English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Monitoring multi-attribute processes is an important issue in many quality control environments. Almost all the priory proposed control charts utilize equal weights for each Attribute Quality Characteristics (AQCs). In such condition, there is no priority among AQCs. But in real-world, compensatory may exist. Hence due to some applied reasons such as function or efficiency, unequal weights for each AQC are possible. This study proposed a novel efficient control chart for simultaneous monitoring of weighted AQC when data expressed by linguistic terms. Correspondingly a new procedure to interpret out-of-control signals is presented. Performance and comparison advantage of the proposed control chart is measured in terms of Average Run Length (ARL) using a real case which priory was expressed. Consequences displayed that considering weight could efficiently extend the prior research for practical circumstancese.

An Efficient Novel Compensatory Multi-attribute Control Chart for Correlated Multinomial Processes