Service Capacity Reserve under Uncertainty by Hospital’s ER Analogies: A Practical Model for Car Services

We define a capacity reserve model to dimension passenger car service installations according to the demographic distribution of the area to be serviced by using hospital’s emergency room analogies. Usually, service facilities are designed applying empirical methods, but customers arrive under uncer...

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Main Authors: Miguel Ángel Pérez Salaverría, José Manuel Mira McWilliams
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2014/586236
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spelling doaj-2b1d33966c1946fe8151a61b0c055d802020-11-24T23:41:42ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472014-01-01201410.1155/2014/586236586236Service Capacity Reserve under Uncertainty by Hospital’s ER Analogies: A Practical Model for Car ServicesMiguel Ángel Pérez Salaverría0José Manuel Mira McWilliams1Jaguar Land Rover SLU, Torre Picasso, Plaza Pablo Ruiz Picasso 1, Planta 42, Complejo Azca, 28020 Madrid, SpainUniversidad Politécnica de Madrid, Avenida Ramiro de Maeztu 7, 28040 Madrid, SpainWe define a capacity reserve model to dimension passenger car service installations according to the demographic distribution of the area to be serviced by using hospital’s emergency room analogies. Usually, service facilities are designed applying empirical methods, but customers arrive under uncertain conditions not included in the original estimations, and there is a gap between customer’s real demand and the service’s capacity. Our research establishes a valid methodology and covers the absence of recent researches and the lack of statistical techniques implementation, integrating demand uncertainty in a unique model built in stages by implementing ARIMA forecasting, queuing theory, and Monte Carlo simulation to optimize the service capacity and occupancy, minimizing the implicit cost of the capacity that must be reserved to service unexpected customers. Our model has proved to be a useful tool for optimal decision making under uncertainty integrating the prediction of the cost implicit in the reserve capacity to serve unexpected demand and defining a set of new process indicators, such us capacity, occupancy, and cost of capacity reserve never studied before. The new indicators are intended to optimize the service operation. This set of new indicators could be implemented in the information systems used in the passenger car services.http://dx.doi.org/10.1155/2014/586236
collection DOAJ
language English
format Article
sources DOAJ
author Miguel Ángel Pérez Salaverría
José Manuel Mira McWilliams
spellingShingle Miguel Ángel Pérez Salaverría
José Manuel Mira McWilliams
Service Capacity Reserve under Uncertainty by Hospital’s ER Analogies: A Practical Model for Car Services
Mathematical Problems in Engineering
author_facet Miguel Ángel Pérez Salaverría
José Manuel Mira McWilliams
author_sort Miguel Ángel Pérez Salaverría
title Service Capacity Reserve under Uncertainty by Hospital’s ER Analogies: A Practical Model for Car Services
title_short Service Capacity Reserve under Uncertainty by Hospital’s ER Analogies: A Practical Model for Car Services
title_full Service Capacity Reserve under Uncertainty by Hospital’s ER Analogies: A Practical Model for Car Services
title_fullStr Service Capacity Reserve under Uncertainty by Hospital’s ER Analogies: A Practical Model for Car Services
title_full_unstemmed Service Capacity Reserve under Uncertainty by Hospital’s ER Analogies: A Practical Model for Car Services
title_sort service capacity reserve under uncertainty by hospital’s er analogies: a practical model for car services
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2014-01-01
description We define a capacity reserve model to dimension passenger car service installations according to the demographic distribution of the area to be serviced by using hospital’s emergency room analogies. Usually, service facilities are designed applying empirical methods, but customers arrive under uncertain conditions not included in the original estimations, and there is a gap between customer’s real demand and the service’s capacity. Our research establishes a valid methodology and covers the absence of recent researches and the lack of statistical techniques implementation, integrating demand uncertainty in a unique model built in stages by implementing ARIMA forecasting, queuing theory, and Monte Carlo simulation to optimize the service capacity and occupancy, minimizing the implicit cost of the capacity that must be reserved to service unexpected customers. Our model has proved to be a useful tool for optimal decision making under uncertainty integrating the prediction of the cost implicit in the reserve capacity to serve unexpected demand and defining a set of new process indicators, such us capacity, occupancy, and cost of capacity reserve never studied before. The new indicators are intended to optimize the service operation. This set of new indicators could be implemented in the information systems used in the passenger car services.
url http://dx.doi.org/10.1155/2014/586236
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AT josemanuelmiramcwilliams servicecapacityreserveunderuncertaintybyhospitalseranalogiesapracticalmodelforcarservices
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