In order to reduce environmental pollution, it is necessary to increase the recycling rate of waste. For this, the separation of recyclables is of utmost importance. The paper conducted a study to automatically discriminate containers by material for beverage containers among recyclables. We developed an algorithm that automatically recognizes containers by four materials: metal, glass, plastic, and paper by measuring the vibration signal generated when the beverage container collides with the bottom plate of the collection box. The amplitude distribution, time series information, and frequency information of the vibration signal were used to extract the characteristics indicating the characteristic difference of the vibration signal for each material, and a classifier was developed through machine learning using these characteristics.

As the pollution from waste marine emissions becomes serious, the government's regulations are becoming more stringent. In addition to sewage sludge, manure sludge and waste sludge were included in the prohibition of off-shore sewage treatment and the allowable standard value of pollutants for the water quality discharged by the companies was increased. The difficulties of the enterprises due to the increase of the wastewater treatment costs are increasing. In order to solve these problems, it is necessary to reduce wastewater treatment costs and the processing burden of the consigned waste processing companies by constructing wastewater pretreatment facilities of their own waste. Therefore, it is urgent to develop low cost wastewater pretreatment or treatment facilities and technologies to meet the situation of wastewater discharge companies. In this study, a low cost system has been developed for filtering sludge in the wastewater by modifying the structure of drum screen and adopting the impact separation method. Using this system, the procedure and cost for purification and subsequent retreatment of a highly concentrated wastewater can be significantly reduced.

Recently, weight lightening is a key issue for various mechanical components to improve the fuel efficiency. For this reason, many researchers have been studying focused on the development of surface hardening treatment and metallic materials with high strength and wear resistance. In this study, we examine the formation of carbide at the surface of the gear machined by SCM420H steel after super-carburizing in order to improve the wear resistance of gear. The experimental results show that super-carburizing heat treatment gives rise to carbide dispersion across wider range of depth and higher carbon concentration than general carburizing heat treatment. Carbide having spheroidal or spherical shape had a size under 2 micro-meter produced in austenite grain boundaries or within austenite grains during super-carburizing. The super-carburized specimen maintained the hardness, HV700 above, at the 0.6mm depth and had a 10.4% lower coefficient of friction which was 0.766. This results from the dispersed carbide which lowered the coefficient of friction and ended up affecting wear resistance. Consequently, we conclude that super-carburizing heat treatment has more influence on the improvement of hardness, wear resistance compared to general carburizing heat treatment.

On-line detection system of the abnormal states in a machining process needs to be developed to implement the IMS(Intelligent Manufacturing System). High productivity and efficient quality control can be achieved through the on-condition maintenance for normal tool condition. Generally it is difficult to determine the exact point of time for a tool change because a tool wear grows gradually on the contrary to other abnormal states such as tool fracture, chattering etc. In this article, the shape variation of cutting force signal generated by a insert during face milling was investigated along with a tool wear. The variance, skewness and kurtosis were used as the shape parameters to describe the shape variation and, consequently, utilized as the features to monitor a tool wear. Experimental results showed that the shape parameters could discriminate the tool condition reliably between a fresh tool and a worn tool. As a result, we proposed the method to diagnose a tool wear by combining these parameters with a neural network algorithm.

Dehydration is a crucial part in the plastic recycling process. Without proper dehydration, a high quality recycled product cannot be produced. This study developed a continuous-type dehydrator using centrifugal force to improve the dehydrating performance and recycling throughput. The designed structure makes it capable to perform a continuous feeding and dehydrating of crushed plastic waste simultaneously. It consists of revolving drum, feed screw, insert screw, differential speed regulator and other components. Several tests were conducted to determine optimal process parameters to achieve results. Field tests using prototypes verified that the dehydrator with the proposed structure has an efficient and excellent performance

In aquaculture operations with nets including scallop aquaculture, there exist many problems as the management of fishing gears is dependent on the traditional method that has been using the pure labor forces. These give rise to the environmental contamination and increase of total fishery costs because they prevent the fishermen from reusing the fishing gears. Due to the eco-friendly issues and aggravation of the management cost, the need to automate the washing operation of the fishing gears has been required consistently. In this study, development of scallop fishing gear washing apparatus was carried out. We conducted the preliminary experiments applying Taguchi experimental method in order to find the influential factors and optimal levels to the washing performance. Based on these result, we designed the structure and the kinematic mechanism of the fishing gear washer. Final prototype was verified to be effective in maximizing the washing rate through the performance test.