Implementation of Production Planning and Scheduling - A Data Mining Approach

M. S. Kalas, Nikita D. Deshpande

Abstract: According to experience, raw material management is a major operational difficulty in the business. The importance of raw materials to the efficient operation of a manufacturing organization cannot be emphasized; the right quality and quantity are critical. Planning and production include determining the level of activity, turn - over, and final profit in a corporation, as well as minimum and maximum stock levels. Raw material management in a manufacturing organization requires specific care and scrutiny in order to achieve uninterrupted production cycles and better operational performance. Maintaining an acceptable stock level can also enhance the amount of available operating capital that can be put to better use. Material management is defined as the coordination of efforts (planning, managing, organizing, and directing) aimed at achieving efficiency in a manufacturing organization's procurement, transportation, stocking, and utilization of inputs. The effectiveness and efficiency of material management have a direct impact on the organization's overall success. This study provides a literature review on data mining definitions as well as a categorization of existing techniques to using data mining to manage production complexity in order to assist manufacturing organizations in implementing data mining.

Keywords: Data Mining, Hierarchical Clustering Algorithm and Association Rule

How to Cite?: M. S. Kalas, Nikita D. Deshpande, "Implementation of Production Planning and Scheduling - A Data Mining Approach", Volume 11 Issue 6, June 2022, International Journal of Science and Research (IJSR), Pages: 1120-1126, https://www.ijsr.net/getabstract.php?paperid=SR22603081404, DOI: https://dx.doi.org/10.21275/SR22603081404