This paper describes the efficient equipment maintenance that can offer the exact time for repair and change of component in root industry. A conventional method offered the fixed time for repair and change of component because the method is based on early guarantee specification of the component. However the operating condition of manufacturing field is often under worse condition than early guarantee condition for high productivity. So, most components can’t use until early guarantee time due to the operation of various different condition. Therefore we suggest the useful method for efficient equipment-maintenance by manufacturing-field analysis and feedback database. For this, the classification of root industry and related equipment is performed and then the detail classification of the process and component for equipment maintenance. And the monitoring module is also designed to gather data for feedback process and the environment is basically implemented for aging and reliability test.

The machining-chatter stands for a sudden relative vibration appeared between a material and a tool while processing with a machine. This chatter is key factor that seriously affects the quality of processed materials as well as being a factor which causes serious damages to the tool and the machine. This study is related to the monitoring and smart control of chatter problem that can compensate machining-chatter faster and produce processed goods with more precision by autonomous compensation. The above-mentioned machining-chatter compensator includes the chatter vibration sensor and the chatter compensator that estimates the compensation value according to the sensor detecting the chatter vibration of machine-tool and the chatter vibration detected from the sensor while having a feature of being organized by interlocking with the machine-tool controller.

In this paper, we propose a novel velocity ripple controller using phase compensation feedforward control. Velocity ripples result in many kinds of performance degradations in manufacturing machines, especially such as ultra-precision roll lathes. The generation of velocity ripple in constant velocity control comes from various causes, such as electrical torque ripples, mechanical worn out, inconsistent mass center, etc. Conventional researches about ripple is mainly for reducing torque ripple in actuator level, which is only one of reasons for velocity ripples, so in this study, we focus on eliminating velocity ripples in upper level controller using phase compensation feedforward controller. The proposed algorithm is composed of several modules, such as ripple extractor, phase adjuster and phase follower etc. The suggested algorithm can be easily extended, and it shows a superior performance in the experiments of ultra-precision roll lathes.

Augmented reality is a novel human-machine interaction that overlays virtual computer-generated information on a real world environment. It has found good potential applications in many fields, such as training, surgery, entertainment, maintenance, assembly, product design and other manufacturing operations. In this study, a smartphone-based augmented reality system was developed for the purpose of monitoring and managing injection molding production lines. Required management items were drawn from a management content analysis, and then the items were divided into two broad management categories: line management and equipment management. Effective work management was enabled by providing those working on the shop floor with management content information combined with the actual images of an injection molding production line through augmented reality.

The biggest factors, which lower the machining accuracy of machine, are thermal deformation and chatter vibration. In this article, we introduce the development case of a device and technology that can automatically compensate thermal deformation errors of machine during long-time processing on the machine tool’s CNC (Computerized Numerical Controller) in real time. In machine processing, the data acquisition of temperature signal in real time and autocompensation of the machine origin of machine tools depending on thermal deformation have significant influence on improving the machining accuracy and the rate of operation. Thus, we attempts to introduce the related contents of the development we have made in this article : The development of a device that embedded the acquisition part of temperature data, linear regression to get compensation value, compensation model of neural network and a system that compensates the machine origin of machine tool automatically during manufacturing process on the CNC.

The biggest factors that lower the machining accuracy are thermal deformation and chatter vibration. In this article, we introduce the study case of technology that can automatically compensate the errors of these factors of a machine during processing on the machine tool"s CNC(Computerized Numerical Controller) in real time. This study is related to the detection and compensation of thermal deformation and chatter vibration that can compensate for faster and produce processed goods with more precision by autonomous compensation. In addition, this study is related to the active control of vibration during machining, monitoring of cutting force and auto recognition of machining axes origin. Thus, we attempt to introduce the related contents of the development we have made in this article.

To overcome many defects such as the high product cost, large energy consumption, and big space capacity in conventional mechanical machining, the miniaturization of machine tool and micro factory systems has been envisioned recently. The object of this paper is to research the effect of dynamic characteristic parameters in bolted-joint beams, which is widely applied to the joining of mechanical structures in order to identify structural system characteristics and to predict dynamic behavior according to scale-down from macro to micro system as the development of micro/mesoscale machine tool and micro factories. Modal parameters such as the natural frequency, damping ratio, and mode shape from modal testing and dynamic characteristics from finite element analysis are extracted with all 12 test beam models by materials, by size, and by joining condition, and then the results obtained by both methods are compared.