Search results for: L.H.S. Luong

Authors: B. Fahimnia, L.H.S. Luong, R. M. Marian

Abstract:

The Aggregate Production Plan (APP) is a schedule of the organization-s overall operations over a planning horizon to satisfy demand while minimizing costs. It is the baseline for any further planning and formulating the master production scheduling, resources, capacity and raw material planning. This paper presents a methodology to model the Aggregate Production Planning problem, which is combinatorial in nature, when optimized with Genetic Algorithms. This is done considering a multitude of constraints of contradictory nature and the optimization criterion – overall cost, made up of costs with production, work force, inventory, and subcontracting. A case study of substantial size, used to develop the model, is presented, along with the genetic operators.

Keywords: Aggregate Production Planning, Costs, and Optimization.

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Authors: B. Fahimnia, L.H.S. Luong, B. Motevallian, R. M. Marian, M. M. Esmaeil

Abstract:

Product Lead Time (PLT) is the period of time from receiving a customer's order to delivering the final product. PLT is an indicator of the manufacturing controllability, efficiency and performance. Due to the explosion in the rate of technological innovations and the rapid changes in the nature of manufacturing processes, manufacturing firms can bring the new products to market quicker only if they can reduce their PLT and speed up the rate at which they can design, plan, control, and manufacture. Although there is a substantial body of research on manufacturing relating to cost and quality issues, there is no much specific research conducted in relation to the formulation of PLT, despite its significance and importance. This paper analyzes and formulates PLT which can be used as a guideline for achieving the shorter PLT. Further more this paper identifies the causes of delay and factors that contributes to the increased product lead-time.

Keywords: Manufacturing Control, Manufacturing Lead Time, Manufacturing Planning, Product Design, and Product Lead Time.

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Authors: Chanchal Saha, Huynh Trung Luong, M. H. Aziz, Tharinan Rattanalert

Abstract:

Now-a-days, numbers of simulation software are being used all over the world to solve Computational Fluid Dynamics (CFD) related problems. In this present study, a commercial CFD simulation software namely STAR-CCM+ is applied to analyze the airflow characteristics inside a 2.5" hard disk drive. Each step of the software is described adequately to obtain the output and the data are verified with the theories to justify the robustness of the simulation outcome. This study gives an insight about the accuracy level of the CFD simulation software to compute CFD related problems although it largely depends upon the computer speed. Also this study will open avenues for further research.

Keywords: Computational fluid dynamics, Hard disk drive, Meshing, Recirculation filter, and Filter physics parameter.

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Authors: Nhon Van Do, Nam Hoai Le, Vien Chan Luong

Abstract:

The Model for Knowledge Base of Computational Objects (KBCO model) has been successfully applied to represent the knowledge of human like Plane Geometry, Physical, Calculus. However, the original model cannot easyly apply in inorganic chemistry field because of the knowledge specific problems. So, the aim of this article is to introduce how we extend the Computional Object (Com-Object) in KBCO model, kinds of fact, problems model, and inference algorithms to develop a program for solving problems in inorganic chemistry. Our purpose is to develop the application that can help students in their study inorganic chemistry at schools. This application was built successful by using Maple, C# and WPF technology. It can solve automatically problems and give human readable solution agree with those writting by students and teachers.

Keywords: artificial intelligence, automated problem solving, knowledge base system, knowledge representation, reasoning strategy, education software/educational applications.

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Authors: Wayan F. Mahmudy, Romeo M. Marian, Lee H. S. Luong

Abstract:

This paper and its companion (Part 2) deal with modeling and optimization of two NP-hard problems in production planning of flexible manufacturing system (FMS), part type selection problem and loading problem. The part type selection problem and the loading problem are strongly related and heavily influence the system-s efficiency and productivity. The complexity of the problems is harder when flexibilities of operations such as the possibility of operation processed on alternative machines with alternative tools are considered. These problems have been modeled and solved simultaneously by using real coded genetic algorithms (RCGA) which uses an array of real numbers as chromosome representation. These real numbers can be converted into part type sequence and machines that are used to process the part types. This first part of the papers focuses on the modeling of the problems and discussing how the novel chromosome representation can be applied to solve the problems. The second part will discuss the effectiveness of the RCGA to solve various test bed problems.

Keywords: Flexible manufacturing system, production planning, part type selection problem, loading problem, real-coded genetic algorithm

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Authors: Wayan F. Mahmudy, Romeo M. Marian, Lee H. S. Luong

Abstract:

This paper presents modeling and optimization of two NP-hard problems in flexible manufacturing system (FMS), part type selection problem and loading problem. Due to the complexity and extent of the problems, the paper was split into two parts. The first part of the papers has discussed the modeling of the problems and showed how the real coded genetic algorithms (RCGA) can be applied to solve the problems. This second part discusses the effectiveness of the RCGA which uses an array of real numbers as chromosome representation. The novel proposed chromosome representation produces only feasible solutions which minimize a computational time needed by GA to push its population toward feasible search space or repair infeasible chromosomes. The proposed RCGA improves the FMS performance by considering two objectives, maximizing system throughput and maintaining the balance of the system (minimizing system unbalance). The resulted objective values are compared to the optimum values produced by branch-and-bound method. The experiments show that the proposed RCGA could reach near optimum solutions in a reasonable amount of time.

Keywords: Flexible manufacturing system, production planning, part type selection problem, loading problem, real-coded genetic algorithm

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Authors: Wayan F. Mahmudy, Romeo M. Marian, Lee H. S. Luong

Abstract:

 This paper deals with modeling and optimization of two NP-hard problems in production planning of flexible manufacturing system (FMS), part type selection problem and loading problem. The part type selection problem and the loading problem are strongly related and heavily influence the system’s efficiency and productivity. These problems have been modeled and solved simultaneously by using real coded genetic algorithms (RCGA) which uses an array of real numbers as chromosome representation. The novel proposed chromosome representation produces only feasible solutions which minimize a computational time needed by GA to push its population toward feasible search space or repair infeasible chromosomes. The proposed RCGA improves the FMS performance by considering two objectives, maximizing system throughput and maintaining the balance of the system (minimizing system unbalance). The resulted objective values are compared to the optimum values produced by branch-and-bound method. The experiments show that the proposed RCGA could reach near optimum solutions in a reasonable amount of time.

Keywords: Flexible manufacturing system, production planning, part type selection problem, loading problem, real-coded genetic algorithm.

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