The article presents a model of fuzzy quality control of a company. The practical relevance of the research consists in the potential use of the developed system as a universal tool to assess efficiency of food production process quality management and to develop a package of actions to increase efficiency of the quality management system. The developed model enables to forecast and manage quality parameters of the manufactured products. Streszczenie. Artykuł przedstawia model rozmytej kontroli jakości firmy produkcyjnej. Praktyczne znaczenie badania polega na potencjalnym wykorzystaniu opracowanego systemu jako uniwersalnego narzędzia oceny efektywności zarządzania jakością procesu produkcji żywności oraz wypracowania działań mających na celu zwiększenie efektywności systemu zarządzania jakością. Opracowany model umożliwia prognozowanie i zarządzanie parametrami jakościowymi produkowanych wyrobów. (Inteligentny system zarządzania produkcją i jakością produktów dla małych i średnich przedsiębiorstw).
The paper considers the technique of modeling and formation educational components of the planned training of CDIO Syllabus, realized in the form of the educational adaptive environment of engineering education. The following key concepts of the methodology have been accepted: competence models of the stages of the CDIO initiative, the method of project training, syntax for describing the concepts of the domain, models for mapping support concepts in the form of expressions of knowledge and ontological engineering.
As organizations increasingly rely on digital technology to operate, protecting their information and data has become a critical concern. Information security systems are designed to safeguard digital assets against unauthorized access, use, disclosure, disruption, modification, or destruction. However, evaluating the effectiveness of an information security system can be challenging due to the complexity of the system and the diversity of threats it faces. In recent years, researchers have proposed using fuzzy inference to evaluate the effectiveness of information security systems. Fuzzy inference is a mathematical approach that can handle uncertain and imprecise information, making it well-suited for evaluating the effectiveness of information security systems. This research aims to develop a method for evaluating the effectiveness of an information security system based on fuzzy inference. The proposed method uses a set of performance indicators to measure the effectiveness of the system, such as the number of security incidents detected, the response time to security incidents, and the number of false positives and false negatives [1]. These indicators are then combined using fuzzy inference to generate an overall effectiveness score for the system. The proposed method will be evaluated using a real-world case study of an information security system deployed in an organization. The effectiveness score generated by the fuzzy inference method will be compared to the results obtained using traditional evaluation methods, such as the cost-benefit analysis or the return-on-investment analysis. The results of the study will demonstrate the effectiveness and usefulness of the proposed method for evaluating information security systems.
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