Nuestros investigadores

Mikel Arcelus Alonso

Publicaciones científicas más recientes (desde 2010)

Autores: García, M.P.; Santos, Javier; Arcelus, Mikel; et al.
Revista: IFIP ADVANCES IN INFORMATION AND COMMUNICATION TECHNOLOGY
ISSN 1868-4238  Vol. 384  2012  págs. 132 -139
Autores: Martinez-Miguelez, S.; Errasti, Ander; Arcelus, Mikel;
Revista: DYNA
ISSN 0012-7361  Vol. 87  Nº 3  2012  págs. 286 - 294
The need to compete in a global economy has forced companies to internationalize their operations. The design and configuration of purchasing, manufacturing, supplying and distributing global operations become a key strategy to align operations strategy with business strategy. The operations strategy formulation must respond to manufacturing location facility, supply strategy, facility strategic role in the global network design, integration or fragmentation of productive and logistic operations, and suppliers and distribution network design in order to carry out the internationalization process in a successful and reliable way. This paper focuses on one of the most complex decisions such as the supply strategy. The authors based on a case study developed with a manufacturer of electric generators for the wind sector, they propose a methodology supported on the use of simulation tools such as DGRAI and discrete event simulation to solve the supply strategy problem. The method and proposed techniques utilization allow increasing sales due to the implementation speed and a better service quality to strategic customers.
Autores: Santos, Javier; Romero, Rodrigo; Arcelus, Mikel; et al.
Revista: INTERNATIONAL JOURNAL OF INFORMATION AND OPERATIONS MANAGEMENT EDUCATION
ISSN 1744-2303  Vol. 4  Nº 1  2011  págs. 69 - 82
In this paper, the use of a graphical simulator called TOCNUN is presented. It helps users to understand plant operations conducted under the philosophy of Theory of Constraints (TOC) developed by Goldratt. TOCNUN is an alternative tool developed to support the teaching of TOC in just six or seven steps, which correspond to six or seven, 90-min learning sessions, including theory. This paper illustrates the structure for practical sessions that should be carried out with the simulator. Finally, validation input from undergraduate students and company managers is presented.
Autores: Santos, Javier; Tanco, Pablo Martín; Errasti, Ander; et al.
Revista: MEMORIA DE TRABAJOS DE DIFUSION CIENTIFICA Y TECNICA
ISSN 1510-7450  Vol. 9  2011  págs. 33 -43
Autores: Santos, Javier; García, M.P.; Arcelus, Mikel; et al.
Revista: INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
ISSN 0951-192X  Vol. 24  Nº 4  2011  págs. 338 - 351
Equipment efficiency can be measured and improved by the availability, performance and quality rates provided by the overall equipment effectiveness (OEE) metric. Because today's managers operate in a complex manufacturing scenario, measurement systems play an important role in transforming data into decisions, and this task needs to be strengthened. Although sophisticated equipment and information technology systems are available, a methodology is required for understanding and managing data in order to make timely decisions regarding improvement. Thus, improvement needs to be supported by an easy-to-understand measurement system and a cutting-edge data-collecting technique. In order to assist not only managers and operators but also students and academia, this article presents a Plug&Lean system supported by a core element, the Plug&Lean wireless device, based on total productivity maintenance (TPM) and Lean methodology for providing a reliable diagnosis of the current state of equipment, to display graphical information about the equipment performance constraints towards to direct improvements activities. The aim of the Plug and Lean wireless device is to collect accuracy data with less effort from production equipment Two case studies are discussed to illustrate the applicability of the system.
Autores: Garcia, M.P.; Santos, Javier; Arcelus, Mikel; et al.
Libro:  Advances in Production Management Systems. Value Networks: Innovation, Technologies, and Management
2012  págs. 132 - 139
Manufacturers have the challenge to increase productivity given complex manufacturing environments. A source that provides substantial levels of productivity is the overall equipment effectiveness (OEE) metric, which is an indicator to improve not only equipment utilization; but also the overall manufacturing operations, because of the valuable information that comes from the availability, performance and quality rates. Although information technologies have been introduced, companies use manually recorder data and have complicated measurement procedures. As a consequence, inaccurate information is generated and opportunities to improve productivity are missed. This paper presents a continuous improvement framework based on Lean manufacturing philosophy, operated by a system of wireless devices to support the real time equipment performance metrics. In order to validate the framework, results of a case study are exposed.
Autores: García, M.P.; Santos, Javier; Arcelus, Mikel; et al.
Libro:  Industrial engineering: innovative networks.
Vol. 28  2011  págs. 247 - 257
Manufacturers continue facing the never ending challenge of finding the best way to increase productivity levels in order to remain competitive. Significant level of productivity are given by the efficient utilization of production equipment, thus manufacturing companies use the overall equipment effectiveness (OEE) rate as an indicator to control equipment utilization related to the maintenance activity; however they do not take into account other valuable OEE-information to improve their entire manufacturing operations. This paper presents a continuous improvement model Plug&Lean-CiMo, whose aims are the accurate calculation of the OEE indicators, the appropriate classification of losses, and the systematic integration of lean manufacturing philosophy tools in an improvement methodology. The model has the advantage of using a portable wireless system to support the automated collection, of data to make the continuous improvement process easier. A case study is presented to illustrate the validation of the model.