تغییرات فرایند تولید: یک روش برنامه ریزی پویا برای مدیریت ظرفیت و تجربه موثر
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|25338||2006||9 صفحه PDF||سفارش دهید||5000 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Production Economics, Volume 104, Issue 2, December 2006, Pages 473–481
The introduction of process changes is often used by management to invest in production competencies. However, implementing process changes causes disturbances in production learning. This work describes a process change strategy to increase the effective capacity of a production system when unit costs are subject to a learning curve. It is found that the optimal process change level is decreasing in the effective capacity level and increasing in the accumulated knowledge level and production learning rate. Conditions are provided under which the optimal process change level is larger/smaller than the myopic process change level.
Manufacturing departments of electronics firms deal with complex and knowledge-intensive production processes. In these environments frequent introductions of changes to the process recipe can be observed. Examples of incremental process changes are equipment changes, implementation of software to support manufacturing, procedural changes, etc. Empirical research shows that such process change implementations are responsible for important jumps backward on the learning curve. Adler and Clark (1991) show that process changes caused by changes of the product have a disruptive effect on learning through sustained production activities. Marcie and Hauptman (1992) worked on the idea that the introduction of important process changes such as a new technology, is a source of uncertainty and as such disturbances. The two problematic attributes identified from the implementation and usage of new technology: the technical complexity and the shift in production approaches and organizing principles involved in using the new technology. Hatch and Mowery (1998) find that the disruptive effects of the introduction of process innovations on learning for the existing process in the semi-conductor industry are significant. Lapre et al. (2000) report that process changes due to quality improvement projects without preparation of the work force, disturb the process of waste reduction in production. Terwiesch and Xu (2004) argue that if process specifications are changed and introduced in the production environment, line workers have to adjust to the new situation: behavioural patterns have to be adjusted and new operating procedures have to be developed to cope with the new environment. As indicated by these authors, the implementation of a process change makes some of the accumulated production knowledge such as operating procedures obsolete. New operating procedures have to be developed to handle the modified process recipe. The more significant a process change is, the larger the decrease of the accumulated production knowledge.
نتیجه گیری انگلیسی
In this paper a multi-period decision model is introduced for a decision-maker that parameterises the environment with the level of production experience and the level of effective capacity of the production system. By choosing the process change level every period, the decision-maker maximises the profit of operating the production system. With an infinite planning horizon and for process changes with instantaneous effects on the knowledge level and effective capacity level, an optimal policy will not always invest more in process change than a myopic policy. For a finite planning horizon, dependent on the difference in salvage value of capacity versus knowledge, an optimal policy will invest more or less in process change than a myopic policy. The myopic process change level is increasing in the knowledge level and decreasing in the effective capacity level. The optimal process change level is increasing in the knowledge level and production learning rate and decreasing in the effective capacity level. Further research will try to describe the structure of the optimal policy more precise through analysis of stability. Also the effects of the initial level of effective capacity and knowledge on the state sequences are interesting to analyse. A natural extension is the inclusion of random shocks or risk on the effect of the process change level on the knowledge level or effective capacity level. Another extension is observation noise on the knowledge level.