Open AccessApplying value stream mapping tools and kanban system for waste identification and reduction (case study: a basic chemical company)
Author(s) -
Wilson Kosasih,
Iphov Kumala Sriwana,
Emelia Sari,
Carla Olyvia Doaly
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/528/1/012050
Subject(s) - value stream mapping , kanban , supply chain , process engineering , computer science , process (computing) , identification (biology) , lead time , waste stream , industrial engineering , environmental science , operations management , operations research , lean manufacturing , engineering , waste management , business , artificial intelligence , botany , control (management) , marketing , biology , operating system
This paper describes how to apply both of value stream mapping tools and kanban system for identifying and reducing wastes that happened on shop-floor. This research was conducted at a basic chemical company which produces the thinner. This study aims to reduce even to eliminate the types of waste that occur on the production line of jerrycan product type. The plot of VSM is used to picture the entire of value stream. The value stream mapping tools are used to analyze the certain waste after it has been figured out by using waste assessment model. Hence in this study two selected tools were applied and discussed further, i.e. process activity mapping, and supply chain response matrix. The Current-VSM shown that value-added time of 472.33 s compared with total lead time of 132,568.76 s, consequently obtained process cycle efficiency (PCE) approximately 0.36%. Kanban system will be implemented to eliminate waste of unnecessary inventory throughout the value stream. At last, the result of improvements shown that value of PCE probably will increase by 67.25%, non-value activity will reduce 6.74%, as well as order fulfillment time of the whole process will be 13 days with 3.59 days of physical stock.