Bibliometric and systemic analysis of production planning optimization

Abstract

Having good production planning is essential to companies who need to maximize the use of their resources and boost their profits. However, to formulate efficient production planning is necessary to consider many variables. That makes analytical solutions almost impossible, forcing companies to use computational methods to solve this kind of problem. Even so, because of the complexity of the problems, much computational effort is needed. In that sense, using 4.0 industry concepts, like artificial intelligence, has been helping companies formulate optimal, or near-optimal, production plans for their process in a feasible time. Since each company has different characteristics and variables, the possibilities to formulate and optimize production planning are diverse. Thus, many case studies can be carried out. Generating a huge range of research opportunities. So, this study is a survey attempting to find some of these gaps through a systemic and bibliometric analysis. To achieve this goal the methodological procedure Knowledge Development Process - Constructivist (ProKnow - C) was used. This method aims to minimize the amount of content out of alignment with the research subject. In the first search, 44,609 articles were found, and after a filtering process that prioritized scientific recognized articles and journals, only 15 articles remained. Finally, common themes among the articles and opportunities for future work were highlighted.