42 research outputs found
āđāļĢāļēāļāļĢāđāļāļĄāļŦāļĢāļ·āļāđāļĄāđāđāļāļāļēāļĢāđāļāđāļēāļŠāļđāđāļĢāļ°āļāļāļāļēāļĢāļāļĨāļīāļāļāļēāļĒāļ āļēāļāđāļāđāļāļāļĢāđāļāļāļāļāļļāļāļŠāļēāļŦāļāļĢāļĢāļĄāļāļĢāļ°āđāļāļĻāđāļāļĒ 4.0Are We Ready for Cyber Physical Manufacturing System of Thailand Industrial 4.0?
The Improvement for Optimization of Head Stack Assembly (HSA) Assembling Process by Using the Virtual Reality 3D Simulation Model
Currently, a case study in the Head Stack Assembly (HSA) assembling process has an average production rate of 198 units an hour, which inadequates in the future of customer satisfaction. Therefore, this research aims to determine an approach for increasing the production rate by using the Arena program in order to build the simulation model and using the Theory of Constraints (TOC) to improve the assembly process. Moreover, the researchers develops the 3D virtual reality model by using the Arena 3DPlayer program, which assists to support for decision working efficiently and applies the OptQuest for Arena for determine the optimal amounts of the shuttles and flow fixtures
The Packaging Design Approach and Evaluation Process by Integrating ISO/TR 14062 in a Decision Support Methodology
The environmental, economic and social conscious are particularly important in the sustainable design product. ISO/TR 14062 suggests the conceptual guideline in environmental management into product and packaging design and development stage. However, the evaluation of the sustainable design selection based upon life cycle thinking is unavailable in detail design process. The objectives of this research are to develop the sustainable packaging methodology at the conceptual design phase, and to enhance the new guidelines to quantify an efficient sustainable packaging evaluation process by integrating ISO/TR 14062 in a decision support methodology. It is intended to integrate between life cycle thinking and major stakeholders for functional quality, cost, and environmental aspects in the early design phases. The methodology has been tested with a very large enterprise in the section of hard disk drive internal factory packaging and it was found that the approach of a new packaging design can assist the designer to develop the sustainable packaging whilst achieving desirable functions, increasing environmental conscious and cost effectiveness. In addition, the evaluation process can assess decision scenarios on the new design according to the investment comparison
The Effects of Diesel-waste Plastic Oil Blends on Engine Performance Characteristics
The objective of this research is to present results of the performance (torque, power, thermal efficiency and specific fuel consumption) in a heavy-duty diesel engine when fueled with diesel-waste plastic pyrolysis oil (WPO) blends in full load condition. The tested engine is installed on an engine test bench and is attached with several sensors. The full factorial experimental design is performed to investigate both main and interaction effects. It is shown that fuel blends, engine speed and interaction of both factors significantly affect all engine performance parameters. The functional relationships between parameters are developed by second-order quadratic models. The result shows that the mathematical models are able to predict the performance characteristic with mean absolute percentage error (MAPE) in the range of 1.614 to 2.987%. The increase of mixing ratio to WPO 75% greatly decreases engine output torque and power approximately by 23.79%. Consequently, thermal efficiency can be reduced by 5.97% while specific fuel consumption can be increased by 31.22%. The results of error analyses, the graphical presentations, the discussions and conclusions are also presented
Design of a Decision Support System on Selection of Multimodal Transportation with Environmental Consideration between Thailand and Vietnam
The objective of this research is to design and develop a decision support system (DSS) to select multimodal transportation route between Thailand and Vietnam under the conditions in term of budget, time, transport risk, and the environmental impact. The developed DSS model uses Analytic Hierarchy Process (AHP) as a tool to bring consistency weight whose decision criteria (both quantitative and qualitative) are expressed in subjective measures according to the point of view of users. Next, weighting derived from the results of AHP is taken as a weight of objective function in goal programming model. In this research, the Zero-One Goal Programming model is used to generate an optimal multimodal transportation routing based upon the criteria in term of budget, time, transport risk, and importantly, the environmental setting which is important to a number of countries. The case study of this research is a transported service, originating from Bangkok in Thailand to a destination at Da Nang port in Vietnam. There are, for example, the user can set the budget at 5,000 USD for 8-day period of transportation, with route risk scale and the environmental impact scale. The results found that the optimal route is sea transport departed from Bangkok to Da Nang Port, and truck service is deliver goods to customers. Transportation cost is equal to 1,080 USD for 8-day period of transportation, route risk scale is equal to 2, an environmental impact scale is equal to 3 and standard deviation is equal to 15.99. The results show that the DSS can guide to choose the lowest cost route in accordance with overall criteria, and minimise the environmental impact effectively. The results analysis, recommendations and limitations are also presented
āļāļļāļāļŠāļēāļŦāļāļĢāļĢāļĄāļĒāļēāļāļĒāļāļāđāđāļāļāđāļēāđāļĨāļ°āļāļĨāļāļĢāļ°āļāļāļāđāļāļāļļāļāļŠāļēāļŦāļāļĢāļĢāļĄāđāļāļĒElectric Vehicle: EV Industry and Impacts to Thai Industry
āļāļ§āđāļēāļŠāļīāļāļāļĩāļĄāļēāđāļĨāđāļ§āļāļĩāđāļāļļāļāļŠāļēāļŦāļāļĢāļĢāļĄ 4.0 (Industry 4.0) āđāļāđāļĄāļĩāļāļēāļĢāļāļģāđāļŠāļāļāđāļāļ§āļāļīāļāđāļāļāļĢāļ°āđāļāļĻāđāļĒāļāļĢāļĄāļāļĩ āļāļēāļāļāļąāđāļāļāļļāļāļŠāļēāļŦāļāļĢāļĢāļĄāļāđāļēāļāđ āđāļāļāļĢāļ°āđāļāļĻāđāļāļĒāđāļāđāđāļĢāļīāđāļĄāļāļĢāļąāļāļāļąāļ§āđāļāđāļēāļŠāļđāđāļāļēāļĢāđāļāđāļāļāļļāļāļŠāļēāļŦāļāļĢāļĢāļĄ 4.0 āļāđāļ§āļĒāļāļēāļĢāļāļģāļŦāļļāđāļāļĒāļāļāđ (Robot) āđāļāđāļēāļĄāļēāđāļāđāđāļāļāļĢāļ°āļāļ§āļāļāļēāļĢāļāļĨāļīāļ āđāļāļĒāđāļāļĒāļļāļāđāļĢāļāļāļ°āđāļāđāđāļāļāđāļāļĩāđāļĒāļ§ (Stand Alone) āļāđāļāļĄāļēāļĄāļĩāļāļēāļĢāđāļāļ·āđāļāļĄāļāđāļ (Connected) āđāļāđāļēāļāđāļ§āļĒāļāļąāļāđāļāđāļāļāļĨāļąāļŠāđāļāļāļĢāđ (Cluster) āđāļāļ·āđāļāđāļŦāđāļŠāļēāļĄāļēāļĢāļāļāļģāļāļēāļāļĢāđāļ§āļĄāļāļąāļ (Synchronized) āļāļąāļāļāļļāļāđāļāļāđāļāļāļĢāđ (Sensors) āđāļāļāļĢāļ°āļāļ§āļāļāļēāļĢāļāļĨāļīāļ āļāļąāļāļāļ°āļāļģāđāļŦāđāļāļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļāđāļāļāļēāļĢāļāļĨāļīāļ (Productivity) āļŠāļđāļāļāļķāđāļāđāļāļāđāļ§āļāđāļ§āļĨāļēāđāļāļĩāļĒāļ§āļāļąāļāļāļąāđāļāļāļļāļāļŠāļēāļŦāļāļĢāļĢāļĄāļĒāļēāļāļĒāļāļāđāđāļāļāđāļē (Electric Vehicle; EV Industry) āđāļāļāļĢāļ°āđāļāļĻāđāļāļĒāđāļāđāļĢāļąāļāļāļēāļĢāļāļāļāļĢāļąāļāļāļĩāļĄāļēāļāļāļķāđāļāļāļēāļāļāļđāđāđāļāđ āļāļąāļāļāļ°āđāļŦāđāļāđāļāđāļāļēāļāļĒāļāļāļāļēāļĒāļāļĩāđāđāļāļīāđāļĄāļŠāļđāļāļāļķāđāļāļāļēāļāļāļđāđāļāļĨāļīāļāļĒāļēāļāļĒāļāļāđāļāđāļēāļāđ āđāļāļĒāđāļāļāļĢāļ°āđāļāļĻāđāļāļĒāļĒāļēāļāļĒāļāļāđāļāļĢāļ°āđāļ āļāđāļāđāļāļēāļāļĢāđāļ§āļĄāļāļąāļāļĢāļ°āļŦāļ§āđāļēāļāļĢāļ°āļāļāđāļāļĢāļ·āđāļāļāļĒāļāļāđāđāļāļ·āđāļāđāļāļĨāļīāļāļŠāļąāļāļāļēāļ (Combustion Engine) āđāļĨāļ°āļĢāļ°āļāļāđāļāļāđāļēāļāļąāļāđāļāļĨāļ·āđāļāļāļāđāļ§āļĒāđāļāļāđāļāļāļĢāļĩāđ (Battery Driving) āļāļķāđāļāļĄāļąāļāđāļĢāļĩāļĒāļāđāļāļĒāļĢāļ§āļĄāļ§āđāļēāļĒāļēāļāļĒāļāļāđāđāļŪāļāļĢāļīāļ (Hybrid Electric Vehicles; HEVs) āđāļĨāļ°āļĒāļēāļāļĒāļāļāđāļāļĨāļąāđāļāļāļīāļāđāļŪāļāļĢāļīāļ (Plugin Hybrid Electric Vehicles; PHEVs) āđāļāđāļāļāļĩāđāļāļīāļĒāļĄāđāļāđāđāļāļāļĢāļ°āđāļāļĻāđāļāļĒāļāļļāļāļŠāļēāļŦāļāļĢāļĢāļĄāļĒāļēāļāļĒāļāļāđāđāļāļāđāļēāđāļāļāļĢāļ°āđāļāļĻāđāļāļĒāļāļģāļĨāļąāļāđāļĢāļīāđāļĄāļāđāļāđāļāļĨāļĩāđāļĒāļāđāļāđāļēāļŠāļđāđāļĒāļļāļāļāļēāļĢāđāļāđāļĒāļēāļāļĒāļāļāđāļāļąāļāđāļāļĨāļ·āđāļāļāļāđāļ§āļĒāļāļĨāļąāļāļāļēāļāđāļāļāđāļēāđāļāļĩāļĒāļāļāļĒāđāļēāļāđāļāļĩāļĒāļ§ āļāļķāđāļāļĄāļąāļāđāļĢāļĩāļĒāļāļ§āđāļē āļĒāļēāļāļĒāļāļāđāđāļāļāđāļē (Electric Vehicles; EVs) āđāļāļĒāđāļāļāļĩ 2020 āļĢāļąāļāļāļēāļĨāđāļāļĒāđāļāđāļ§āļēāļāđāļāļāđāļĢāļāđāļĄāļ (Roadmap) āđāļŦāđāļĄāļĩāļāļēāļĢāļāļĨāļīāļāļĢāļāļĒāļāļāđ EVs āļāļģāļāļ§āļ 250,000 āļāļąāļ āļĢāļāđāļĄāļĨāđ EV āļāļģāļāļ§āļ 3,000 āļāļąāļ āđāļĨāļ°āļĢāļāļĄāļāđāļāļāļĢāđāđāļāļāđ (Electric Motorcycle) āļāļģāļāļ§āļ 53,000 āļāļąāļ āļ āļēāļĒāđāļāļāļĩ 202
The Future of Green Industry from Luxury Niche Market of Crocodile Leather to Major Industry Using AI Deep Learning and Virtual Reality: An Empirical Study in Thailand During Covid-19 Era
Design of a decision support system to evaluate the investment in a new distribution centre
āļāļēāļĢāļŦāļēāļāđāļģāļŦāļāļąāļāļāļ§āļēāļĄāļŠāļģāļāļąāļāļāļāļāļāļēāļĢāļēāļĄāļīāđāļāļāļĢāđāđāļāļĢāļ·āđāļāļāļĒāļāļāđāļāļĩāđāļāļĨ āļāđāļ§āļĒāļāļēāļĢāļāļąāļāļŠāļīāļāđāļāđāļāļāļāļĨāļļāđāļĄ Weighting of Diesel Engineâs Parameters by Using Group Decision Making
āļāļāļāļąāļāļĒāđāļÂ āļāļēāļĢāļāļģāļāļĨāļāļēāļĢāļ§āļīāļāļąāļĒāļāđāļēāļāļāļĨāļąāļāļāļēāļāļāļāđāļāļāđāļāđāļāļĢāļ·āđāļāļāļĒāļāļāđāļāļĩāđāļāļĨāđāļāđāļāđāļāļēāļāļāļĢāļīāļāļāđāļāļāļāļģāļāļķāļāļāļąāđāļāļāđāļēāļāļŠāļĄāļĢāļĢāļāļāļ°āđāļāļĢāļ·āđāļāļāļĒāļāļāđāđāļĨāļ°āļĄāļĨāļāļīāļĐāđāļāđāļŠāļĩāļĒāļāļĩāđāđāļāļīāļāļāļķāđāļ āļāļĒāđāļēāļāđāļĢāļāđāļāļēāļĄ āļāļąāļāļ§āļīāļāļąāļĒāđāļĄāđāļĄāļĩāļāđāļāļĄāļđāļĨāļāđāļģāļŦāļāļąāļāļāļ§āļēāļĄāļŠāļģāļāļąāļāļāļāļāļāļēāļĢāļēāļĄāļīāđāļāļāļĢāđāļāļāļāđāļāļĢāļ·āđāļāļāļĒāļāļāđāļāļĩāđāļāļĨāļāļķāļāļāļģāđāļŦāđāļāļēāļĢāļāļąāļāļŠāļīāļāđāļāļ āļēāļĒāđāļāđāđāļāļāļāđāļāļŦāļļāļāļđāļ (multi-criteria decision making) āđāļĄāđāļĄāļĩāļāļĢāļ°āļŠāļīāļāļāļīāļ āļēāļ āļāļēāļāļ§āļīāļāļąāļĒāļāļĩāđāļāļķāļāļĄāļĩāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļ·āđāļāļĻāļķāļāļĐāļēāļ§āļīāļāļĩāļŦāļēāļāđāļģāļŦāļāļąāļāļāļ§āļēāļĄāļŠāļģāļāļąāļāļāļāļāļāļēāļĢāļēāļĄāļīāđāļāļāļĢāđāđāļāļĢāļ·āđāļāļāļĒāļāļāđāļāļĩāđāļāļĨāļāļĩāđāļŠāļģāļāļąāļāļāļģāļāļ§āļ 8 āļāđāļē āđāļāļĒāļāļēāļĢāļāļŠāļĄāļāļŠāļēāļāļ§āļīāļāļĩāļāļēāļĢāļāļąāļāļŠāļīāļāđāļāļāđāļ§āļĒāļāļĢāļ°āļāļ§āļāļāļēāļĢāļĨāļģāļāļąāļāļāļąāđāļāđāļāļīāļāļ§āļīāđāļāļĢāļēāļ°āļŦāđ (AHP) āđāļāđāļēāļāļąāļāļ§āļīāļāļĩāđāļāļĨāļāļēāļĒ (Delphi) āđāļāļ·āđāļāļāļģāļāļēāļĢāļāļąāļāļŠāļīāļāđāļāđāļāļāļāļĨāļļāđāļĄ (group decision making) āļāļķāđāļāļāļĨāļāļēāļĢāļĻāļķāļāļĐāļēāļāļāļ§āđāļē AHP āļŠāļēāļĄāļēāļĢāļāđāļāļĨāļĩāđāļĒāļāļāļ§āļēāļĄāđāļŦāđāļāļāļāļāļāļđāđāđāļāļĩāđāļĒāļ§āļāļēāļ āļāļķāđāļāđāļāđāļāļāđāļāļĄāļđāļĨāđāļāļīāļāļāļļāļāļ āļēāļāđāļŦāđāđāļāđāļāļāđāļāļĄāļđāļĨāđāļāļīāļāļāļĢāļīāļĄāļēāļāđāļāđāļāļĒāđāļēāļāļĄāļĩāļāļĢāļ°āļŠāļīāļāļāļīāļ āļēāļ āļāļĩāļāļāļąāđāļ AHP āļĄāļĩāļāļēāļĢāļāļĢāļ§āļāļŠāļāļāļāđāļēāļāļąāļāļĢāļēāļŠāđāļ§āļāļāļ§āļēāļĄāļŠāļāļāļāļĨāđāļāļāļāļąāļāļāļāļāļāđāļāļĄāļđāļĨ (consistency ratio) āļŠāļēāļĄāļēāļĢāļāļĒāļ·āļāļĒāļąāļāļāļļāļāļ āļēāļāļāļāļāļāđāļāļĄāļđāļĨāļāļēāļĢāļĻāļķāļāļĐāļēāđāļāđāđāļāđāļāļāļĒāđāļēāļāļāļĩ āđāļāļāđāļ§āļāļāđāļāļāļāļāļāļēāļāļ§āļīāļāļąāļĒ āļāļēāļĢāļāļĢāļ°āđāļĄāļīāļāļāđāļģāļŦāļāļąāļāļāļ§āļēāļĄāļŠāļģāļāļąāļāļāļāļ§āđāļēāļāļđāđāđāļāļĩāđāļĒāļ§āļāļēāļāļāļąāđāļ 8 āļāļ āļĄāļĩāļāļ§āļēāļĄāđāļŦāđāļāļāļĩāđāđāļāļāļāđāļēāļāļāļąāļ āļāļēāļāļ§āļīāļāļąāļĒāļāļĩāđāļāļķāļāđāļāđāđāļāļāļāļīāļāđāļāļĨāļāļēāļĒāđāļāļ·āđāļāļāļĢāļīāļŦāļēāļĢāļāļąāļāļāļēāļĢāļāļ§āļēāļĄāđāļŦāđāļāļāļĩāđāđāļāļāļāđāļēāļāļāļąāļāļ āļēāļĒāđāļāļāļĨāļļāđāļĄāļāļđāđāđāļāļĩāđāļĒāļ§āļāļēāļ āļāļķāđāļāļāļāļ§āđāļēāļŦāļĨāļąāļāļāļēāļāļāļēāļĢāļāļĢāļ°āđāļĄāļīāļāļāđāļģāļŦāļāļąāļāļāļ§āļēāļĄāļŠāļģāļāļąāļāļāļģāļāļ§āļ 3 āļāļĢāļąāđāļ āļāđāļāļĄāļđāļĨāļĄāļĩāđāļāļ§āđāļāđāļĄāļāļąāļāđāļāļāļ§āđāļēāļāļđāđāđāļāļĩāđāļĒāļ§āļāļēāļāļāļļāļāļāļāđāļāļīāļāļāļ§āļēāļĄāđāļŦāđāļāļāđāļāļāļāđāļāļāļāļąāļ āļāļĨāļāļēāļĢāļ§āļīāļāļąāļĒāļŠāļĢāļļāļāđāļāđāļ§āđāļēāļāļĢāļ°āļŠāļīāļāļāļīāļ āļēāļ, āđāļĢāļāļāļīāļ, āđāļāļĄāđāļēāļāļ§āļąāļāļāļģ āđāļĨāļ°āļāļāļāđāļāļāđāļāļāļāđāļāđāļāļĢāđāļāļāļĄāļĩāļāļ§āļēāļĄāļŠāļģāļāļąāļāļāļąāļāđāļāļĢāļ·āđāļāļāļĒāļāļāđāļāļĩāđāļāļĨāļĄāļēāļāļāļķāļ 23.67, 20.93, 21.72 āđāļĨāļ° 10.38% āļāļēāļĄāļĨāļģāļāļąāļ āđāļāļāļāļ°āļāļĩāđāļāļēāļĢāđāļāļāļāđāļāļāļāļāđāļāļāđ, āđāļŪāđāļāļĢāļāļēāļĢāđāļāļāļ, āļāļģāļĨāļąāļ āđāļĨāļ°āļāļēāļĢāđāļāļāļāļĄāļāļāļāļāđāļāļāđāļĄāļĩāļāļ§āļēāļĄāļŠāļģāļāļąāļāļāđāļāļĒāļĨāļāļāļēāļĄāļĨāļģāļāļąāļ āļāļĨāļāļēāļĢāļāļĢāļ°āđāļĄāļīāļāđāļāļĒāļāļđāđāđāļāļĩāđāļĒāļ§āļāļēāļ āļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāļĨ āđāļĨāļ°āļāļēāļĢāļāļģāļāļ§āļāļāđāļģāļŦāļāļąāļāļāļ§āļēāļĄāļŠāļģāļāļąāļāļāļāļāļāļēāļĢāļēāļĄāļīāđāļāļāļĢāđāđāļāđāļāļđāļāļāļģāđāļŠāļāļāļāļĒāļđāđāļ āļēāļĒāđāļāļāļāļāļ§āļēāļĄAbstractThe applications of alternative fuel in diesel engine must consider both engine output performance and exhaust gas emissions. However, researchers do not have any data of the weight of each parameter. This leads to the low efficiency in multi-criteria decision making. Therefore, this research aims to investigate the weight of eight important diesel engineâs parameters by using integrated Analytical Hierarchy Process (AHP) and Delphi technique for group decision making. The investigation shows that AHP can convert specialistâs perceptions, which is qualitative data, to quantitative data efficiently. Moreover, consistency ratios are verified and confirm the quality of research data. Evaluation results from eight specialists reveal incongruities in the beginning of the research. Hence, Delphi technique has performed in this study, which aims to manage these disagreements. After 3 rounds of specialistâs evaluations, the data shows very apparent trend of the group consensus. The results show that engine efficiency, torque, Particulate Matter (PM) and Oxides of Nitrogen (NOx) receive a high significance with the weights of 23.67, 20.93, 21.72 and 10.38%, respectively. While Carbon dioxide (CO2), Total Hydrocarbon (THC), power and Carbon monoxide (CO) show less importance, respectively. Specialistâs evaluations, discussions and weight calculations are also presented.