Product Variety Deployment and its Optimization Under Modular Architecture and Module Commonalization

1999 ◽  
Author(s):  
Kikuo Fujita ◽  
Hisato Sakaguchi ◽  
Shinsuke Akagi
Keyword(s):  
Product Variety ◽  
Optimization Method ◽  
Manufacturing Firms ◽  
Integer Programming Problem ◽  
Modular Architecture ◽  
Virtual Design ◽  
Abstract Form ◽  
Multiple Products ◽  
Simultaneous Design ◽  
Television Receiver

Abstract Simultaneous design of multiple products has become essential for manufacturing firms to expand design optimization basis. Various viewpoints on this issue have been provided from investigation of practices, but their outcomes still stay on descriptive stages. This paper discusses product variety design under modular architecture and module commonalization toward a computational methodology. It reviews the module based product variety with a mixture of views from customer’s needs, functions, manufacturing modules and hierarchical representation of systems. Based on the consequent framework, this paper also mathematically formulates the problem of product variety design as a 0-1 integer-programming problem in a systematically abstract form, and develops an optimization algorithm based on a simulated annealing technique. These discussion and optimization method are applied to a virtual design problem of television receiver circuits to show their validity and promise.

Product Variety Optimization: Simultaneous Optimization of Module Combination and Module Attributes

2001 ◽  
Author(s):  
Kikuo Fujita ◽  
Hiroko Yoshida
Keyword(s):  
Product Variety ◽  
Optimization Method ◽  
Programming Method ◽  
Simultaneous Optimization ◽  
Mixed Integer ◽  
Strategy System ◽  
Multiple Products ◽  
Simultaneous Design ◽  
Design Paradigm ◽  
Quadratic Programming Method

Abstract This paper proposes a simultaneous optimization method for both module combination and module attributes of multiple products. As manufacturing competition has become restricted with high profitability and external constraints, simultaneous design of multiple products, which is called product variety design etc., becomes an important strategy. System-based optimal design paradigm is expected to be essential to rationalize such practices, since design for product variety is more complicated than one for a single product. Toward such a direction, we configure an optimization method for both module combination and module attributes across multiple products. The optimization method hybridizes a genetic algorithm, a mixed-integer programming method with a branch-and-bound technique, and a constrained nonlinear programming method, i.e., a successive quadratic programming method. In its optimization process, the first optimizes the combinatorial pattern of module commonality and similarity among different products, the second optimizes the directions of similarity on scale-based variety, and the third optimizes the continuous module attributes under the others. Finally it is applied to the simultaneous design problem of multiple airplanes to demonstrate its validity and effectiveness.

The Optimal Controlled Partitioning Strategy for Power System Based on Master-Slave Problem

2013 ◽  
Vol 385-386 ◽  
pp. 999-1006
Author(s):  
Wei Wang ◽  
Ting Yu ◽  
Tian Jiao Pu ◽  
Ai Zhong Tian ◽  
Ji Keng Lin
Keyword(s):  
Large Scale ◽  
Optimization Method ◽  
Mixed Integer ◽  
Master Problem ◽  
Decomposition Algorithms ◽  
Integer Programming Problem ◽  
Complete Model ◽  
New Approach ◽  
Mixed Integer Programming Problem ◽  
Partitioning Strategy

Controlled partitioning strategy is one of the effective measures taken for the situation when system out-of-step occurs. The complete splitting model, mostly solved by approximate decomposition algorithms, is a large-scale nonlinear mixed integer programming problem. A new alternate optimization method based on master-slave problem to search for optimal splitting strategy is proposed hereby. The complete model was converted into master-slave problems based on CGKP (Connected Graph Constrained Knapsack Problem). The coupling between master problem and slave problem is achieved through load adjustment. A better splitting strategy can be obtained through the alternating iteration between the master problem and the salve problem. The results of the examples show that the method can obtain better splitting strategy with less shed load than other approximate algorithms, which verifies the feasibility and effectiveness of the new approach presented.

Global Product Family Design: A Mathematical Model for Simultaneous Decision of Module Commonalization and Supply Chain Configuration

2011 ◽  
Author(s):  
Kikuo Fujita ◽  
Hirofumi Amaya ◽  
Ryota Akai
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Product Family ◽  
Product Variety ◽  
Optimization Method ◽  
Product Family Design ◽  
Design Production ◽  
Supply Chain Configuration ◽  
The Given ◽  
Chain Configuration

Today’s manufacturing has become global at all aspects of marketing, design, production, distribution, etc. While product family design has been an essential viewpoint for meeting with the demand for product variety, its meaning is becoming more broad and complicated with linking product design with issues on market systems, supply chain, etc. This paper calls such a design situation ‘global product family design,’ and firstly characterizes its components and complexity. Following them, this paper develops a mathematical model for the simultaneous decision problem of module commonalization strategies under the given product architecture and supply chain configuration through selection of manufacturing sites for module production, assembly and final distribution as an instance of the problems. This paper demonstrates some numerical case studies for ascertaining the validity and promise of the developed mathematical model with an optimization method configured with a genetic algorithm and a simplex method. Finally, it concludes with some discussion on future works.

Simultaneous small UAV and autopilot system design

2016 ◽  
Vol 88 (6) ◽  
pp. 818-834 ◽  
Author(s):  
Turgul Oktay ◽  
Mehmet Konar ◽  
Murat Onay ◽  
Murat Aydin ◽  
Mohamed Abdallah Mohamed
Keyword(s):  
System Design ◽  
Optimization Method ◽  
Civil Aviation ◽  
Flight Performance ◽  
Content Type ◽  
Simultaneous Design ◽  
Small Uav ◽  
Directorate General ◽  
Model Aircraft ◽  
Design Idea

Purpose The purpose of this paper is to increase flight performance of small unmanned aerial vehicle (UAV) using simultaneous UAV and autopilot system design. Design/methodology/approach A small UAV is manufactured in Erciyes University, College of Aviation, Model Aircraft Laboratory. Its wing and tail is able to move forward and backward in the nose-to-tail direction in prescribed interval. Autopilot parameters and assembly position of wing and tail to fuselage are simultaneously designed to maximize flight performance using a stochastic optimization method. Results are obtained are used for simulations. Findings Using simultaneous UAV and autopilot system design idea, flight performance is maximized. Research limitations/implications Permission of Directorate General of Civil Aviation in Turkey is required for testing UAVs in long range. Practical implications Simultaneous design idea is very beneficial for improving UAV flight performance. Originality/value Creating a novel method to improve flight performance of UAV and developing an algorithm performing simultaneous design idea.

scholarly journals Improving Autonomous Performance of a Passive Morphing Fixed Wing UAV

2020 ◽  
Vol 49 (1) ◽  
pp. 28-35
Author(s):  
Sezer Coban
Keyword(s):  
State Space ◽  
Real Time ◽  
Flight Control ◽  
High Performance ◽  
Block Diagram ◽  
State Space Model ◽  
Optimization Method ◽  
Simultaneous Design ◽  
Computer Environment ◽  
Aerial Vehicle

In this study, it is examined that simultaneous flight control system and lateral and longitudional state-space model of a Unmanned Aerial Vehicle (UAV) and real time application. For this purpose an UAV whose wing and tail unit can be assembled to fuselage from different points in a prescribed interval and whose wing and tail can move forward and backward independently in tail to nose direction is manufactured. Following this, an autopilot is purchased and it lets change of P, I, D coefficients in certain intervals. First, dynamic model, and longitudinal and lateral state space models of UAV are obtained and then simulation model of UAV is reached. At the same time block diagram of autopilot system and modeling of it in MATLAB/Simulink environment are found. After these, using these two models and also benefiting and adaptive stochastic optimization method namely SPSA, simultaneous design of UAV and autopilot is done in order to minimize a cost function consisting of rise time, settling time and maximum overshoot. Therefore, primarily autonomous performance is maximized in computer environment. Moreover, high performance is observed by looking at simulation responses and real-time flights.

Ant Colony Optimization Method for Product Platform Formation

2004 ◽  
Author(s):  
Rupesh Kumar ◽  
Venkat Allada ◽  
Sreeram Ramakrishnan
Keyword(s):  
Ant Colony Optimization ◽  
Product Variety ◽  
Optimization Method ◽  
Ant Colony ◽  
Product Platform ◽  
Probabilistic Search ◽  
Design Variables ◽  
Product Customization ◽  
Scaling Variables ◽  
Effective Product

Product platform concepts are often deployed to achieve product variety and hence effective product customization. One of the popular methods to achieve product variety is to scale one or more design variables called the scaling variable(s). This necessitates efficient methods for identifying the values for scaling variables. This paper presents a graph-based optimization method called Platform Ant Colony Optimization (PACO) for identifying the values of the scaling variable(s) for platform formation. In PACO, the overall decision is a function of the cumulative decisions of simple computing agents called the ‘ants.’ The method employs an autocatalytic mechanism using a probabilistic search to improve the solution iteratively. We use a universal electric motor example cited in the literature to test the efficiency of the proposed method. Simulation results on the example problem indicate that the PACO method produces promising results.

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