| 1. |
- Goienetxea Uriarte, Ainhoa, et al.
(author)
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An Innovative Collaboration Between Industry, University and Nonprofit Agency, for a Competitive Industry : A Swedish case
- 2011
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In: ICERI 2001. - : International Association of Technology, Education and Development, IATED. - 9788461533244 ; , s. 4154-4162
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Conference paper (peer-reviewed)abstract
- In a knowledge based economy, manufacturing industry has to continuously improve their operations, processes and develop their employees in order to remain competitive in the market.In this context, the collaboration between industry and universities becomes of vital importance. Universities and industry have traditionally maintained fairly informal or lose ways of cooperation when it comes to education. This article presents a fruitful cooperation which has been established between the University of Skövde, the Industrial Development Center in the region, IDC West Sweden AB, and the manufacturing industry.The paper describes the development, lessons learned and the outcome of more than 3 years’ experience of close collaboration between the different stakeholders. It presents a methodology, used by the consortium to help manufacturing industries to improve their competiveness using a well defined process including: a company analysis, applied education and long-term coaching. A special focus is put on a long-term commitment by all partners. This alliance has performed more than 140 company analysis, conducted applied education for more than 2500 employees from more than 120 companies and performed coaching of more than 80 companies on site. The trend is that these figures will increase over time.The established collaboration has been strengthened over this period of time by a number of shared research projects. One of these projects involves an evaluation of the impact that this presented consortium has had on the region´s industry. Lean Learning Academies is another project that has been funded by the European Union within the Lifelong Learning Program, with the aim to increase the competitiveness of European companies and enhance the employability of students.
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| 2. |
- Goienetxea Uriarte, Ainhoa, et al.
(author)
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Improved system design of an emergency department through simulation-based multiobjective-optimization
- 2014
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Conference paper (peer-reviewed)abstract
- Healthcare facilities, and especially emergency departments (ED), are usually characterized by its complexity due to the variability and stochastic nature of the processes involved in the system. The combination of different flows of patients, staff and resources also increments the complexity of this kind of facilities. In order to increase its efficiency, many researchers have proposed discrete-event simulation (DES) as a powerful improvement tool. However, DES can be a limited approach in the case a simulation model has too many combinations of input parameters, complex correlations between the input and output parameters and different objective functions. Hence, to find the best configuration of a complex system, an approach combining DES and meta-heuristic optimization becomes an even more powerful improvement technique. Simulation-based multiobjective-optimization (SMO) is a promising approach to generate multiple trade-off solutions particularly when multiple conflicting objectives exist within a complex system. The generated solutions provide decision makers with feasible and optimal alternatives to improve, modify or design healthcare systems. The aim of this paper is to present the work done at the ED of the regional Hospital of Skövde in Sweden, where SMO implemented in modeFromtier has been successfully applied. The result and methodology present a successful approach for decision makers in healthcare systems to reduce the waiting time of patients saving considerable time, money and resources.
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| 3. |
- Ng, Amos, et al.
(author)
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Factory flow design and analysis using internet-enabled simulation-based optimization and automatic model generation
- 2011
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In: Proceedings of the 2011 Winter Simulation Conference. - : IEEE conference proceedings. - 9781457721090 - 9781457721083 ; , s. 2176-2188
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Conference paper (peer-reviewed)abstract
- Despite simulation offers tremendous promise for designing and analyzing complex production systems, manufacturing industry has been less successful in using it as a decision support tool, especially in the early conceptual phase of factory flow design. If simulation is used today for system design, it is more often used in later phases when important design decisions have already been made and costs are locked. With an aim to advocate the use of simulation in early phases of factory design and analysis, this paper introduces FACTS Analyzer, a toolset developed based on the concept of integrating model abstraction, automatic model generation and simulation-based optimization under an innovative Internet-based platform. Specifically, it addresses a novel model aggregation and generation method, which when combined together with other system components, like optimization engines, can synthetically enable simulation to become much easier to use and speed up the time-consuming model building, experimentation and optimization processes, in order to support optimal decision making.
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| 4. |
- Urenda Moris, Matías
(author)
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Dealing with variability in the design, planning and evaluation of Healthcare inpatient units : a modelling methodology for patient dependency variations
- 2010
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Doctoral thesis (other academic/artistic)abstract
- This research addresses the fluctuating demand and high variability in healthcare systems. These system’s variations need to be considered whilst at the same time making efficient use of the systems’ resources. Patient dependency fluctuation, which makes determining the level of adequate staffing highly complex, is among the variations addressed. Dealing with variability is found to be a key feature in the design, planning and evaluation of healthcare systems. Healthcare providers are facing increasing challenges resulting from an aging population, higher patient expectancies, a shortage of healthcare professionals, as well as increasing costs and reduced funding. Despite the accentuated need for effective healthcare systems and efficient use of resources, many healthcare organisations are inadequately designed and, moreover, poorly managed. Hospital systems consist of complex interrelations between relatively small units, each of which is sensitive to stochastic variations in demand. In addition to this aspect of the system view, a critical resource for the patients’ wellbeing and survival is the staffing level of nurses. This puts the planning and scheduling of human resources as one of the system’s foremost aims. Current tools for staffing and personnel planning in healthcare organisations do not take into consideration the workload variations that result from the variable nature of patient dependency levels.The work presents the empirical findings of a number of case studies conducted at a regional hospital in Sweden. Principles and practical suggestions for the robust system design of inpatient wards using Discrete Event Simulation (DES) have been identified. Although DES techniques have, in principle, all the features for modelling the variation and stochastic nature of systems, DES has not been previously used for workload studies of inpatient wards. The main contribution of this work is therefore how a combination of DES and the data of Patient Classification Systems (PCSs) can be used to model workload variations and, subsequently, plan the nurse staffing requirements in systems with high variability. The work presented gives step by step guidance in how the analysis and subsequent modelling of an inpatient ward should be carried out. It defines a novel modelling methodology for patient dependency variations and length of stay modelling of a patient’s dependency progression, including an adaptation to the ward’s discharge figures. The modelling approach opens a novel way of analysing and evaluating the system design of inpatient wards.
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| 5. |
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| 6. |
- Urenda Moris, Matías, et al.
(author)
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Diseño Y Análisis De Sistemas Productivos Utilizando La Optimización Mediante Simulación Basado En Internet
- 2012
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In: Ingenieria Industrial. - : Universidad del Bio-Bio. - 0717-9103 .- 0718-8307. ; 11:1, s. 37-49
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Journal article (other academic/artistic)abstract
- Los ingenieros de producción buscan contínuamente configuraciones óptimas de sus sistemas productivos, con el fin de alcanzar el máximo rendimiento en los mismos. Este es un trabajo que consume mucho tiempo en la industria, y rara vez se le conceden los recursos necesarios para que las decisiones a tomar sean las acertadas. Para poder tomar estas decisiones de una manera más eficiente, es necesario disponer de herramientas nuevas e innovadoras.Este artículo presenta la segunda generación de FACTS Analyzer, una herramienta cuya función se basa en la integración de una variedad de metodologías y técnicas, incluyendo: el modelado rápido por medio de un nuevo concepto de agregación y funciones simplificadas, la generación de modelos de simulación de manera automática y optimización mediante simulación apoyada por una innovadora arquitectura basada en Internet. Dichas metodologías y técnicas permiten que la simulación sea mucho más fácil de utilizar, y aceleran el tiempo de diseño y desarrollo de modelos, la fase de experimentación y los procesos de optimización, con el fin de apoyar el proceso de toma de decisiones. FACTS Analyzer es el resultado de varios años de investigación y desarrollo, en estrecha colaboración con la industria automotriz en Suecia.
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