Keyhoon Ko

Technical note: Automatic feedrate adjustment for pocket machining

As high-speed machining and unmanned machining become common, the demand for cutting-load regularization increases, so NC machining can be more efficient. To be presented is a simple cutting-load regularization method for pocket machining. As the conventional off-line approaches where cutting-load is predicted and cutting parameters are adjusted before actual cutting, the proposed method requires a cutting force model, which is quite simplified with the function of two independent variables. One is the geometric measure so called 2D chip-load (cutter-engagement angle or effective cutting depth), and the other is the feedrate. Based on the 2D chip-load analysis for the concave line-line segment of the NC tool path, the adjusted feedrate is calculated by using the simplified-cutting force model (SCFM) obtained by the cutting experiment with a tool dynamometer. The concept of the automatic feedrate adjustment (AFA) method to be proposed is very simple, and the implementation requires little effort. Furthermore, the proposed method does not need much calculation time because there are no complex calculations or cutting simulation.

C-space based CAPP algorithm for freeform die-cavity machining

Presented in the paper is a C-space based computer automated process planning (CAPP) algorithm for freeform die-cavity machining, which is an extension of the hierarchical CAPP model proposed earlier by the authors. In order to demonstrate its validity, the proposed CAPP algorithm has been implemented and applied to actual die-cavity machining examples.

Simulation based FAB scheduler: SeePlan®

In a typical FAB factory, various types of products are produced around the clock. Complex constraints and re-entrant flows make it difficult for a human scheduler to generate a production schedule based on his/her experience and knowledge. This paper introduces a simulation based FAB scheduler, SeePlan®, which was developed by the authors. A Korea based semi-conductor and LCD maker designated SeePlan as a standard advanced planning and scheduling solution and has used in several FAB factories around the world.

Development of Intelligent Mold Shop

Presented in the paper is an approach to developing an intelligent mold shop as a means to overcome the difficulties faced by mold-makers due to skill shortages and increased global competition. A machine shop where as much as of the human skills are replaced by a set of intelligent systems is called an intelligent machine shop , and an intelligent mold-making machine shop is called an intelligent mold shop (IMS) . By analyzing the contents of operator’s skill, three intelligent S/W stations have been designed: Technical Data Processing (TDP) Station, Loading Schedule Station, and Real-time Monitoring Station. A detailed architecture of the TDP station is described, and measures of effectiveness of IMS are elaborated.

New key performance indices for complex manufacturing scheduling

Diversified and complicated manufacturing sites make optimal scheduling of production lines difficult. Under current manufacturing processes, it is almost impossible for schedulers to consider all the constraints of production processes. A strategy of simulation-based advanced planning and scheduling (APS) is employed to overcome difficulties that interfere with satisfactory on-time delivery and commitment to the current status. In simulation-based scheduling, key performance indices (KPIs) are important for selecting optimal dispatching rules in scheduling. In cases involving complex processes, in which the identification of appropriate KPIs is limited to selection among existing KPIs, KPIs should be chosen and modified carefully to optimize process management and to reflect all of the existing constraints of production. However, the existing methodologies for modifying KPIs are misplaced in complex manufacturing environments such as job-shop processes. We propose a new method to design and select appropriate KPIs that meet the characteristics of any given process, and verify with empirical analysis whether or not the KPIs meet requirements from experts of production lines.

Gantt Chart Simulation for FAB Scheduling

Capital-intensive facilities called electronic fabrications (“FABs” in short) are operated twenty-four hours a day to meet the massive orders on time. The main objectives of scheduling the complex manufacturing process are to meet the on time delivery and to maximize machine utilization. A discrete event simulation approach has brought good results to generate an efficient and practical schedule. However, the approach tends to make short-term decision, which loads any job rather than stays idle. When the setup time is long and the number of crews is limited, being idle could be a better decision than changing jobs. This paper proposes a method to compensate for the limitations of simulation-based schedulers. We propose a Gantt chart simulation approach that formulates WIP level with an incoming profile and a consuming profile with the number of loaded machines. With two profiles, we can determine when to add or release a machine for each job. The proposed method has been applied to a real factory and showed promising results.

Use of image processing to collect the time data of NC machining

To control the production schedule for mold making, it is important to collect the actual results of machining operations, yet machine operators seldom record the results. Some die and mold shops have constructed a system which interfaces with NC controllers and which identifies the status of the machining operation from signals. This method depends totally on the NC controller and requires higher installation cost. We propose a method that is independent of the NC controller. This method uses a low-cost PC camera and image processing technology; and it has one algorithm for tracking moving objects and another for detecting scene changes. To demonstrate the validity of the proposed method, we applied it to both attended and unattended NC machining.

A Hierarchical CAPP System Architecture for Die Cavity Machining

This paper proposes a hierarchical CAPP (computer automated process planning) system architecture for die cavity machining. The CAPP system structure has been developed on the basis of the current practices of die cavity machining and is composed of five modules — Form EDM, Clean-up, Finish, Semi-finish, and Roughing planning. The individual CAPP modules are connected in a sequential manner They are identical in structure and each module consists of four sub-functions for feature extraction, process planning, machined surface update, and NC-code generation. Input to the CAPP system are 1) a CAD model of the die surface geometry, 2) the geometry of the raw stock, and 3) a set of available cutting tools with machinability data. Output from the CAPP system is a set of NC-codes. A process plan example, which is generated by a prototype CAPP system developed on the proposed structure, shows that the proposed CAPP architecture is practical and valid in the die cavity machining.