This research aims to study the important factors that affect the decision making in the manufacturing process development of industrial factories according to the Industry 4.0 concept and to create decision models. The model developed from applying Analytic Hierarchy Process (AHP) to this group of experts focuses on the most strategy and organization factors accounted for 28.3 percent followed by the smart factory accounted for 17.8 percent smart products accounted for 16.3 percent smart operations accounted for 13.1 percent employees accounted for 12.5 percent and the data-driven services accounted for 11.9 percent by the model test results with 3 factories. In conclusion this model can decide the way to improve the production process of industrial plants according to the Industry 4.0 concept that is suitable for the context and limitations of each industrial plant can be used for all types of industrial plants and will directly benefit the decision makers of industrial plants to improve the production process and develop into smart factory based on the Industry 4.0 concept.

The objective of this research was presented a decision support making process for efficiency improvement of drinking water processing using retrofit technique for machine and equipment rehabilitate. This methodology was applied Analytic Hierarchy Process (AHP) for selecting an appropriate maintenance sub-contractor. To complete the research existing water purifying machine and tools were inspected to assess its capacity. Future capacity of the purifying machine was also identified. Consequently machine and tools such as water tank and water filter were inspected for retrofitting for the example water tank water filter water quality control and bottle packing. Finally the analytic hierarchy process was utilized to select the most appropriate maintenance sub-contractor. In this process both qualitative and quantitative processes were analysed. The result of this research has been found that this multicriteria decision making process could be used to support the decision making investment process of water purification retrofit unit at Faculty of Engineering Rajamangala University of Technology Phra Nakorn efficiently. Furthermore it could be reduced bias from decision makers while the decision was accepted by all stakeholders.