An alternative approach to experimentation and data analysis

• Main Author: Wahid, Zaharah
• Format: Conference or Workshop Item
• Language: English; English
• Published: 2012
• Subjects: QA Mathematics; T55.4 Industrial engineering.Management engineering.; T57 Applied mathematics. Quantitative methods. Operation research. System analysis
• Online Access: http://irep.iium.edu.my/27499/1/2212C.pdf; http://irep.iium.edu.my/27499/4/dr.zaharah.pdf; http://irep.iium.edu.my/27499/
• Institution: Universiti Islam Antarabangsa Malaysia

Our knowledge about a product, process or a system in the scientific and engineering disciplines is often obtained from experimentation. Experiments can discover many unexpected things and highlighted issues for further detailed study. The emerging of advanced products and processes are changing rapidly, customers are more demanding and product life-cycle and time to market are shrinking. In this environment engineers and scientists need a strategic approach to overcome this demand. DOE is the answer to these challenges. It allows a researcher to understand what happen to the output (response) when the settings of the input variables in a system are purposely changed. As a result these changes permit work to be done better, faster, and easier. In addition, DOE has proven to be extremely useful tool in research and industrial development applications. Unfortunately there are many scientists and engineers still practice the study one factor-at a-time (OFAT). DOE offers a number of advantages over the traditional OFAT approach to experimentation. One of the important advantages of DOE is that it has the ability to discover the presence of interaction between the factors of the process, while OFAT does not. The objective of this paper is to demonstrate how DOE approach works. This paper describes a case study on rubber glove manufacturing process. It illustrates interaction between factors that cannot be found when varying only one factor at a time. Model that describes the relationships between the inputs and output variables were then developed and used to indicate areas where operations may be improved. Successful experiments begin with systematic planning followed by good project management and coordination. When these things are done properly, the potential benefits of DOE are tremendous.