ADREAN: Process mining and simulation for resilient production processes

The ADREAN research project combines process mining and simulation to analyse production and logistics processes on the basis of data, design robust process structures and enable simulation-based optimisations. A key objective is the automatic generation of realistic simulation models from actual event data and the evaluation of alternative process variants to increase efficiency and resilience.

rEUman – Smart human-centric remanufacturing

The rEUman research project is developing a digitally supported, human-centric solution for remanufacturing to make processes at factory and value chain level more efficient, flexible and traceable, thereby strengthening the competitiveness of the European remanufacturing industry.

growING – Resilient specification of requirements in mechanical and plant engineering

The growING research project is developing digital tools and digital twins to make collaboration and requirements specification in mechanical and plant engineering more resilient, flexible and efficient. The aim is to replace conventional specifications with data-based approaches, shorten time-to-market and increase project quality by creating data space-supported tools for coordination and specification.

FlexIndustries – Monitoring, analysis and optimisation of energy-intensive industrial processes

The FlexIndustries project is developing a digital energy and process management platform that can be used to monitor, analyse and optimise energy-intensive industrial processes. The aim is to use energy efficiency measures and process flexibility methods in such a way that plants can respond more flexibly to renewable energy sources and demand response mechanisms. This should make industrial processes more energy-efficient and resilient.

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VaStNet – Optimisation of value streams with neural networks

The VaStNet project is developing an AI-supported assistant that facilitates the creation and correction of digital value stream models. The aim is to make simulation-capable models accessible even to less experienced users and to make production and supply chains more efficient.

RemaNet – the future of sustainable remanufacturing in Europe

The RemaNet project aims to promote concepts for remanufacturing, recycling and reducing material use. The focus is on developing a new remanufacturing business model based on building a community in which different players contribute their expertise.

SDM4FZI – Software-defined manufacturing for the automotive and supplier industry

In SDM4FZI, SimPlan is primarily concerned with further developing value stream and logistics models into value stream and logistics twins by integrating them into the SDM4FZI platform. Furthermore, the usability of value stream and logistics twins to support adaptability is being demonstrated together with application partners such as Audi and Bosch.

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E2COMATION – Future factories work sustainably with less energy

In this project, SimPlan will continue to drive forward holistic simulation approaches in which energy and media consumption are taken into account in addition to material and information flows.

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DigiPrime – Digital platform for the circular economy of cross-sector and sustainable networks

The DigiPrime research project has the task of developing a new concept for a digital platform for the circular economy that is intended to overcome the current information asymmetry between the players in the value chain. New cross-industry business models are to be created based on the data-supported recovery and reuse of functions and materials from products with high added value.

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ENERMAN – ENERgy-efficient manufacturing system MANagement

ENERMAN conceptualises the factory as a living organism that can manage its energy consumption in an autonomous way. It creates an energy and sustainability management framework that collects data from the factory and processes it holistically to create specific energy and sustainability metrics.

kompAKI – Competence Centre for Work and Artificial Intelligence

In the kompAKI project, new potentials for human-centred AI applications and their business models are being tapped, new approaches to cooperative AI are being developed with which users can use AI more transparently and easily, and new methods for evaluating work in AI-supported work systems are being developed. The knowledge gained will be validated in pilot projects with partner companies, mainly from the production sector.

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AI-Mod – Learning process for the automatic conversion of a modelled value stream into a simulated value stream

Building simulation models for a value stream in a factory is a time-consuming task. The idea of the project is to train a learning procedure in such a way that it supports the modeller in fulfilling this requirement and points out where building blocks, edges or data may still be missing.

SEAMLESS – Simulation-supported, assistance system-based engineering and maintenance services for lean aftersales services

The aim of the SEAMLESS research project is the development and seamless provision of SME-compliant, internet-based aftersales services. Aftersales services refer to the provision of consulting, training and spare parts services following a sale.

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DaWis – Development of an integrated solution for data farming and knowledge discovery in simulation data

The aim of the project is to transfer the method of knowledge discovery in simulation data, which has so far mainly been considered in academic case studies in the field of production and logistics, to practice. To this end, methods of smart experiment design were evaluated and implemented, methods for the (cloud-based) distribution of experiments were developed and suitable data mining and visual analytics methods were planned.

MobiSim – App-based value stream simulation, simulation service in the cloud

MobiSim is the parent project in which the original form of today’s SimVSM app was developed. The aim of the project was to develop a software application for use on mobile devices in the production environment of manufacturing companies.