How can KPIs be calculated to improve the productivity of container cranes?

KPI calculation is based on the event-driven analysis of process signals for each load cycle. With ibaPDA-PLC-Xplorer, relevant control data are captured and processed into KPIs using ibaAnalyzer. These KPIs represent key performance indicators such as cycle times or utilization rates. This enables the targeted identification of bottlenecks and inefficiencies.

How can distributed plant locations be centrally monitored and compared?

A centralized data architecture enables cross-site analysis of operational data. With ibaHD-Server, data are stored locally and made available for centralized access. ibaAnalyzer allows direct comparison of KPIs across multiple sites. This creates transparency regarding the overall performance of distributed operations.

How can bottlenecks in logistics processes be identified based on data?

Bottlenecks become visible through the analysis of cycle times, downtimes, and load profiles. With ibaAnalyzer, these KPIs can be extracted and evaluated from the recorded raw data. Data acquisition is performed via ibaPDA-PLC-Xplorer. This allows precise localization of constraints and supports the implementation of targeted optimization measures.

How can data-driven maintenance be implemented in port logistics?

An effective preventive maintenance concept requires continuous analysis of usage data and load profiles. With ibaDatCoordinator, relevant KPIs are automatically transferred into databases and made available for further analysis. In combination with ibaHD-Server, this creates a long-term data foundation. This enables condition-based planning of maintenance activities.

How can the actual service life of plant components be determined based on data?

The real service life can be determined by analyzing operating cycles, load conditions, and usage frequency. ibaAnalyzer enables the evaluation of these parameters based on historical data. Data acquisition is carried out via ibaPDA-PLC-Xplorer, while ibaHD-Server ensures long-term storage. This allows maintenance intervals to be optimized and lifetime predictions to be refined.

iba System Provides Complete Overview of Operations in Different Ports

KPI Calculation to Increase Productivity of Container Cranes

When it comes to port logistics, time is money. In order to identify existing bottlenecks more easily and thus to exploit optimization potentials, a multinational logistics company decided to take a closer look at the operation of their container cranes.

Business Benefits The Technology Used Functions More Success Stories

Therefore, the iba system was installed in four Australian ports with five to seven loading cranes each and became an eye-opener for the company: For the first time, the customer had a central and complete overview of the crane operation in all ports. In addition to the capacity utilization, the planning of the preventive maintenance was improved permanently.

Central and complete overview

of crane operation in all ports

Improvement of maintenance schedules

and introduction of a preventive maintenance concept

Determination of the life span

of a crane based on actual usage

A large blue shipping container is lifted by a crane against a backdrop of colorful stacked containers.

The Technology

For each loading and unloading cycle of a crane, the logistics company specified about 30 relevant KPIs. These were to be extracted into a central database. In the installed iba system, the crane data is acquired via ibaPDA-PLC-Xplorer, with about 20 signals being acquired per crane. In a further step, the requested parameters are calculated event-driven via macros and functions of ibaAnalyzer and extracted into an SQL database with the help of ibaDatCoordinator and ibaDatCoordinator-DB. For each port, one virtualized ibaPDA system and one ibaHD-Server are used. During the entire duration of the project, iba Oceania took care of the engineering and commissioning of the solution.

Schematic illustration of the iba system

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The use of the iba system was an eye-opener: For the first time, the customer has a central and complete overview of crane operations across all ports and is able to optimize the processes on this basis.

Ross Gibbs
Lead Engineer, iba Oceania

Used Functions

The following functions of the iba system are used in this success story.

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Frequently Asked Questions (FAQ)

How can KPIs be calculated to improve the productivity of container cranes?: KPI calculation is based on the event-driven analysis of process signals for each load cycle. With ibaPDA-PLC-Xplorer, relevant control data are captured and processed into KPIs using ibaAnalyzer. These KPIs represent key performance indicators such as cycle times or utilization rates. This enables the targeted identification of bottlenecks and inefficiencies.
How can distributed plant locations be centrally monitored and compared?: A centralized data architecture enables cross-site analysis of operational data. With ibaHD-Server, data are stored locally and made available for centralized access. ibaAnalyzer allows direct comparison of KPIs across multiple sites. This creates transparency regarding the overall performance of distributed operations.
How can bottlenecks in logistics processes be identified based on data?: Bottlenecks become visible through the analysis of cycle times, downtimes, and load profiles. With ibaAnalyzer, these KPIs can be extracted and evaluated from the recorded raw data. Data acquisition is performed via ibaPDA-PLC-Xplorer. This allows precise localization of constraints and supports the implementation of targeted optimization measures.
How can data-driven maintenance be implemented in port logistics?: An effective preventive maintenance concept requires continuous analysis of usage data and load profiles. With ibaDatCoordinator, relevant KPIs are automatically transferred into databases and made available for further analysis. In combination with ibaHD-Server, this creates a long-term data foundation. This enables condition-based planning of maintenance activities.
How can the actual service life of plant components be determined based on data?: The real service life can be determined by analyzing operating cycles, load conditions, and usage frequency. ibaAnalyzer enables the evaluation of these parameters based on historical data. Data acquisition is carried out via ibaPDA-PLC-Xplorer, while ibaHD-Server ensures long-term storage. This allows maintenance intervals to be optimized and lifetime predictions to be refined.