| Title |
Production data analysis system using novel process capability indices-based circular economy |
| ID_Doc |
28950 |
| Authors |
Lin, KP; Yu, CM; Chen, KS |
| Title |
Production data analysis system using novel process capability indices-based circular economy |
| Year |
2019 |
| Published |
Industrial Management & Data Systems, 119.0, 8 |
| DOI |
10.1108/IMDS-03-2019-0166 |
| Abstract |
Purpose The purpose of this paper is to establish mechanisms for process improvement so that production efficiency and product quality can be expected, and create a sustainable development in terms of circular economy. Design/methodology/approach The authors obtain a critical value from statistical hypothesis testing, and thereby construct a process capability indices chart, which both lowers the chance of quality level misjudgment caused by sampling error and provides reference for the processes improvement in poor quality levels. The authors used the bottom bracket of bicycles as an example to demonstrate the model and methods proposed in this study. Findings This approach enables us to plot multiple quality characteristics, despite varying attributes and specifications, onto the same process capability analysis chart. And it therefore increases accuracy and precision to reduce rework and scrap rates (reduce), increase product availability, reduce maintenance frequency and increase reuse (reuse), increase the recycle rates of components (recycle) and lengthen service life, which will delay recovery time (recovery). Originality/value Parts manufacturers in the industry chain can upload their production data to the cloud platform. The quality control center of the bicycle manufacturer can utilized the production data analysis model to identify critical-to-quality characteristics. The platform also offers reference for improvement and adds the improvement achievements and experience to its knowledge management to provide the entire industry chain. Feedback is also given to the R&D department of the bicycle manufacturer as reference for more robust product designs, more reasonable tolerance designs, and selection criteria for better parts suppliers, thereby forming an intelligent manufacturing loop system. |
| Author Keywords |
Internet of Things (IoT); Intelligent manufacturing; I-cloud; Process capability indices; Production data analysis |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000487074800006 |
| WoS Category |
Computer Science, Interdisciplinary Applications; Engineering, Industrial |
| Research Area |
Computer Science; Engineering |
| PDF |
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