Further development of manufacturing technology, in particular machining requires the search for new innovative technological solutions. This applies in particular to the advanced processing of measurement data from diagnostic and monitoring systems. The increasing amount of data collected by the embedded measurement systems requires development of effective analytical tools to efficiently transform the data into knowledge and implement autonomous machine tools of the future. This issue is of particular importance to assess the condition of the tool and predict its durability, which are crucial for reliability and quality of the manufacturing process. Therefore, a mathematical model was developed to enable effective, real-time classification of the cutting blade status. The model was verified based on real measurement data from an industrial machine tool.

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This paper presents an empirical study on the impact of maintenance function on more sustainable manufacturing processes. The work methodology comprises four stages. At first, ten factors of maintenance activities from a sustainable manufacturing point of view were identified. Then, in the second stage, the matrix of crossed impact multiplications applied to a classification (MICMAC) was carried out to categorize these factors based on their influence and dependence values. In the third stage, the criteria for evaluation of maintenance factors were defined, then the fuzzy analytic hierarchy process (F-AHP) was applied to determine their relative weights. In the last stage, the results of MICMAC and F-AHP analyses were used as inputs for the fuzzy technique for order preference by similarity to ideal solution (F-TOPIS) to generate aggregate scores and selection of the most important maintenance factors that have an impact on sustainable manufacturing processes. A numerical example is provided to demonstrate the applicability of the approach. It was observed that factors “Implementation of preventive and prognostic service strategies”, “The usage of M&O data collection and processing systems”, and “Modernization of machines and devices” are the major factors that support the realization of sustainable manufacturing process challenges.

Sustaining high operational efficiency of a machine park requires the use of state-of-art solutions that support both monitoring of residual processes and performing thorough analysis of thereby collected data. What meets the needs of entrepreneurs who strive for high reliability of technological infrastructure is a modern approach to maintenance prediction. The literature of the subject offers numerous studies presenting the use of various statistical models for time series prediction. The objective of this paper is to verify whether tests used in econometrics such as the augmented Dickey-Fuller test and the Utrzymanie wysokiego poziomu efektywności eksploatacyjnej parku maszynowego wymaga stosowania nowoczesnych rozwiązań wspierających monitorowanie procesów resztkowych i poddawania szczegółowej analizie uzyskanych w ten sposób informacji. Naprzeciw oczekiwaniom przedsiębiorców dotyczących utrzymywania wysokiego poziomu niezawodności infrastruktury technicznej wychodzi nowoczesne podejście w obszarze gospodarki remontowo-konserwacyjnej, jakim jest predyktywne utrzymanie ruchu. W literaturze przedmiotu wielokrotnie prezentowano wykorzystanie różnych modeli statystycznych pozwalających na prognozowanie wartości szeregów czasowych. Celem niniejszej pracy było sprawdzenie czy stosowany w ekonometrii rozszerzony test Dickeya-Fullera oraz test Kwiatkowskiego, Phillipsa, Schmidta i Shina mogą zostać użyte do predykcji zdarzeń niepożądanych jakimi są awarie. Symulację przeprowadzono dla wartości jednego parametru diagnostycznego jakim była temperatura. Słowa kluczowe: predykcja awarii, utrzymanie ruchu, testy stacjonarności, ADF, KPSS.KosicKA E, KozłowsKi E, MAzurKiEwicz D. The use of stationary tests for analysis of monitored residual processes. Eksploatacja i Niezawodnosc -Maintenance and reliability 2015; 17 (4): 604-609, http://dx.doi.org/10.17531/ein.2015.4.17. Eksploatacja i NiEzawodNosc -MaiNtENaNcE aNd REliability Vol.17, No. 4, 2015 605 sciENcE aNd tEchNology Stationary processes and system reliabilityThe behaviour of physical, economic and technical systems is usually described by mathematical models. First, based on historical data, values of structural parameters are determined, and then, following parametric identification, these models can be used to predict the behaviour of systems being described. The behaviour of machines and devices is often predicted by time series models. By predicting future values of system states, we can draw conclusions about a possibility of failure of machines and devices.Time series can be divided into stationary and non-stationary (see e.g. [2,11,7,27] x ∈ is said to be homogeneous non-stationary (homoscedastic) if, by separating a non-random component from the time series, we obtain a stationary series. Homogenously non-stationary series can contain among others a deterministic or stochastic trend; they can have a seasonal or periodic character. Following the application of a differential operator, such series can be reduced to stationary series [2,11]. is said to be in...

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