Scania

30 credits - Dynamic forecasting models for repair contract pricing in heavy trucks

Rekryterare
Scania
Plats
Sodertalje, Stockholm
Annonserat
den 14 oktober 2019
Stängs
den 6 december 2019
Ref:
20194051
Kategori
Övriga jobb
Anställningsform
Tillsvidare
Sysselsättning
Heltid
Ingress
Thesis project at Scania is an excellent way of making contacts for your future working life. Many of our current employees started their career with a thesis project.

Background
The aftermarket, repair and maintenance, is a major source of revenue for Scania, and repair and maintenance contracts is a major tool to grow the aftermarket business. Large scale analysis of historical repair data is an important ingredient in setting contract prices. The Quality Information group (YQI) supports these efforts with statistical forecasts of repair and maintenance needs of different markets and truck segments. The present thesis project aims to improve the quality, performance, and capabilities of these forecasts. We will make use of structured databases for warranty costs, workshop visits, vehicle configuration, and operational data for individual vehicles.

Scania uses a modular design that makes it possible to create a large number of different configurations to meet the needs of individual customers, and results in a heterogeneous fleet. Moreover, the product is continuously evolving as new features are introduced and existing components and production practices are updated. This creates a challenging forecasting problem, as patterns in the data evolve over time and data from old vehicles gradually become obsolete.

Target
Contribute to method development within repair forecasting by exploring and evaluating statistical methods and models suitable for a continuously evolving population and investigate new regression variables.

Assignment
  • Literature study of dynamic forecasting methods, predominantly within the field of automotive warranty forecasting, and of existing software packages.
  • Adapt, implement, and evaluate one or several models/methods on a limited, pre-defined market segment or population.
  • Discuss the outlook for extending the method and putting it in production.

Requirements
We seek motivated MSc students in statistics, applied mathematics or engineering with strong mathematical background and analytical skills, an interest in statistical modelling, and programming skills in R or python.

Experience with structured databases and SQL is advantageous, as is knowledge of time series methods, generalized linear models, Kalman filters, latent variable models, and Gaussian processes.

Education
Master of Science in statistics, applied mathematics, data science or equivalent.

Number of students: 1
Start date: January 2020 (negotiable)
Estimated time needed: 20 weeks

Contact persons and supervisors
Martin Lindén, PhD, data scientist at YQI, 08 - 553 521 98, martin.linden@scania.com

Scania is a world-leading provider of transport solutions. Together with our partners and customers we are driving the shift towards a sustainable transport system. In 2018, we delivered 88,000 trucks, 8,500 buses as well as 12,800 industrial and marine engines to our customers. Net sales totalled to over SEK 137 billion, of which about 20 percent were services-related. Founded in 1891, Scania now operates in more than 100 countries and employs some 52,000 people. Research and development are concentrated in Sweden, with branches in Brazil and India. Production takes place in Europe, Latin America and Asia, with regional production centres in Africa, Asia and Eurasia. Scania is part of TRATON SE. For more information visit: www.scania.com.

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