СЪДЪРЖАНИЕ
- автоматика
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- М. Хаджийски, Необходимият баланс между алтернативи при проектиране и използване на интелигентни системи за персонализирано инженерно обучение
- Дни на Джон Атанасов 2024
- 75-годишен юбилей на проф. д-р инж. Коста Бошнаков
Key Words: Predictive diagnostics; competitiveness; costs; innovation.
Abstract. In today’s highly competitive economic environment, effective predictive maintenance of equipment is critical to ensuring high productivity, product quality, on-time delivery and a safe work environment. Predictive maintenance itself is a well-established approach that uses equipment condition data to predict and project future operating conditions leading to system-wide improvements. Having an integrated, computer-based information management system is a strong competitive advantage over today’s complex manufacturing systems. To automate and optimize these processes, advanced systems including Internet of Things (IoT) modules are often used, which enable intelligent devices to exchange information with each other and with others via the Internet, creating a large-scale network of interconnected devices. Such connectivity helps in cost accounting, production and maintenance planning, environmental compliance data, etc. A successfully implemented system will provide an opportunity for effective communication and coordination of predictive maintenance activities leading to continuous improvements of key indicators.