The purpose of this research is to determine the optimal factors existing in the aluminum riveting process. First a 25 full-factorial design was used to screen five factors and two levels by selecting a lapping-joint method using only one rivet which exhibited significant riveting shear. The five riveting parameters used were press force 5000 and 8000 newtons a thickness of material of 2.5 and 4mm a size of hole of 4.7 and 5.2 mm over long rivets of 4.7 and 5.2 mm and press times of 5 and 15 seconds. There were three parameter levels: thickness of the metal (2.5 3.2 and 4.0 mm) size of the hole (2.5 3.2 and 4.0 mm) and size of the over-long rivet (4.5 5.6 and 6.7mm) then a Box-Behnken design was used in order to analyze the data and find the optimization point. The experiment found that a standard rivet has a shear strength resistance of 1113.30 newtons. The study methodology was to prepare the riveting specimens use by selecting a lapping joint per one rivet to test the mechanical quality and shear. The results of the experiment show that the optimal conditions (to a statistically significant degree) were to use a 5.2 mm hole a 2.8 mm level of thickness and a 6.3 mm over-long rivet. The optimal point for the shear test was 1417.55 newtons and an over-shear strength of 303 newtons could be increased by 27.32 percent.

Phenol is an important raw material in many branches of industry (petrochemical pharmaceutical plastic and pesticidal chemical industry ). This research study on phenol production processes by using two different phenol production processes which are cumene oxidation (the Hock process) and toluene oxidation (the Dow process). In order to study in environmental impacts Life Cycle Assessment (LCA) is applied to evaluate environmental impacts of phenol production processes. Environmental impacts are evaluated according to cradle-to-gate approach by using SimaPro 7.1 software for Life Cycle Assessment . Approach by IMPACT 2002+ . The result shows that cumene process is more environmentally favorable than toluene process.

The aim of this research is to design and create the sorting machine within the engineering knowledge by using the three-layer sieve set cylindrical sorting machine under the various conditions of experimental. Furthermore the Specific Energy Consumption [SEC] of Robusta coffee bean separates the standard size of Robusta coffee bean the total of product separated are regarded. For the experiment condition rotation speed adjustable to 9.6 and 14.4 rpm. The raw material flow through to sieve and determination the standard size for calculating the [SEC]. The result of experiment found that the average of total of product separated was 165.1 kg/hr. and 164.7 kg/hr or 99.57% from that were passed the criteria of standard according to the ministry of agriculture cooperative. In order to the [SEC] the cylindrical sorting machine was 0.01631 MJ/kg at 14.4 rpm of rotation speed. However the values of [SEC] may be change from the effect of rotation speed of sieve set.

Diode high voltage the equipment assembles. That have necessity and important for a room practices for test experiment research and for the instruction. But diode high voltage to bring an element in a room practices something still must buy from the foreign countries and expensive. This problem corrects by designing and establish by oneself. This project has designed and build to diode high voltage for a laboratory by diode high voltage 100 kV. That can bring assemble all circuit get the circuit voltage multiplier etc. Building from the inventory at can seek can buy in house diode high voltage. That design and build that is the series diode on print circuit and electric oil insulator. Base principle of diode data technical of the components for applies in designing. The way builds to diode high voltage diagnose of designing builds consider the test diode high voltage the office designs. Which test has followed the objective is pass the power frequency withstand voltage test 120 kV 22 mA

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.