to communicate and interact with machines and humans in a distributed environment, to monitor the wear condition of functionally relevant components, and to self-adapt their behaviour to a given situation. This article gives an overview about the historical development of intelligent production systems in the context of value-adding business models. The focus is on condition monitoring and predictive maintenance in an availability oriented business model. Technical as well as organizational prerequisites for an implementation in the production industry are critically analysed and discussed on the basis of best practice examples. The paper concludes with a summary and an outlook on future research topics that should be addressed

Monitoring of slowly progressing deterioration of computer numerical control machine axes

The feed axes of computer numerical control (CNC) grinding machine tools are among the most mechanically stressed components of machine tools owing to the high process forces and rough manufacturing environment which they encounter. The resulting wear and tear depends strongly on the product range and the manner of machine operation. To counteract a functional deficiency of these central machine units, the current usual approach is preventive maintenance. The manual inspection of feed axes is complex and time consuming. A complicating matter is that the deterioration normally progresses very slowly and depends on the position of the stress along the axis. Existing approaches to automated estimation of the 'health status' of feed axes do not take this factor into account. This paper presents a procedure that addresses this gap. During simple test routines, the drive current, axis position, and feed rate are recorded. With the help of additional machine data, characteristic values are computed directly at the computer of the human-machine interface (HMI). The results are then transferred to and stored on a database server at the machine manufacturer. This approach enables the service technician to trace the progression of the axes' 'health status' over a long time. This approach makes it possible to detect trends in the characteristic values at an early point in time. This leads to a better planning of necessary maintenance actions adapted to the remaining lifetime of the wearing component

Verfügbarkeits-Monitoring: Schaffung innovativer Dienstleistungen durch Life-Cycle Monitoring von Maschinen

Um ein hohes Maß an Produktivität zu erzielen, muss die Funktionstüchtigkeit der eingesetzten Produktionsmittel sichergestellt sein. Laut einer Branchenumfrage wird die Bedeutung der Zuverlässigkeit von Werkzeugmaschinen noch vor deren Genauigkeit genannt. Häufige Ursachen für eine technisch bedingte eingeschränkte Verfügbarkeit von Maschinen und Anlagen sind neben der Fehlbedienung durch den Nutzer verschleißbedingte Ausfälle mechanisch belasteter Maschinenkomponenten. Um wartungsbedingte Stillstände so gering wie möglich zu halten, wird die zustandsorientierte Instandhaltung empfohlen. Die größte Herausforderung bei der Umsetzung dieser Strategie besteht in der automatisierten Bestimmung des tatsächlichen Zustands funktionsrelevanter Verschleißteile. Da der Verschleißverlauf maßgeblich von der Art des Betreibens und damit von der Belastungshistorie der Maschine abhängt, bietet es sich an, neben zyklischen Tests auch entsprechende Life-Cycle-Daten in die Zustandsbewertung und -prognose mit einfließen zu lassen. Dieser Fachbeitrag zeigt einen Lösungsansatz zur automatisierten Dokumentation des Maschinen-Life-Cycles mit integrierter Zustandsanalyse von Vorschubachsen. Für die Umsetzung werden ausschließlich steuerungsinterne Signale und Meldungen verwendet, die bei offenen CNC-Architekturen per OPC erfassbar sind. Als gemeinsame Kommunikationsschnittstelle dient XML, ein universelles Datenaustauschformat, das für Menschen und Programme gleichermaßen lesbar ist. Das verwendete Konzept der verteilten Systemarchitektur erlaubt die zentrale Datenhaltung und Auswertung großer Datenmengen beim Maschinenhersteller. Um Veränderungen der Zustände an Vorschubachsen zu ermitteln, werden auto matisiert Testläufe gefahren und verschleißbezogene Kennwerte generiert. Die lokal an der Maschine stattfindende Grenzüberwachung dieser Kennwerte meldet gravierende Zustandsveränderungen direkt, während Trends in den gesammelten Daten beim Hersteller analysiert werden. Gemeinsam mit den Informationen zum Life-Cycle der Maschine wird somit eine Basis geschaffen, die den technischen Service des Maschinenherstellers unterstützt und ihm ein erweitertes Dienstleistungsangebot ermöglicht