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Purpose: Currently, in Poland, the process of patient registration at the hospital emergency department (SOR) is carried out in accordance with the S.T.A.R.T. (Simple Triage And Rapid Treatment) standard. According to this procedure, based on a preliminary interview, patients are selected and assigned to one of five risk categories, described by colors: red, orange, yellow, green, or blue. Since this standard is relatively new (introduced in 2019), its analysis using quantitative, not only qualitative, methods are highly desired. Design/methodology/approach: The so-called mean-value approach for studying the proposed queueing model is used in the paper. Findings: For each category of patients, the mean number of patients present in the system, the mean queue length, and the average values of waiting time for admission by a doctor and time spent in the emergency department are found. Two priorities are considered: nonpreemptive (absolute) and preemptive-resume (relative). Numerical calculations illustrate theoretical results. Originality/value: Explicit representations for key queueing characteristics are found analytically. Moreover, illustrating numerical results simulating the "behavior" of a real hospital emergency department are presented and discussed. [ABSTRACT FROM AUTHOR]

One of the most important characteristic of each queueing model is time to buffer overflow. In the paper the distribution of that time in a single-channel manufacturing system, modelled by a Markovian finite-buffer queue with machine breakdowns, is studied. By using the analytical approach based on the idea of embedded Markov chain, total probability law and linear algebra, the formula for Laplace transform of the time to buffer overflow conditional distribution is found. Numerical illustration is presented.

Increase flexibility of manufacturing requires implementation of effective planning IT tools. Planning and scheduling problems traditionally consider the production resources as the only constraints. Since the raw material and intermediate transferring times are relevant in relation to the production times, it is required to model the material handling equipment and its activities. The problem of scheduling subject to manufacturing and logistical constraints based on data-driven models generation method is presented. A KbRS and FlexSim systems are used as a scheduling tool.

The paper presents application of ant colony optimisation algorithm for scheduling multi-resources operations in flexible job shop type of production systems. Operations that require the participation of two or more resources are common in industrial practice, when planning are subject not only machines, but also other additional resources (personnel, tools, etc.). Resource requirements of operation are indicated indirectly by resource groups. The most important parameters of the resource model and resource groups are also described. A basic assumptions for ant colony algorithm used for scheduling in the considered model with multiresources requirements of operations is discussed. The main result of the research is the schema of metaheuristic that enables searching best-score solutions in manufacturing systems satisfying presented constraints.

The method of maintenance and production task scheduling is proposed to make the production system insensitive to a disruption. The method enables the maintenance of high values of schedule evaluation indicators in variable conditions, such as stability robustness and quality robustness. The frequency of a machine failure is described by the Maxwell distribution. Formulae for different reliability characteristics are given. The parameters of the distribution are estimated using maximum likelihood, empirical moments and a method based on the renewal theory. The advantage of the last method is the ability to achieve accurate predictions of failure-free time of a machine, when there is a lack of complementary and reliable historical data. In the related literature, only the first method is used to estimate unknown parameters of the probability distribution. The methods are applied to job-shop scheduling problems to evaluate their impact on achieving predictive schedules. [ABSTRACT FROM AUTHOR]

A single-channel FIFO queueing model with finite buffer capacity and the multiple vacation policy is investigated, in which jobs arrive according to a compound Poisson process and are being processed individually with a general-type distribution function of the service time. A multiple vacation period, consisting of a number of independent generally-distributed server vacations, is being started each time when the system becomes empty. During this period, the processing of jobs is suspended. Successive server vacations are being initialised until at least one job is present in the buffer at the completion epoch of one of them. A compact formula for the Laplace transform of the distribution of the time to the first buffer overflow, conditioned by initial number of packets present in the buffer, is found. The analytical approach is based on the paradigm of embedded Markov chain, integral equations and Korolyuk's potential idea. Numerical illustrating examples are attached as well. [ABSTRACT FROM AUTHOR]

A model of a single-machine production system with finite magazine capacity is investigated. The input ow of jobs is organized according to geometric distribution of interarrival times, while processing times are assumed to be generally distributed. The closed-form formula for the generating function of the time to the first buffer overow distribution conditioned by the initial buffer state is found. The analytical approach based on the idea of embedded Markov chain, the formula of total probability and linear algebra is applied. The corresponding result for next buffer overows is also given. Numerical examples are attached as well. [ABSTRACT FROM AUTHOR]