An alternative work measurement method and its application to a manufacturing industry

• Published in: Journal of loss prevention in the process industries 2011-09, Vol.24 (5), p.563-567
• Main Authors: Dağdeviren, Metin, Eraslan, Ergün, Çelebi, Fatih V.
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Artificial neural network; Artificial neural networks; Manufacturing; Mathematical models; Neural networks; Productivity measurement; Standard data; Time measurement; Time study; Work measurement
• ISSN: 0950-4230; 1873-3352
• DOI: 10.1016/j.jlp.2010.06.017

Difficulties in determining the standard time justify the need to develop alternative methods to direct measurement procedures. The indirect methods which are comparison and prediction, standard data and formulation, predefined movement-time systems have several deficiencies in time measurement procedures. In this study, an alternative indirect work measurement method based on artificial neural networks (ANNs) is presented which is simple and inexpensive. For the application of the proposed method, the products that have similar production processes are selected among the whole product family produced in a manufacturing company. The standard times of the sampled products that are previously measured are used and the standard times of the remaining several products and semi-products are predicted by the proposed method. The model results show that the proposed method can be applied accurately in companies which produce similar products.