• Management Science and Financial Engineering
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• v.8 no.2
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• pp.1-20
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• 2002

This paper presents a model that analyzes the impact of uncertainties in demand and processing times on the production lead time of a Kanban system. We consider the waste associated with under-production as well as over-production when we measure the production lead time. We set up an optimization model to minimize the production lead time. A simple heuristic procedure is developed to determine solutions in terms of the size of containers and the number of Kanban cards. In addition, we numerically examine the behavior of the optimal Kanban system.

• Proceedings of the Safety Management and Science Conference
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• 2011.11a
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• pp.557-561
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• 2011

The study proposes three types of production lead time according to the production or demand pattern. First of all, it discusses the difference of three lead times. While pitch time and cycle time are used in push system with process stock and mass conveyor production, the tact time is used in pull system like as JIT based lean production system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.93-103
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• 1995

This paper des with an economic production quantity model with partial backorders for the situation in which production lead time is deterministic and demand during lead time follows a continuous distribution. In the model, an objective function is formulated In minimize an average annual inventory cost. And then the procedure of iterative solution method for the model is developed to find both production reorder point and production quantity. Finally, sensitivity analysis for various partial backorder ratios and standard deviations of demand during production lead time are presented.

• IE interfaces
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• v.21 no.4
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• pp.418-434
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• 2008

This paper studied issues in decision making on the production control policy of a cathode plate manufacturing process in zinc refining plant. The present production system has a long lead time from raw materials (aluminum plate) to products (cathode plate) due to many WIP inventories. Because WIP inventories are stocked at each process and moved from one place to another frequently, they are the main cause of inefficiency in the process. In this paper, to solve this problem, several production control policies have been identified and studied. Several simulation models are used to compare the performances of these production control policies. The output lead time and WIP (Work In Process) of real production system are compared with those of simulation models. PUSH, CONWIP, DBR, KANBAN and CONWIP-DBR models have been used to simulate and review the optimized production control policy that achieves the target output quantities with decreased lead time and WIP. The simulation results of each production control policy show that CONWIP and CONWIP-DBR models are the good production control policy under the present production system. Especially in present production system, CONWIP with one parameter is easier control policy than CONWIP-DBR with two parameters. Therefore CONWIP has been selected as the best optimum production control policy. With CONWIP, lead time has been reduced by 97% (from 6,653 to 187 minute) and WIP has been reduced from 1,488 to 53, compared to the present system.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.428-439
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• 2020

The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as the basic cycle time and lead time. Improvement measures are necessary to enable the industry to respond swiftly to changes in the production environment. In this study, the lead times for fabrication, assembly of ship block, spool fabrication and painting were predicted using machine learning technology to propose a new management method for the process lead time using a master data system for the time element in the production data. Data preprocessing was performed in various ways using R and Python, which are open source programming languages, and process variables were selected considering their relationships with the lead time through correlation analysis and analysis of variables. Various machine learning, deep learning, and ensemble learning algorithms were applied to create the lead time prediction models. In addition, the applicability of the proposed machine learning methodology to standard work hour prediction was verified by evaluating the prediction models using the evaluation criteria, such as the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Logarithmic Error (RMSLE).

• Korean Management Science Review
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• v.13 no.1
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• pp.47-55
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• 1996

Rapid globalization of production and marketing functions makes choice of international transportation mode of great importance. In this paper, transportation mode is characterized by two factors, mean and variability of transportation lead time. We developed a simple mathematical model to estimate the relative impact of mean lead time, lead time variance and demand variance on the required average inventory level under specified service rates.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.140-152
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• 2021

During the shift from gasoline vehicles to electric ones, auto parts manufacturing companies have realized the importance of improvement in the manufacturing process that does not require any layout changes nor extra investments, while maintaining their current production rate. Due to these reasons, for the auto part manufacturing company, I-company, this study has developed the simulation model of the PUSH system to conduct a process analysis in terms of production rate, WIP level, and logistics work's utilization rate. In addition, this study compares the PUSH system with other three manufacturing systems -KANBAN, DBR, and CONWIP- to compare the performance of these production systems, while satisfying the company's target production rate. With respect to lead-time, the simulation results show that the improvement of 77.90% for the KANBAN system, 40.39% for the CONWIP system, and 69.81% for the DBR system compared to the PUSH system. In addition, with respect to WIP level, the experimental results demonstrate that the improvement of 77.91% for the KANBAN system, 40.41% for the CONWIP system, and 69.82% for the DBR system compared to the PUSH system. Since the KANBAN system has the largest impacts on the reduction of the lead-time and WIP level compared to other production systems, this study recommends the KANBAN system as the proper manufacturing system of the target company. This study also shows that the proper size of moving units is four and the priority allocation of bottleneck process methods improves the target company's WIP and lead-time. Based on the results of this study, the adoption of the KANBAN system will significantly improve the production process of the target company in terms of lead-time and WIP level.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.78-86
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• 2015

Up-to-date business environment for manufacturers is very complex and rapidly changing. In other words, companies are facing a variety of changes, such as diversifying customer requirements, shortening product life cycles, and switching to small quantity batch production. In this situation, the companies are introducing the concept of JIT (just-in-time) to solve the problem of on-time production and on-time delivery for survival. Though many companies have introduced ERP (enterprise resource planning) systems and MRP (material requirement planning) systems, the performance of these systems seems to fall short of expectations. In this paper, the case study on introducing an APS (advanced planning and scheduling) system based on dispatching rules to a machining company and on finding a method to establish an efficient production schedule is presented. The case company has trouble creating an effective production plan and schedule, even though it is equipped with an MRP-based ERP system. The APS system is applied to CNC (computer numerical control) machines, which are key machines of the case company. The overall progress of this research is as follows. First, we collect and analyze the master data on individual products and processes of the case company in order to build a production scheduling model. Second, we perform a pre-allocation simulation based on dispatching rules in order to calculate the priority of each order. Third, we perform a set of production simulations applying the priority value in order to evaluate production lead time and tardiness of pre-defined dispatching rules. Finally, we select the optimal dispatching rule suitable for work situation of the case company. As a result, an improved production schedule leads to an increase in production and reduced production lead time.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.1
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• pp.47-47
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• 1988

Rapid globalization of production and marketing functions makes choice of international transportation mode of great importance. In this paper, transportation mode is characterized by two factors, mean and variability of transportation lead time. We developed a simple mathematical model to estimate the relative impact of mean lead time, lead time variance and demand variance on the required average inventory level under specified service rates.

• The Journal of Information Systems
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• v.17 no.4
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• pp.301-319
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• 2008

The display market has been replaced by the FPD (Flat Panel Display) from the CRT (Cathode-Ray Tube) since the late 1990s. In the FPD production line, the most equipment has high price. Thus, when the equipment has multi-function, the repetitive process is arranged for the equipment. However, such disposition of equipment results in more complicated process flow owing to repetitive operations. This reduces the production capacity and increases lead-time in turn. In this paper, we develop an AutoMod simulation system that derives to information about the quantity, production lead-time, utilities of facilities, and occupation rates of racks. In this simulation system, we consider the situation where the equipment might be broken and suspended randomly. For the developed system, we first evaluate a production plan with current layout and then, propose a revised alternative plan. Using the same simulation scheme, we investigate comparing the production quantity and lead-time with the two plans. In addition, for a proposed alternative, we try to forecast the most adequate rule between the two job dispatching rules which are FOR (Fewest Operation Remaining) and FCFS (First Come First Serve) through simulation.