Thesis Energy Efficient Optimization of Lifting Operations

Background and Motivation

Lifting operations in automated systems are often energy-intensive and contribute significantly to overall power consumption and cycle many existing implementations the lifting motor is driven at or near full speed with limited motion shaping.

This can result in high mechanical shock loads when engaging or lifting a payload leading to increased mechanical stress on the motor transmission components and structural elements.

With increasing demands for sustainability performance and system durability optimizing lifting behavior at the software and control level has become increasingly important. Improved motion planning can not only reduce energy consumption and cycle time but also decrease peak forces mechanical impact and wear thereby potentially extending hardware lifetime and reducing maintenance requirements.

Problem Statement

Existing lifting strategies may lead to unnecessary energy consumption longer cycle times and elevated mechanical stress due to aggressive movements. These dynamic loads can negatively impact component lifetime and system reliability.

Methodology

The work will involve modeling the lifting system including motor characteristics and constraints. Optimization techniques will be applied to generate energy-e icient motion profiles.

The proposed approaches will be evaluated through simulation and/or experimental measurements comparing energy usage peak power cycle time and mechanical impact.

Expected Outcomes

Optimized lifting and motion profiles

Quantitative reduction in energy consumption and/or cycle time

Reduced peak mechanical loads and smoother load engagement Evaluation of concurrency strategies and their impact on system performance

Scope

The thesis focuses on control and motion planning strategies and does not include mechanical redesign or motor hardware changes.

Addition to Expected Outcomes (Optional)

If implemented the thesis may additionally deliver: Investigation and implementation of load weight estimation method

Qualifications :

Who are we looking for

A motivated thesis student with a hands-on mindset strong problem-solving skills and an interest in industrial automation robotics and product development.

Relevant skills

Software engineering
Electrical engineering

Additional Information :

What we offer you

• A place in an enthusiastic young organisation with the necessary ambitions
• The necessary freedom and the opportunity to take initiatives
• Location Office : Lokeren
• Satellite office in Berchem ( Antwerp )

Unsolicited representations by third parties (recruitment agencies headhunters ...) of CVs via mail and/or telephone for our vacancies are considered as direct applications where no compensation is provided to the third party. Any T&Cs from these third parties will not be accepted unless upon signature of the T&Cs by a person in charge of HR. Candidates remain registered in the system for 12 months and cannot be proposed again during this period.

Remote Work :

No

Employment Type :

Full-time