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research:projects:philips_flagship [2015/10/15 15:44]
hverbeek
research:projects:philips_flagship [2017/10/02 18:13] (current)
hverbeek [Staff involved]
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 The following four PhD positions will be related to the topic of process mining: The following four PhD positions will be related to the topic of process mining:
  
-  - **Product-centric Consumer Data Analytics: Product Usage Lifecycle Analysis** [part of the "Data Driven Value Proposition" ​theme]. Digital components are being added to Philips lifestyle products. The data from these products as well as from Philips touch points must be combined to optimize user experience and maintain customer satisfaction. Process mining techniques will be used to analyze the usage of products over a longer period of time.+  - **Product-centric Consumer Data Analytics: Product Usage Lifecycle Analysis** [part of the Data Driven Value Proposition theme]. Digital components are being added to Philips lifestyle products. The data from these products as well as from Philips touch points must be combined to optimize user experience and maintain customer satisfaction. Process mining techniques will be used to analyze the usage of products over a longer period of time.
   - **Transforming Event Data into Predictive Models** [part of the Healthcare Smart Maintenance theme]. Philips has strong leadership positions in healthcare imaging and patient monitoring systems. In the healthcare domain, reducing equipment downtime and cost of ownership for hospitals is of vital importance. Smart maintenance exploits that professional equipment is connected to the internet and aims to use event and sensor data for overall cost reduction. Process mining techniques will be used to learn dynamic models that can be used for prediction and optimization.   - **Transforming Event Data into Predictive Models** [part of the Healthcare Smart Maintenance theme]. Philips has strong leadership positions in healthcare imaging and patient monitoring systems. In the healthcare domain, reducing equipment downtime and cost of ownership for hospitals is of vital importance. Smart maintenance exploits that professional equipment is connected to the internet and aims to use event and sensor data for overall cost reduction. Process mining techniques will be used to learn dynamic models that can be used for prediction and optimization.
   - **Predictive Analytics for Healthcare Workflows** [part of the Optimizing Healthcare Workflows theme]. Processes play an important role in pathology and radiology. It is not just about collecting data and supporting individual activities, but also about improving the underlying end-to-end workflow processes. To improve these operational processes in terms of costs, efficiency, speed, reliability,​ and conformance,​ we can learn from the way that processes are conducted in practice. One can learn from problems in the past and compare different process variants and process instances. This project aims to obtain insight in these workflows, in order to understand what goes well and what can be improved, using a process mining approach. The cross-fertilization between process mining and visualization will provide a novel angle on workflow improvements in pathology and radiology.   - **Predictive Analytics for Healthcare Workflows** [part of the Optimizing Healthcare Workflows theme]. Processes play an important role in pathology and radiology. It is not just about collecting data and supporting individual activities, but also about improving the underlying end-to-end workflow processes. To improve these operational processes in terms of costs, efficiency, speed, reliability,​ and conformance,​ we can learn from the way that processes are conducted in practice. One can learn from problems in the past and compare different process variants and process instances. This project aims to obtain insight in these workflows, in order to understand what goes well and what can be improved, using a process mining approach. The cross-fertilization between process mining and visualization will provide a novel angle on workflow improvements in pathology and radiology.
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 ===== Staff involved ===== ===== Staff involved =====
  
-  * [[http://​www.tue.nl/​staff/w.m.p.v.d.aalst|Wil van der Aalst]] +  * [[:organization:​staff:w.m.p.v.d.aalst|Wil van der Aalst]] 
-  * [[http://​www.tue.nl/​staff/j.c.a.m.buijs|Joos Buijs]] +  * [[:organization:​staff:j.c.a.m.buijs|Joos Buijs]] 
-  * [[http://​www.tue.nl/​staff/p.m.dixit|Alok Dixit]] +  * [[:organization:​staff:p.m.dixit|Alok Dixit]] 
-  * [[http://​www.tue.nl/​staff/b.f.a.hompes|Bart Hompes]] +  * [[:organization:​staff:b.f.a.hompes|Bart Hompes]] 
-  * [[http://​www.tue.nl/​staff/m.koorneef|Marie Koorneef]] +  * <del>[[:organization:​staff:m.koorneef|Marie Koorneef]]</​del>​ 
-  * [[http://​www.tue.nl/​staff/n.sidorova|Natalia Sidorova]] +  * [[:organization:​staff:n.sidorova|Natalia Sidorova]] 
-  * [[http://​www.tue.nl/​staff/n.tax|Niek Tax]]+  * [[:organization:​staff:n.tax|Niek Tax]]