19 research outputs found
Manufacturing decisions under uncertainty : models and methodology
Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 1989.Includes bibliographical references.by Sriram Dasu.Ph.D
Reducing overcrowding in an emergency department: a pilot study
OBJETIVO
Explorar o uso de modelos de previsão e ferramentas de simulação para estimar a demanda e reduzir o tempo de espera dos pacientes em Departamentos de Emergência (DE).
METODOLOGIA
A análise foi baseada em dados coletados em maio de 2013, no DE do Recanto das Emas, Distrito Federal, Brasil, que utiliza o Protocolo de Manchester como sistema de triagem. Um total de 100 pacientes consecutivos foram incluídos: 70 amarelos (70%) e 30 verdes (30%). Padrões de fluxo, tempo de espera observado e tempos entre as chegadas dos pacientes foram registrados. Mapas de processo, demanda e dados de capacidade foram utilizados na construção de uma simulação que foi calibrada de acordo com o fluxo observado. Uma análise do tipo “e se...” foi conduzida para reduzir os tempos de espera.
RESULTADOS
Os padrões de tempo de chegada para pacientes verdes e amarelos foram semelhantes, mas os tempos entre chegadas foram 5 e 38 minutos, respectivamente. O tempo de espera foi de 14 minutos para pacientes amarelos e 4 horas para pacientes verdes. A equipe médica era composta por quatro médicos por turno. Uma simulação previu que a inclusão de mais um médico por turno reduziria o tempo de espera para 2,5 horas para pacientes verdes, com um impacto pequeno no tempo de espera dos pacientes amarelos. A manutenção de quatro médicos e a inclusão de um médico exclusivamente para pacientes verdes reduziria o tempo de espera para 1,5 horas para pacientes verdes e aumentaria em 15 minutos para os pacientes amarelos. O melhor cenário simulado utilizou cinco médicos por plantão, com dois médicos exclusivos para pacientes verdes.
CONCLUSÃO
Os tempos de espera podem ser reduzidos equilibrando a distribuição de médicos para pacientes verdes e amarelos e relacionando a disponibilidade dos médicos aos padrões de demanda previstos. Simulações de DE podem ser utilizadas para gerar e testar soluções para diminuir a superlotação.OBJECTIVE
Exploring the use of forecasting models and simulation tools to estimate demand and reduce the waiting time of patients in Emergency Departments (EDs).
METHODS
The analysis was based on data collected in May 2013 in the ED of Recanto das Emas, Federal District, Brasil, which uses a Manchester Triage System. A total of 100 consecutive patients were included: 70 yellow (70%) and 30 green (30%). Flow patterns, observed waiting time, and inter-arrival times of patients were collected. Process maps, demand, and capacity data were used to build a simulation, which was calibrated against the observed flow times. What-if analysis was conducted to reduce waiting times.
RESULTS
Green and yellow patient arrival-time patterns were similar, but inter-arrival times were 5 and 38 minutes, respectively. Wait-time was 14 minutes for yellow patients, and 4 hours for green patients. The physician staff comprised four doctors per shift. A simulation predicted that allocating one more doctor per shift would reduce wait-time to 2.5 hours for green patients, with a small impact in yellow patients’ wait-time. Maintaining four doctors and allocating one doctor exclusively for green patients would reduce the waiting time to 1.5 hours for green patients and increase it in 15 minutes for yellow patients. The best simulation scenario employed five doctors per shift, with two doctors exclusively for green patients.
CONCLUSION
Waiting times can be reduced by balancing the allocation of doctors to green and yellow patients and matching the availability of doctors to forecasted demand patterns. Simulations of EDs’ can be used to generate and test solutions to decrease overcrowding
The Customer Service Solution: Managing Emotions, Trust, and Control to Win Your Customer's Business
Class dependent departure process from multiclass phase queues: Exact and approximate analyses
A Review of Open Queueing Network Models of Manufacturing Systems
In this paper we review open queueing network models of manufacturing systems. The paper consists of two parts. In the first part we discuss design and planning problems arising in manufacturing. In doing so we focus on those problems that are best addressed by queueing network models. In the second part of the paper we describe the developments in queueing network methodology. We are primarily concerned with features such as general service times, deterministic product routings, and machine failures- features that are prevalent in manufacturing settings. Since these features have eluded exact analysis, approximation procedures have been proposed. In the second part of this paper we review the developments in approximation procedures and highlight the assumptions that underlie these approaches. A significant development in the study of queueing network models is the discovery (empirical) that under conditions that are not very restrictive in practice: (i) equilibrium expected queue lengths behave as if they are convex functions of the processing rate of the server, and (ii) altering the processing rate at one station has minimal effect on the equilibrium expected queue lengths at other stations in the network. As a result researchers have been able to approximate some of the optimal design problems by convex programs. In the second part of this paper we describe these developments. Inspite of the advances made in the analysis of open queueing networks, several of the problems described in the first part of the paper cannot be analyzed without further progress in 2 methodology. One of the objectives of this paper is to expose the gap between the problems arising in manufacturing and the analytical tools that are currently available. We hope that by first describing the problems and then discussing the methodological developments the gap becomes apparent to the reader
Dynamic pricing when consumers are strategic: Analysis of posted and contingent pricing schemes
We study dynamic pricing policies for a monopolist selling perishable products over a finite time horizon to strategic buyers. Buyers are strategic in the sense that they anticipate the firm's price policies. It is expensive and administratively difficult for most brick and mortar retailers to change prices, placing limits on the number of price changes and the types of pricing policies they can adopt. The simplest policy is to commit to a set of price changes. A more complex alternative is to let the price depend on sales history. We investigate two pricing schemes that we call posted and contingent pricing. Using the posted pricing scheme, the firm announces a set of prices at the beginning of the horizon. In the contingent pricing scheme, price evolution depends upon demand realization. Our focus is on the posted pricing scheme because of its ease of implementation. Counter to intuition, we find that neither a posted pricing scheme nor a contingent pricing scheme is dominant and the difference in expected revenues of these two schemes is small. Limiting the number of price changes will result in a decrease in expected revenues. We show that a multi-unit auction with a reservation price provides an upper bound for expected revenues for both pricing schemes. Numerical examples suggest that a posted pricing scheme with two or three price changes is enough to achieve revenues that are close to the upper bound. Dynamic pricing is only useful when strategic buyers perceive scarcity. We study the impact of scarcity and derive the optimal stocking levels for large markets. Finally, we investigate whether or not it is optimal for the seller to conceal inventory or sales information from buyers. A firm benefits if it does not reveal the number of units it has available for sale at the beginning of the season, or subsequently withholds information about the number of units sold.Revenue management Dynamic pricing Customer strategic behavior
Optimal Operating Policies in the Presence of Exchange Rate Variability
We study the structure of the optimal policies for a firm operating plants in different countries. The relative costs of production between the plants are assumed to vary over time due to economic and political factors such as exchange rates, inflation, taxes, and tariffs. Based on the costs, the firm can alter the quantity produced in each plant. We determine the structure of the optimal policies for deciding when and by how much to alter the production quantities. When the switch-over costs are linear or step functions, regardless of whether the variable production costs are concave or piece-wise linear convex, and regardless of whether the firm is supplying one or more markets, the optimal policy is always a barrier policy. The optimal barriers can be determined by using linear programming techniques, and the optimal costs can be computed by solving a system of linear equations. When the number of optimal barriers is two, the optimal expected costs and the condition that determines the optimal barriers are explicitly derived.international operations, exchange rate variability, optimal policies, setup costs, synthetic fiber industry
A review of the open queueing network models of manufacturing systems
HD28 .M414 no.3229-, 90,
Optimizing an International Network of Partially Owned Plants Under Conditions of Trade Liberalization
For the last four decades the preferred economic philosophy in much of Latin America was that of import-substituting industrialization. As a result multinational corporations (MNCs) approached different countries with the expectation that each plant would primarily serve its domestic market. Each of these plants was partially owned by the MNC. Beginning in the late 1980s, Latin America countries began decreasing barriers to cross-border trade. This made competition between the units belonging to a common network possible for the first time. Operations which had subsisted side by side in spite of differences in costs and quality of output, and which were under the control of different owners now found themselves in competition with one another and having to rationalize their efforts. In this paper we analyze the problem of operating a network of plants under conditions of free trade and exchange rate fluctuations, when the firms that compose it are partially-owned subsidiaries of an MNC. A model of three subsidiaries and four countries is developed for one industry, based on actual corporate and economic data. We study the problem of coordinating the activities of the subsidiaries and allocating the gains arising from coordination.international operations, multiplant networks, synthetic fiber industry, Latin America
The Dynamic Line Allocation Problem
Consider a plant that has information about the arrival schedule of its "inputs" over a planning cycle. The plant has parallel production lines for processing multiple types of products. However, changeover cost and changeover time are incurred when a line changes from processing one type of products to a different type of products. We present a dynamic line allocation problem that determines an optimal line allocation so that the total relevant cost (changeover and waiting costs) is minimized. In this paper we analyze the complexity of the problem and develop three different heuristics for generating near-optimal allocations.production planning, setup/changeover operation, resource allocation, heuristic