A problem of finding the optimal repair/replacement policy of a technical object is under investigation. Depending on the distribution of the time-to-repair and certain cost parameters, a decision is taken whether to repair a failed object or replace it immediately after it fails. If a repair is chosen and it is not completed within a certain period, it is interrupted and the object is replaced by a new one. The optimization task consists in formulating the conditions for choosing between immediate replacement and repair, and deriving the analytical equation for the maximum duration of a repair. The objective function is the expected cost of restoring the object to the operating condition. It is assumed that the cumulative distribution function (CDF) of the time-to-repair is a rational function (a quotient of polynomials). The properties of such CDFs are analyzed and the solutions of several optimization tasks with different CDFs that are rational functions are presented. The issue of fitting the time-to-repair distribution to empirical data is also addressed.
The introduction describes the most important facts about the development of polyolefins. This is followed by a description of the role of polyolefins and the most important applications in industry and everyday life. The paper presents new, highly active precatalysts for oligomerization of olefins. These are coordination compounds based on chromium(III) cation, anions of various polycarboxylic acids and auxiliary ligands, such as 1,10-phenanthroline or 2,2'-bipyridyl. This review presents their crystallographic structures and basic parameters describing the elementary cell. The catalytic properties of the obtained oligomerization products using chromium(III) coordination compounds by MALDI-TOF MS are described. In conclusion, the presented precatalysts are compared with others described in the literature.
A new method of estimating the scale and shape parameters of the Weibull distribution is presented. According to this method, a Weibull distributed time-to-failure (TTF) of a test item is measured m times. It undergoes a minimal repair after each of the first m-1 failures, and is put out of use after the m-th failure. This procedure is repeated n times. Based on m TTFs of one test item, which are neither independent nor identically distributed (IID), the maximum likelihood estimators (MLE) of the scale and shape parameters, called n m-sample estimators, are obtained. The accuracy of the m-sample estimators is low, however, it can be improved by using the mean values of their n IID realizations as more precise estimators. The latter are called n·m-sample estimators, have the same biases as the respective m-sample ones, but their variances are n times smaller. Interestingly enough, the n·m-sample estimators of the scale and shape parameters, as well as their biases, are given by relatively simple explicit formulas. This is somewhat unexpected in view of the fact that the standard MLE of the shape parameter, based on IID TTFs of non-repairable test items, is obtained from an equation that cannot be solved analytically.
In this chapter the author presents a comprehensive model of a multi-component technical system aimed at simulating and optimizing its operation process. Among other things, the model postulates load-related dependencies between the system’s components and delayed repairs or replacements scheduled according to the components’ priorities, where delays result from limited maintenance personnel. During the last several decades researchers in the field of reliability theory constructed various maintenance models, more or less applicable to real systems. Many authors follow purely analytical approach which, due to restrictive assumptions adopted for the purpose of analytical tractability, results in limited applicability of the considered models. These assumptions include: mutually independent components, exponentially distributed time-to-failure and time-to-repair, repairs started immediately after failures or carried out in negligible time, etc. The model proposed here does not impose such limitations, because it is designed to use simulation rather than analytical methods for computing purposes. The following assumptions bring the model closer to reality in comparison with its counterparts from the literature: 1) components are mutually dependent, i.e. a component’s failure rate can depend of the states of some other components 2) after a repair a component can be “as good as new”, “as good as used” or “as good as old” (perfect, imperfect, or minimal repair) 3) if maintenance personnel is busy, newly failed components await repair in a priority queue, 4) the state of a component may be hidden and its failure can only be revealed by inspection. The chapter’s main result is a quite elaborate algorithm simulating the modeled system’s behavior over time. Examples are given how, based on the proposed model and the adopted maintenance policy, selected reliability-related parameters can be optimized by repeated simulation. Although computationally intensive, the simulation approach allows to find performance and reliability characteristics for systems whose complexity or way of functioning rule out the application of analytical methods.
A d-cut-set in a flow network is a set of components whose removal or blockage causes the maximum flow (MF) to fall below value d, provided that in fully operational network MF is greater or equal to d. A min-d-cutset is a d-cut set such that it does not contain any other d-cut-set. In turn, a cut-set is a set of components whose removal disconnects the source and the sink, which results in MF being equal to 0. A min-cut-set contains no other cut-set. The method works as follows: the min-cut-sets are ordered according to increasing flow capacities, then from every min-cut-set a number of d-cut-sets are generated and each of them is checked for being minimal and unique. The method features two different algorithms respectively applied if Φ(C) < 2d or Φ(C) ≥ 2d. C is the min-cut-set from which d-cut-sets are generated, and Φ(C) is the flow capacity of C. This distinction results in quick generation of min-d-cut-sets without finding many non-d-cut-sets or nonminimal d-cut-sets. Compared to the similar methods, the new one is highly efficient, due to several original solutions, e.g. an efficient method of checking the redundancy of candidates for min-d-cut-sets. Min-d-cut-sets have two main applications. First, they can be used to compute various reliability characteristics of flow networks. Second, the knowledge of these sets facilitates or even enables management and maintenance of various flow networks such as data transmission, water, power supply, or traffic networks, field drainage systems, etc.
The report focuses on the antidiabetic, also termed insulin-like, effect of various vanadium and chromium derivatives, proposed mechanisms of their activity, their use in in vivo and in vitro studies, as well as in diabetic patients, their toxicity and effectiveness in controlling clinical signs of diabetes. Studies indicate that compounds of vanadium and chromium is necessary for regulation of carbohydrate and lipid metabolism mainly due to increasing the number of insulin receptors and its activation by phosphorylation. Some authors believe that compounds of chromium(III) deficiency can lead to glucose intolerance and symptoms of type 2 diabetes. However, due to methodological limitations of many clinical studies, the statements of major diabetes associations concerning recommendation of various vanadium and chromium derivatives supplementation in individuals with diabetes and obesity still remains negative. Additional studies are urgently needed to elucidate the mechanism of action of chromium and vanadium compounds and its role in the prevention and control of diabetes.
In - vitro methods of determination of the antioxidant activity of complex compounds are very interesting and not fully investigated areas of knowledge from the borderline of chemistry and biology. Methods used for determination of the activity of antioxidant complex compounds are modified due to the conditions of the experiments in which they should be carried out, e.g. reactions at physiological pH. Civilization diseases, stress related to the fast pace of life and increasing requirements of our lives cause the formation of free radicals in our body, i.e. particles characterized by a high reactivity. The methods of determination of the antioxidant activity of complexes discussed in this work apply tests carried out in laboratory conditions - in - vitro.
This article describes the in-vivo methods of studying the antioxidant properties of complex compounds. The reduced glutathione (GSH) method, which uses the reactivity of the reduced form of GSH with free radicals, is among the described methods. Further the in-vivo methods are based on the use of antioxidant enzymes such as glutathione peroxidase, glutathione S-transferase, superoxide dismutase, catalase. These types of enzymes occur naturally in the human body and they are responsible for the inactivation of free radicals, e. g. superoxide dismutase catalyzes the reaction of disproportionation of superoxide anion radical to water and oxygen. The next in-vivo methods described in this article use y-glutamyl transpeptidase and glutathione reductase, which are components of the antioxidant mechanism occurring in an organism. The last method described in this work relates to the lipid peroxidation, which is determined by the concentration of dimalonic aldehyde.
This paper is both a summarization and extension of [6] and [7], where a stochastic model of interacting operations carried out in a generic Baltic Sea Region port was proposed and analyzed. Each operation involves a number of possible unwanted events (critical incidents) whose instances occur randomly and can cause instances of other events affecting this or other operations. This can lead to a cause-effect chain of events affecting one or multiple operations. The model presented in [6] is somewhat complex, therefore it was downgraded to a simpler, application-oriented version demonstrated in [7], where an algorithm computing the risks of critical incidents is constructed and then applied to a real-life example. The current paper, apart from presenting a method of computing the risks of critical incidents, occurring by themselves or resulting from the cascade effect, also features a method of root-cause analysis of such incidents. First, the formulas for the root-cause probabilities are derived, where such a probability quantifies the likelihood that a critical incident occurring in step h of a cascade was caused by another incident that initiated this cascade. Second, an algorithm computing the root-cause probabilities, based on the derived formulas, is constructed. This algorithm is illustrated by its application to the example given in [7]. The presented results can be used as a tool for fault propagation analysis and fault diagnosis applied not only to a port environment, but to any complex industrial system.
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