Model-based evaluation environment for sustainability

Nowadays, many companies are using enterprise models within an enterprise planning system to develop their business strategy. In order to follow a holistic sustainability approach, environmental, economic and social aspects have to be integrated into these models on a strategic, tactical and operational level. This results in an increased model complexity and requires mechanisms to ensure consistency and efficient model management. Furthermore, the user is confronted with a variety of data and is not able to perform model validation and verification as well as using the enterprise model as a tool for operational support. This paper presents an approach of a model-based evaluation environment by extending enterprise models with sustainability artefacts, to empower the users within their decision-making towards a sustainable enterprise orientation. A framework for contextual enterprise modelling is applied to provide configurable individual model evaluation and application views

Sustainability in Model-based Planning and Control of Global Value Creation Networks

Manufacturing companies are affected by an increasing complexity driven thru fast changing requirements in the global market. To meet the large catalogue of requirements, enterprises are forming global value creation networks and provide services jointly. The existing time pressure and the involvement of many stakeholders results in a demand of methods and tools for a quick configuration of such networks. Beside the management of material, information and money flows the quest of a sustainable corporate development poses a further challenge for the decision makers. The consideration of sustainability in business process management is one approach to take also social, economic and environmental aspects within global value creation networks into account. Reviewing existing modelling techniques shows that the requirements for a fast configuration and an adequate management of sustainability are just insufficiently addressed or are raising the complexity further. This paper will explore capabilities of an enterprise modelling technique which supports an integrated handling of network configuration and sustainability management in a fast and efficient manner.DFG, 199828953, SFB 1026: Sustainable Manufacturing - Globale Wertschöpfung nachhaltig gestalte

Model-based evaluation environment for sustainability

Nowadays, many companies are using enterprise models within an enterprise planning system to develop their business strategy. In order to follow a holistic sustainability approach, environmental, economic and social aspects have to be integrated into these models on a strategic, tactical and operational level. This results in an increased model complexity and requires mechanisms to ensure consistency and efficient model management. Furthermore, the user is confronted with a variety of data and is not able to perform model validation and verification as well as using the enterprise model as a tool for operational support. This paper presents an approach of a model-based evaluation environment by extending enterprise models with sustainability artefacts, to empower the users within their decision-making towards a sustainable enterprise orientation. A framework for contextual enterprise modelling is applied to provide configurable individual model evaluation and application views

Ressourcenadaptive Produktionssysteme: Design und Betrieb bei volatilem Energieangebot

Ein heute wichtiger Wirtschaftsfaktor mit einem wesentlichen Beitrag auf dem Weg zu einer nachhaltigen Entwicklung ist der effiziente Umgang mit Ressourcen. Eine Schlüsselrolle spielen dabei Erneuerbare Energien für die Energieversorgung, Energiespeichertechnologien sowie die intelligente Steuerung des Produktionssystems. Letztere soll vor allem einen energieeffizienten Betrieb sicherstellen, also Leistungsverläufe optimieren und Spitzenlasten vermeiden. Um Energie zu einer zentralen Zielgröße in der Produktionsplanung und -steuerung zu machen, haben die Projektpartner ein neues Planungstool entwickelt. Die Basis dafür bildete die modellhafte Beschreibung des Produktionssystems, die Fertigungsschritte zur Herstellung eines Produkts und umgebende Planungs- und Steuerungsprozesse kombiniert

JUMP 4.0. Mobile Jobeinplanungsunterstützung für Meisterinnen und Meister in der Produktion

The research project "JUMP 4.0" develops an interactive process management system that is tailored to the needs of master craftsmen in order to plan, monitor and secure processes

Situation Awareness Monitor And Liquidity Assessment For Enterprise Resilience Management

Currently, companies are becoming increasingly vulnerable towards unforeseen disruptive events. One example of such an event is the COVID-19 pandemic, in which many companies are facing existential difficulties. The sudden loss of suppliers and customers as well as frequent changes in regulations at short notice present companies with considerable challenges. Potential uncertainties and complexity complicate the planning and the implementation of measures. A fast and effective overview and the benefit of measures is usually missing. Situation awareness monitors have long provided orientation for first responders and rescue operators within the field of crisis management and can be just as relevant for companies. Identifying, gathering, interpreting and visualizing external information from the corporate environment in relation to relevant disruptions remains an unsolved problem. In addition to the decision to implement effective measures before, during and after a crisis, an approach for the simulation of the disruptive impact and the effect of resilience measures on the company’s performance as well as liquidity is required. In this paper, a Situation Awareness Monitor (SAM) for resilience management is presented to address the aforementioned issues. First, the model-based IT architecture for the monitor is depicted. The enterprise model is coupled with an approach to assess critical processes of small and medium enterprises. Statistical models are applied to draw up the balance between single components, like input, output, supplier, storage and production. The result shows a continuous performance-based liquidity assessment to evaluate the resilience against disruptive events. Finally, single enhancement measures in alignment to the resilience phases – prepare, prevent, protect, respond and recover – can be analyzed