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Article citation info: Introduction and literature surveyMany maintenance strategies, policies and methods have been developed, which are aimed at making maintenance cheaper and more effective. Such programs have the minimization of costs, downtime and losses due to failure of critical objects of the equipment as their main objective. Cost minimization improves the effectiveness and profitability of the organization [1,2,9,12,13,20].For creation of the maintenance policies, well described data mining input is very important. [4].In recent years, useful models of preventive and predictive maintenance optimization with different complexity and applicability have been further developed.In the paper, [5] the authors proposed a quasi-periodic imperfect preventive maintenance policy. Finally, a real case study of preventive maintenance on Chinese diesel locomotives is examined to illustrate the proposed maintenance policy.The paper [6] proposes an approach in which preventive and failure replacement costs as well as inspection cost are taken into account to determine the optimal replacement policy and an age-based inspection scheme, such that the total average costs of replacements and inspections is minimized.Determination of the preventive effect of optimal replacement policies in the paper [8] is based on aging intensity and the cost ratio of failure and preventive replacements. One of its conclusions is that not every preventive maintenance is fully effective and a policy of, "run to failure" can be more effective (note: in some cases).The proposed model in the paper [10] takes into consideration the stochastic nature of equipment failures. The output from the model is a cost distribution against the time from which the minimum cost may be found for a particular period and this period is defined as the optimum lifespan of the machine part.The paper [11] considers periodic preventive maintenance policies for a deteriorating repairable system. On each failure, the system is repaired and, at the planned times, it is periodically maintained to improve its performance reliability. Most periodic preventive maintenance (PM) models for repairable systems have been studied assuming that the failure process between two PMs follows the nonhomogeneous Poisson process (NHPP), implying the minimal repair on each failure.The paper [14] regarding warranty policy considering three maintenance options for products with multiple failure modes also showed the broad usability of the Weibull distribution. This fact supports the decision of the authors to also use the Weibull function.The paper [15] presents a new mathematical function to model an improvement based on the ratio of maintenance and repair costs, and demonstrate how it outperforms fixed improvement factor models by analyzing the effectiveness in terms of cost and reliability of a system. Legát V, MošnA F, ALeš Z, JurčA V. Preventive maintenance models -higher operational reliability. eksploatacja i niezawodnosc - Maintenance and reliability 2017; 19 (1): 134-141, http://dx...

Methodology of overall equipMent effectiveness calculation in the context of industry 4.0 environMent Metodologia obliczania ogólnej efektywności sprzętu w kontekście środowiska industry 4.0 Industry 4.0 and related Maintenance 4.0 demand higher requirement for productivity and maintenance effectiveness. Nakajim's OEE indicator still plays an important role in measuring effectiveness of production and maintenance. In connection with the current Industry 4.0 challenge, the issue of Industrial Internet of Things (IIoT) is highly accentuated. This topic includes the matter of autonomous management and communication of individual machines and equipment within higher and more complex production units. Authors propose original calculations OEE for the whole production line from OEE knowledge and individual machines, including knowledge of their nominal and actual performance. The presented solution allows a greater depth of analysis of machine efficiency and overall effectiveness calculation of different assembled production lines based on knowledge of individual machines efficiencies.

Authors define general dependability characteristics (reliability, maintainability, supportability and availability) and their measures. Further there is introduced method of data collection which shall be planned taking into account appropriate targets. Dependability data analysis needs clear understanding of an object, its operation, environment and physical attributes to be obtained required dependability measures which are described. These measures can be used as indicators for measuring maintenance impacts on reliability and maintainability. Data collection and its evaluation help to monitor the impact of maintenance on these indicators. Dependency between non-fulfillment of preventive maintenance and failure intensity including maintenance costs are also evaluated.

The purpose of this paper is to provide an overview of state-of-the-art of maintenance management audit and to show a case study of maintenance audit and its results in the Czech Republic. Authors proposed audit methodology based on world and own experiences. It was defined hundred thirty audit criteria divided into ten maintenance management areas. Using expert approach to review of maintenance managers and documentation according to audit criteria enables to obtain answers and their assessment presented in percentage of audit criteria fulfilment. After that there is applied SWOT analysis method to determine mainly weakness (gaps) in real maintenance management processes comparing with world excellence maintenance class. On the base of the gaps there are recommended topics for maintenance improvement. Value of the results is a help to maintenance managers and supervisors in maintenance audit executing as a tool for maintenance management improvement.