Production flow analysis includes various families of components and groups of machines. Machine-part cell formation means the optimal design of manufacturing cells consisting of similar machines producing similar products from a similar set of components. Most of the algorithms reorders of the machine-part incidence matrix. We generalize this classical concept to handle more than two elements of the production process (e.g. machine - part - product - resource - operator). The application of this extended concept requires an efficient optimization algorithm for the simultaneous grouping these elements. For this purpose, we propose a novel co-clustering technique based on crossing minimization of layered bipartite graphs. The present method has been implemented as a MATLAB toolbox. The efficiency of the proposed approach and developed tools is demonstrated by realistic case studies. The log-linear scalability of the algorithm is proven theoretically and experimentally.
|Number of pages||20|
|Journal||Acta Polytechnica Hungarica|
|Publication status||Published - 2016|
ASJC Scopus subject areas