The Assembly lines typically employ dozens and sometime hundreds of workers. So absenteeism and turnover are encountered daily in these lines. This research analyzes the impact of absenteeism and turnover in assembly and production lines of mixed model mass production. It shows that model sequencing policy has very significant effect on the line's throughput. Replacing an experienced absent worker by a new one in a station results in a learning curve of the new worker. The new worker starts slowly and has a good chance of becoming a bottle-neck and dictating the pace for all the line. In that case, the throughput at the end of the line mirrors the new worker learning curve. In mixed model assembly lines the work in some stations varies according to the arriving model. A new replacement worker at such a station has slower learning process due to the less repetitive work. Still, there are typically many work elements that are common to all the models; there may be work elements that are only missing in one model, etc. We show how to compute the station's learning curve in such cases. A small case study shows that sustitute workers generate smaller throughput on mixed model lines than on a single model line.
The Combined Effect of Multiple Models Sequencing and Absenteeism/Turnover on the Throughput of Assembly Lines
FACCIO, MAURIZIO
2012
Abstract
The Assembly lines typically employ dozens and sometime hundreds of workers. So absenteeism and turnover are encountered daily in these lines. This research analyzes the impact of absenteeism and turnover in assembly and production lines of mixed model mass production. It shows that model sequencing policy has very significant effect on the line's throughput. Replacing an experienced absent worker by a new one in a station results in a learning curve of the new worker. The new worker starts slowly and has a good chance of becoming a bottle-neck and dictating the pace for all the line. In that case, the throughput at the end of the line mirrors the new worker learning curve. In mixed model assembly lines the work in some stations varies according to the arriving model. A new replacement worker at such a station has slower learning process due to the less repetitive work. Still, there are typically many work elements that are common to all the models; there may be work elements that are only missing in one model, etc. We show how to compute the station's learning curve in such cases. A small case study shows that sustitute workers generate smaller throughput on mixed model lines than on a single model line.
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
