Indexing the Capability of Multi-Characteristic Processes with Minimum Statistics. | ||||
| MEJ- Mansoura Engineering Journal | ||||
| Article 3, Volume 26, Issue 1, March 2001, Page 15-28 PDF (346.27 K) | ||||
| Document Type: Research Studies | ||||
| DOI: 10.21608/bfemu.2021.143592 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| Hassan Ali Mohamed Soltan* | ||||
| Prod. and Mechanical Design Engineering Department., Faculty of Engineering., El-Mansoura University., Mansoura 35516, Egypt. | ||||
| Abstract | ||||
| A Process capability index provides a quantitative prediction of a stable process's ability to meet specifica- tions. The concept of process capability and process capability indices are of great value to modern quality management. Many ever-growing firms have adopted this concept as a part of their quality improvement strategies which aimed at measuring and reducing a current proeess variation. These quantities can be merged in replacement policies to differentiate available process alternatives. This research defines the stan- dard process capability indices, and develops a methodology for evaluating a complex process which returns more than one characteristic. Two types of analysis are proposed as a foundation: (1) industrial analysis clas- sifies the process operations into four categories and (2) statistical analysis includes: (a) regression analysis between the most popular standard index and the probability of conforming and (b) simple screening tech nique used for eliminating the odd operations from the overall evaluation of a complex process. Moreover, some relationships between output characteristics are built according to modified statistical tolerance for- mulas extracted from formulas designed for interacting dimensions. A computational experiment was con ducted on a randomly generated problem—with specific variations to capture expected trade-offs between some formulas which were proposed for overall evaluation. Note that the overall evaluation may not be fed as a direct input to a quality program, but it demonstrates the interaction between the operations, and at least it supports a decision of maintaining all operations. This methodology has been presented to implement the processes related to discrete products, but it can be extended to service systems. For the processes related to coalesced products, the problem needs to extensive studies. | ||||
| Keywords | ||||
| quality'; process variation/capability indices; interacting dimensions, regression analysis, statisti- cal tolerance formulas: characteristics; overall index/evaluation | ||||
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