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Institute
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In diesem Beitrag werden die Ergebnisse aus einer Studie in der Papierindustrie vorgestellt. Dabei zeigt sich eine deutliche Korrelation zwischen guten Ergebnissen in der Effektivität und Effizienz des Zuverlässigkeitsmanagements und dem Unternehmenserfolg. Der Unternehmenserfolg – im Sinne einer hohen Umsatzrendite – kann zwar nicht allein auf einen entscheidenden Einflussfaktor zurückgeführt werden, da der Umsatz durch eine Vielzahl von Faktoren bestimmt wird. Die durchgeführten Analysen und Interviews innerhalb der Studie deuten allerdings darauf hin, dass in der Tat das operative Anlagenmanagement einen maßgeblichen Erfolgsfaktor darstellt, sich „Reliability“ in der Prozessindustrie folglich auszahlt. Überdies konnte gezeigt werden, wie sich Methoden und Verhaltensweisen von Instandhaltung und Produktion auf die Zuverlässigkeit von Anlagen und die Effizienz deren Bewirtschaftung auswirken.
In diesem Beitrag werden die aktuellen Aktivitäten im Forschungsprojekt „SiZu – Integration von Echtzeitsimulation und Zustandsüberwachung zur Bauteilprognose und Fehleranalyse für die Instandhaltung“ vorgestellt. Ziel des Projektes ist es, die bislang separat genutzten Funktionalitäten Condition-Monitoring und Echtzeitsimulationen in einem Analysewerkzeug (Condition- Analyser) für die Instandhaltung zusammenzuführen und damit Zustandsüberwachungssysteme um die Möglichkeit der Nutzung historischer Anlagendaten und Echtzeitsimulation zu erweitern. Neben der detaillierten Beschreibung der angestrebten Forschungsergebnisse und den daraus resultierenden Nutzungspotentialen für die Instandhaltung wird die zur Zielerreichung entwickelte Vorgehensweise vorgestellt und diskutiert.
The topics Internet of Things and Industry 4.0 increasingly lead to the fact that the customer is increasingly focused on manufacturing companies. He wants to know delivery date of the product, wants to make changes at short notice, get an individualized product and much more. Technologically, these requirements have already been met, but the structures within the company as well as the operational processes are not yet or only partially prepared to cope with the increasing complexity and dynamics of production. This leads to many deviations with which the production controller must deal, whether they are complex or trivial.
In order to counteract the increasing number and frequency of deviation situations which are currently encountered with complex manual interventions, it is necessary to systematically evaluate deviations and then to allocate them a dominant reaction strategy (manual, partially automated, automated) from which a suitable reaction measure can be derived. This relieves the production controller, since assistance systems partially eliminate deviations independently.
As a result, the production controller gets more time to deal with the cause of deviations so that a new occurrence of deviations can be avoided and the number of deviations can be reduced sustainably. The following paper provides a solution for the assessment of deviations. In addition, it includes differentiation logic to allocate one of the three different reaction strategies to the identified deviation.
One of the major tasks of operations managers is to boost uptime while simultaneously keeping budget. To meet this challenge they discover reliability-based management as strategic factor to improve performance. But which parameters are the key to “reliability excellence” and drive a company’s performance? What are the relevant levers to pull in reliability-based management?
To answer these questions McKinsey & Company partnered with Aachen University to launch a global reliability survey in process industries. Objective of the initiative is to provide a statistically proven picture of key factors that drive maintenance and reliability excellence. Furthermore benchmarks and best practices concerning overall operational performance will be identified. The study is based on a questionnaire-based approach which addresses all relevant departments within a company, complemented by best practice analyses.
This paper provides results of the survey. The results demonstrate that reliability pays off. Some unproven beliefs have been confirmed (e.g. a good reliability performance results in a low spare part inventory) but also surprises like a correlation between safety and performance were identified. The analysis also shows that structural differences like company size or geography do not influence reliability performance.
Die Herausforderungen der Zukunft werden geprägt durch digital veredelte Produkte von höchster Qualität und hoher Variantenvielfalt bei gleichzeitig kleiner werdenden Losgrößen. Konventionelle Entwicklungsmethoden stoßen aufgrund zunehmender Komplexität und kürzer werdender Lebenszyklen auf Produktebene an ihre Grenzen. Dadurch werden bei kundenindividueller Produktion die Aufwände in der Arbeitsplanung und -vorbereitung überproportional größer. Eine mögliche Lösung stellt die generative Erstellung der Produktionsstückliste während der Montage dar. Durch das eventbasierte „Mitschreiben der Montage“ werden administrative und planungsintensive Prozesse in der Arbeitsvorbereitung überproportional reduziert und die Erstellung der Stückliste in die manuelle Montage transferiert.
Unternehmen des Maschinen- und Anlagenbaus konzentrieren sich bereits seit mehreren Jahren verstärkt auf ihre spezifischen Kernkompetenzen innerhalb des Produktionsprozesses. Damit einher ging die umfängliche Verlagerung diverser logistischer Leistungsprozesse auf andere Unternehmen und die Bildung zahlreicher, komplexer Wertschöpfungsnetzwerke. Vielfach unterschätzt wurden dabei jedoch die resultierenden Herausforderungen der überbetrieblichen Auftragsabwicklung wie Schnittstellenvielfalt und Dateninkonsistenz. Symptomatisch für die mangelhafte Integration der Zusammenarbeit in diesen logistischen Netzwerken ist, dass Briefpost, Telefon und Fax nach wie vor die gebräuchlichsten Kommunikationsmedien der überbetrieblichen Auftragsabwicklung darstellen.
Der vorliegende Beitrag greift diese Problemstellung auf, adaptiert die grundsätzliche Betrachtungsweise des Lean Thinking auf die überbetriebliche Projektabwicklung im Maschinen- und Anlagenbau und identifiziert hierfür wesentliche Ansatzpunkte zur Vermeidung von „Verschwendung“. Als Lösungsansatz für eine durchgängig integrierte Auftrags- und Projektabwicklung wird der neue Quasi-Standard „myOpenFactory“ vorgestellt und dessen Umsetzung in marktgängigen ERP-/PPS-Systemen und einer frei verfügbaren Internet-Anwendung skizziert.
In most European countries a structural change from a production dominated towards a service oriented society is progressing. Companies increasingly consider services as means to gain competitive advantages in a global competition. In order to provide holistic, value-adding solutions while simultaneously guaranteeing high quality standards, production companies increasingly join forces with external services‘ providers. Models, methods and tools for service development are rare and in most cases immature. In the context of virtual services‘ development this leads to a dual set of simultaneous chal-lenges: an alignment of systematic services‘ and product development and the coordination of distributed R&D partners. The objective is to provide a meta-process that identifies all steps and decision points necessary to successfully develop innovative services. It is a result of combined service development and virtual enterprises‘/ networks‘ research.
The Aim of this article is to provide a framework which enhances the existing scope of manufacturing asset management by specifically addressing industrial services provided by external suppliers as an integral part of today’s manufacturing structures. Existing research shows that sourcing industrial services from specialized service organizations establishes complex and unique interdependencies and links total production efficiency to the performance of the external service suppliers. Within the context of the EU-Project InCoCo-S - “Innovation, Coordination and Collaboration in Service Driven Manufacturing Supply Chains” a standard business reference model with key focus on operation and integration of business related services (BRS) in the supply chain has been developed. Based on the service type retrofit this paper aims on the one hand to present the modules of the reference model and on the other hand to explain how the model can be used to enhance the retrofit business.
In den folgenden Abschnitten werden Szenarien zur Weiterentwicklung der Projektergebnisse von myOpenFactory vorgestellt, die neben der bereits erwähnten und begonnenen Internationalisierung des Standards möglich und sinnvoll sind. Diese Darstellung ist nicht vollständig und als Anregung für den weiteren Handlungsbedarf zu verstehen.
Industrial Service Providers (ISP) are exposed to constantly raising competitive pressures regarding both cost and performance aspects. The massive challenges caused by the current worldwide financial and economic crisis even intensified the need for process optimizations aimed at increasing the productivity of service production. To reach this goal the evaluation and elimination of waste in their production processes becomes a crucial ability for ISPs. This paper proposes a new approach for increasing productivity in service production processes using a generic measurement model for the detection and evaluation of waste. The model is based on established lean management principles, but tailored to the specifics of ISPs by adopting a customers’ perspective to track down and eliminate waste. The evaluation builds on an in-depth-analysis of particular types of waste in the industrial service production processes. Viewed from the customers’ perspective and taking into account the specific characteristics of services (e.g. intangibility, heterogeneity, inseparability, and perishability) and service production (e.g. volatile demand, a tendency to over-capacity, and limits to planning) the approach employs a service blueprint reference model to then determine the different types of waste in the various parts of the service production process.