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Predictive maintenance for Valmet's breast roll shaker
(2019)
Digitalization and the Industrial Internet of Things (IIoT) enables the collection and analysis of vast amounts of data. Big data is often not utilized optimally, especially when regarding the condition and maintenance of ...
Data analytics for predictive maintenance in a pulp mill : case electric motors
(2018)
Industry is going through the fourth industrial revolution, as sensors and devices in industrial
sites are being connected to the Internet. The collected data can be refined with
machine learning and data analytics to ...
Detection and data-driven root cause analysis of paper machine drive anomalies
(2019)
The Industrial Internet has increased interest in the collection and utilization of data. The latter has become easier due to increased computing power and the development of analytical methods. The goal of this thesis is ...
Analysis of production testing data and detecting abnormal behavior
(2020)
This thesis presents methods to improve production testing methods by applying unsupervised machine learning to find anomalies from the data collected during testing. These methods are applied to a real-world case with the ...
Ohjelmistoekosysteemin ISV-kumppaneiden klusterointi ja priorisointi
(2021)
Nykypäivän kovasti kilpailulla ohjelmistokehityksen markkinoilla asiakkaat vaativat yrityksiltä entistä enemmän personointia, kätevyyttä ja hyviä kokemuksia. Näihin vaatimuksiin ohjelmistoja tarjoavan yrityksen on helpompi ...
Predicting lead times of purchase orders using gradient boosting machine
(2020)
A company can make more accurate predictions of its internal processes and sales lead
times when it has accurate predictions of the lead times of purchase orders. It results in more
efficient processes as well as improved ...
Utilization of the internet of things and machine learning in digital development of predictive maintenance at Finnish pulp mills
(2020)
The topic of this thesis is the utilization of the internet of things and machine learning in digital development of predictive maintenance at Finnish pulp mills. This thesis examines the architecture and steps needed to ...
Detecting factors affecting contract terminations in the electricity distribution system
(2022)
Distribution system contract terminations are a factor of economic interest in the electricity market, as they affect the willingness of the distribution system operators (DSOs) to invest in the improvement of the distribution ...
Predicting disease-specific survival of colorectal cancer patients using serum and tissue data : a comparison of statistical and machine learning techniques for survival analysis, imputation, and feature selection
(2022)
Globally colorectal cancer (CRC) is the third most common cancer. The incidence rates of CRC are rising, especially in high-income countries. In Finland CRC has one of the highest mortality rates compared to other cancers. ...
Predicting sepsis in the intensive care unit using machine learning
(2020)
Sepsis is a major burden to modern hospitals in terms of cost and death. Sepsis is a condition that lacks a diagnostic test making it hard to detect timely even for experienced medical professionals. The objective of this ...