An intelligent forward quality enhancement system to achieve product customization

Abstract

PurposeThis paper proposes an infrastructural framework, involving various emerging technologies, for the development of an agent‐based quality enhancement system with the distinct feature of the ability to cope with the potential quality problems from various customers' requirements.Design/methodology/approachThe proposed system is equipped with the “distributed problem solving” feature which automatically identifies and divides the potential quality problems into sub‐problems and directs straight to the associated agents that are capable of interacting and negotiating with each other to support customer needs. The new feature of this agile quality enhancement system is characterized with the incorporation of the quality mining engine through the capabilities of the online analytical processing, case‐based reasoning, fuzzy logic and artificial neural networks, achieving the optimization of the performance of organizations.FindingsIn this paper, the detailed architecture and the components included in the proposed system are described with a case study to validate its feasibility of application in actual environment.Originality/valueThe proposed system is to enhance customer satisfaction by automating problem solving procedures in all business processes.

A fuzzy group quality function deployment model for e-CRM framework assessment in agile manufacturing

“…A study of a number of papers indicates that the coherent meaning of agile manufacturing is the capability of an organization to react quickly in response to the customers' dynamic demands (Brown & Bessant, 2003;Chen, Parker, & Lin, 2006;Christopher, 2000;Goh, 2006;Gupta, Messerschmidt, & Herath, 2006;Ho, Lau, Lee, & Ip, 2005;Mason-Jones & Towill, 1999;Nieminen & Takala, 2006;Yusuf & Adeleye, 2002). Jin-Hai, Anderson, and Harrison (2003), Cao and Dowlatshahi (2005) and Ramesh and Devadasan (2007) have enumerated the definitions of agile manufacturing given by various authors.…”

A fuzzy logic approach to forecast energy consumption change in a manufacturing system

“…In the business sector, fuzzy logic principles have been especially applied in modeling for managerial decisionmaking (Zimmermann, 1996) for instances, Ho, Lau, Lee, and Ip (2005) incorporate fuzzy logic concepts into the agile quality enhancement system to achieve the optimization of the performance of organizations. Collan and Liu (2003) use a fuzzy approach for supporting capital budgeting and investment decision making.…”

Defects tracking in mass customisation production using defects tracking matrix combined with principal component analysis

“…Motwani et al (2005) studied the framework of business process change (BPC) in total quality management (TQM) and treated MCP as a new challenge to quality control. Ho et al (2005) studied an agent-based quality enhancement system with the incorporation of various computational intelligence techniques including case-based reasoning (CBR), object-oriented technology, online analytical processing (OLAP), fuzzy reasoning and ANNS. In 2007, Jiang et al (2007) proposed a quality management system model of customisation based on customer satisfaction and collaborative quality design, production process quality management, application and service quality management and quality evaluation.…”