Development of a two-stage network data envelopment analysis (DEA) model to analyze production line's performance : combination of automation and labor

• Main Author: Nik Afieza, Che Azhar
• Format: Thesis
• Language: English
• Published: 2016
• Subjects: T Technology (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/16698/16/Development%20of%20a%20two-stage%20network%20data%20envelopment%20analysis%20%28DEA%29%20model%20to%20analyze%20production%20line%27s%20performance%20%20combination%20of%20automation%20and%20labor.pdf; http://umpir.ump.edu.my/id/eprint/16698/

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 without proper production line evaluation. In this research, we studied the effectiveness of production Jine that equipped with combination between automation usage and labor to determine the productivity and quality of the production line. Then, compare those production line with production line that use labor energy. 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. Therefore, the model of Two-Stage Network DEA was developed in order to measure those production line in different stages. As a result, the evaluation of data through this model will show all the effectiveness of the production line. The model will benefit the related industries in their performance by show the efficiency of each production line then company can make improvement toward those inefficient production line.