Cycle Time Range Determination based on Minimum Difference Method and Weighted Score Method

This study presents two innovative methods for determining the cycle time range in industrial production lines: the Minimum Difference Method (MDM) and the Weighted Score Method (WSM). These methods are designed to enhance accuracy in establishing cycle time ranges, crucial for optimizing production efficiency. MDM focuses on minimizing the variance between upper and lower cycle time limits, facilitating better process control and predictability. WSM, on the other hand, integrates multiple parameters, including density and falling probability, to derive a more comprehensive and tailored cycle time range. The effectiveness of both methods is compared and analyzed in diverse industrial settings. Results indicate that accurate cycle time range determination is pivotal in streamlining production planning and resource allocation, significantly impacting process efficiency and cost-effectiveness. The study contributes to the field by offering a detailed comparative analysis of these methods, providing a practical framework for industries to enhance their production line efficiency.

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Published
2024-09-20
DOI
https://doi.org/10.1109/icmra62519.2024.10809291
Primary Topic
Engineering Applied Research
Type
article
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article

Cycle Time Range Determination based on Minimum Difference Method and Weighted Score Method

Haomiao Li, Xiaomao Xia
Engineering Applied Research
article

Cycle Time Range Determination based on Minimum Difference Method and Weighted Score Method

Haomiao Li, Xiaomao Xia
article en

Abstract

This study presents two innovative methods for determining the cycle time range in industrial production lines: the Minimum Difference Method (MDM) and the Weighted Score Method (WSM). These methods are designed to enhance accuracy in establishing cycle time ranges, crucial for optimizing production efficiency. MDM focuses on minimizing the variance between upper and lower cycle time limits, facilitating better process control and predictability. WSM, on the other hand, integrates multiple parameters, including density and falling probability, to derive a more comprehensive and tailored cycle time range. The effectiveness of both methods is compared and analyzed in diverse industrial settings. Results indicate that accurate cycle time range determination is pivotal in streamlining production planning and resource allocation, significantly impacting process efficiency and cost-effectiveness. The study contributes to the field by offering a detailed comparative analysis of these methods, providing a practical framework for industries to enhance their production line efficiency.

Cornell University (US), Jacobs Institute (US)
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Engineering Applied Research
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