• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2000.04a
• /
• pp.135-138
• /
• 2000

This paper is intended to propose what manufacturing configuration (manufacturing planning and shop floor control) is suitable for the tire industry. Basically tire-manufacturing process is mixed-products, parallel-disconnected-flow-shop. Both throughput time and cycle tine are very short, the variety of tires is very high, the setup time is long, shop floor data reporting requirements is high, and there are many equipments and people working. And with no exception, tire industry also now confronts increasing requirements of delivery conformance with the above peculiar characteristics of tire manufacturing and changing market environments, this paper suggests, weekly master scheduling with no MRP is desirable and traditional kanban is right selection for shop floor control/scheduling. This paper describes why this configuration should be, using the manufacturing engineering principles and some new insights like four primitives of parallel flow shop. Generally known that shop with high parallel-product-mix and long setup time isn't good candidate for kanban. The four primitives of parallel flow shop explain why kanban is also useful scheduling technique in that environment.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.14 no.24
• /
• pp.43-52
• /
• 1991

The short-term production planning of an automated manufacturing system is to determine the production rate of each part type or family of part types. The purpose of this paper is to develop an optimal algorithm for solving the short-term production planning problem while machine failures, repairs. and changes in demand requirements are anticipated. The problem is formulated by LP and it shows that the production surplus is approached or stays at the hedging point. In addition, the long-term average frequencies of set-us with relation to a multilevel hierarchical production planing scheme are considered An example to show the effectiveness of the algorithm is presented.

• IE interfaces
• /
• v.16 no.3
• /
• pp.352-361
• /
• 2003

Vehicle manufacturing plant is a typical mixed-model production system. Generally it consists of three main shops including body shop, painting shop and assembly shop in addition to engine shop. Each shop contains diverse manufacturing processes, all of which are integrated in a form of flow line. Due to the high pressure from the market requesting small-volume large variety production, production planning becomes very critical for the competitiveness of automotive industry. In order to save costs and production time, production planning system is requested to meet some designated requirements for each shop: to balance the work load in body and assembly shops, and to minimize the number of color changes in painting shop. In this context, we developed a sequencing module for a vehicle production planning system using the ILOG Solver Library. It is designed to take into account all the manufacturing constraints at a time with meeting hard constraints in body shop, minimizing the number of soft constraints violated in assembly shop, and minimizing the number of color changes in painting shop.

• Journal of Digital Convergence
• /
• v.13 no.12
• /
• pp.55-62
• /
• 2015

IT SMEs' product planning, product design, and manufacturing capabilities are of importance to creating their sustainable competitive advantages in the context of digital convergence. However, there have been few empirical studies investigating the relationships among them, which has made this research attempt to model the relationships and empirically test them. Especially, this study divided IT SMEs' product design capability into the product exterior and interior design capabilities and focused on the mediating effects of the product exterior and interior design capabilities between the product planning and manufacturing capabilities. By analyzing the 310 samples of Korean IT SMEs with the ordinary least squares regression analysis, this study has empirically revealed that IT SMEs' product exterior and interior design capability jointly and fully mediate the positive relationship between their product planning and manufacturing capabilities.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.29 no.11
• /
• pp.1421-1431
• /
• 2005

In this study, outsourcing behaviors of shoe manufacturing companies were studied and four types of outsourcing were generated based on qualitative data collected through in-depth interviews with 21 practitioners of shoe manufacturing companies. In results, shoe manufacturers are actively adopting outsourcings in production of raw materials(RM) as well as final products(FP). However, relatively less effect is being made on outsourcing in the field of product planning, international marketing and information technology. Four types of outsourcing include shoe manufacturers focusing on: 1) domestic production of RH and FP, 2) domestic production of RM and international production of FP, 3) domestic/international production of RM and FP, and 4) international production of RH and FP. These types were differed. from their manufacturing items, product planning skills and target markets of shoe manufacturing companies.

• Korean Journal of Computational Design and Engineering
• /
• v.11 no.3
• /
• pp.223-233
• /
• 2006

Layered manufacturing(LM) is emerging as a new technology that enables the fabrication of three dimensional heterogeneous objects such as Multi-materials and Functionally Gradient Materials (FGMs). Among various types of heterogeneous objects, more attention has recently paid on the fabrication of FGMs because of their potentials in engineering applications. The necessary steps for LM fabrication of FGMs include representation and process planning of material information inside an FGM. This paper introduces a new process planning algorithm that takes into account the processing of material information. The detailed tasks are discretization (i.e., decomposition-based approximation of volume fraction), orientation (build direction selection), and adaptive slicing of heterogeneous objects. In particular, this paper focuses on the discretization process that converts all of the material information inside an FGM into material features like geometric features. It is thus possible to choose an optimal build direction among various pre-selected ones by approximately estimating build time. This is because total build time depends on the complexity of features. This discretization process also allows adaptive slicing of heterogeneous objects to minimize surface finish and material composition error. In addition, tool path planning can be simplified into fill pattern generation. Specific examples are shown to illustrate the overall procedure.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.29 no.2
• /
• pp.77-95
• /
• 2004

This paper deals with the process planning of flexible manufacturing systems (FMS) with various flexibilities and multiple objectives. The consideration of the manufacturing flexibility is crucial for the efficient utilization of FMS. The machine, tool, sequence, and process flexibilities are considered In this research. The flexibilities cause to increase the Problem complexity. To solve the process planning problem, an this paper an evolutionary algorithm is used as a methodology. The algorithm is named multiobjective competitive evolutionary algorithm (MOCEA), which is developed in this research. The feature of MOCEA is the incorporation of competitive coevolution in the existing multiobjective evolutionary algorithm. In MOCEA competitive coevolution plays a role to encourage population diversity. This results in the improvement of solution quality and, that is, leads to find diverse and good solutions. Good solutions means near or true Pareto optimal solutions. To verify the Performance of MOCEA, the extensive experiments are performed with various test-bed problems that have distinct levels of variations in the four kinds of flexibilities. The experiments reveal that MOCEA is a promising approach to the multiobjective process planning of FMS.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.24 no.4
• /
• pp.13-26
• /
• 1999

When we try to design a production planning system for a manufacturing company, it is a time consuming task to analyze various planning activities and identify inter-relationship among a lot of decisions made for the production planning. Most of the research efforts have been concentrated to well-organized independent decision-making problems that may usually be identified only after analyzing the characteristics of the decision-making process as a whole. In this paper, a methodology is suggested to characterize the whole process of the production planning for a manufacturing company and reduce the complexity of decision-making problems. The methodology is based on an experience of developing a production planning software for an automobile component manufacturer in korea. First, it is explained how to identify and represent the dependency among various decision-making variables. And a methodology is proposed to analyze the identified dependency among decision variables and identify decision-making process. Lastly, a practical example is provided to illustrate the analysis procedure in this paper.

• Journal of Korean Institute of Industrial Engineers
• /
• v.30 no.2
• /
• pp.130-145
• /
• 2004

This paper addresses the integrated problem of process planning and scheduling in FMS (Flexible Manufacturing System). The integration of process planning and scheduling is important for an efficient utilization of manufacturing resources. In this paper, a new method using an artificial intelligent search technique, called asymmetric multileveled symbiotic evolutionary algorithm, is presented to handle the two functions at the same time. Efficient genetic representations and operator schemes are considered. While designing the schemes, we take into account the features specific to each of process planning and scheduling problems. The performance of the proposed algorithm is compared with those of a traditional hierarchical approach and existing evolutionary algorithms. The experimental results show that the proposed algorithm outperforms the compared algorithms.

• IE interfaces
• /
• v.10 no.1
• /
• pp.15-22
• /
• 1997

In semiconductor manufacturing, the probe process between fabrication and assembly process is constrained mostly by the equipment capacity because most products pass through the similar procedures. The probe process is usually performed in a batch mode with relatively short cycle times. The capability of the probe process can be determined by the optimal combination of the equipments and the products. A probe line usually has several types of equipment with different capacity. In this study, the probe line is modeled in terms of capacity to give the efficient planning and control procedure. For the practical usage, the hierarchical capacity planning procedure is used. First, a monthly capacity plan is made to meet the monthly production plan of each product. Secondly, the daily capacity planning is performed by considering the monthly capacity plan and the daily fabrication output. Simple heuristic algorithms for daily capacity planning are developed and some experimental results are shown.