Optical dimensional metrology has playing a long-term key role from high-precision engineering to large-scale industrial manufacturing. Various methods of optical dimensional metrology have been proposed and demonstrated to respond to the ever-growing industrial demands as well as fundamental science demands for the measurement precision and range. However, most of them demonstrated under laboratory conditions have a long way to go outside the laboratory. Here, we present a progress review on optical modulation technique-based dimensional metrology, which has already been used in real applications and has been commercialized. Amplitude modulation (AM) and frequency modulation (FM) based dimensional measurement techniques are described with their operating principles, and recent progresses and applications in 3D imaging are presented in this review.

The fourth industrial revolution is rapidly emerging as a new innovation trend for industrial automation. Accordingly, the demand for inspection equipment is highly increasing and vision sensor technologies are continuously evolving. Machine vision algorithms applied to deep learning are also being rapidly developed to maximize the performance of inspection equipment. In this review, we highlight the recent progress of vision sensor technology for the industrial inspection system. In particular, inspection principles and industrial applications of a vision sensor are classified according to the vision scanning methods. We also discuss machine vision-based inspection techniques containing rule- and deep learning-based image processing algorithms. We believe that this review provides novel approaches for various inspection fields of agriculture, medicine, and manufacturing industries.

In this work, recent advances in temperature control techniques and the resulting contemporary progress in precision thermometry are addressed together with a broad review of traditional temperature control methods. Particular emphases are placed on clarification of the nature of temperature control and its classification, and the relevant technical issues are addressed based on this clarification and classification. Being a thermodynamic quantity having the same dimension as energy, temperature of an object is traditionally controlled by means of the changing rate of energy (Heat) transfer; however, this approach has led to a slow, less stable, and uneven temperature field due to inherent limits caused by finite properties of materials. To overcome this problem, thermodynamic characteristics of two-phase heat transfer devices, such as heat pipes and loop heat pipes, have been extensively employed where high-speed nature of fluid flow was exploited to realize a uniform temperature field, and unique thermodynamic linkage between saturation temperature and pressure was successfully applied to attain a fast, stable, and predictable temperature control of a finite-sized isothermal space. Representative examples and applications are provided in the context of unique features of the introduced contemporary temperature control techniques, which caused significant scientific strides in the related fields.

Sensors and measurements are the most basic means of collecting physical data, and the measurement results should be trusted and utilized. The management system of the future measurement network based on the next-generation sensor has limitations in responding to the current quality assurance system due to changes in the use of sensors, an increase in observation points, and changes in the method of using measurement results. Due to this reason, the measurement strategy direction should be investigated to ensure the reliability of measurement data. The basic approach can be summarized as follows: change in the viewpoint from hardware devices to measured data themselves, openness to novel type of devices, and removal of uncertainties by the process of sharing the basis of reliability through clear and efficient information exchange. In principle, the direction should be targeted for novel sensors to remove the barriers to enter the industry and market, based on the continuity with the current measurement standard system and traceability to the International System of Units.

Recently, large-scale accidents caused by minor damage from fatigue failure and impact on structures have been frequently reported. Therefore, a real-time damage monitoring system of structures is considered to be one of the most important technologies to ensure safety in various types of research. The piezoelectric sensor, which has an advantage of converting deformation of a structure into an electrical signal without using an additional power source, has been reported as one of the most suitable methods for real-time monitoring systems. This review aims to describe the structural monitoring system utilizing piezoelectric paint sensors. First, we present the concept of a piezoelectric paint sensor with the advantages of flexibility and piezoelectric performance. Then, factors affecting the performance of the piezoelectric paint sensor are introduced. Finally, an overview of piezoelectric paint sensors for structural monitoring, such as vibration detection and impact monitoring, are provided. The state-of-the-art of the application of the piezoelectric sensor is also introduced, providing feasibility in industrial fields.

SMEs encounter many difficulties in integrating and operating various information systems introduced to build smart factories. The source of this difficulty comes from integrated management of data interface between information systems. This research proposes a data interface middleware that can operate and manage various data interfaces between information systems in an integrated manner. First, this study identifies the types of information systems and operational information needed to build smart factories and analyzes the ways of data interface and requirements suitable for the manufacturing environment of SMEs. Structure and detailed functions of the data interface middleware are designed based on the analysis results. The proposed data interface middleware consists of the function layer, engine layer, and DB layer. The function layer is a set of functions for operating the middleware, and the engine layer comprises core engines for executing the functions. The DB layer manages all information that gathers when the data interface is executed. We applied the proposed middleware to connect data between the existing ERP and newly introduced smart factory package software in SMEs. Application results show that the associated data types are consistent in the two systems, and accuracy of the data parsing process is reliable.

It is important to minimize electric energy consumption of a data center that uses enormous electricity for maintaining an adequate indoor temperature. Most data centers have applied the outdoor air cooling method on account of economic feasibility. However, it is necessary that data centers have an efficient control method in order to achieve extra energy savings. In this paper, we propose an artificial intelligence based real-time optimal control method that minimizes electricity consumption and assures safe operation simultaneously. The main idea of our proposed method is to evolutionary search the optimal range of controlled variable during a normally operative condition. Furthermore, an optimal operating condition can be achieved without requiring large-scale data to learn a model. Experimental results demonstrate that indoor temperature of a data center can be constantly controlled safely and cost effectively based on our proposed methodology.

In this study, the structural integrity of a 6.8 L composite pressure vessel manufactured using H2550 carbon fiber was evaluated by the finite element analysis method, and the reliability of the analysis method was verified by comparing the hydrostatic test and analysis results. The pressure vessel was manufactured using the filament winding method and a hydrostatic test was performed to evaluate the failure mode and burst pressure of the manufactured composite pressure vessel. To construct the finite element model, a cyclic symmetric model, which only considers 1° of the front part, was used to reduce the analysis time and increase the modeling efficiency. As the carbon fiber was wound along the curved surface of the dome part, the winding angle and lamination thickness were modeled to change according to the dome radius. Comparison of the analysis and test results confirmed similar behavior in the axial and hoop strain diagrams due to internal pressure. In addition, it was found that the maximum fiber direction stress of the hoop layer showed an error of 3%, verifying the reliability of the finite element analysis method.

Elastomeric bushings are structural elements that are used in automotive suspension systems. An elastomeric bushing is a hollow cylinder that is contained between an outer steel cylindrical sleeve and an inner steel cylindrical rod. The outer steel cylindrical sleeve is connected to the components of the suspension system and is used to transfer forces and moments from the wheel to the chassis. The elastomeric material reduces the shock and vibration in this connection. Dynamic simulations of the automotive suspension system involve the interaction between many components. The accurate determination of the transmitted forces and moments between the components, the motion of the components, stress in the components, and energy dissipation is affected by the quality of the bushing model. Several Pipkin-Rogers models have been proposed for the axial mode, radial mode, and torsional mode and modified Pipkin-Rogers models have been proposed for the axial mode and torsional mode. In this research, the modified Pipkin-Rogers model for the torsional mode was verified in a frequency-related rotational angle control test. The results showed that the moment outputs of the modified Pipkin-Rogers model were in very good agreement with those of the Pipkin-Rogers model in the sinusoidal rotational angle control test.

Among the types of new and renewable energy, perovskite solar cells, which are next-generation solar cells, are capable of a solution process at a low temperature of 200oC or less, and have the advantages of high efficiency and low cost; hence, many studies have been conducted. Research has been performed on perovskite solar cells mainly produced using spin coating, but they have a disadvantage of occurrence of pinholes and cracks when fabricated over a large area, reducing the uniformity and density of the thin film. For the production of large-area perovskite solar cells, research is underway using solution shearing process technology among printed electronic process technologies, and most of the processes have been carried out at low speeds. This is due to the size of the crystal, which is one of the most important factors of high efficiency of the solar cell. When printing at high speed for mass production, the size of the crystal is reduced, resulting in charge loss and lower efficiency, making it difficult to apply the roll-to-roll process. In this study, to apply the roll-to-roll process for mass production, perovskite crystallization experiments were performed under high-speed conditions and crystal size changes according to meniscus stability.