Master Thesis: Determination of 3 axis milling operation level CO2 footprint energy efficient process planning in CAM
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As industries adapt to evolving global constraints, the significance of energy-efficient process planning and its impact on the CO2 footprint of machining operations has intensified. Sandvik Manufacturing Solutions (SMF), in partnership with Visibility of Value Networks for Circularity and Eco-efficiency (VIVACE), is teaming up with Chalmers and KTH. This collaboration aims to enhance the user experience for Computer Aided Manufacturing (CAM) programmers and improve the overall capabilities of CAM platforms. Ultimately, the objective is to refine process planning from a sustainability perspective, inform decision-making, and enhance resource utilization.
Background and scope of the project
This master's project investigates the influence of specific factors – such as machine type, tooling selection, and tool path parameters – on process planning efficiency from a CO2 footprint standpoint. The student will apply mathematical modeling and instrumentation-based techniques to the 3-axis milling process planning, focusing primarily on low-carbon or low-alloy steel. Contributions will expand on current analytical and optimization methods, incorporating instrumentation-enabled analysis (using current sensors and controller-collected power data) and linking this data to CAM software operations. The CO2 footprint will be determined using established LCA databases. The student/students will familiarize themselves with Vericut and its API within the project's goals. The goal is to harness machining process data, fusing it with engineering techniques to simulate the machining process.
The master thesis project aims to forge a prototype that assists machining process planners by offering an extended analytical view of their choices concerning CO2 footprint, in addition to existing productivity and tool lifespan optimization methods. The vision is to merge current modeling methods with machine-gathered data, thereby enhancing the CAM process planning.
Key tasks include:
Reviewing literature to understand the current state of the target area.
Conducting machining tests to obtain machine tool power consumption data.
Investigating techniques to model the CO2 footprint of machining within the project's framework.
Documentation and dissemination.
This master thesis work can start on very short notice, so please don’t hesitate to send your application!
Duration of project
The thesis project lasts 20 weeks, starting at the beginning of 2024.
The location is in Stockholm or Gothenburg
We're seeking students with a keen interest in machining and a solid background in:
Proficiency in Python, C++, and API usage is advantageous. All required cutting tools and raw materials will be provided. Additionally, there is flexibility regarding the acquisition of necessary additional hardware. This project is a collaborative effort between Sandvik Manufacturing Solutions KTH and Chalmers. Most experimental work will take place at KTH or Chalmers.
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How to apply
As we have an ongoing selection process, please send your application as soon as possible, and no later than December 15, 2023 (Job ID: R0061205). You can send your application to the contacts below.
Sandvik Manufacturing andMachining Solutions is a business area within the Sandvik Group and a global market-leading manufacturer of tools and tooling systems for advanced industrial metal cutting.The business area also comprises the areas of additive manufacturing and digital manufacturing solutions. In 2022, saleswereapproximately 49billion SEK withabout 20,800 employees.