Research on the module configuration of complex products considering the evolution of the product family

2020 ◽  
Vol 39 (3) ◽  
pp. 4577-4595
Author(s):  
Zhenhua Liu ◽  
Mengting Zhang ◽  
Yupeng Li ◽  
Xuening Chu
Keyword(s):  
Customer Satisfaction ◽  
Programming Model ◽  
New Technology ◽  
Pareto Frontier ◽  
Product Family ◽  
Product Configuration ◽  
Future Market ◽  
Complex Products ◽  
Configuration Scheme

The evolution of the product family is the essential driving force for the development of a complex product. Only customer satisfaction is emphasized in the traditional module configuration methods, which is not beneficial for product family evolution that is due to non-customer factors such as the emergence of new technology. In this study, the intuitionistic fuzzy number is employed to quantify the degree of correlation between each module and configuration targets, namely customer satisfaction and the degree of evolution of the product family, respectively. The bi-objective integer programming model is constructed by maximizing the degree of customer satisfaction and product family evolution. An improved Pareto ant colony optimization (P-ACO) is designed to solve this model and subsequently the Pareto frontier is obtained. The radar chart is adopted to represent the performance of each configuration scheme in the Pareto frontier. The feasibility and effectiveness of the proposed method are expounded by a case study and result comparison, showing that this method can provide a more competitive product configuration scheme to customers in the future market.

Process configuration: Combining the principles of product configuration and process planning

2001 ◽  
Vol 15 (5) ◽  
pp. 411-424 ◽  
Author(s):  
KARSTEN SCHIERHOLT
Keyword(s):  
Process Planning ◽  
Product Family ◽  
Product Configuration ◽  
Process Configuration ◽  
Rolling Industry ◽  
Configuration System ◽  
Planning Task ◽  
Product Specifications ◽  
Additional Product

Product configuration is the process of generating a product variant from a previously defined product family model and additional product specifications for this variant. The process of finding and sequencing the relevant operations for manufacturing this product is called process planning. This article combines the two principles in a new concept of process configuration that solves the process planning task using product configuration methods. The second section develops characteristics for two process configuration concepts, the interactive process configuration and the automation-based process configuration. Following an overview of the implementation of a process configuration system, the results of a case study in the aluminum rolling industry are presented. The main benefits of the process configuration concept are observed in a reduced knowledge-maintenance effort and in increased problem-solving speed.

scholarly journals Developing a Quick Response Product Configuration System under Industry 4.0 Based on Customer Requirement Modelling and Optimization Method

2019 ◽  
Vol 9 (23) ◽  
pp. 5004 ◽  
Author(s):  
Lee ◽  
Chen ◽  
Lin ◽  
Li ◽  
Zhao
Keyword(s):  
Customer Satisfaction ◽  
Industry 4.0 ◽  
Quality Function Deployment ◽  
Programming Model ◽  
Optimization Method ◽  
Product Configuration ◽  
Quick Response ◽  
Kano Model ◽  
Configuration System ◽  
Technical Specifications

In the Industry 4.0 environment, the new manufacturing transformation of mass customization for high-complexity and low-volume production is moving forward. Based on cyber-physical system (CPS) and Internet of things (IoT) technology, the flexible transformation of the manufacturing process to suit diverse customer manufacturing requirements is very possible, with the potential to provide digital “make-to-order” (MTO) services with a quick response time. To achieve this potential, a product configuration system, which translates the voice of customers to technical specifications, is needed. The purpose of this study is to propose a methodology for developing a quick-response product configuration system to enhance the communication between the customer and the manufacturer. The aim is to find an approach to receive requests from customers as inputs and generate a product configuration as outputs that maximizes customer satisfaction. In this approach, engineering characteristics (ECs) are defined, and selection pools are initially constructed. Then, quality function deployment (QFD) is modified and integrated with the Kano model to qualitatively and quantitatively analyze the relationship between customer requirements (CRs) and customer satisfaction (CS). Next, a mathematical programming model is applied to maximize the overall customer satisfaction level and recommend an optimal product configuration. Finally, sensitivity analysis is conducted to suggest revisions for customers and determine the final customized product specification. A case study and an OrderAssistant system are implemented to demonstrate the procedure and effectiveness of the proposed quick response product configuration system.

scholarly journals Product Module Attribute Parameter Configuration Model considering Customer Requirements Preferences

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yang Qin ◽  
Ye Zhaofa ◽  
Li Xuzheng ◽  
Zhang Zufang ◽  
Chang Weijie ◽  
...  
Keyword(s):  
Quality Function Deployment ◽  
Programming Model ◽  
Weight Vector ◽  
Product Configuration ◽  
Configuration Model ◽  
Preference Weight ◽  
Customer Requirements ◽  
Parameter Configuration ◽  
Preference Graph ◽  
Configuration Scheme

In the process of modular product configuration, it is necessary to transform customer requirements into product module attributes (PMA) parameters. However, previous research lacks consideration about customer requirement preference in the process of this transformation. First, we use a preference graph (PG) to obtain the customer preference weight vector for the requirement node. Second, on the basis of traditional Quality Function Deployment (QFD), the method of fuzzy correlation evaluation is introduced to get the correlation value between module attributes, and the combination programming model of PMA is further obtained by synthesizing the preference weight vector. Finally, the final configuration scheme is obtained by solving the model with the genetic algorithm. By integrating the weights of the above-mentioned nodes, the similarity of the product case is obtained, and a more satisfied case of the customer is obtained. Taking the automated guided vehicle car product as an example, the effectiveness and practicability of the proposed method are verified.

Case Study: User Adoption of a Product Configuration Management System at a Modular Playground Equipment Producer

2006 ◽  
Author(s):  
Bethany M. Byron ◽  
Steven B. Shooter
Keyword(s):  
Management System ◽  
Product Family ◽  
Information Management System ◽  
Product Configuration ◽  
Training Methods ◽  
Product Families ◽  
Product Configuration Management ◽  
Storage And Retrieval ◽  
User Adoption

Product platform and product family strategies place tremendous demands on the efficient capture, storage, and retrieval of information in the form of product data. The user’s adoption of an information management system for product families and mass customization is critical for allowing the system to perform as it ought. The following is a case study at a major modular playground equipment producer undergoing the implementation of a new graphical-based configurator for managing its mass customized products. The case study examines the proliferation of software packages to perform configuration and the flow of information in the configuration process. Next, the new configurator is evaluated on its new features to capture, store, and reuse configurations and its visual appeal. Last, the paper addresses the personal behaviors and training methods used for increasing adoption and their success.

scholarly journals A New Classification Analysis of Customer Requirement Information Based on Quantitative Standardization for Product Configuration

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Zheng Xiao ◽  
Zude Zhou ◽  
Buyun Sheng
Keyword(s):  
Product Family ◽  
Hierarchical Structures ◽  
Product Configuration ◽  
Customer Requirement ◽  
New Classification ◽  
Classification Analysis ◽  
Data Formats ◽  
Subsequent Application

Traditional methods used for the classification of customer requirement information are typically based on specific indicators, hierarchical structures, and data formats and involve a qualitative analysis in terms of stationary patterns. Because these methods neither consider the scalability of classification results nor do they regard subsequent application to product configuration, their classification becomes an isolated operation. However, the transformation of customer requirement information into quantifiable values would lead to a dynamic classification according to specific conditions and would enable an association with product configuration in an enterprise. This paper introduces a classification analysis based on quantitative standardization, which focuses on (i) expressing customer requirement information mathematically and (ii) classifying customer requirement information for product configuration purposes. Our classification analysis treated customer requirement information as follows: first, it was transformed into standardized values using mathematics, subsequent to which it was classified through calculating the dissimilarity with general customer requirement information related to the product family. Finally, a case study was used to demonstrate and validate the feasibility and effectiveness of the classification analysis.

Product-Service Family Enabled Product Configuration System for Cloud Manufacturing

2017 ◽  
Author(s):  
Shiqiang Yu ◽  
Pai Zheng ◽  
Chunyang Yu ◽  
Xun Xu
Keyword(s):  
Product Family ◽  
Cloud Manufacturing ◽  
Product Configuration ◽  
The Internet ◽  
Product Service ◽  
Process Manufacturing ◽  
Service Oriented ◽  
Configuration System ◽  
Engineer To Order

Rapid responsiveness to diverse customer needs is considered a competitive advantage in manufacturing business. To shrink the inquiry-to-order process, manufacturing firms will benefit a lot from building a product configuration system (PCS) which is the enabler of mass customisation (MC). PCS has matured in consumer businesses for decades but in capital goods industries, typically operating in engineer-to-order (ETO) manner, things differ a lot. It is for the reason that conventional PCS is incapable of extending customisation from order-delivery processes to the design/engineering phase. Cloud manufacturing, which is an emerging service-oriented manufacturing paradigms enabled by cyber-physical system, the Internet of Things and the Internet of Service, is promising to break the bottleneck of “ETO PCS” by the provision of technical infrastructure for product, service and data customisation. With the introducing of manufacturing-as-a-service (MaaS) concept, a product family is extended to a product-service family (PSF) in this paper for implementing in-depth product configuration process with scalable customisation depth (i.e., the degree of customisation freedom). Additionally, an approach of service delegation in product configuration process is proposed to support customer-centric product customisation. At last, the methodology proposed in this paper is validated by a case study in which the product configuration process of a complex ETO product is performed.

scholarly journals Optimal Configuration Algorithm for Mechanical Products Based on the Constraint of Carbon Footprint

2015 ◽  
Vol 9 (1) ◽  
pp. 312-319
Author(s):  
Wei Bo ◽  
Li Renwang ◽  
Zheng Hui ◽  
Zong Xianliang
Keyword(s):  
Carbon Footprint ◽  
Comprehensive Evaluation ◽  
Product Configuration ◽  
Benefit Evaluation ◽  
Mechanical Products ◽  
Comprehensive Benefit ◽  
Three Stages ◽  
Configuration Scheme ◽  
Grey Relation

The concept of carbon footprint controllable product is proposed to assess carbon footprint during the stage of product development and configuration. It’s different from carbon footprint assessment afterwards. As a result, the control objectives can be quantified accurately and realized easily. Relations among product characteristics, which include carbon footprint, are uncertain. In order to obtain the optimal product configuration scheme based on constraint of carbon footprint, three-stage theory is proposed. These three stages refer to functional configuration, compliance evaluation of carbon footprint, and optimal comprehensive evaluation. Using this theory, functional feasible solution set, carbon footprint conforming set and the optimal scheme are generated respectively. Grey relation analysis is verified as an effective method for comprehensive benefit evaluation. Reducer design is used as a case study to illustrate the proposed concept.

Design for Customer Satisfaction in One-of-a-Kind Production Environment

2006 ◽  
Author(s):  
G. Hong ◽  
L. Hu ◽  
D. Xue ◽  
Y. L. Tu ◽  
Y. L. Xiong
Keyword(s):  
Customer Satisfaction ◽  
Genetic Programming ◽  
Constrained Optimization ◽  
Product Family ◽  
Product Configuration ◽  
Production Environment ◽  
Linear Relations ◽  
Evaluation Measures ◽  
Satisfaction Index ◽  
Work Variations

This research addresses the issues to identify the optimal product configuration and its parameters based on the requirements of customers on performance and costs of products in one-of-a-kind production (OKP) environment. In this work, variations of product configurations and parameters in an OKP product family are modeled by an AND-OR tree and parameters of the nodes in this tree. Different product configurations with different parameters are evaluated by performance and cost measures. These evaluation measures are converted into comparable customer satisfaction indices using the non-linear relations between the evaluation measures and the customer satisfaction indices. The optimal product configuration and its parameters with the maximum overall customer satisfaction index are identified by genetic programming and constrained optimization.

Integrated Quantitative Analysis of Customer Satisfaction Based on Kano's Model

2012 ◽  
Vol 224 ◽  
pp. 358-361
Author(s):  
Zhi Jun Fan ◽  
Zhao Liang Jiang
Keyword(s):  
Quantitative Analysis ◽  
Customer Satisfaction ◽  
Product Configuration ◽  
Customer Requirements ◽  
Kano’S Model ◽  
Group Satisfaction

The satisfaction of customer requirements (CRs) is the objective of product configuration. A methodology Based on the Kano's model was proposed to explore customers' stated needs and unstated desires and to resolve them into different categories which have different impacts on customer satisfactions (CSs). The customer satisfactions are classified into group satisfaction and individual satisfaction, and each of them has three types with Kano theory. Group requirements items were selected frequently by the same kind of customers. Individual requirements were specified by the customer himself. Based on a combination of group satisfactions and individual satisfactions, the integrated satisfaction was determined. A case study is provided to illustrate the effectiveness of the presented method.

Blockchain in Supply Chain: Case Study of Lottemart Ciputat

2019 ◽  
Vol 5 (1) ◽  
pp. 38-49 ◽  
Author(s):  
B. K. Handoyo ◽  
M. R. Mashudi ◽  
H. P. Ipung
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Information Asymmetry ◽  
New Technology ◽  
Business Case ◽  
Analysis Method ◽  
Chain Management ◽  
Production Processes

Current supply chain methods are having difficulties in resolving problems arising from the lack of trust in supply chains. The root reason lies in two challenges brought to the traditional mechanism: self-interests of supply chain members and information asymmetry in production processes. Blockchain is a promising technology to address these problems. The key objective of this paper is to present qualitative analysis for blockchain in supply chain as the decision-making framework to implement this new technology. The analysis method used Val IT business case framework, validated by the expert judgements. The further study needs to be elaborated by either the existing organization that use blockchain or assessment by the organization that will use blockchain to improve their supply chain management.

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