Abstract:
This paper presents various measures of a port’s optimum throughput to which its actual throughput can be compared in order to evaluate its performance. A port’s engineering optimum throughput is its maximum (technically efficient) throughput that physically can be handled by the port under certain conditions. A port’s economic optimum throughput is that throughput that satisfies an economic objective. It may be either an economic: (1) technically efficient optimum throughput (based upon the port’s economic production function), (2) cost efficient optimum throughput (based upon the port’s economic cost function) or (3) effectiveness optimum throughput (based upon the port’s effectiveness operating objective such as maximizing profits).Keywords:
Port (circuit theory)
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Build to order
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Capacity planning
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Inventory-production coordination for customer orders is becoming increasingly important for companies to increase customer responsiveness and achieve economic purposes. In this paper, the joint optimization of inventory and production is considered for stochastic customer orders to maximize the throughput. Demands of customer orders dynamically arrive at the inventory department, and each incoming order consists of multiple product types with random workloads. To process the workloads, certain amounts of a common raw material are required and need to be drawn from the inventory department. A customer order will be lost if there do not exist enough raw materials in the inventory department. With the necessary materials, workloads of accepted orders will be assigned to a set of unrelated parallel servers to be processed in the production department. This paper intends to maximize the effective throughput through proper coordination of the inventory and the production departments. For this problem, system bottlenecks are identified and analyzed, and mathematical programming models are developed to determine the optimal throughput and the corresponding inventory and production policies. Several special cases are also explored to provide intuitive insights into the relationship between the system parameters and optimal throughput. Relationships between key model parameters and effective throughput are identified through sensitivity analysis and further validated by the results of computational experiments.
Order fulfillment
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Proper utilization of manufacturing resources is of crucial importance to any manufacturing industry in today's global arena of competition.Simulation is extremely valuable tool for analyzing complex manufacturing systems.This paper presents a simulation study carried out at a flywheel manufacturing industry.This manufacturing industry required analysis of its manufacturing process in an attempt to increase its throughput and overall productivity.The main objective of this work was to simulate the existing flywheel manufacturing system and to find whether the current layout gives maximum throughput if not to find out the maximum throughput of the facility and to find the current bottlenecks to the throughput.The work provides information about performance of manufacturing system after optimization of certain parameters.A simulation model of existing flywheel manufacturing system was developed using manufacturing simulation tool.The simulation output helped to answer above mentioned questions.A set of feasible modifications to the existing manufacturing process was prepared.These modifications were included in the simulation model and output of the modified model was analyzed.The results show significant amount of improvement in the parameters like throughput and the work in process (WIP).
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In this paper, we discussed a simulation study for improving the throughput of a crankshaft manufacturing line in an automotive factory, where there is the limitation of budget for purchasing new machines. Although this problem is a kind of knapsack problem, it is not easy to calculate the throughput by mathematical analysis, and therefore simulation model was developed using ARENA ® . To determine the investment plan, we used two methods, arrow assignment rule and all enumeration method.
Factory (object-oriented programming)
Line (geometry)
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The complexity of manufacturing systems makes the accurate prediction of production throughput difficult because of many variables. Continuously developing and implementing scientific methods can advance the understanding of the throughput of complex manufacturing systems. This throughput study addresses the main factors of manufacturing systems in the setting of a serial line. The factors include the reliability and cycle time of workstations, the length of a manufacturing line, and the capacity and locations of internal buffers in a manufacturing line. To effectively study these factors, the authors propose and use Design of Experiments (DOE) and Discrete-Event Simulation (DES) to analyze and predict the throughput of a manufacturing system under different settings. The study results provide a new understanding of the impacts of these factors on the production throughput of serial manufacturing lines. The study outcomes can be a valued reference for the development of such complex manufacturing systems to achieve the desired throughput.
Workstation
Production line
Discrete-Event Simulation
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To remain competitive and to boost profitability, manufacturers in capital-intensive and highly competitive industries want to maximize throughput and minimize flow time. Achieving high throughput conflicts with achieving low flow time. In order to unhide the tradeoff between throughput and flow time, a performance measure, called manufacturing performance, has been developed. The manufacturing performance is defined by the quotient of the ratio between throughput and flow time of an actual manufacturing system and this ratio of a reference system. The reference system can be adapted by the user in correspondence with objectives. By applying the manufacturing performance to one workstation and using analytic approximations for this workstation, manufacturing performance can be expressed analytically. It seems that manufacturing performance has an optimal value that is given by equipment availability and coefficient of variation. Manufacturing performance is applied also to a four-workstation manufacturing line. Results from analytic approximations show the practicability of the manufacturing performance. Comparison of manufacturing performance with overall fab efficiency, an earlier proposed metric, showed that the manufacturing performance is a more clear metric. This conclusion was based upon simulations with a two-stations manufacturing line. The manufacturing performance is a technical performance metric for manufacturing lines that supports, for instance, economical considerations to obtain optimal throughput-flow time combinations under economical optimal results. This is a useful addition to the existing metrics, which may benefit manufacturers in their operations. The authors consider this contribution as a discussion paper and demand for comment.
Workstation
Performance metric
Manufacturing
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Maintainability
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[The entire thesis is written in English] In this assignment, the main goal is to reduce the throughput time of the production of product A, an aircraft engine component. The action problem proposed by the company is: “How can the throughput time of product A be minimized from 9 weeks to a maximum of 4 weeks?” The main goal in order to achieve this is improving the current planning and control approach. By doing a literature study, multiple planning and control approaches have been identified (e.g. MRP, Kanban, ConWIP) Their applicability to company A has been assessed. The potential best approaches have been tested in a simulation model. Next to the planning and control approach, multiple other scenarios have been tested and compared within the simulation model, in order to reduce the throughput time. Lastly, a capacity analysis has been done in order to determine the costs of achieving the required goal of four weeks.
Component (thermodynamics)
Kanban
Build to order
Material requirements planning
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In order to determine the efficiency of a production system, batch size and throughput are two important parameters that must be considered. In order to ensure system efficiencies and meet optimum utilization, batch size must conform to the throughput. The use of Queuing Network Theory to study the effect of batch size and throughput in optimizing the resource utilization, particularly machine resources, in a manufacturing system is discussed in this paper. A manufacturing company industry dealing with assembling operations in its production lines was chosen for this study. The findings of the study concluded that increasing batch size and throughput increases the utilization. When the capacity is not enough to meet the demand requirement, bottlenecks will occur.
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