Job Description:

Project background

In the complex and dynamic environment of manufacturing, production scheduling within a short-term horizon (24 hours) relies heavily on the tacit knowledge and expertise of experienced schedulers. These professionals make decisions based on a combination of factors, many of which are not fully formalized or documented, creating variability in how scheduling is done across different factories, especially those with diverse technologies and operational setups.

The purpose of this master thesis project is to reveal the key principles and logic that guide production schedulers in their daily tasks, and to develop a systematic framework that allows this tacit knowledge to be codified. The framework should encompass methods, sets of questions, algorithms, and a clear set of steps to extract the decision-making process behind scheduling.

This project is ideal for a student who seeks to explore the interface between operations management, knowledge codification, and industrial automation. The resulting framework should be universally applicable across factories with varying technologies and operating conditions.

The final output should be a set of scheduling rules that can be easily translated into system algorithms, although the automation itself is beyond the scope of this project.

This project offers the student an opportunity to contribute significantly to the field of production scheduling, as well as to develop a practical framework that could have real-world applications in manufacturing.

Understand and codify the tacit knowledge of schedulers regarding production scheduling in a 24-hour horizon.Develop a standardized framework that includes methods, key questions, and algorithms to capture and document the decision-making logic of schedulers.Ensure broad applicability of the developed framework to various factories, each potentially operating with different production technologies and constraints.Create a set of scheduling rules that describe the logic and principles of production scheduling in a way that can easily be incorporated into software systems for potential future automation.

Intern's tasks

Literature Review and Industry Analysis: A report on existing knowledge and methods used for short-term production scheduling, including an overview of challenges in codifying tacit knowledge in scheduling across industries.

Tacit Knowledge Extraction Framework: A methodology that includes:

Key questions and prompts to interview schedulers.Algorithms or decision trees that represent the decision-making process.A structured set of steps to codify the findings into rules.​

Scheduling Logic & Rules Document: A final deliverable that presents a codified set of scheduling rules for 24-hour production, validated across multiple factories with different technologies.

Validation and Case Study: A case study applying the developed framework in at least one real-world factory setting to validate its effectiveness.

Essential requirements for internship role:Project management: Ability to get a group of people working together, set a project meetings cadence, review action plans, follow up on late actions.Production Planning & Scheduling: Familiarity with production processes and scheduling practices in manufacturing environments.Knowledge Management: Understanding of how tacit knowledge can be codified and formalized.Qualitative Research: Experience in conducting interviews, analyzing qualitative data, and extracting patterns from expert knowledge.Basic Algorithm Design: Ability to create decision trees, logical frameworks, or simple algorithms that can be used to represent scheduling decisions.

Mars is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. If you need assistance or an accommodation during the application process because of a disability, it is available upon request. The company is pleased to provide such assistance, and no applicant will be penalized as a result of such a request.