Autonomy in Dry Docking: Engineering Pathways, Operational Realities, and Strategic Imperatives
Autonomy in Dry Docking: Engineering Pathways, Operational Realities, and Strategic Imperatives
The MOC
By David Von Schmidt
May 21, 2026
Introduction
What is autonomy in dry docking? Until recently, the question itself would have seemed misplaced in most shipyards. Dry docking has traditionally been viewed as one of the most human-dependent evolutions in the maritime industry: an operation built upon judgment, experience, timing, and coordination under constantly changing conditions. Unlike highly repetitive industrial processes, dry docking involves variables that are often dynamic, imperfectly known, and operationally interdependent.
For decades, the prevailing industry assumption was that dry docking was simply too complex to automate in any meaningful way. Shipyard executives and naval leadership frequently sought methods to improve efficiency, reduce delays, and increase throughput, particularly as maintenance demands expanded. Yet the response was often the same: the operation was too variable, too dependent upon human interpretation, and too unforgiving of error to permit substantial autonomous integration.
That assumption is now being challenged.
Autonomy in dry docking is not emerging as a wholesale replacement for dockmasters, engineers, riggers, or shipyard personnel. Rather, it is developing incrementally through specialized systems capable of automating discrete operational functions with increasing precision and reliability. Automated ballast control systems, synchronized shiplift mechanisms, AI-assisted planning tools, and digitally integrated transfer systems are already altering the operational landscape of modern shipyards.
At the same time, the adoption of autonomous technologies raises legitimate engineering and operational concerns. Questions surrounding system redundancy, cybersecurity, data integrity, overreliance on automation, workforce competency degradation, and operational resiliency remain unresolved in many areas. The issue is whether autonomy is sufficiently mature to improve operations safely and where human judgment must continue to remain dominant.
This paper evaluates the current state of autonomy in dry docking, distinguishing between technologies that are operationally mature and those that remain developmental. It further examines the strategic pressures driving adoption, the risks associated with technological stagnation, and the criteria necessary for responsible implementation within the shipyard and dry docking sector.
Defining Autonomy in Dry Docking
A critical distinction must be made between automation and autonomy. Many systems currently described within the shipyard sector as “autonomous” are more accurately categorized as advanced automation. Automated systems execute pre-programmed functions within defined operational parameters. Autonomous systems, by contrast, interpret changing conditions, adapt to uncertainty, and make conditional operational decisions with reduced human intervention. For example, in a floating dry dock operation, an automated ballast control system may simply flood and dewater tanks according to a pre-set docking sequence, whereas an autonomous docking system could detect an unexpected vessel list, changing tide conditions, or uneven block loading and independently adjust ballast distribution and docking rates in real time to maintain vessel stability and dock safety.
Most existing dry docking technologies remain firmly within the realm of automation rather than full autonomy. This distinction is important because dry docking operations frequently involve complex, nonlinear conditions that resist deterministic programming. Variations in vessel condition, loading irregularities, weather effects, degraded infrastructure, sensor faults, or inaccurate hydrostatic assumptions can rapidly alter an evolution beyond programmed expectations.
As a result, truly autonomous dry docking operations remain limited by the industry’s inability to fully digitize and predict real-world operational variability. Human operators continue to serve as the primary mechanism for contextual interpretation and risk management when conditions deviate from expected parameters.
Autonomy in dry docking should not be misconstrued as the wholesale removal of human operators. Rather, it is best understood as the integration of automated and semi-autonomous control systems that reduce manual intervention, enhance precision, and provide decision-support capabilities.
From an engineering standpoint, autonomy exists along a spectrum:
Assisted Operations: Human-controlled systems augmented with automation (e.g., digital ballast monitoring). These are simple systems with few elements, variables and states. Checklists and stepwise procedures can be applied by anyone including automation to solve problems.
Supervised Autonomy: Automated subsystems executing tasks under human oversight (e.g., programmable ballast sequences). These are complicated systems with a large number of elements, variables and states, but like simple systems have been designed and assembled.
Conditional Autonomy: Systems capable of executing complex operations with limited human input, intervening only when required. These are complex systems with any variables that are tightly inter related. Small changes can have outsize and unpredictable impacts.
Current dry docking technologies largely occupy Assisted Operations and Supervised Autonomy, with emerging capabilities approaching Conditional Autonomy in specific domains.
Existing Autonomous Technologies in Dry Docking
Automated Ballast Control Systems
Modern floating dry docks (FDDs) are increasingly equipped with advanced automated ballast control systems. These systems enable precise control over ballast tank filling and discharge, allowing for:
Real-time trim and heel adjustments
Pre-programmed docking sequences
Integrated sensor feedback loops
Despite their advantages, automated ballast systems remain heavily dependent upon sensor reliability, calibration accuracy, and operator validation. Faulty tank level indications, corrupted inputs, valve failures, or inaccurate vessel loading assumptions can create cascading operational risks if operators become overly reliant on automated outputs. Consequently, mature ballast automation systems are most effective when implemented as decision-support and execution tools operating under experienced human supervision rather than as fully independent control systems.
By David Von Schmidt
Introduction
What is autonomy in dry docking? Until recently, the question itself would have seemed misplaced in most shipyards. Dry docking has traditionally been viewed as one of the most human-dependent evolutions in the maritime industry: an operation built upon judgment, experience, timing, and coordination under constantly changing conditions. Unlike highly repetitive industrial processes, dry docking involves variables that are often dynamic, imperfectly known, and operationally interdependent.
For decades, the prevailing industry assumption was that dry docking was simply too complex to automate in any meaningful way. Shipyard executives and naval leadership frequently sought methods to improve efficiency, reduce delays, and increase throughput, particularly as maintenance demands expanded. Yet the response was often the same: the operation was too variable, too dependent upon human interpretation, and too unforgiving of error to permit substantial autonomous integration.
That assumption is now being challenged.
Autonomy in dry docking is not emerging as a wholesale replacement for dockmasters, engineers, riggers, or shipyard personnel. Rather, it is developing incrementally through specialized systems capable of automating discrete operational functions with increasing precision and reliability. Automated ballast control systems, synchronized shiplift mechanisms, AI-assisted planning tools, and digitally integrated transfer systems are already altering the operational landscape of modern shipyards.
At the same time, the adoption of autonomous technologies raises legitimate engineering and operational concerns. Questions surrounding system redundancy, cybersecurity, data integrity, overreliance on automation, workforce competency degradation, and operational resiliency remain unresolved in many areas. The issue is whether autonomy is sufficiently mature to improve operations safely and where human judgment must continue to remain dominant.
This paper evaluates the current state of autonomy in dry docking, distinguishing between technologies that are operationally mature and those that remain developmental. It further examines the strategic pressures driving adoption, the risks associated with technological stagnation, and the criteria necessary for responsible implementation within the shipyard and dry docking sector.
Defining Autonomy in Dry Docking
A critical distinction must be made between automation and autonomy. Many systems currently described within the shipyard sector as “autonomous” are more accurately categorized as advanced automation. Automated systems execute pre-programmed functions within defined operational parameters. Autonomous systems, by contrast, interpret changing conditions, adapt to uncertainty, and make conditional operational decisions with reduced human intervention. For example, in a floating dry dock operation, an automated ballast control system may simply flood and dewater tanks according to a pre-set docking sequence, whereas an autonomous docking system could detect an unexpected vessel list, changing tide conditions, or uneven block loading and independently adjust ballast distribution and docking rates in real time to maintain vessel stability and dock safety.
Most existing dry docking technologies remain firmly within the realm of automation rather than full autonomy. This distinction is important because dry docking operations frequently involve complex, nonlinear conditions that resist deterministic programming. Variations in vessel condition, loading irregularities, weather effects, degraded infrastructure, sensor faults, or inaccurate hydrostatic assumptions can rapidly alter an evolution beyond programmed expectations.
As a result, truly autonomous dry docking operations remain limited by the industry’s inability to fully digitize and predict real-world operational variability. Human operators continue to serve as the primary mechanism for contextual interpretation and risk management when conditions deviate from expected parameters.
Autonomy in dry docking should not be misconstrued as the wholesale removal of human operators. Rather, it is best understood as the integration of automated and semi-autonomous control systems that reduce manual intervention, enhance precision, and provide decision-support capabilities.
From an engineering standpoint, autonomy exists along a spectrum:
Current dry docking technologies largely occupy Assisted Operations and Supervised Autonomy, with emerging capabilities approaching Conditional Autonomy in specific domains.
Existing Autonomous Technologies in Dry Docking
Modern floating dry docks (FDDs) are increasingly equipped with advanced automated ballast control systems. These systems enable precise control over ballast tank filling and discharge, allowing for:
Despite their advantages, automated ballast systems remain heavily dependent upon sensor reliability, calibration accuracy, and operator validation. Faulty tank level indications, corrupted inputs, valve failures, or inaccurate vessel loading assumptions can create cascading operational risks if operators become overly reliant on automated outputs. Consequently, mature ballast automation systems are most effective when implemented as decision-support and execution tools operating under experienced human supervision rather than as fully independent control systems.