Fuzzy Topsis Decision Method for Configuration Management

Mass customization refers to an environment in which reducing quantities and increasing varieties of products are being manufactured. A product configuration is defined as an aggregation of parts whose functions and performance parameters must be defined and controlled to achieve the overall performance of a system or product. Since the product configurations would be varied based on consumer needs, selecting effective product configurations from among several alternatives is a challenge during the mass customization design stage. This study developed a structural model which combines a fuzzy quality function deployment with a fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) to solve this problem. The configuration alternatives ranked using the proposed method can provide a useful reference for decision makers in implementing configuration management

Generic bill of functions, materials, and operations for SAP2 configuration

International audienceMost available studies on configuration focus on either sales configuration specifying functional features or production configuration addressing product components. It has been well recognised that automating most of the activities associated with specification, engineering, and process planning of customised products and their interactions is one key in achieving product customisation. Thus, treating sales configuration and product configuration separately may not contribute to product customisation from a systematic view although they may lead to the improvement of individual stages. Recognising this limitation of existing studies, in this paper, we propose integrated SAles, Product and Production (SAP2) configuration, which helps achieve product customisation from a holistic view. Its rationale lies in automating consistently sales, product and production configuration activities in one system. In view of the importance of configuration models, we focus on the model underpinning SAP2 configuration called generic bill of functions, materials and operations (GBoFMO) and discuss it in detail. As the core of SAP2 configuration, GBoFMO can provide companies with an insight into organising the large volumes of data and knowledge in the life cycle of product family development. We also report a case study of light passenger aircrafts to illustrate the GBoFMO

Optimisation of the concurrent product and process configuration: an approach to reduce computation time with an experimental evaluation

International audienceConcurrent configuration of a product and its associated production process is a challenging problem in customer/supplier relations dealing with customisable or configurable products. It gathers in a single model multiple choices and constraints which come simultaneously from products (choices of components or functionalities), from processes (choices of resources and quantities) and from their mutual interrelations. Considering this problem as a Constraint Satisfaction Problem (CSP), the aim of this article is to improve its optimisation, while considering multiple objectives. Using an existing evolutionary optimisation algorithm as a basis, we propose an approach that reduces the computation time required for optimisation. The idea is first to quickly compute a rough Pareto of solutions, then ask the user to select an area of interest, and finally to launch a second computation on this restricted area. After an introduction to the problem, the approach is explained and the algorithm adaptations are presented. Then various computation experiments results demonstrate that computation times are significantly reduced while keeping the optimality level

Towards customization : Evaluation of integrated sales, product, and production configuration

Acknowledgement We are grateful to the anonymous reviewers for their constructive comments, which helped us improve both the quality and presentation of the paper.Peer reviewedPostprin

Risk prediction of product-harm events using rough sets and multiple classifier fusion:an experimental study of listed companies in China

With the increasing of frequency and destructiveness of product-harm events, study on enterprise crisis management becomes essentially important, but little literature thoroughly explores the risk prediction method of product-harm event. In this study, an initial index system for risk prediction was built based on the analysis of the key drivers of the product-harm event's evolution; ultimately, nine risk-forecasting indexes were obtained using rough set attribute reduction. With the four indexes of cumulative abnormal returns as the input, fuzzy clustering was used to classify the risk level of a product-harm event into four grades. In order to control the uncertainty and instability of single classifiers in risk prediction, multiple classifier fusion was introduced and combined with self-organising data mining (SODM). Further, an SODM-based multiple classifier fusion (SB-MCF) model was presented for the risk prediction related to a product-harm event. The experimental results based on 165 Chinese listed companies indicated that the SB-MCF model improved the average predictive accuracy and reduced variation degree simultaneously. The statistical analysis demonstrated that the SB-MCF model significantly outperformed six widely used single classification models (e.g. neural networks, support vector machine, and case-based reasoning) and other six commonly used multiple classifier fusion methods (e.g. majority voting, Bayesian method, and genetic algorithm)

Incorporating temporal-bounded CBR techniques in real-time agents

Nowadays, MAS paradigm tries to move Computation to a new level of abstraction: Computation as interaction, where large complex systems are seen in terms of the services they offer, and consequently in terms of the entities or agents providing or consuming services. However, MAS technology is found to be lacking in some critical environments as real-time environments. An interaction-based vision of a real-time system involves the purchase of a responsibility by any entity or agent for the accomplishment of a required service under possibly hard or soft temporal conditions. This vision notably increases the complexity of these kinds of systems. The main problem in the architecture development of agents in real-time environments is with the deliberation process where it is difficult to integrate complex bounded deliberative processes for decision-making in a simple and efficient way. According to this, this work presents a temporal-bounded deliberative case-based behaviour as an anytime solution. More specifically, the work proposes a new temporal-bounded CBR algorithm which facilitates deliberative processes for agents in real-time environments, which need both real-time and deliberative capabilities. The paper presents too an application example for the automated management simulation of internal and external mail in a department plant. This example has allowed to evaluate the proposal investigating the performance of the system and the temporal-bounded deliberative case-based behaviour. 2010 Elsevier Ltd. All rights reserved.This work is supported by TIN2006-14630-C03-01 projects of the Spanish government, GVPRE/2008/070 project, FEDER funds and CONSOLIDER-INGENIO 2010 under Grant CSD2007-00022.Navarro Llácer, M.; Heras Barberá, SM.; Julian Inglada, VJ.; Botti Navarro, VJ. (2011). Incorporating temporal-bounded CBR techniques in real-time agents. Expert Systems with Applications. 38(3):2783-2796. https://doi.org/10.1016/j.eswa.2010.08.070S2783279638

How to scope configuration projects and manage the knowledge they require

Purpose: This paper aims to explore the use of the knowledge management (KM) perspective for configuration projects. Configuration projects implement configurators as information technology systems that help companies manage the specification process of customised products. An effective method of retrieving and formalising knowledge for configurators is essential, because it can reduce the risk of unsuccessful implementation and the time and effort required for development. Unfortunately, no standard KM frameworks are available specifically for configuration projects. This study identifies the knowledge necessary for different phases of a configuration project (which knowledge, for what purpose and from what sources), examines how it is transformed during a configuration project (what KM activities and tools are used) and establishes how the knowledge can be documented for future maintenance and updates. Design/methodology/approach: This paper proposes a four-step framework for making the KM process more efficient in configuration projects. The framework is based on the literature, developed in collaboration with industrial partners and tested on four configuration projects in two engineering companies. The framework is a structured KM approach designed to save time for both domain experts and the configuration team. The authors have used a qualitative exploratory design based on multiple data sources: documentation, workshops and participant observation. Findings: The proposed framework comprises four steps: determination of the system\u2019s scope, to establish the project\u2019s goal based on stakeholders\u2019 requirements and prioritise the required products and processes; knowledge acquisition, to classify the knowledge according to the desired output and identify different knowledge sources; modelling and knowledge validation; and documentation and maintenance, to ensure that the KM system can be maintained and updated in the future. Research limitations/implications: Because the framework is tested on a limited number of cases, its generalisability may be limited. However, focusing on a few case applications allows us to assess the effectiveness of the framework in detail and in depth to identify the practical challenges of applying it. The results of the tests support the framework\u2019s validity. Although the framework is designed mainly for engineering companies, other industries could benefit from using it as well. Practical implications: The individual steps of the framework create a structured approach for the KM process. Thus, the approach can save both time and resources for companies, without the need for additional investment. Originality/value: A standard framework is lacking in the literature on KM for configuration projects. This study fills that gap by developing a KM framework for configuration projects, based on KM frameworks developed for IT projects, and KM tools

Applying case-based reasoning for product configuration in mass customization environments

[[abstract]]Product variation and customization is a trend in current market-oriented manufacturing environment. Companies produce products in order to satisfy customer’s needs. In the customization environment, the R&D sector in an enterprise should be able to offer differentiation in product selection after they take the order. Such product differentiation should meet the requirement of cost and manufacturing procedure. In the light of this, how to generate an accurate bill of material (BOM) that meets the customer’s needs and gets ready for the production is an important issue in the intensely competitive market. The purpose of this study is to reduce effectively the time and cost of design under the premise to manufacture an accurate new product. In this study, the Case-Based Reasoning (CBR) algorithm was used to construct the new BOM. Retrieving previous cases that resemble the current problem can save a lot of time in figuring out the problem and offer a correct direction for designers. When solving a new problem, CBR technique can quickly help generate a right BOM that fits the present situation

A Semantic Similarity Method for Products and Processes

豊橋技術科学大