Graduation: Next Process Step Predictor

Posted 8 Days Ago
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Veghel
Internship
Logistics • Other • Software
The Role
The role involves developing a predictive model to identify sub-optimal process steps in Vanderlande systems. The candidate will utilize data science techniques and programming skills in Python or Java, following the CRISP-DM process to enhance process efficiency and reduce manual efforts.
Summary Generated by Built In

Job TitleGraduation: Next Process Step Predictor

Job Description

Assignment type: Graduation

Start date: February 2025

Assignment Duration: 6 months

Location: Veghel

Educational Level: Master

Desired Study: Data Science or related studies

Language: English

 

Assignment

What is the issue? Processes in Vanderlande systems are challenging to understand. The processes are complex and there are numerous combinations of process steps. It is hard to determine when the behavior is unexpected.
Why does this issue occur?  The first step for improvement in the system is finding when things were sub-optimal. Currently there is no automated way to find when process steps were sub-optimal.
What is the impact of the issue? Currently large manual efforts are spent to find where the process has issues and what to improve. The conclusions are not always fact-based by data. This leads to sub optimal improvements which do not solve the inefficiencies in the system processes.
How can a predictive model be developed to identify sub-optimal process steps in Vanderlande systems, and what impact would this model have on reducing manual efforts and improving process efficiency? 

 

Department

Digital Service Platform (DSP) builds the digital service solutions for Vanderlande. DSP is part of the DCS or software development department within Business Unit Technology. The student works in the product team of Process Optimization in DSP.

Your responsibilities

  • The research should deliver the model that can efficiently predict expected behavior, a way to compare this to the actual behavior and highlight unexpected behavior in the process
  • The student must follow the CRISP-DM process understand the business questions, the data, build and verify the solution, and finally share this with relevant stakeholders

Your profile

  • The student should have a basic understanding of data science techniques for building predictive models
  • The student should be able to program in python or Java to build the solution
  • Mandatory enrolment in a Dutch Education System and resident of The Netherlands* 

 

Contact

Do you recognize yourself in this challenging profile? And are you looking for an internship/graduation assignment in our organization?
Please fill out the application form and upload your resume and cover letter. For more information, contact us by e-mail: [email protected]

Top Skills

Java
Python
The Company
HQ: Veghel
7,500 Employees
On-site Workplace
Year Founded: 1949

What We Do

Vanderlande is the global market leader for future-proof logistic process automation at airports. The company is also a leading supplier of process automation solutions for warehouses and in the parcel market.

Vanderlande’s baggage handling systems are capable of moving over 4 billion pieces of baggage around the world per year. Its systems are active in more than 600 airports including 12 of the world’s top 20. More than 52 million parcels are sorted by its systems every day, which have been installed for the world’s leading parcel companies. In addition, many of the largest global e-commerce players and retailers have confidence in Vanderlande’s efficient and reliable solutions.

The company focuses on the optimisation of its customers’ business processes and competitive positions. Through close cooperation, it strives for the improvement of their operational activities and the expansion of their logistical achievements. Vanderlande’s extensive portfolio of integrated solutions – innovative systems, intelligent software and life-cycle services – results in the realisation of fast, reliable and efficient automation technology.

Established in 1949, Vanderlande has more than 7,500 employees, all committed to moving its customers’ businesses forward at diverse locations on every continent. With a consistently increasing turnover of 1.8 billion euros, it has established a global reputation over the past seven decades as a highly reliable partner for future-proof logistic process automation.

Vanderlande was acquired in 2017 by Toyota Industries Corporation, which will help it to continue its sustainable profitable growth. The two companies have a strong strategic match, and the synergies include cross-selling, product innovations, and research and development.

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