1,720,990 research outputs found
Evaluating measurement and process capabilities using tabular algorithm procedure with three quality measures
No full text In a normal quality improvement activity, the measurement system analysis (MSA) is assessed prior to process capability analysis (PCA). The tabular algorithm is widely applied for MSA. This research extends the use of the tabular algorithm for concurrent MSA and PCA. In practice, several indices are used to judge the capability of the measurement system, including precision-to-tolerance ( PTR), percentage repeatability, and repeatability and reproducibly (% R& R), number of distinct categories ( NDC), whereas the most common index for assessing the capability of manufacturing process is the potential process capability index, C p. In order to assess the capabilities of a measurement system and manufacturing concurrently, these indices are combined into two proposed capabilities assessment procedures. The first procedure adopts the PTR, % R& R and C p, while the second procedure employs the PTR, NDC and C p. Three previously conducted case studies are utilized for illustration. The results showed that the tabular algorithm with either capabilities assessment procedure effectively judged the capabilities of the measurement system and manufacturing process, which may save considerable engineering efforts. In conclusion, the tabular algorithm combined with the proposed assessment procedures can provide valuable guidelines that can be easily understood and applied by practitioners in a wide range of industrial applications. </jats:p
Super-Efficiency DEA Approach for Optimizing Multiple Quality Characteristics in Parameter Design
No full textThis paper proposes an efficient approach for optimizing the multiple quality characteristics (QCHs) in manufacturing applications on the Taguchi method using the super efficiency technique in data envelopment analysis (DEA). Each experiment in Taguchi’s orthogonal array (OA) is treated as a decision making unit (DMU) with multiple QCHs set as inputs or outputs. DMU’s efficiency is measured then adopted as a performance measure to identify the combination of optimal factor levels. Three real case studies were employed for illustration in which the proposed approach provided the largest total anticipated improvements in multiple QCHs among other techniques such as principal component analysis (PCA) and DEA based ranking (DEAR) approach. Analysis of variance is finally employed to decide significant factor effects and to predict performance.</jats:p
A Structural Model to Investigate Factors Affect Patient Satisfaction and Revisit Intention in Jordanian Hospitals
No full textOptimizing performance with multiple responses using cross-evaluation and aggressive formulation in data envelopment analysis
No full textCluster Analysis of Customer Churn in Telecom Industry
No full textThe research examines the factors that affect customer churn (CC) in the Jordanian telecom industry. A total of 700 surveys were distributed. Cluster analysis revealed three main clusters. Results showed that CC and customer satisfaction (CS) were the key determinants in forming the three clusters. In two clusters, the center values of CC were high, indicating that the customers were loyal and SC was expensive and time- and energy-consuming. Still, the mobile service provider (MSP) should enhance its communication (COM), and value added services (VASs), as well as customer complaint management systems (CCMS). Finally, for the third cluster the center of the CC indicates a poor level of loyalty, which facilitates customers churn to another MSP. The results of this study provide valuable feedback for MSP decision makers regarding approaches to improving their performance and reducing CC
Optimal Performance of Plastic Extrusion Process Using Fuzzy Goal Programming
Get PDFThis study optimized the performance of plastic extrusion process of drip irrigation pipes using fuzzy goal programming. Two main responses were of main interest; roll thickness and hardness. Four main process factors were studied. The L18 array was then used for experimental design. The individual-moving range control charts were used to assess the stability of the process, while the process capability index was used to assess process performance. Confirmation experiments were conducted at the obtained combination of optimal factor setting by fuzzy goal programming. The results revealed that process capability was improved significantly from -1.129 to 0.8148 for roll thickness and from 0.0965 to 0.714 and hardness. Such improvement results in considerable savings in production and quality costs
Optimizing Performance of Tablet's Direct Compression Process Using Fuzzy Goal Programming
No full textThis paper aims at improving the performance of the tableting process using statistical quality control and fuzzy goal programming. The tableting process was studied. Statistical control tools were used to characterize the existing process for three critical responses including the averages of a tablet’s weight, hardness, and thickness. At initial process factor settings, the estimated process capability index values for the tablet’s averages of weight, hardness, and thickness were 0.58, 3.36, and 0.88, respectively. The L9 array was utilized to provide experimentation design. Fuzzy goal programming was then employed to find the combination of optimal factor settings. Optimization results showed that the process capability index values for a tablet’s averages of weight, hardness, and thickness were improved to 1.03, 4.42, and 1.42, respectively. Such improvements resulted in significant savings in quality and production costs
Optimising correlated QCHs in robust design using principal components analysis and DEA techniques
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Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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