• Journal of the Korean Society for Precision Engineering
• /
• v.18 no.11
• /
• pp.74-79
• /
• 2001

In this two-part paper, a virtual machine tool (VMT) is presented. In part 1, the analytical foundation of a virtual machining system, envisioned as the foundation for a comprehensive simulation environment capable of predicting the outcome of cutting processes, is developed. The VMT system purposes to experience the pseudo-real machining before real cutting with a CNC machine tool, to provide the proper cutting conditions for process planners, and to compensate or control the machining process in terms of the productivity and attributes of products. The attributes can be characterized with the machined surface error, dimensional accuracy, roughness, integrity and so forth. The main components of the VMT are cutting process, application, thermal behavior and feed drive modules. In part 1, the cutting process module is presented. The proposed models were verified experimentally and gave significantly better prediction results than any other method. The thermal behavior and feed drive modules are developed in part 2 paper. The developed models are integrated as a comprehensive software environment in part 2 paper.

• Journal of Korean Institute of Industrial Engineers
• /
• v.20 no.4
• /
• pp.51-63
• /
• 1994

Many themes have been studied for FMS problems. But most researches have focused on specific themes; Machine selection, Loading, Routing, Machine layout, etc. So many decision makers who want to introduce FMS to his factory, have many problems, because they do not know either what size of FMS should be introduced or what amount of money should be invested. The objective of this research is to help the decision makers who want to introduce FMS. This research consists of three major part, first, Machine selection, second, Loading, and third, Machine Layout. In the first part of the research, machines are selected with minimum cost satisfying the given demand of each part. In the second part, each operations with its required tools are allocated to those machines. In the third part the locations of each selected machines are determined. And dissimilarity coefficients between each pair of machines are calculated as the measure of distance. With above three steps, we have selected machines, allocated operations to those machines, and the layout configuration of those machines. And for each three steps, Mixed Integer Programming models are formulated. In order to solve the large problems and reduce the computer execution time, three heuristic algorithms are developed for the three mixed integer programming models.

• IE interfaces
• /
• v.10 no.2
• /
• pp.1-13
• /
• 1997

The problem of the formation of machine-part cells in FMS is a very important issue at the planning and operating stages of FMS. This problem is inherently a combinatorial optimization problem, proven to be NP-complete(or, NP-hard). Among the several kinds of approaches which have been applied to solve the combinatorial optimization problems, the Simulated Annealing(SA) algorithm, a technique of random search type with a flexibility in generating alternatives, is a powerful problem solving tool. In this paper, the SA algorithm is used to solve machine cell-part family formation problems. The primary purpose of the study is to find the near-optimal solution of machine cell-part family formation problem, whare the product volume and number of operations are prespecified, that can minimize the total material handling cost caused by exceptional elements and intercell moves as much as possible. The results show that the SA algorithm is able to find a near-optimal solution for practical problems of the machine cell-part family formation.

• Journal of Biosystems Engineering
• /
• v.34 no.6
• /
• pp.425-433
• /
• 2009

The developed final shattering machine for labor-saving mechanization of shattering of sesame consisted of input part, shattering part, re-shattering part for unshattered pod and pneumatic sorter. The bundle of sesame was held as upside down and fed into the machine continuously. Then, the fed bundle of sesame was shattered by side shock and agitation. The performance of shattering for the sun dried bundle of sesame of conventional manual work and final shattering machine was compared. Since the shattering ratio measured by the final machine was 97.2% at the first operation, in case of fully dried sesame by drying stand, the harvest of sesame can be completed by only one time shattering operation. The work hour per area of 10 a for the mechanical work and the manual work were 0.3 hour and 13.9 hour, respectively. The total shattering ratio of the final machine with vertical feedings of bundle of sesames was 97.2%.

• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.12
• /
• pp.72-80
• /
• 1998

In this study, a design approach based on genetic algorithm is proposed to solve the manufacturing cell design problem considering alternative process plans and alternative machines. The problem is formulated as a 0-1 integer programming model which considers several manufacturing parameters, such as demand and processing time of part, machine capacity, manufacturing cell size, and the number of machines in a machine cell. A genetic algorithm is used to determine process plan for each part, part family and machine cell simultaneously.

• Journal of the Korean Society for Precision Engineering
• /
• v.7 no.3
• /
• pp.66-74
• /
• 1990

This paper presents a knowledge-based computer aided process planning system that automatically selects machine tools, machining operations and cutting tools and determines sequences of the machining operations for prismatic parts in die manufacturing. In the proposed system, parts are described by manufacturing features and grouped into part families based on the functions. Each part is repressented by a part frame which consists of basic data and manufacturing features. Knowledge for manufacturing is acquired from the domain expert and represented by frames. A decision model for selection of machine tools, machining operations and cutting tools and for determining sequences of the machining operations are developed by employing the Mealy machine in finite automata with output. The decision procedure and the order of priority which inputs manufacturing features into the Mealy machine are represented by rule for each part family. Backward chaining is used for the proposed system. The proposed system is implemented by using TURBO-PROLOG on the IBM PC/AT. A case study for the slide core is presented to show the function of the proposed system.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.04a
• /
• pp.432-437
• /
• 1997

In this paper, Fuzzy ART which is one of the competitive learing neural networks is applied to machine-part cell formation problem. A large matrix and varios types of machine-part incidence matrices, especially including bottle-neck machines, bottle-neck parts, parts shared by several cells, and machines shared by several cells are used to test the performannce of Fuzzy ART neural network as a cell formation algorithm. The result shows Fuzzy ART neral network can be efficiently applied to machine-part cell formation problem which are large, and/or have much imperfection as exceptions, bottle-neck machines, and bottle-neck parts.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.23 no.61
• /
• pp.137-146
• /
• 2000

One of the problems faced in implementing cellular manufacturing systems is machine-part group formation. This paper proposes machine-part grouping algorithms based on Self-Organizing Map(SOM) neural networks and K-Means algorithm in cellular manufacturing systems. Although the SOM spreads out input vectors to output vectors in the order of similarity, it does not always find the optimal solution. We rearrange the input vectors using SOM and determine the number of groups. In order to find the number of groups and grouping efficacy, we iterate K-Means algorithm changing k until we cannot obtain better solution. The results of using the proposed approach are compared to the best solutions reported in literature. The computational results show that the proposed approach provides a powerful means of solving the machine-part grouping problem. The proposed algorithm Is applied by simple calculation, so it can be for designer to change production constraints.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.14 no.6
• /
• pp.110-116
• /
• 2005

A single-piece-machined-part has superior characteristics to an assembly of several pieces of part especially for aircraft components. It is necessary to develop high efficient 'multi-head router machine' for machining a large size single-piece-part on a large scale. In this type machine, many cutting chips are generated. These chips should be removed automatically f3r productivity and part precision. In this study, the design evaluation of the cutting chip collecting apparatus for 'multi-head router machine' was complemented using performance test and finite element analysis.

• Journal of Korean Institute of Industrial Engineers
• /
• v.31 no.1
• /
• pp.1-9
• /
• 2005

This paper proposes the heuristic algorithm for the generalized GT problems to consider the restrictions which are given the number of machine cell and maximum number of machines in machine cell as well as minimum number of machines in machine cell. This approach is split into two phase. In the first phase, we use the similarity coefficient which proposes and calculates the similarity values about each pair of all machines and sort these values descending order. If we have a machine pair which has the largest similarity coefficient and adheres strictly to the constraint about birds of a different feather (BODF) in a machine cell, then we assign the machine to the machine cell. In the second phase, we assign parts into machine cell with the smallest number of exceptional elements. The results give a machine-part grouping. The proposed algorithm is compared to the Modified p-median model for machine-part grouping.