Effective factors on sustainability of manufacturing processes, overcoming shrinkage in improved processes

摘要

Although process owners, theorists and scholars have various viewpoints about effective ways of improvement of processes, they have consensus on two important subjects. First, process improvement activities have an extraordinary effect on increasing efficiency and second, there are barriers against consistency and maintenance of current level of improved processes. In enterprise level, it is easier to talk about problems of sustainability of processes than suggesting a formula including related factors. In this article, an abstract is presented about findings of a broad study on companies executing process improvement plans. The study aims to recognize and analyze effective factors on sustainability of improved processes, using discriminate regression and a model for sustainable improved processes. To do this, using multi criteria decision making (MCDM) and experts’ viewpoints, effective factors on sustainability of process improvement activities are determined. Then, a sixteen-factor model resulted from experts’ viewpoints is applied in the form of questionnaires to gather the related data from 75 manufacturing processes in some major Iranian companies. In this analysis, the criteria include trends and percentage of improvements. Among the sustainability factors, a formal system for recording problems has the highest effect on discrimination of sustained processes (with a high ranking level from the experts’ viewpoints). In addition, documentation and standardization of processes are in the second level from both academic and industrial professionals' viewpoints. In sustainability of manufacturing processes in the aforementioned companies, a clear picture about necessity of improvement is in the third level (albeit, from experts’ viewpoint, it’s in the fifth level). As a result, some factors such as a list of daily problems of processes, clear perception of the necessity of improvement, process monitoring and standardization are selected as independent or predictive variables with a significant effect on discrimination of two sustainability groups (as dependent variables).