• International Journal of Safety
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• v.5 no.2
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• pp.34-37
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• 2006

As part of an effort to systematize the operation planning for cutting processes, the neural network method has been applied to model the process of selecting cutting conditions and subsequently to arrive at effective and safe cutting conditions through learning during training of the model. New cutting conditions that are more effective and safer for the given circumstance are obtained. The proposed algorithm deletes the old information previously learned, and then makes the network make at improvement by learning. As a result, the new algorithm provides useful cutting conditions for safer manufacturing environments. A variety of simulation cases illustrate the performance of the proposed methodology. The simulation results are provided and discussed.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.4
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• pp.80-86
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• 2021

Plastics are widely used in mechanical and other fields due to their light weight, design flexibility, and molding processability. In processing plastics, defective products are mixed and reprocessed to improve production efficiency and reduce costs. In this study, an experiment was conducted to confirm the coefficient of thermal expansion of HDPE during this reprocessing. The coefficient of thermal expansion was measured at different measurement directions and heating rates. As a result, we observed that the coefficient of thermal expansion in the direction perpendicular to the injection direction is greater than that in the horizontal direction.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.1
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• pp.78-84
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• 2019

Design of an electric power system on the solar-electric vehicle is very important because sunlight intensity is changed by weather conditions and road environments. Power output of solar module on the vehicle being changed by unsteady sunlight intensity. In this paper, design method of an electric power system are proposed to generate steady electric power output. The test results shows the electric power system are effective because the solar-electric vehicle have steady driving speed under unsteady sunlight conditions.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.1
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• pp.111-118
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• 2022

The vehicle industry requires superior technology that can increase the efficiency of the battery of an electric vehicle. A coolant heater that can optimize the temperature of the battery is one of the most effective techniques for cold environments. However, the vibrations generated by this device can cause major complications, such as leakage and system errors. Therefore, the vibrations of the device must be suppressed to improve the stability. In this study, the fastening conditions of a coolant heater were analyzed using a computer simulation to investigate the natural frequencies and mode shapes which reflect the primary reasons for the largest vibrations under the given operating conditions. The results showed that six-bolted joints could considerably improve the stability of the fastening device

• Journal of Platform Technology
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• v.9 no.1
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• pp.15-22
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• 2021

In a smart manufacturing environment, more and more devices are connected to the Internet so that a large volume of data can be obtained during all phases of the product life cycle. The large-scale industries, companies and organizations that have more operational units scattered among the various geographical locations face a huge resource consumption because of their unorganized structure of sharing resources among themselves that directly affects the supply chain of the corresponding concerns. Cloud-based smart manufacturing paradigm facilitates a new variety of applications and services to analyze a large volume of data and enable large-scale manufacturing collaboration. The manufacturing units include machinery that may be situated in different geological areas and process instances that are executed from different machinery data should be constantly managed by the super admin to coordinate the manufacturing process in the large-scale industries these environments make the manufacturing process a tedious work to maintain the efficiency of the production unit. The data from all these instances should be monitored to maintain the integrity of the manufacturing service system, all these data are computed in the cloud environment which leads to the latency in the performance of the smart manufacturing service system. Instead, validating data from the external device, we propose to validate the data at the front-end of each device. The validation process can be automated by script validation and then the processed data will be sent to the cloud processing and storing unit. Along with the end-device data validation we will implement the APM(Asset Performance Management) to enhance the productive functionality of the manufacturers. The manufacturing service system will be chunked into modules based on the functionalities of the machines and process instances corresponding to the time schedules of the respective machines. On breaking the whole system into chunks of modules and further divisions as required we can reduce the data loss or data mismatch due to the processing of data from the instances that may be down for maintenance or malfunction ties of the machinery. This will help the admin to trace the individual domains of the smart manufacturing service system that needs attention for error recovery among the various process instances from different machines that operate on the various conditions. This helps in reducing the latency, which in turn increases the efficiency of the whole system

• IE interfaces
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• v.15 no.1
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• pp.26-39
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• 2002

Two key data areas of the integrated production database in computer-integrated manufacturing (CIM) systems are the product structure in the forms of bills of material(BOM) and the process structure in the forms of routings. The great majority of existing information systems regard the BOM and routing as two separate data entities, possibly with some degree of cross-referencing. This paper proposes new information structure called the bills of material and routings(BMR) that logically integrates the BOM and routings for the CIM systems in ship production. The characteristics of ship production are described as: 1) make-to-order production type, 2) combined manufacturing principles (workshop production and construction site production), 3) significant overlapping of design, planning and manufacturing, 4) very long order throughput time, 5) complex product structure and production process. The proposed BMR systematically manages ail parts and operations data needed ship production considering characteristics of ship production. Also, the BMR situated on the integrated production database more efficiently supports interface between engineering and production functions, and integrates a wide variety of functions within production such as production planning, process planning, operation scheduling, material planning, costing etc., and simplifies information flow between sub-systems in CIM systems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.277-280
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• 2000

Reverse Engineering is a procedure where the results of engineering decisions in manufacturing is feedback to the design phase and the knowledge-base is generated from the process know-how to reduce the errors. Since it used to take lots of time and efforts to finalize the machining of dies out of the original CAD design especially for die spotting and try-outs, reverse engineering is important to improve the productivity and quality of the die manufacturing process. In this regard, we developed system to support reverse engineering in machining of stamping dies for auto-body production. They automatically generate the relevant MC programs for a CMM simply with the input of measuring points in CAD environments, and show the CAD model and the results of inspection simultaneously for the ease of comparison. They also help reduce the overall clearance between the lower and upper dies. Applying these systems to the machining process of stamping dies, we could improve the reliability of measuring and get the optimal compensation distance between the two dies. We also analyzed the expected benefits of the system in terms of savings in time and costs.

• Journal of the Korean Society for Precision Engineering
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• v.34 no.1
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• pp.29-34
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• 2017

The operating environments of factories and manufacturing units have changed dramatically due to globalization, population, and customization. The existing factories are converted into smart units using information and communications technology (ICT). These smart factories can produce, control, repair, and manage themselves. The manufacturing processes are efficiently optimized using the monitoring and analysis methods of ICT. In this experimental study, we carried out a survey on the system solution providers and consumer companies to determine the field conditions and requirements necessary for assembling a smart factory. Using the results of this survey, we effectively devised smart factory solutions and implemented them on the existing conditions in various factories.

• IE interfaces
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• v.12 no.1
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• pp.10-18
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• 1999

Job shop manufacturing environments are using the concept of cellular manufacturing systems(CMS) which has several advantages in reducing production lead times, setup times, work-in-process, etc. Utilizing the similarities between cell-machine, part-machine, and the shape/size of parts, CMS can group machines and parts resulting in improved efficiency of this system. However, when grouping machines and parts in machine cells, there inevitably occurs exceptional elements(EEs), which can not operate in the same machine cell. Minimizing these EEs in CMS is a critical point that improving production efficiency. Constraints in machine duplication cost, machining process technology, machining capability, and factory space limitations are main problems that prevent achiving the goal of maintaining an ideal CMS environment. This paper presents an algorithm that minimizes EEs under the constraints of machine duplication cost and factory space limitation. Developing exceptional operation similarity(EOS) by cell-machine incidence matrix and part-machine incidence matrix, it brings the machine cells that operate the parts or not. A mathematical model to minimize machine duplication is developed by EOS, followed by a heuristic algorithm in order to reflect dynamic situation resulting from minimizing exceptional elements process and the mathematical model. A numerical example is provided to illustrate the algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.1027-1033
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• 2016

There is an increasing need for manufacturing systems to produce batches in small quantities. Such manufacturing systems are significantly difficult to develop with conventional automation equipment. Recently, several research groups have applied industrial dual-arm robots to cell production lines. A synchronization method for robots is necessary for the cell production process when robots work in a shared workspace. Conventional automation factories do not need this method because the main control system operates all of the machines or robots. However, our intended application for the developed robot is in small manufacturing environments that cannot install an expensive main control system. We propose an inexpensive and high-performance method with a simple digital in/out channel using a real-time communication protocol. The developed method was validated in a pilot production line for cellular phone packing.