The proposed optimization approach is used for modelling, optimization and automated design of technological processes, as well as for determination of the properties of the products under different conditions. This is achieved via a specially developed software, which is required to perform the necessary calculations.
The basis for these calculations can be experimental and simulation research, generalized to adequate regression models and models with artificial neuron networks.
The software solution depicts the investigated output(s), depending on 2 to 10 input parameters. It is provided with several options, making the solution extremely user-friendly.
The approach consist of improvement of existing or design of new, non-established technological processes, the parameters of which vary within a range, by which, after an experimental check, benefits are guaranteed achieved through a certain economic effect.
Objects of research can be:
- A new non-established technological process or technology, for which a process of designing the processing mode is forthcoming.
- Non-optimized process, for which better quality indicators (set of indicators) through optimization may be offered or savings of used raw materials or energy are achieved by maintaining the levels of quality parameters.
- Optimization of simulation Computer Aided Engineering /CAE/ calculations to optimize and achieve a rational technological option.
The Bulgarian university is looking for market realization of their automated method, which solves specific problems, but when solving the tasks, the assigning company will need to take over part of the assignment in terms of defining the managing and managed parameters, as well as to present the necessary links between them, obtained through simulations or experiment. This is the reason why the university is looking for a commercial agreement with technical assistance.
The assistance from the Bulgarian university experts includes choosing the parameters of the technological process that guarantee results that are relevant to the respective manufacturing company.