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設(shè)備效率改善環(huán)SMC

設(shè)備效率改善環(huán)SMC

 數(shù)字化車間管理系統(tǒng)Digital SFM

數(shù)字化車間管理系統(tǒng)Digital SFM

 節(jié)拍分析

節(jié)拍分析

 數(shù)字化價值流Digital VSM

數(shù)字化價值流Digital VSM

 智能標(biāo)準(zhǔn)化

智能標(biāo)準(zhǔn)化

 全員生產(chǎn)維護系統(tǒng)Digital TPM

全員生產(chǎn)維護系統(tǒng)Digital TPM

Overview of Cycle Time Analysis

The Cycle Time analysis function automatically collects Cycle Time data from equipment and manual workstations through equipment interconnection and exclusive algorithms, achieving more accurate capacity analysis. By actively warning of Cycle Time anomalies, it reduces equipment performance losses and increases output.

Cycle Time Statistics Diagram
Cycle Time Statistics Diagram

Product Functions

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Automatic Cycle Time Statistics for Equipment

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Automatic Cycle Time Statistics for Manual Workstations Based on Smart Gloves

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Multidimensional Cycle Time Analysis, Including Average Cycle Time, Cycle Time Distribution, Cycle Time Fluctuation, etc.

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Standard Cycle Time Setting

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Cycle Time Balance Chat

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Active Cycle Time Deviation Notification Function

Product Value

Product Value

Automatic Cycle Time Statistics and Analysis for Equipment and Manual Workstations arrow

By collecting data and calculating Cycle Times for automatic equipment and manual workstations, identify bottlenecks in these areas that lead to reduced production efficiency. Develop improvement plans based on analysis results. Optimizing problem areas can help improve overall production efficiency and reduce production cycles.

Quickly Identify Cycle Time Deviations arrow

Set standard Cycle Times and deploy real-time monitoring systems. Use sensors, PLCs, and other devices to collect production data from automatic equipment and manual workstations for Cycle Time statistics. Utilize data visualization tools to compare actual production Cycle Times with standard Cycle Times, helping quickly identify any deviations.

Active Notification of Cycle Time Anomalies to Eliminate Deviations in Time arrow

Set up an alarm mechanism to promptly notify relevant personnel when Cycle Time deviations are detected. Use automated analysis tools, such as data analysis software or AI systems, to quickly identify patterns, anomalies, and trends. These tools can automatically analyze large amounts of data, provide in-depth insights, and help determine which factors cause Cycle Time deviations. Develop quick and targeted improvement plans based on identified deviations.