Daimler Trucks Driveline Innovation

The team will work closely with Daimler representatives to:
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Remove the hurdle of updating database manually
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Set up the Tool logic to be independent for every shaft
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Set up thorough Error Checks
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Automate manual steps of the Tool whilst still allowing manual operations as a contingency
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Allow pre-set values to be overwritten for prototyping purposes
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Analyze Tool data to understand the common CWO trends
How will the project tasks be sub-divided?
Product Development Teams: The priority is to develop an update to the current tool to cut down reliance on manual operations. A higher-level goal, after the development of the basic tool, is to incorporate aspects of Machine Learning and AI to automate as many aspects of the design process as possible.
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Product Owner
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SCRUM Master
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Developers
Data Analysis/Mechanical Engineering: The secondary goal of the project is to analyze the custom work order trends to identify common causes of manual operations on ordered trucks.
Goals:
- Students will use the SCRUM methodology to develop and update the Driveline Custom Work Order (CWO).
- Students will learn to work in an industry setting with Daimler representatives to develop user stories, prioritize them and conduct regular sprints to introduce features in the tool.
- Students will also learn the use of GitHub and documentation standards.
- In addition, students will learn to use ZOS APIs to interact with the mainframe and extract data.
- Students will learn to test and debug the application. Alongside, evolving their programming skills, students will also learn how to set up databases and use the IBM DB2 Tables.
- Students will be hone skills in UI/UX by developing a user-friendly interaction tool.
- Students will also learn the analysis of commercial vehicle drivetrain performance, packaging and limitations.
- Students will also learn data analysis on large quantities of build data to identify potential improvements and innovations. This will innovate/ improve the efficiency and prototyping ability of DTNA’s driveline design/integration team.
- Students will also learn leadership and communication skills pertinent to professional collaboration.
Methods and Technologies
- Production level coding
- Databases
- Product Development Lifecycle
- IBM ZOS Connect
- Data Analysis
- Machine Learning
- Business Management
- SCRUM Methodology
- Mechanical Engineering
Majors
- Computer Science
- Computer Engineering
- Mechanical Engineering
- Data Science
- Mathematics
- Physics
- Business and Technology Management
- Business Administration
Partners
- Daimler Trucks North America LLC
Daimler Points of Contact
James Vue
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Email: james.vue@daimler.com
Robert P Martin
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Email: robert.p.martin@daimler.com
Matt Walling
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Email: matthew.walling@daimler.com
Shayan Khan
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Email: shayan.khan@nyu.edu
NYU Faculty Advisor
- Email: sh7373@nyu.edu