Process Mining Machine Recoveries to Reduce Downtime

33:28Recorded on 20 June 2019 at TU Eindhoven

Freerk Jilderda(ASML, Netherlands)

ASML is the leading developer of photolithography systems for the semiconductor industry. Freerk shows how he has used process mining to analyze and improve lithography system start and calibration sequences, resulting in higher system availability.

Synopsis

ASML provides chip makers with everything they need to mass-produce patterns on silicon, helping to increase the value and lower the cost of a chip. The key technology is the lithography system, which brings together high-tech hardware and advanced software to control the chip manufacturing process down to the nanometer. All of the world’s top chipmakers like Samsung, Intel and TSMC use ASML’s technology, enabling the waves of innovation that help tackle the world’s toughest challenges.

The machines are developed and assembled in Veldhoven in the Netherlands and shipped to customers all over the world. Freerk Jilderda is a project manager running structural improvement projects in the Development & Engineering sector. Availability of the machines is crucial and, therefore, Freerk started a project to reduce the recovery time.

A recovery is a procedure of tests and calibrations to get the machine back up and running after repairs or maintenance. The ideal recovery is described by a procedure containing a sequence of 140 steps. After Freerk’s team identified the recoveries from the machine logging, they used process mining to compare the recoveries with the procedure to identify the key deviations. In this way they were able to find steps that are not part of the expected recovery procedure and improve the process.

Join us online for this year's camp!

This year's Process Mining Camp will take place online, from 15 to 24 June 2020Come join us for eight special days, and meet the global process mining community!

Find out more!

More from Process Mining Camp 2019

Process Mining as Enabler for Digital Transformations

Jozef Gruzman (Raiffeisen Bank International) and Claus Mitterlehner (Raiffeisen Bank International)

Jozef and Claus developed a standard approach for black-box process discoveries. Using process mining, they first explore and review the processes on their own and then dive deeper in the analysis with the subject matter experts.

Using Process Mining to Improve Conversational Interfaces

Zvi Topol (MuyVentive)

Zvi shows how process mining techniques can be leveraged to improve natural language interfaces by analyzing conversational data from chatbot interactions with customers.

Process Mining at PGGM

Bas van Beek (PGGM) and Frank Nobel (PGGM)

Bas and Frank Nobel made an impact with process mining at the Dutch pension provider PGGM. The process lies at the heart of most of their improvement initiatives and they are always a multi-disciplinary effort.

Building Operational Profiles for Philips MRI Machines

Mark Pijnenburg (Philips Healthcare) and Carmen Bratosin (ESI)

Mark and Carmen applied process mining to understand how Philips' MRI machines are actually used by physicians in the field. The discovered usage patterns increase the test coverage based on real-life behavior for these machines.

Process Mining and Simulation

Sudhendu Rai (AIG)

Sudhendu developed a ‘Process Wind Tunnel’ framework by combining process mining and simulation. Based on real-world data, discrete-event simulation optimization is used for improving insurance business processes within AIG.

Process Mining in Logistics

Boris Nikolov (Vanderlande)

Boris applied process mining in the area of logistic process automation. He validated and optimized test scenarios during some of the most critical phases of a project — acceptance testing and operational trials.

Process Mining Meets Football

Hadi Sotudeh (JADS)

Hadi brought his enthusiasm for football and his love for data together when he analyzed the 2018 World Cup data with process mining. He realized that the key to finding patterns is to make the right assumptions when preparing the data.

Responsible Data Science For Process Miners

Wil van der Aalst (RWTH Aachen)

The final speaker at Process Mining Camp 2019 was Wil van der Aalst, the founding father of process mining. In his closing keynote, Wil talked about responsible data Science for process miners.

Explore Process Mining Camp 2019

© 2020 by Fluxicon BV, all rights reserved.
You can read our privacy policy here.

Page created in 50.3 ms.