Development of Two-Stage Network Data Envelopment Analysis (DEA) Model to Measure Production Line’s Performance: Combination of Automation and Labor

• Main Authors: N.A., Che Azhar, Muhamad Arifpin, Mansor, S. A., Rusdan, S. N., M. Saffe
• Format: Article
• Language: English
• Published: Penerbit Universiti Malaysia Pahang 2016
• Subjects: HD28 Management. Industrial Management
• Online Access: http://umpir.ump.edu.my/id/eprint/16170/1/ftek-2016-6.pdf; http://umpir.ump.edu.my/id/eprint/16170/; http://ijets.ump.edu.my/images/archive/Vol6/6.pdf
• Institution: Universiti Malaysia Pahang

Nowadays, the growth of industry can be seen as a nature of the world. Each company race again each other to increase productivity to produce new, high quality and product that fulfil customer demand. One can achieve the Key Performance Indicator (KPI) or targeted goal but without considering the cost, manpower, time or others elements is inefficient toward productivity. Upgrade production line in manufacturing industry needs huge investment to come out with good performance. The company can receive Return of Investment (ROI) and save more money from paying labor salary and increase productivity. However, the company also may have the risk of losing their money from the investment done. In this research, we studied the effectiveness of production line that equipped with automation usage to determine the productivity and quality of the product produced. We apply Data Envelopment Analysis (DEA) to measure efficiencies of the production line where DEA is one of an excellent tool that can evaluate efficiencies and have been using widely in many sectors. The model that will be used in this study is Two-Stage Network DEA. As a case study, this research focuses on the production line that producing a product with a high and continues demand to observe how the investment on automation can give good return or otherwise.