71 research outputs found
A tool for helping operations research
This paper describes an integrated environment in which a student can acquire and test knowledge about Operations Research techniques. In this environment all the interactions with the users are performed by means of an appropriated graphical interface related to the problem and the algorithm chosen to solve it During a step-by-step problem solving session, the user makes the decisions and lets the system process the necessary computations. Moreover, this environment is able: (i) to check the correctness of the user's replies, (ii) to display warnings every time a wrong decision is taken, and (iii) to return to any previous step in order to give more flexibility to the teacher's exposition. The system is designed to include: Primal Simplex, Dual Simplex, Revised Simplex, Stepping-Stone Method for Transportation Problems, Hungarian Method for Assignment Problems, and Sensitivity Analysis
VSSI (X)over-bar charts with sampling at fixed times
A standard (X) over bar chart for controlling the process mean takes samples of size no at specified, equally-spaced, fixed-time points. This article proposes a modification of the standard (X) over bar chart that allows one to take additional samples, bigger than no, between these fixed times. The additional samples are taken from the process when there is evidence that the process mean moved from target. Following the notation proposed by Reynolds (1996a) and Costs (1997) we shortly call the proposed (X) over bar chart as VSSIFT (X) over bar chart: where VSSIFT means variable sample size and sampling intervals with fixed times. The (X) over bar chart with the VSSIFT feature is easier to be administered than a standard VSSI (X) over bar chart that is not constrained to sample at the specified fixed times. The performances of the charts in detecting process mean shifts are comparable
(X)over-bar charts with variable parameters
Varying the parameters of the (X) over bar chart has been explored extensively in recent years. In this paper, we extend the study of the (X) over bar chart with variable parameters to include variable action limits. The action limits establish whether the control should be relaxed or not. When the (X) over bar falls near the target, the control is relaxed so that there will be more time before the next sample and/or the next sample will be smaller than usual. When the (X) over bar falls far from the target but not in the action region, the control is tightened so that there is less time before the next sample and/or the next sample will be larger than usual. The goal is to draw the action limits wider than usual when the control is relaxed and narrower than usual when the control is tightened. This new feature then makes the (X) over bar chart more powerful than the CUSUM scheme in detecting shifts in the process mean
Joint (X)over-bar and R charts with variable sample sizes and sampling intervals
Recent studies have shown that the (X) over bar chart with variable sampling intervals (VSI) and/or with variable sample sizes (VSS) detects process shifts faster than the traditional (X) over bar chart. This article extends these studies for processes that are monitored by both the (X) over bar and R charts. A Markov chain model is used to determine the properties of the joint (X) over bar and R charts with variable sample sizes and sampling intervals (VSSI). The VSSI scheme improves the joint (X) over bar and R control chart performance in terms of the speed with which shifts in the process mean and/or variance are detected
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