Ontology Building of Manufacturing Quality Knowledge for Design Decision Support

This work was funded by National Natural Science Foundation of China (No: 70472066, 70771091), the project of Bureau of Science, Technology and Industry for National Defence, China (No. Z142008A001), the NPU Foundation for Humanities, Social Science, and Management Science Development (No. RW200817), which are gratefully acknowledged.Manufacturing knowledge on product quality is a kind of typical knowledge for supporting design decisions. In order to clearly identify and understand design decisions and their knowledge needs on manufacturing quality, an ontology of design decisions and manufacturing quality knowledge is developed. The methodology and tool used for the development of the proposed ontology is firstly introduced. The design decisions are organized along with five main design phases ranging from planning and task clarification, conceptual design, embodiment design to detail design. The knowledge needs of different design decisions, especially on the manufacturing quality knowledge, are analyzed through competition questions. Then, the ontology is built in the form of a hierarchical structure through the proposed methodology and ontology editor. Based on the developed ontology, further instances of the classes in the ontology can be filled as detailed knowledge, and can be accumulated for further construction of knowledge base

Is It Possible for “Electronic Word-of-Mouth” and “User-Generated Content” to be Used Interchangeably?

The advance of web 2.0 that facilitates contents to be created, shared and exchanged through online platforms has led to profound changes in consumer behavior. Modern consumers appreciate nonprofessional-produced contents as they are perceived to be more trustworthy. As a result, electronic Word-of-Mouth (eWOM) and user-generated content (UGC) have become two of the most frequent researched objects over the last ten years in marketing area. However, extant studies have confounded these two concepts which may cause significant academic problems. In this paper the authors aim to disentangle eWOM and UGC by comparing their fundamental attributes. Findings prove that despite sharing similar attributes, eWOM and UGC are two distinctive concepts with different scope and meaning. It is thus concluded that eWOM and UGC cannot be used interchangeably. The results of this study provide important implications for future research. Keywords: eWOM, UGC, creation, dissemination, publicity. DOI: 10.7176/JMCR/65-04 Publication date: February 29th 202

Ontology Building of Manufacturing Quality Knowledge for Design Decision Support

This work was funded by National Natural Science Foundation of China (No: 70472066, 70771091), the project of Bureau of Science, Technology and Industry for National Defence, China (No. Z142008A001), the NPU Foundation for Humanities, Social Science, and Management Science Development (No. RW200817), which are gratefully acknowledged.International audienceManufacturing knowledge on product quality is a kind of typical knowledge for supporting design decisions. In order to clearly identify and understand design decisions and their knowledge needs on manufacturing quality, an ontology of design decisions and manufacturing quality knowledge is developed. The methodology and tool used for the development of the proposed ontology is firstly introduced. The design decisions are organized along with five main design phases ranging from planning and task clarification, conceptual design, embodiment design to detail design. The knowledge needs of different design decisions, especially on the manufacturing quality knowledge, are analyzed through competition questions. Then, the ontology is built in the form of a hierarchical structure through the proposed methodology and ontology editor. Based on the developed ontology, further instances of the classes in the ontology can be filled as detailed knowledge, and can be accumulated for further construction of knowledge base

Analysis of Data Quality and Information Quality Problems in Digital Manufacturing

 This work focuses on the increasing importance of data quality in organizations, especially in digital manufacturing companies. The paper firstly reviews related works in field of data quality, including definition, dimensions, measurement and assessment, and improvement of data quality. Then, by taking the digital manufacturing as research object, the different information roles, information manufacturing processes, influential factors of information quality, and the transformation levels and paths of the data/information quality in digital manufacturing companies are analyzed. Finally an approach for the diagnosis, control and improvement of data/information quality in digital manufacturing companies, which is the basis for further works, is proposed.

Optimal Scheme for Process Quality and Cost Control by Integrating a Continuous Sampling Plan and the Process Yield Index

The single level continuous sampling plan (CSP-1) is an in-line process control tool that has been commonly adopted in various manufacturing industries. However, CSP-1 is designed for only satisfying the quality constraint. At the same time, CSP-1 has disadvantages with the high probabilities of both Type I and Type II errors due to its inherent deficiency coming from the operating procedure. In this work, an optimal scheme for process quality and cost control is proposed to monitor the process cost and improve the process quality. The CSP-1 and the process yield index (Spk) are integrated in the present scheme, which work independently and complementarily. The four parameters (clearance number, inspecting fraction, sample size, and critical value) are designed in the proposed scheme under simultaneously considering the quality and cost constraints. The sole feasible inspection scheme in CSP-1 under the two constraints is found and used for controlling the process quality. The probabilities of Type I and Type II errors are concurrently controlled at the stipulated level with the risk control scheme, which is constructed with two nonlinear inequation based on the accurate distribution of the index Spk. A case study is illustrated to validate the effectiveness and practicality of the proposed scheme

Qualité des données pour l'aide à la décision dans la conception de produits

La conception des produits implique de grandes quantités de décisions (MQD). Le soutien pertinent et efficace des connaissances est important pour les décisions. La plupart des travaux ont été réalisées sur les connaissances de conception comme support à la conception. Cependant la connaissance de fabrication sur la qualité des produits est également une caractéristique qui n'est pas jugé suffisant. Entre-temps, de grands volumes de données de fabrication sont générés et enregistrés. Des connaissances nécessaires à la production sont implicites dans ces données. Les travaux présentés dans cette thèse se concentre sur l'extraction de connaissances de fabrication de qualité dans ces données en utilisant des méthodes d'exploration de données et de retour d expérience utiles pour les concepteurs de produits (une ontologie regroupant les éléments importants à la prise de décision a été définie). Des techniques de Data Mining sont ensuite exploitées afin de répondre aux problèmes de qualité de la connaissance en production. Un prototype support à la prise de décision en conception de produits a été défini. Il considère les critères de qualité dans l extraction et la recherche des connaissancesThis work studies knowledge extraction in manufacturing quality data (MQD) for support-ing design decisions. Firstly, an ontological approach for analyzing design decisions and identifying designer s needs for manufacturing quality knowledge is proposed. The decisions are analyzed ranging from task clarification, conceptual design, embodiment design to detail design. A decision model is proposed in which decisions and its knowledge elements are illustrated. An ontology is constructed to represent the decisions and their knowledge needs. Secondly, MQD preparation for further knowledge discovery is described. The nature of data in manufacturing is described. A GT (group technology) and QBOM (Quality Bill of Material)-based method is proposed to classify and organize MQD. As an important factor, the data quality (DQ) issues related with MQD is also analyzed for data mining (DM) application. A QFD (quality function deployment) based approach is proposed for translating data consumers DQ needs into specific DQ dimensions and initiatives. Thirdly, a DM-based manufacturing quality knowledge discovery method is proposed and validated through two popular DM functions and related algorithms. The two DM functions are illustrated through real world data sets from two different production lines. Fourthly, a MQD-based design support proto-type is developed. The prototype includes three major functions such as data input, knowledge extraction and input, knowledge searchTROYES-SCD-UTT (103872102) / SudocSudocFranceF

Analysis of consumers’ requirements for data/information quality by using HOQ

International audienc

Enablers Supporting the Implementation of Knowledge Management in the Healthcare of Pakistan

Knowledge is considered to be an important resource; it is the source of competitive advantage. However, if knowledge is managed well with Knowledge Management (KM), then it becomes a source for sustainable competitive advantage for organizations. If KM is implemented in an organization, it would improve the organizational competitiveness, performance, and productivity, and facilitate the efficient use of resources. Due to intense competition in the global market, many organizations are moving towards the adoption of KM. The healthcare sectors of many developed countries have moved towards the implementation of KM because it can improve the procuring of knowledge from ongoing activities by the effective use of data repositories. Developing countries have now realized the potential and benefits of KM adoption. Pakistan is one of the developing countries that have recently shown an inclination towards the adoption of KM in its healthcare sector to improve performance of its healthcare. This study was composed of two main research phases. Firstly, the enablers of KM were reviewed from earlier studies. Secondly, interpretive structural modeling (ISM) and MICMAC (Cross-Impact Matrix Multiplication Applied to Classification) techniques were used to show the interrelationships between KM enablers and driving and dependence power of each enabler. The application of ISM and MICMAC technique shows that policy incentive, long-term strategic planning, Information Technology (IT), and alignment of KM efforts with business strategy are the main enablers of KM adoption in the healthcare of Pakistan. Focusing on the identified enablers will help in the implementation of KM. Policy incentives can work as a catalyst to promote KM adoption in the healthcare of Pakistan

MANUFACTURING QUALITY INFORMATION SUPPORTING CONCURRENT DESIGN DECISIONS

International audienceAt the view of using manufacturing quality information (MQI) actively, this paper proposes one product design problem solving process based on MQI. To use MQI, one framework of MQI-based design decisions support system (DDSS) is outlined and six procedures of building this system are explained. The flow of MQI is sketched, and the content of MQI is analyzed which is divided into three categories such as inspection quality information, control quality information and management quality information. A requirement analysis of product design decisions for MQI is proposed by a matrix. Finally the acquisition and representation of MQI is discussed