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1
EN
The purpose of this paper is to study effectiveness measures of the control of production process. The text refers to research study conducted in some industrial and service organizations in Poland, which was to identify mechanisms of problems in production processes. One of the outputs of the study was classification of some basic sub-mechanisms of the creation of problems. These were: control standards, control data and resources used to control. Some probabilistic measures were established to estimate the effectiveness of control and the probability of problems arising from imperfect control. Findings: effectiveness of control, expressed in terms of the probability of achieving definite goals, is determined by the existence of effective control standards. This, in turn, imposes certain requirements on the data necessary to realise the control scheme and accordingly - on the appropriate material resources. This dependence defines certain order in the set of factors: control standards ? control data ? control material resources; role of factors: control standards, control data and control material resources turns out to be symmetric. Effectiveness of each of them determines limit for the effectiveness of control. Probability of problem associated with imperfection of control is not smaller than the probability of imperfection of the weakest factor. The paper focuses on some issues that decide on effectiveness of preventing problems in manufacturing processes. The considerations may be useful for organizations that are high sensitive to problems.
2
Content available remote Wpływ kontroli jakości na zawodność konstrukcji
EN
The problem of influence of design supervision and inspection during execution on the unreliability of building structures is considered. Probability of unreliability has been defined as the weighted sum of two conditional events, namely the probability of collapse or severe damage and the probability of decommissioning due to quality control. The coefficient of control efficiency is assumed to be a fuzzy number and depends on design supervision and inspection levels. It enables to consider the influence of qualitative, vague and subjective information about quality control levels on the total probability of failure. In practice, the coefficient of control effciency is more than zero and the probability of decomissioning has decisive influence on the resultant probability of failure.
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