Subject Classification of data on the condition of equipment is important for arranging a single information space and effective asset management of a large industrial enterprise. We consider the tasks of classification and clustering of information on equipment as part of applied research in the field of integrated approach to improvement of the management of repair services providing operation of complex utility facilities. Objectives The aim is to design an approach to data collection and processing to obtain practical information about the structure of equipment, its faulty components, technical and economic implications of unloading and business interruption. Based on the data, we develop measures and identify priority areas for repair services improvement. Methods We employ general scientific methods of research that rest on the tenets of the theory of classification and coding, the cluster analysis, the systems theory, the fuzzy sets theory, the theory of management, reliability of technology, and other engineering disciplines. Results We developed and tested the system of classifiers for equipment database structuring. The offered approach to classification, clustering and coding of data enables to apply modern methods to assess the efficiency of maintenance and repair services at large enterprises. Conclusions Classification of equipment, causes and consequences of defects, remedial actions and areas of repair services improvement is a complex cross-functional challenge. It is addressed via special techniques by the enterprise personnel together with engineering experts under the supervision of senior managers and subject to corporate and operational strategies.
Keywords: maintenance service, maintenance and repair, classification and clustering, equipment database, defects and failures
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