Abstract
The development of machinery performance monitoring systems along with the prospect of intelligent factories developed under the concept of industrial revolution 4.0 affect dynamic changes in the field of maintenance. Therefore, based on an overview of the literature and observations of production enterprises, we propose a model of maintenance service support system with respect to failure prediction and decision making in the area of maintenance works. In the designing stage the QFD method was employed with a view to testing its usefulness for the process.
Highlights
The development of manufacturing companies resulting from the emergence of the Industry 4.0 sets high requirements for IT systems designed to support enterprises in most areas of their operation
Efforts regarding the development of machinery monitoring systems, analysis and inference expert system decision systems based on generated forecasts and database systems require thorough preparation of the initial designing stage
The matrix demonstrates that it will be necessary to find compromise solutions with respect to: ‒ system window loading time and the type of Bring Your Own Device (BYOD) approach used by the company, ‒ system window loading time and updates, ‒ system window loading time and real-time mathematical operations
Summary
The development of manufacturing companies resulting from the emergence of the Industry 4.0 sets high requirements for IT systems designed to support enterprises in most areas of their operation. A distinct tendency to design systems and applications that put more and more emphasis on replacing the human factor with IT solutions, especially at the stage of decision making, can be widely observed In effect, this approach contributes to the creation of expert systems dedicated to manufacturing enterprises. Efforts regarding the development of machinery monitoring systems, analysis and inference expert system decision systems based on generated forecasts and database systems require thorough preparation of the initial designing stage. To this end, a range of available quality management tools can be implemented already at the conceptual stage
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