dc.contributor.author | Dorda, Michal | |
dc.contributor.author | Teichmann, Dušan | |
dc.contributor.author | Graf, Vojtěch | |
dc.date.accessioned | 2020-06-18T06:26:48Z | |
dc.date.available | 2020-06-18T06:26:48Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | MM Science Journal. 2019, vol. 2019, p. 2975-2981. | cs |
dc.identifier.issn | 1803-1269 | |
dc.identifier.issn | 1805-0476 | |
dc.identifier.uri | http://hdl.handle.net/10084/139536 | |
dc.description.abstract | Queueing theory is a mathematical tool which can be applied for capacity planning and optimisation of production, manufacturing or logistics systems. One of the possible applications of queueing theory is service capacity optimisation. Let us consider that an engineering company operates m homogeneous machines. We assume that the machines are successively operating and down and times between failures and times to repair are exponentially distributed. The broken-down machines are repaired by n repairmen; we assume that n < m. In the article a mathematical model of the problem is presented; the model can be used for optimisation of the number of the repairmen with respect to costs of the system. Results obtained by the mathematical model are compared with simulation results; a simulation model of the problem is based on coloured Petri nets. | cs |
dc.language.iso | en | cs |
dc.publisher | MM Science | cs |
dc.relation.ispartofseries | MM Science Journal | cs |
dc.relation.uri | http://doi.org/10.17973/MMSJ.2019_10_201889 | cs |
dc.subject | service capacity | cs |
dc.subject | optimisation | cs |
dc.subject | queueing theory | cs |
dc.subject | simulation | cs |
dc.subject | coloured Petri nets | cs |
dc.subject | Matlab | cs |
dc.subject | CPN tools | cs |
dc.title | Optimisation of service capacity based on queueing theory | cs |
dc.type | article | cs |
dc.identifier.doi | 10.17973/MMSJ.2019_10_201889 | |
dc.rights.access | openAccess | cs |
dc.type.version | publishedVersion | cs |
dc.type.status | Peer-reviewed | cs |
dc.description.source | Web of Science | cs |
dc.description.volume | 2019 | cs |
dc.description.lastpage | 2981 | cs |
dc.description.firstpage | 2975 | cs |
dc.identifier.wos | 000532567900006 | |