Disruption Analysis - An Important Tool in Lean Production
Sammanfattning: This thesis is divided in two parts which are strongly connected. Part one deal with disruptions occurring in connection with machine down-time, quality losses and increased cycle time. The analysis is based on 10 studies, in which down-time losses in Swedish industry have been registered. In part two, the Japanese lean production concept is analysed with the aid of literature studies and studies of lean production companies in Japan and the USA. DISRUPTION ANALYSIS: The analysis of the ten field studies showed that the machines were utilised for operative work during 59% of the planned production time. Of the remaining time, 39% was taken up by maintenance related work, 24% by setting-up procedures and 20% by material-related down-time. Altogether, down-time losses represented 80% of the total losses in connection with disruptions. Cycle and quality losses constituted 14% and 6% of the total losses, respectively. Based on the down-time analysis, a general model, describing how different technical and organisational events together lead to disruptions in any manufacturing system was also developed. This model has been further developed to include a description of how connections between various disruptions arise. As an example, it is described how a quality loss automatically leads to a down-time loss. Finally, a model has been developed to simulate how reduced disruption losses effect the manufacturing capacity of a specifik manufacturing system. LEAN PRODUCTION: It is no coincidence that companies that practice lean production are successful in disruption reduction. This is a logical consequence of their industrial concept which, to a large extent, is based on the effiency gains made possible with low disruption levels. A necessary, and previously disregarded, factor within the lean production concept consists of the support systems around the more well-known tools such as "Kaizen", "SMED" (Single-Minute Exchange of Die), "QC-circles", etc. In this work, these support systems have been divided into staff-related systems, which aim at developing the competence, flexibility and motivation of the staff and visualisation systems aimed at identifying possible and actual disruptions in the manufacturing process. In conclusion, a model has been develped describing how continuous improvements, according to the Kaizen philosophy, arise from the dynamic co-operation between the support systems and the well-known improvement tools.
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