Case study on lean manufacturing system implementation in batch printing industry Malaysia

• Main Authors: Tang, Sai Hong, Ng, Tan Ching, Chong, Wei Jian, Chen, Kah Pin
• Format: Conference or Workshop Item
• Language: English
• Published: EDP Sciences 2016
• Online Access: http://psasir.upm.edu.my/id/eprint/50088/1/matecconf_icmit2016_05002.pdf; http://psasir.upm.edu.my/id/eprint/50088/; http://www.matec-conferences.org/articles/matecconf/abs/2016/33/matecconf_icmit2016_05002/matecconf_icmit2016_05002.html
• Institution: Universiti Putra Malaysia

Lean Manufacturing is a popular tool to be implemented in printing industry fields for the purpose of achieving the successful production goals and it is a well-organized method used to eliminate the waste or non-value added activities. Lean Manufacturing consists of several tools like 5S, TPM, Kanban, Kaizen and others. In this paper, the researcher is focus on TPM (Total Productive Maintenance). TPM is a concept used for maintaining plants and equipment with the involvement of all employees in the company in order to increase the overall equipment effectiveness (OEE). In this paper, the researcher will identify the problem faced in company’s production line and then implement lean tools in order to improve the productivity. Afterward, the researcher will carry out time study on company’s production line. The purpose of time study is to getting the result for OEE and the time taken for producing one piece of product. The researcher is then designed and suggested one-piece flow system to the management with showing the result on simulation that getting improvement in productivity. The result was simulated by using Flexsim and shows that 7.59 seconds was saved in producing one piece of calendar. At the end, the result shows that OEE increase from 34.3% to 60% and the company total save around 6 hours per month by implement one-piece flow. At last, by verifying the distribution of collected data, the researcher will perform Anderson Darling Normality test to ensure the distribution of data are normal.