Wyniki wyszukiwania - BazTech

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Using fuzzy logic to support maintenance decisions according to Resilience-Based Maintenance concept

Bukowski Lech, Werbińska-Wojciechowska Sylwia

Eksploatacja i Niezawodność

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2021

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Vol. 23, no. 2

294--307

EN

Many authors have highlighted the importance of physical assets maintenance management in relation to resilience engineering, especially for systems operating under significant uncertainty. Thus, the authors presented a new approach to system maintenance based on resilience concept implementation. They introduced Maintenance Support Potentials (MSP) as a measure of an organization's maintenance support capacity. Moreover, based on the MSP definition, they developed a fuzzy-based organization's maintenance support potential level assessment method. The proposed approach takes into account two main MSP parameters – potential readiness level and process regency. It followed four main steps, including organization's MSP identification/evaluation, MSP weights assessment, Maintenance Support Capacity assessment, and final reasoning. A case study of a global manufacturer from the automotive industry is presented to illustrate the method's applicability. The authors also indicated further research directions to optimize the maintenance strategy based on Resilience-Based Maintenance concept.

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A method for estimating the probability distribution of the lifetime for new technical equipment based on expert judgement

Andrzejczak Karol, Bukowski Lech

Eksploatacja i Niezawodność

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2021

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Vol. 23, no. 4

757--769

EN

Managing the exploitation of technical equipment under conditions of uncertainty requires the use of probabilistic prediction models in the form of probability distributions of the lifetime of these objects. The parameters of these distributions are estimated with the use of statistical methods based on historical data about actual realizations of the lifetime of examined objects. However, when completely new solutions are introduced into service, such data are not available and the only possible method for the initial assessment of the expected lifetime of technical objects is expert methods. The aim of the study is to present a method for estimating the probability distribution of the lifetime for new technical facilities based on expert assessments of three parameters characterizing the expected lifetime of these objects. The method is based on a subjective Bayesian approach to the problem of randomness and integrated with models of classical probability theory. Due to its wide application in the field of maintenance of machinery and technical equipment, a Weibull model is proposed, and its possible practical applications are shown. A new method of expert elicitation of probabilities for any continuous random variable is developed. A general procedure for the application of this method is proposed and the individual steps of its implementation are discussed, as well as the mathematical models necessary for the estimation of the parameters of the probability distribution are presented. A practical example of the application of the developed method on specific numerical values is also presented.

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Logistics decision-making based on the maturity assessment of imperfect knowledge

Bukowski Lech

Engineering Management in Production and Services

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2019

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Vol. 11, no. 4

65--79

EN

The main purpose of this article is to develop a method that allows for an objective quality assessment of imperfect knowledge, which is necessary for decision-making in logistics. The methodology aimed at achieving this goal is established on the system analysis of the entire process employed for obtaining, processing and using data and information as well as the knowledge generated on this basis. The result of this work is a general framework that can be used for managerial decision-making in smart systems that are part of Industry 4.0, and, in particular, Logistics 4.0. A key theoretical contribution of this framework is the concept for quantitative assessment of the maturity of imperfect knowledge acquired from Big Data. The practical implication of this concept is the possibility to use the framework for the assessment of the acceptable risk associated with a managerial decision. For this purpose, the article presents a brief example of how to use this methodology in the risk-taking decision-making process. Finally, the summary and discussion of the results are offered.