In order to offer our customers and business partners broad and qualified expertise, DUALIS participates in pioneering joint projects to promote research and development. We are also members of associations and societies that represent their interests, provide important impetus and offer a large network. On this page, we have listed only those associations that are also active internationally.
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Center Integrated Business Applications
The Center Integrated Business Applications drives the establishment and expansion of networked IT system landscapes in order to increase the added value of manufacturing companies in the long term.
For its members, the centre is a strategic partner for innovation, neutral project support and market positioning on the supplier side and a partner for the implementation and continuous coaching of selection, harmonisation, and implementation projects on the user side.
As an independent partner for business software users as well as for providers and integrators, the centre develops and secures sustainable future added value for all companies involved in the integration process.
DIAZI
Transforming production plants in the automotive sector into state-of-the-art digital factories is the aim of the pioneering "DIAZI" project. Continental leads the consortium of eight renowned partners from industry and research whereas DUALIS is one of them. The results of the project should enable automotive industry players to digitalise manufacturing processes and make them significantly more effective - and thus make a comprehensive contribution to sustainable mobility.
The project "Digitalization of the Industrialization Process in the Automotive and Supplier Industries" (or DIAZI) is funded by the German Federal Ministry for Economic Affairs and Climate Protection and is scheduled to run for three years. It started in January 2023.
Our role in the DIAZI project
In general, we are researching how digital line planning (design and layout, lean check: analysis and improvement of production processes using various lean management methods) can be supported by simulation and which tools can improve the planning process in addition to the existing options. We are also developing workflows and tools to support virtual commissioning, for example to reduce the effort involved in model generation and standardization.
Project duration: 1.01.2023 to 31.12.2025
GUIDES
Generalized Support and Investigation Design for Nested Systems
A project of DUALIS GmbH IT Solution and the Chair of Software Technology at TU Dresden
In general terms, detailed planning can be described as a multi-criteria optimization task, which involves solving a combinatorial problem with several conflicting objectives while taking many constraints into account. This class of problems has a non-linear complexity, which can lead to very long runtimes, especially for very large problems.
Initial situation
Intuitive and frequently used approaches for solving these problems, which are classified under the generic term MOO, use heuristics to iteratively approach the optimization result, sometimes with massive use of IT. The specialized methods developed over a long period of time combine the generation of valid solutions and the step-by-step improvement of these, but therefore operate within a narrowly limited range of the possible solution space, without information about the entire result potential.
Objective of the project
Therefore, new ways to generalize MOO tasks are sought in order to combine them in an integrating approach with the existing embedded heuristics (nested). Innovative algorithms for model transformations and cluster analysis enable a view of the problem that encompasses the entire solution space (Bird's Eye) and support the specialized existing algorithms in their tasks, improve their results and make them evaluable (Support and Investigation). The approach of the GUIDES project is made up of these aspects.
Implementation and benefits
In this way, a hybrid procedure is created that efficiently analyzes large and inhomogeneous data models in a pre-processing step, i.e. first transforms and structures them using modern Knowledge Discovery in Databases (KDD) methods in order to narrow down those areas of the entire solution space in which the respective global optima are to be assumed. This information is then made available to the specialized detailed planning heuristics via dedicated interfaces, so that the scheduling algorithm is extended by functions for the early detection of suboptimal partial solutions, which prevents stagnation in local optima and makes global optimization potentials assessable. Suitable KDD methods have already been tested in advance to ensure sufficiently low time complexity.
Project duration: 01.09.2015 to 30.11.2017
This measure was co-financed by tax funds on the basis of the budget approved by the members of the Saxon state parliament.
KIPro
AI-based assistance system platform for complex production processes in mechanical and plant engineering
The aim of the project initiated by the Homag Group is to develop AI-controlled analysis and forecasting tools for mechanical and plant engineering while interacting with the MES solution iTAC.MOM.Suite and the APS system GANTTPLAN.
For DUALIS, the research work focuses on how detailed scheduling process can be optimised. One of the main aspects is the forecasting of realistic process times and the consideration of employee qualification and learning curves when prioritising the planning process.
Optimization platform for energy-efficient production
A joint project of DUALIS GmbH IT Solution, BischoffGlastechnik AG and Fraunhofer EAS
DUALIS, Bischoff Glastechnik AG and Fraunhofer EAS are developing the optimization and planning platform OptPlanEnergie, which can be used to optimize the production of safety glass. The production process is viewed holistically and optimized with regard to high production output, high product quality and low energy consumption.
Objective of the project
A production and energy schedule is generated from the platform to achieve the optimum. The aim is to reduce energy consumption by approx. 25% (= 2 million kWh/year). The basis is the modeling and simulation of the production process at an adapted abstraction level, including the energy balances.
Implementation
At the highest level, the use of resources is summarized in a process model. Detailed physical/mathematical models for the critical thermodynamic sub-processes of heating and tempering are integrated into this process model. The following stages are planned:
(1) Requirements analysis (2) Development of the sequence and process simulator (3) Adaptation of the optimization methods (4) Modelling and optimization of safety glass production (5) Implementation of the optimized production and energy schedule (6) the user interface of the platform.
Project duration: 01.12.2014 to 30.11.2017
OptPlanEnergie is supported by the Federal Ministry for Economic Affairs and Energy
PLUSS
Development of a software system for operative production planning under uncertainty - Dresden
In the WK-Potential PLUSS project, a new type of software system for operational production planning is to be developed, which serves both to support decision-making and to automate processing in planning scenarios that are characterized by uncertainty and are therefore subject to constant change.
The development of a component for operational production planning with real-time capable optimization algorithms is carried out in PLUSS.Opt by DUALIS GmbH IT Solution.
In the PLUSS research project, the companies DUALIS IT Solutions GmbH, Dresden Informatik GmbH and apromace data systems GmbH are receiving scientific support from the Dresden Fraunhofer Institute for Transportation and Infrastructure Systems (IVI).
Project duration: 01.01.2012 to 31.12.2013
REPLAKI
More realistic planning with AI
The challenges of "batch size 1" in the field of volatile, often insufficiently digitalised value chains in the automotive sector is the trigger point for this project funded by the German Federal Ministry of Economics and Climate Protection.
The aim of the project is to analyse interdependencies in historical process data using artificial intelligence (AI) and machine learning (ML) and to use them to increase the predictive accuracy of production plans.
The focus is on more realistic forecasting of delivery dates and process durations as well as data-supported planning of new parts.
Associated partners: Frauenthal Airtank Elterlein GmbH and Zecher GmbH.
Project sponsor: VDI Technologiezentrum GmbH
Project duration: 01.01.2023 - 31.12.2025
Silicon Saxony
With over 500 members, Silicon Saxony is the largest high-tech network in Saxony, one of the largest ICT clusters in Germany and the largest microelectronics cluster in Europe.
With 3,600 members, the VDMA is the largest network organization and an important voice for the machinery and equipment manufacturing industry in Germany and Europe. The association represents the common economic, technical and scientific interests of this unique and diverse industry.
