The purpose of this paper is to develop an applied fuzzy model of information technology to obtain quantitative estimates of environmental start-up projects in air transport. The developed model will become a useful tool for venture funds, business angels, or crowdfunding platforms for the development of innovative air transport businesses. Obtaining a quantitative estimate of the environmental start-up projects will increase the sustainability of the decision making on the security of financing of such projects by investors. This article develops a fuzzy evaluation model of project start-ups in air transport as an application of our neuro-fuzzy model in a specific air transport environment. The applied model provides output ranking of start-up project teams in air transport based on a four-layer neuro-fuzzy network. The presented model declares the possibilities of the application to solve these economic problems and offers the space for subsequent research focused on its usability in several areas of start-up development, in sectors and processes differentiated. The benefits are also visible for several types of policies, with an emphasis on decision-making processes in regulatory mechanisms to support the state funding in Slovakia, the EU etc.
The Six Sigma DMAIC can be considered a guide for problem solving and product or process improvement. The majority of companies start to implement Six Sigma using the DMAIC methodology. The paper deals with application of Six Sigma using the DMAIC methodology in the process of product quality control. The case study is oriented on the field of metallurgical operations. The goal of the Six Sigma project was to ensure the required metallurgic product quality and to avoid an increase in internal costs associated with poor product quality. In this case study, a variety of tools and techniques like flow chart, histogram, Pareto diagram, analysis of FMEA (Failure Mode and Effect Analysis) data, cause and effect diagram, logical analysis was used. The Sigma level has improved by approximately 13%. The achieved improvements have helped to reduce the quantity of defective products and the processing costs (technology for re-adjusting). Benefits resulting from the DMAIC implementation can be divided into three levels: the qualitative, economic and safety level.
Precision manufacturing requires a technically clean environment to ensure repeatability of production while maintaining the required quality. The current VDA 19.2 standard classifies clean environments into three classes. In the course of 2020/2021, the requirements for electromagnetically clean areas shall be added to these requirements. This article highlights the potential of measurements used in this field nowadays.
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