In present there are widely use robot in many fields. Mobile robot can help us in several task such as moving to toxic area risk area or explosion area mine. Movement control can be used in many ways. This paper proposed mobile robot that move by wheels. It move to previous defined picture. By using small camera process an images and check it that is the previous one by using neural network. If it is robot will move toward to that picture. The movement is in flat plane. If that defined picture is not in center robot will move to left or right depend on its position until it is on center. This paper proposed image processing only.

This research aimed to design and construct a forecasting support system on demand of fresh durian of Thailand by applying 2 mathematical models which were Time Series model and Artificial Neural Network model in order to find an accurate model of forecasting support system on demand of durian yield to forecast durian yield quantity of Thailand in advance and use the forecast results to plan and determine quantity of fresh durian and durian product conforming with domestic consumption and export in order not to be over demand and cheap durian sold price. The forecast models were applied with Time Series model by using Moving Average Weighted Moving Average Single Exponential Smoothing and Holt’s Linear Exponential Smoothing techniques and Back Propagation of Artificial Neural Network model which used 4 input variables relating to durian yield. All of the forecast models were used to forecast total durian yield quantity in 26 provinces of durian cultivated area all around Thailand. Durian yield quantity data used was from 1996 to 2008. After that the forecast results were used to find the errors of MAE MSE RMSE and MAPE. Then the errors of each forecast model were compared. The forecast model which had the least error was the most accurate forecast model. The research result is following. Back Propagation with 4-8-1 structure of Artificial Neural Network model had the least error so that it was the most accurate forecast model to forecast fresh durian yield quantity in advance.

This industrial research was studied an improvement of efficiency in natural fiber production plant. The objective was improvement process by using IE techniques which this method was once green technology for industrial problems solving. Now process had build-up in process (WIP) due to unbalance times between trimming station and visual inspection of station. Therefore the research studied work of staffs; time study and data analysis through 5W1H were used for analysis of WIP root cause. The cause of problems founded were the transportation loss of between section had over necessity and loss of visual inspection for repair. Therefore it had bottleneck in process. Consequently the researchers applied ECRS in each working processed by separation of repair station. Repairs of items were isolated from the main flow path of the process. Calculating of work flow rate was used for identified operator for repair station. As a result of the above production improvement Times of visual inspection in a lot was decrease from 283.84 hrs to 160.19 hrs. It was decreased in 43.56%. In addition the effect of separation from the repair process made the total times of all process was decreased from 792.78 hrs/lot to 669.14 hrs/lot. It was decreased in 15.60% and decreased work in process had from 17 lots/day to no work in process.

This research was concerned about clothes production from remnant fabrics that can increase product value and meet market demand by using patchwork and appliqué technique. The research was conducted into 3 phases : data collecting prototype production and consumer satisfaction evaluation. Questionnaires were used as instrument for data collecting. The first one the researcher inquired; what kind of products that consumer expected to see from remnant fabrics and collected data as market demand in order to produce 9 prototypes by using patchwork and appliqué technique. Finally the prototype was provided to the sample group with the questionnaire in order to evaluate consumer satisfaction toward the prototype. The obtained data from the first questionnaire showed the most of sample was believed that product from remnant fabrics was a low price with poor quality and has no attractive design. The majority of sample interested in apparel product produced from remnant fabrics and sign of the zodiac was selected for decorative pattern. In comparison the result between the first and second questionnaire found that patchwork and appliqué technique could change people attitude toward the product from remnant fabrics. The satisfaction of sample group towards prototype product was ranging in high level. The most of sample group agree to patchwork and appliqué was appropriate technique for transformation and value added to remnant fabric. A price of prototype estimated by consumer was 2001 - 3000 baht per item.

The objective of this research is to design forecasting support models on demand of durian for domestic markets and export markets for durian gardeners durian entrepreneurs of domestic markets and export markets and the Office of Agricultural Economics to plan durian demand conforming with domestic markets and export markets because of Production and marketing main problems (The Agricultural Information Center The office of Agricultural Economics: 2008) such as over - much durian production during production capital increased farmers durian sold price tended to be lower and lower inefficient domestic market management and more export but cheaper price therefore after that to design forecasting for the purpose in order that durian would not be over demand which is containing factors of the demand of durian fresh durian frozen durian paste and durian chips for domestic markets and export markets exported to Asia America Australia and Africa. The research involves historical collection data in the period of 2002 to 2008. The basic of forecast models are the designed and improved models using an intelligent knowledge-based approach beginning Moving average Deseasonalized Exponential smoothing Double exponential smoothing and Artificial neural network (ANNs) program within the model of new value Creation and comparative accuracy models. The evaluation result of forecasting durian demand showed that lowest MAPE of Deseasonlized models at 3 month was durian fresh durian frozen and durian paste but durian chips showed that lowest MAPE of ANNs at 4 input 10 hidden layers and 1 output was high accurate forecasting and optimal models. The analysis recommendations and error forecast of durian demand are also presented.